Artificial Intelligence

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Recent submissions

Any replacements are listed further down

[138] viXra:1408.0129 [pdf] submitted on 2014-08-19 07:39:37

Professor Jeff's Algorithm Notes (1) — Some Remarks on Acm Contest Problems

Authors: Cheng Tianren
Comments: 200 Pages.

This is a paper which selected more than 50 ACM contest questions. You can also see a complete solution to these questions nextly, and all these programs are correctable compiled from C++. The essence part of our paper is the remarks after every exercises. In this remarks, we not only give a reasonable explanation to every question and its solution, but also give a challenging problem for every of them, which are related with the most essential and most important topics in computer algorithms. So do not easily make a conclusion to any of these open problems, carefully consideration and researches are necessary . Since all the remarks in our paper are written in Chinese, so we hope there will appear an enthusiastic person, who can help us translate them into English. For which they can be reading by our friends all around the world in most convenient way.
Category: Artificial Intelligence

[137] viXra:1408.0122 [pdf] submitted on 2014-08-18 13:10:12

Bird's-eye view on Noise-Based Logic

Authors: Laszlo B. Kish, Claes-Goran Granqvist, Tamas Horvath, Andreas Klappenecker, He Wen, Sergey M. Bezrukov
Comments: 5 Pages. In: Proceedings of the first conference on Hot Topics in Physical Informatics (HoTPI, 2013 November). Paper is in press at International Journal of Modern Physics: Conference Series (2014).

Noise-based logic is a practically deterministic logic scheme inspired by the randomness of neural spikes and uses a system of uncorrelated stochastic processes and their superposition to represent the logic state. We briefly discuss various questions such as (i) What does practical determinism mean? (ii) Is noise-based logic a Turing machine? (iii) Is there hope to beat (the dreams of) quantum computation by a classical physical noise-based processor, and what are the minimum hardware requirements for that? Finally, (iv) we address the problem of random number generators and show that the common belief that quantum number generators are superior to classical (thermal) noise-based generators is nothing but a myth.
Category: Artificial Intelligence

[136] viXra:1408.0121 [pdf] submitted on 2014-08-18 13:12:46

Brain: Biological Noise-Based Logic

Authors: Laszlo B. Kish, Claes-Goran Granqvist, Sergey M. Bezrukov, Tamas Horvath
Comments: 4 Pages. In press at: Advances in Cognitive Neurodynamics Vol. 4 - Proc. 4th International Conference on Cognitive Neurodynamics (Springer, 2014)

Neural spikes in the brain form stochastic sequences, i.e., belong to the class of pulse noises. This stochasticity is a counterintuitive feature because extracting information - such as the commonly supposed neural information of mean spike frequency - requires long times for reasonably low error probability. The mystery could be solved by noise-based logic, wherein randomness has an important function and allows large speed enhancements for special-purpose tasks, and the same mechanism is at work for the brain logic version of this concept.
Category: Artificial Intelligence

[135] viXra:1408.0017 [pdf] submitted on 2014-08-04 03:55:23

Mining Software Metrics from Jazz

Authors: Jacqui Finlay, Andy M. Connor, Russel Pears
Comments: 7 Pages. 9th International Conference on Software Engineering Research, Management and Applications

In this paper, we describe the extraction of source code metrics from the Jazz repository and the application of data mining techniques to identify the most useful of those metrics for predicting the success or failure of an attempt to construct a working instance of the software product. We present results from a systematic study using the J48 classification method. The results indicate that only a relatively small number of the available software metrics that we considered have any significance for predicting the outcome of a build. These significant metrics are discussed and implication of the results discussed, particularly the relative difficulty of being able to predict failed build attempts.
Category: Artificial Intelligence

[134] viXra:1408.0012 [pdf] submitted on 2014-08-04 02:42:53

Synthetic Minority ov er-Sampling Technique (Smote) for Predicting so Ftware Build Outcomes

Authors: Russel Pears, Jacqui Finlay, Andy M. Connor
Comments: 6 Pages. wenty-Sixth International Conference on Software Engineering and Knowledge Engineering (SEKE 2014) held at Hyatt Regency, Vancouver, Canada, 2014-07-01 to 2014-04-03

In this research we use a data stream approach to mining data and construct Decision Tree models that predict software build outcomes in terms of software metrics that are derived from source code used in the software construction process. The rationale for using the data stream approach was to track the evolution of the prediction model over time as builds are incrementally constructed from previous versions either to remedy errors or to enhance functionality. As the volume of data available for mining from the software repository that we used was limited, we synthesized new data instances through the application of the SMOTE oversampling algorithm. The results indicate that a small number of the available metrics have significance for prediction software build outcomes. It is observed that classification accuracy steadily improves after approximately 900 instances of builds have been fed to the classifier. At the end of the data streaming process classification accuracies of 80% were achieved, though some bias arises due to the distribution of data across the two classes over time.
Category: Artificial Intelligence

[133] viXra:1408.0008 [pdf] submitted on 2014-08-03 10:17:37

The Grow-Shrink Strategy for Learning Markov Network Structures Constrained by Context-Specific Independences

Authors: Alejandro Edera, Yanela Strappa, Facundo Bromberg
Comments: 12 Pages.

Markov networks are models for compactly representing complex probability distributions. They are composed by a structure and a set of numerical weights. The structure qualitatively describes independences in the distribution, which can be exploited to factorize the distribution into a set of compact functions. A key application for learning structures from data is to automatically discover knowledge. In practice, structure learning algorithms focused on "knowledge discovery" present a limitation: they use a coarse-grained representation of the structure. As a result, this representation cannot describe context-specific independences. Very recently, an algorithm called CSPC was designed to overcome this limitation, but it has a high computational complexity. This work tries to mitigate this downside presenting CSGS, an algorithm that uses the Grow-Shrink strategy for reducing unnecessary computations. On an empirical evaluation, the structures learned by CSGS achieve competitive accuracies and lower computational complexity with respect to those obtained by CSPC.
Category: Artificial Intelligence

[132] viXra:1406.0081 [pdf] submitted on 2014-06-13 20:26:37

Quantum Computing by Simulations.

Authors: Michail Zak
Comments: 28 Pages.

Quantum computing by simulations is based upon similarity between mathematical formalism of quantum mechanics and phenomena to be computed. It exploits a dynamical convergence of several competing phenomena to an attractor which can represent an extrenum of a function, an image, a solution to a system of ODE, or a stochastic process. In this chapter, a quantum version of recurrent nets (QRN) as an analog computing device is discussed. This concept is introduced by incorporating classical feedback loops into conventional quantum networks. It is shown that the dynamical evolution of such networks, which interleave quantum evolution with measurement and reset operations, exhibit novel dynamical properties. Moreover, decoherence in quantum recurrent networks is less problematic than in conventional quantum network architectures due to the modest phase coherence times needed for network operation. It is proven that a hypothetical quantum computer can implement an exponentially larger number of the degrees of freedom within the same
Category: Artificial Intelligence

[131] viXra:1405.0335 [pdf] submitted on 2014-05-27 15:31:17

Solving NP-Complete Problem by Simulations.

Authors: Michail Zak
Comments: 5 Pages.

Abstract. The mathematical formalism of quantum resonance combined with tensor product decomposability of unitary evolutions is mapped onto a class of NP-complete combinatorial problems. It has been demonstrated that nature has polynomial resources for solving NP-complete problems and that may help to develop a new strategy for artificial intelligence, as well as to re-evaluate the role of natural selection in biological evolution.
Category: Artificial Intelligence

[130] viXra:1405.0222 [pdf] submitted on 2014-05-12 17:28:46

Learning Markov Networks Structures Constrained by Context-Specific Independences

Authors: Alejandro Edera, Federico Schlüter, Facundo Bromberg
Comments: 41 Pages. This work is under revision in the IJAIT

This work focuses on learning the structure of Markov networks. Markov networks are parametric models for compactly representing complex probability distributions. These models are composed by: a structure and a set of numerical weights. The structure describes independences that hold in the distribution. Depending on the goal of learning intended by the user, structure learning algorithms can be divided into: density estimation algorithms, focusing on learning structures for answering inference queries; and knowledge discovery algorithms, focusing on learning structures for describing independences qualitatively. The latter algorithms present an important limitation for describing independences as they use a single graph, a coarse grain representation of the structure. However, many practical distributions present a flexible type of independences called context-specific independences, which cannot be described by a single graph. This work presents an approach for overcoming this limitation by proposing an alternative representation of the structure that named canonical model; and a novel knowledge discovery algorithm called CSPC for learning canonical models by using as constraints context-specific independences present in data. On an extensive empirical evaluation, CSPC learns more accurate structures than state-of-the-art density estimation and knowledge discovery algorithms. Moreover, for answering inference queries, our approach obtains competitive results against density estimation algorithms, significantly outperforming knowledge discovery algorithms.
Category: Artificial Intelligence

[129] viXra:1405.0214 [pdf] submitted on 2014-05-11 19:30:31

Communication Neutrosophic Routes

Authors: editors Florentin Smarandache, Stefan Vladutescu
Comments: 217 Pages.

The life of human beings is a place of communication. Consequently, any cognitive and cogitative manifestation presents a route of communication. People consume their lives relating by communicational. Some communicational relationships are contradictory, others are neutral, since within the manifestations of life there are found conflicts meanings and/or neutral meanings. Communicational relations always comprise a set of neutral, neutrosophic meanings. Particularly, we talk about scientific sculptural communication, esthetic communication and so on, as specific manifestations of life. It can be asserted that in any communication there are routes of access and neutrosophic routes. Any communication is traversed by neutrosophic routes of communication. [F. Smarandache & S. Vladutescu] The book has 10 chapters written by the following authors and co-authors: Florentin Smarandache, Stefan Vladutescu, Ioan Constantin Dima, Mariana Man, Alexandra Iorgulescu, Alina Tenescu, Madalina Strechie, Daniela Gifu, MIhaela Gabriela Paun, Maria Nowicka-Skowron, Sorin Mihai Radu, Janusz Grabara, Ion Cosmescu, and Bianca Teodorescu.
Category: Artificial Intelligence

[128] viXra:1404.0425 [pdf] submitted on 2014-04-19 02:45:15

Algorithms for Image Analysis and Combination of Pattern Classifiers with Application to Medical Diagnosis

Authors: Harris V Georgiou
Comments: 12 Pages.

Medical Informatics and the application of modern signal processing in the assistance of the diagnostic process in medical imaging is one of the more recent and active research areas today. This thesis addresses a variety of issues related to the general problem of medical image analysis, specifically in mammography, and presents a series of algorithms and design approaches for all the intermediate levels of a modern system for computer-aided diagnosis (CAD). The diagnostic problem is analyzed with a systematic approach, first defining the imaging characteristics and features that are relevant to probable pathology in mammo-grams. Next, these features are quantified and fused into new, integrated radio-logical systems that exhibit embedded digital signal processing, in order to improve the final result and minimize the radiological dose for the patient. In a higher level, special algorithms are designed for detecting and encoding these clinically interest-ing imaging features, in order to be used as input to advanced pattern classifiers and machine learning models. Finally, these approaches are extended in multi-classifier models under the scope of Game Theory and optimum collective deci-sion, in order to produce efficient solutions for combining classifiers with minimum computational costs for advanced diagnostic systems. The material covered in this thesis is related to a total of 18 published papers, 6 in scientific journals and 12 in international conferences.
Category: Artificial Intelligence

[127] viXra:1404.0050 [pdf] submitted on 2014-04-06 22:23:17

The Human Computer Science of 13,800,000,000 B.C.

Authors: Rodney Bartlett
Comments: 10 Pages.

The hardest part of writing this was selecting a category. It involves physics, maths, biology, philosophy. But it speaks of computer science and the AI of bits being responsible for all creation. So maybe this is the right category? This article is another version of my entry in FQXi’s 2014 contest – http://fqxi.org/community/forum/topic/1977. I was inspired to write this new version after reading "The Missing Universe" by Bob Berman (Astronomy magazine - April 2014) which says, "... MOND (MOdified Newtonian Dynamics) works well in predicting how galaxies rotate, but it doesn't work as well in predicting motions at much larger scales, such as those between galaxy groups (clusters and superclusters - DM, dark matter, seems compelling at the largest scales)." This sounds like a message from the universe that we don't have to choose between dark matter and modified gravity. The following article shows that they can be integrated. And if a Theory of Everything really does describe the universe, the strong force and electromagnetic force (p.28 of Bob Berman's article) must also be capable of integration with DM/MOND. To do this, I'll "Einsteinize" my article by reminding readers of a 1919 paper he wrote. Further Einsteinization will return us to the Theory of Everything by speaking of his Unified Field Theory. Then I’ll finish with “What is Gravity?” (thanks to Einstein’s General Relativity explaining that gravity is the warping of space-time, this could also be called “What is Space-time?”) and a new interpretation of infinity.
Category: Artificial Intelligence

[126] viXra:1312.0069 [pdf] submitted on 2013-12-10 14:57:20

War Crimes Avoidance & Detection: Battlefield Management Systems

Authors: Nyagudi Musandu Nyagudi
Comments: 20 pages

In today's world, almost any armed conflict involving national military forces or non-state actors,results in allegations of war crimes and calls for investigations and prosecutions. As continuedpenetration of the Internet in the society leads to ever more thorough scrutiny of military operations,the world's military forces are in a continuous struggle for situational awareness via their own networkcentric Battlefield Management Systems(BMS). But in many publications on the subject matter, little attention is paid as pertains to improving the humanitarian conditions in the Battle-space. The focus for the moment seems to be geared towards the attainment of tactical military objectives, by conducting military operations against, seemingly virtual adversaries. Pragmatically speaking 'claiming that a war can be conducted without atrocities, is akin to claiming that a market can be free from fraud'.
Category: Artificial Intelligence

[125] viXra:1312.0067 [pdf] submitted on 2013-12-10 11:49:55

Revolution in Military Affairs : An Intuitive Informatics Model for Evaluating a Commander's Proficiency

Authors: Nyagudi Musandu Nyagudi
Comments: 10 pages

The Informatics of Selecting Military Commanders
Category: Artificial Intelligence

[124] viXra:1311.0180 [pdf] submitted on 2013-11-27 12:30:45

Introduction to Neutrosophic Measure, Neutrosophic Integral, and Neutrosophic Probability

Authors: Florentin Smarandache
Comments: 140 Pages. Keywords: Neutrosophics, Neutrosophic Measure, Neutrosophic Integral, Neutrosophic Probability, Neutrosophic Logic, Neutrosophic Set, Neutrosophy.

In this book, we introduce for the first time the notions of neutrosophic measure and neutrosophic integral, and we develop the 1995 notion of neutrosophic probability. We present many practical examples. It is possible to define the neutrosophic measure and consequently the neutrosophic integral and neutrosophic probability in many ways, because there are various types of indeterminacies, depending on the problem we need to solve. Neutrosophics study the indeterminacy. Indeterminacy is different from randomness. It can be caused by physical space materials and type of construction, by items involved in the space, etc.
Category: Artificial Intelligence

[123] viXra:1310.0040 [pdf] submitted on 2013-10-05 19:17:48

Connections Between Extenics and Refined Neutrosophic Logic

Authors: Florentin Smarandache
Comments: 9 Pages.

The aim of this presentation is to connect Extenics with new fields of research, i.e. fuzzy logic and neutrosophic logic. We show herein: - How Extenics is connected to the 3-Valued Neutrosophic Logic, - How Extenics is connected to the 4-Valued Neutrosophic Logic, - How Extenics is connected to the n-Valued Neutrosophic Logic, when contradictions occurs.
Category: Artificial Intelligence

[122] viXra:1310.0039 [pdf] submitted on 2013-10-05 19:25:24

New Operations on Intuitionistic Fuzzy Soft Set

Authors: Said Broumi, Pinaki Majumdar, Florentin Smarandache
Comments: 10 Pages.

In this paper, we have defined First Zadeh’s implication , First Zadeh’s intuitionistic fuzzy conjunction and intuitionistic fuzzy disjunction of two intuitionistic fuzzy soft sets and some their basic properties are studied with proofs and examples.
Category: Artificial Intelligence

[121] viXra:1310.0038 [pdf] submitted on 2013-10-05 19:29:18

Intuitionistic Neutrosphic Soft Set Over Rings

Authors: Said Broumi, Florentin Smarandache
Comments: Pages.

S.Broumi and F.Smarandache introduced the concept of intuitionistic neutrosophic soft set, which is an extension to the soft set. In this paper we apply the concept of intuitionistic neutrosophic soft set to rings theory .The notion of intuitionistic neutrosophic soft rings is introduced and their basic properties are presented . Intersection, union, AND, and OR operations of intuitionistic neutrosophic soft rings are defined . Also ,we have defined the product of two intuitionistic neutrosophic soft set over Ring.
Category: Artificial Intelligence

[120] viXra:1310.0036 [pdf] submitted on 2013-10-05 19:49:13

Correlation Coefficient of Interval Neutrosophic Set

Authors: Said Broumi, Florentin Smarandache
Comments: 9 Pages.

In this paper we introduce for the first time the concept of correlation coefficients of interval valued neutrosophic set (INS for short). Respective numerical examples are presented.
Category: Artificial Intelligence

[119] viXra:1310.0035 [pdf] submitted on 2013-10-05 19:53:37

More on Intuitionistic Neutrosophic Soft Sets

Authors: Said Broumi, Florentin Smarandache
Comments: 14 Pages.

Intuitionistic Neutrosophic soft set theory proposed by S.Broumi and F. Samarandache [28 ], has been regarded as an effective mathematical tool to deal with uncertainties. In this paper new operations on intuitionistic neutrosophic soft sets have been introduced . Some results relating to the properties of these operations have been established. Moreover ,we illustrate their interconnections between each other.
Category: Artificial Intelligence

[118] viXra:1310.0032 [pdf] submitted on 2013-10-05 21:25:30

Several Similarity Measures of Neutrosophic Sets

Authors: Said Broumi, Florentin Smarandache
Comments: 11 Pages.

Smarandache (1995) defined the notion of neutrosophic sets, which is a generalization of Zadeh's fuzzy set and Atanassov's intuitionistic fuzzy set. In this paper, we first develop some similarity measures of neutrosophic sets. We will present a method to calculate the distance between neutrosophic sets (NS) on the basis of the Hausdorff distance. Then we will use this distance to generate a new similarity measure to calculate the degree of similarity between NS. Finally we will prove some properties of the proposed similarity measures.
Category: Artificial Intelligence

[117] viXra:1310.0029 [pdf] submitted on 2013-10-05 21:41:20

Intuitionistic Neutrosophic Soft Set

Authors: Said Broumi, Florentin Smarandache
Comments: 11 Pages.

In this paper we study the concept of intuitionistic neutrosophic set of Bhowmik and Pal. We have introduced this concept in soft sets and defined intuitionistic neutrosophic soft set. Some definitions and operations have been introduced on intuitionistic neutrosophic soft set. Some properties of this concept have been established.
Category: Artificial Intelligence

[116] viXra:1310.0027 [pdf] submitted on 2013-10-05 22:02:44

A Study of Quality in Primary Education Combined Disjoint Block Neutrosophic Cognitive Maps (CDBNCM)

Authors: A.Victor Devadoss, M. Clement Joe Anand, A. Joseph Bellarmin
Comments: 6 Pages.

Quality in primary education has been classified into five factors involving learners, content, processes, environment and outcomes. In this paper we analyzed, quality in primary education in Chennai and find out its solution using Neutrosophic cognitive maps (NCMS), which is the generalization of fuzzy cognitive maps (FCMS) defined by W.B. Vasantha Kandasamy and Florentine Smarandache. This paper has five sections. First section gives information about development of fuzzy cognitive maps and Neutrosophic cognitive maps. Second section gives the preliminaries of FCMS and NCMS. In section three, we give the description of the problem; final section gives the conclusion based on our study.
Category: Artificial Intelligence

[115] viXra:1309.0149 [pdf] submitted on 2013-09-21 20:25:54

A Complexity of Bridge Double Dummy Problem

Authors: Piotr Beling
Comments: 10 pages in Polish

This paper presents an analysis of complexity of a bridge double dummy problem. Values of both, a state-space (search-space) complexity and a game tree complexity have been estimated.
Category: Artificial Intelligence

[114] viXra:1309.0130 [pdf] submitted on 2013-09-17 16:04:54

Storkey Learning Rules for Hopfield Networks

Authors: Xiao Hu
Comments: 9 Pages.

We summarize the Storkey Learning Rules for the Hopfield Model, and evaluate performance relative to other learning rules. Hopfield Models are normally used for auto-association, and Storkey Learning Rules have been found to have good balance between local learning and capacity. In this paper we outline different learning rules and summarise capacity results. Hopfield networks are related to Boltzmann Machines: they are the same as fully visible Boltzmann Machines in the zero temperature limit. Perhaps renewed interest in Boltzmann machines will produce renewed interest in Hopfield learning rules?
Category: Artificial Intelligence

[113] viXra:1309.0129 [pdf] submitted on 2013-09-17 18:52:12

An Effective Neutrosophic Set-Based Preprocessing Method for Face Recognition

Authors: Mohammad Reza Faraji, Xiaojun Qi
Comments: 4 Pages.

Face recognition (FR) is a challenging task in biometrics due to various illuminations, poses, and possible noises. In this paper, we propose to apply a novel neutrosophic set (NS)- based preprocesssing method to simultaneously remove noise and enhance facial features in original face images.
Category: Artificial Intelligence

[112] viXra:1309.0128 [pdf] submitted on 2013-09-17 19:01:02

On Similarity and Entropy of Neutrosophic Sets

Authors: Pinaki Majumdar, S. K. Samanta
Comments: 13 Pages.

In this paper we have introduced the notion of distance between two single valued neutrosophic sets and studied its properties. We have also defined several similarity measures between them and investigated their characteristics. A measure of entropy of a single valued neutrosophic set has also been introduced.
Category: Artificial Intelligence

[111] viXra:1309.0102 [pdf] submitted on 2013-09-16 09:11:51

On the Continuous-time Consensus Problems with Markovian Switching

Authors: Evgeniy Grechnikov, Ricardo Vieira Godoy
Comments: 9 Pages.

In this paper, we study the linear distributed asymptotic consensus problem for a network of dynamic agents whose communication network is modeled by a randomly switching graph. A finite state Markov process dominates each topology corresponding to a state of the process. We address both the cases where the dynamics of the agents is expressed in continuous and discrete time. As long as the consensus matrices are doubly stochastic, convergence to average consensus can be shown to be achieved in the mean square and almost sure sense. A necessary and sufficient condition is the graph resulted from the union of graphs corresponding to the states of the Markov process contains a spanning tree.
Category: Artificial Intelligence

[110] viXra:1309.0071 [pdf] submitted on 2013-09-10 20:24:28

On Fuzzy Soft Matrix Based on Reference Function

Authors: Said Broumi, Florentin Smarandache, Mamoni Dhar
Comments: 8 Pages.

In this paper we study fuzzy soft matrix based on reference function.Firstly, we define some new operations such as fuzzy soft complement matrix and trace of fuzzy soft matrix based on reference function.Then, we introduced some related properties, and some examples are given. Lastly, we define a new fuzzy soft matrix decision method based on reference function.
Category: Artificial Intelligence

[109] viXra:1309.0030 [pdf] submitted on 2013-09-07 11:50:47

Neutrosophic Soft Set

Authors: Pabitra Kumar Maji
Comments: 12 Pages.

In this paper we study the concept of neutrosophic set of Smarandache. We have introduced this concept in soft sets and de¯ned neutrosophic soft set. Some de¯nitions and operations have been intro- duced on neutrosophic soft set. Some properties of this concept have been established.
Category: Artificial Intelligence

[108] viXra:1309.0029 [pdf] submitted on 2013-09-07 11:52:42

A Neutrosophic Soft Set Approach to a Decision Making Problem

Authors: Pabitra Kumar Maji
Comments: 7 Pages.

The decision making problems in an imprecise environment has found paramount importance in recent years. Here we consider an object recognition problem in an imprecise environment. The recognition strategy is based on multiobserver input parameter data set.
Category: Artificial Intelligence

[107] viXra:1308.0031 [pdf] submitted on 2013-08-05 20:03:33

Connection Between Extenics and Refined Neutrosophiclogic

Authors: Florentin Smarandache
Comments: 21 Pages.

The aim of this presentation is to connect Extenicswith new fields of research, i.e. fuzzy logic and neutrosophiclogic. We show herein: -How Extenicsis connected to the 3-Valued NeutrosophicLogic; -How Extenicsis connected to the 4-Valued NeutrosophicLogic; -How Extenicsis connected to the n-Valued NeutrosophicLogic; when contradiction occurs.
Category: Artificial Intelligence

[106] viXra:1305.0080 [pdf] submitted on 2013-05-13 07:19:22

Reduction of Logic to Arithmetic

Authors: Ranganath G Kulkarni
Comments: 3 Pages.

It is possible to make decisions mathematically of first order predicate calculus. A new mathematical formula is found for the solution of decision problem. We can reduce a logical algorithm into simple algorithm without logical trees
Category: Artificial Intelligence

[105] viXra:1304.0155 [pdf] submitted on 2013-04-27 09:28:39

Foundations of Neutrosophic Logic and Set and Their Applications to Information Fusion

Authors: Florentin Smarandache
Comments: 101 Pages.

Neutrosophy, neutrosophic logic, neutrosophic set, and neutrosophic probability are presented. Also their applications to various scientific fields.
Category: Artificial Intelligence

[104] viXra:1304.0139 [pdf] submitted on 2013-04-25 07:02:03

A Novel Neutrosophic Logic SVM (N-SVM) and Its Application to Image Categorization

Authors: Wen Ju, H. D. Cheng
Comments: 14 Pages.

Neutrosophic logic is a relatively new logic that is a generalization of fuzzy logic. In this paper, for the first time, neutrosophic logic is applied to the field of classifiers where a support vector machine (SVM) is adopted as the example to validate its feasibility and effectiveness. The proposed neutrosophic set is integrated into a reformulated SVM, and the performance of the obtained classifier N-SVM is evaluated under a region-based image categorization system. Images are first segmented by a hierarchical two-stage self-organizing map (HSOM), using color and texture features. A novel approach is proposed to select the training samples of HSOM based on homogeneity properties. A diverse density support vector machine (DD-SVM) framework is then applied to viewing an image as a bag of instances corresponding to the regions obtained from image segmentation. Each bag is mapped to a point in the new bag space, and the categorization is transformed to a classification problem. Then, the proposed N-SVM is used as the classifier in the new bag space. N-SVM treats samples differently according to the weighting function, and it helps to reduce the effects of outliers. Experimental results have demonstrated the validity and effectiveness of the proposed method which may find wide applications in the related areas.
Category: Artificial Intelligence

[103] viXra:1304.0133 [pdf] submitted on 2013-04-24 11:58:17

An Indicator of Inclusion with Applications in Computer Vision

Authors: Ovidiu Ilie Şandru, Florentin Smarandache
Comments: 3 Pages.

In this paper we present an algorithmic process of necessary operations for the automatic movement of a predefined object from a video image in the target region of that image, intended to facilitate the implementation of specialized software applications in solving this kind of problems.
Category: Artificial Intelligence

[102] viXra:1304.0101 [pdf] submitted on 2013-04-20 11:05:18

Multicriteria Decision-Making Method Using the Correlation Coefficient Under Single-Valued Neutrosophic Environment

Authors: Jun Ye
Comments: 9 Pages.

The paper presents the correlation and correlation coefficient of single-valued neutrosophic sets (SVNSs) based on the extension of the correlation of intuitionistic fuzzy sets and demonstrates that the cosine similarity measure is a special case of the correlation coefficient in SVNS. Then a decision-making method is proposed by the use of the weighted correlation coefficient or the weighted cosine similarity measure of SVNSs, in which the evaluation information for alternatives with respect to criteria is carried out by truth-membership degree, indeterminacy-membership degree, and falsity-membership degree under single-valued neutrosophic environment. We utilize the weighted correlation coefficient or the weighted cosine similarity measure between each alternative and the ideal alternative to rank the alternatives and to determine the best one(s). Finally, an illustrative example demonstrates the application of the proposed decision-making method.
Category: Artificial Intelligence

[101] viXra:1304.0091 [pdf] submitted on 2013-04-19 06:08:36

Cryptography Using an Image

Authors: Yousuf Ibrahim Khan
Comments: 10 Pages.

An information is a message which is received and understood. Information can be sent one person to another over a long range but the process of sending information must be done in a secure way especially in case of a private message. Mathematicians and Engineers have historically relied on different algorithmic techniques to secure messages and signals. Cryptography, to most people, is concerned with keeping communications private. Indeed, the protection of sensitive communications has been the emphasis of cryptography throughout much of its history. Sometimes it is safer to send a message using an image and thus cryptography can also be done using images during an emergency. The need to extract information from images and interpret their contents has been one of the driving factors in the development of image processing and cryptography during the past decades. In this paper, a simple cryptographic method was used to decode a message which was in an image and it was done using a popular computational software.
Category: Artificial Intelligence

[100] viXra:1304.0085 [pdf] submitted on 2013-04-18 02:30:46

Artificial Neural Network based Short Term Load Forecasting of Power System

Authors: Salman Quaiyum, Yousuf Ibrahim Khan, Saidur Rahman, Parijat Barman
Comments: 7 Pages.

Load forecasting is the prediction of future loads of a power system. It is an important component for power system energy management. Precise load forecasting helps to make unit commitment decisions, reduce spinning reserve capacity and schedule device maintenance plan properly. Besides playing a key role in reducing the generation cost, it is also essential to the reliability of power systems. By forecasting, experts can have an idea of the loads in the future and accordingly can make vital decisions for the system. This work presents a study of short-term hourly load forecasting using different types of Artificial Neural Networks.
Category: Artificial Intelligence

[99] viXra:1304.0084 [pdf] submitted on 2013-04-18 02:35:31

Application of Computational Intelligence in Motor Modeling

Authors: Yousuf Ibrahim Khan
Comments: 8 Pages.

Modeling is very important in the field of science and engineering. Modeling gives us an abstract and mathematical description of a particular system and describes its behavior. Once we get the model of a system then we can work with that in various applications without using the original system repeatedly. Computational Intelligence method like Artificial Neural Network is very sophisticated tool for modeling and data fitting problems. Modeling of Electrical motors can also be done using ANN. The Neural network that will represent the model of the motor will be a useful tool for future use especially in digital control systems. The parallel structure of a neural network makes it potentially fast for the computation of certain tasks. The same feature makes a neural network well suited for implementation in VLSI technology. Hardware realization of a Neural Network (NN), to a large extent depends on the efficient implementation of a single neuron. In this paper only a motor model is presented along with some neural networks those will mimic the motor behavior acquiring data from the original motor output.
Category: Artificial Intelligence

[98] viXra:1304.0064 [pdf] submitted on 2013-04-14 07:10:21

A Study of Non-Linear Control for Energy Storage Systems

Authors: Chenwen Zheng, Margaret Jenkins
Comments: 4 Pages.

This paper presents an overall solution consisting of a wind plant with a Smart Storage Modular System (SSMS). The SSMS consists in a Short Time Storage Module (STSM based on a flywheel with induction motor) and a Medium/Long Time Storage Module (MLTSM based on a Vanadium Redox flow Battery). The aim of this paper is to provide a nonlinear sensorless control solution for the induction motor (IM) within the inertial storage system based on flywheel. To this related one, computer simulations and laboratory tests are accomplished.
Category: Artificial Intelligence

[97] viXra:1304.0011 [pdf] submitted on 2013-04-02 21:49:41

Lie Algebrized Gaussians for Image Representation

Authors: Liyu Gong, Meng Chen, Chunlong Hu
Comments: 8 Pages.

We present an image representation method which is derived from analyzing Gaussian probability density function (\emph{pdf}) space using Lie group theory. In our proposed method, images are modeled by Gaussian mixture models (GMMs) which are adapted from a globally trained GMM called universal background model (UBM). Then we vectorize the GMMs based on two facts: (1) components of image-specific GMMs are closely grouped together around their corresponding component of the UBM due to the characteristic of the UBM adaption procedure; (2) Gaussian \emph{pdf}s form a Lie group, which is a differentiable manifold rather than a vector space. We map each Gaussian component to the tangent vector space (named Lie algebra) of Lie group at the manifold position of UBM. The final feature vector, named Lie algebrized Gaussians (LAG) is then constructed by combining the Lie algebrized Gaussian components with mixture weights. We apply LAG features to scene category recognition problem and observe state-of-the-art performance on 15Scenes benchmark.
Category: Artificial Intelligence

[96] viXra:1303.0202 [pdf] submitted on 2013-03-26 07:59:36

Mobile Robot Navigation Using Artificial Landmarks and GPS

Authors: Kimihiro OKUYAMA, Mohd ANASRI, Florentin SAMARANDACHE, Valeri KROUMOV
Comments: 6 Pages.

移動ロボットのナビゲーションを行うにはロボットが 十分に現在位置と周囲の環境を認識する必要がある。そ のために、ロボットにレーザーレンジスキャナや超音波 センサ、カメラ、オドメトリ、GPS (Global Positioning System) 等のセンサを搭載することで、ロボットは現在 位置・姿勢、周囲の様子、移動距離、周囲の物との距離 等を知ることができるようになる。しかし、センサか らの情報には誤差が含まれており、移動している環境 や搭載しているセンサにより生じる誤差が累積される ことで、現在の位置がわからなくなり、走行経路から 外れて、目的地へたどりつけなくなることがある。正 しい位置を認識するには、定期的に誤差を解消し、位 置の校正を行う必要がある。位置校正を向上させるた めに、ロボットにSLAM (Simultaneous Localization and Mapping)[1] アルゴリズムやKalman Filter[2] などの制 御技術が導入される。
Category: Artificial Intelligence

[95] viXra:1303.0192 [pdf] submitted on 2013-03-25 10:36:22

NP!=P

Authors: Liu Ran
Comments: 10 Pages.

Any NP problem can reduce to P problem, any P problem can reduce to instructions. If NP=P, it violate information entropy principle.
Category: Artificial Intelligence

[94] viXra:1303.0072 [pdf] submitted on 2013-03-09 21:04:02

On Godel's Incompleteness Theorem(s), Artificial Intelligence/life, and Human Mind

Authors: Victor Christianto, Florentin Smarandache
Comments: 8 Pages. This paper is not yet submitted to any journal.

In the present paper we discussed Godel’s incompleteness theorem(s) and plausible implications to artificial intelligence/life and human mind. Perhaps we should agree with Sullins III, that the value of this finding is not to discourage certain types of research in AL, but rather to help move us in a direction where we can more clearly define the results of that research. Godel’s incompleteness theorems have their own limitations, but so do Artificial Life (AL)/AI systems. Based on our experiences so far, human mind has incredible abilities to interact with other part of human body including heart, which makes it so difficult to simulate in AI/AL. However, it remains an open question to predict whether the future of AI including robotics science can bring this gap closer or not. In this regard, fuzzy logic and its generalization –neutrosophic logic- offer a way to improve significantly AI/AL research.
Category: Artificial Intelligence

[93] viXra:1303.0069 [pdf] submitted on 2013-03-09 11:52:15

Set-Theoretic Operators on Degenerated Neutrosophic Set (DNS)

Authors: H. Wang, Y. Zhang, R. Sunderraman, F. Song
Comments: 14 Pages.

We define set-operators on DNS.
Category: Artificial Intelligence

[92] viXra:1303.0068 [pdf] submitted on 2013-03-09 11:54:52

A Neutrosophic Multicriteria Decision Making Method

Authors: Athar Kharal
Comments: 19 Pages.

This work presents a method of multicriteria decision making using neutrosophic sets. Besides studying some interesting mathematical properties of the method, algorithm viz neut-MCDM is presented. The work also furnishes the fundamentals of neutrosophic set theory succinctly, to provide a …rst introduction of neutrosophic sets for the MCDM community. To illustrate the computational details, neut-MCDM has been applied to the problem of university faculty selection against a given set of criteria.
Category: Artificial Intelligence

[91] viXra:1303.0066 [pdf] submitted on 2013-03-09 11:13:19

An Approach to Model Interest for Planetary Rover Through DSmT

Authors: Matteo Ceriotti, Massimiliano Vasile, Mauro Massari
Comments: 28 Pages.

Dezert-Smarandache Theory (DSmT) used for the planetary rover.
Category: Artificial Intelligence

[90] viXra:1302.0175 [pdf] submitted on 2013-02-28 09:32:15

A Knowledge Representation for Expressing Simple Algorithms

Authors: Sridhar Natarajan
Comments: 7 Pages.

This paper is about designing a platform for creating formalized semantic representations to express algorithmic knowledge and their implementations in a high level language program. Representations are mechanisms for expressing any linguistic utterance. Improvements in human understanding of those utterances is achieved when each of those utterances are expressed using representations with the most appropriate semantic properties. This principle is applied for design of this platform. The platform can be used by computer scientists, teachers and engineers who make attempts at conveying their knowledge about a specific algorithm and its corresponding high level language program. The principal objective of the platform is aimed at improving human understanding of representations for algorithmic knowledge.
Category: Artificial Intelligence

[89] viXra:1302.0015 [pdf] submitted on 2013-02-03 10:52:56

Set-Theoretic Operators on Degenerated Neutrosophic Set

Authors: Haibin Wang, Yanqinq Zhang, Rajshekhar Sunderraman, Feijun Song
Comments: 14 Pages.

žIn this paper we define the set-theoretic operators on an instance of neutrosophic set, called Degenerated Neutrosophic Set (DNS).
Category: Artificial Intelligence

[88] viXra:1301.0183 [pdf] submitted on 2013-01-29 17:59:27

Computer Vision Applications on the Cloud

Authors: Yu Zhou
Comments: 3 Pages.

Cloud computing offers the potential to help scientists to process massive number of computing resources often required in machine learning application such as computer vision problems. This proposal would like to show that which benefits can be obtained from cloud in order to help medical image analysis users (including scientists, clinicians, and research institutes). As security and privacy of algorithms are important for most of algorithms’ inventors, these algorithms can be hidden in a cloud to allow the users to use the algorithms as a package without any access to see/change their inside. In another word, in the user part, users send their images to the cloud and configure the algorithm via an interface. In the cloud part, the algorithms are applied to this image and the results are returned back to the user. My proposal has two parts: (1) investigate the potential of cloud computing for computer vision problems and (2) study the components of a proposed cloud-based framework for medical image analysis application and develop them (depending on the length of the internship). The investigation part will involve a study on several aspects of the problem including security, usability (for medical end users of the service), appropriate programming abstractions for vision problems, scalability and resource requirements. In the second part of this proposal I am going to thoroughly study of the proposed framework components and their relations and develop them. The proposed cloud-based framework includes an integrated environment to enable scientists and clinicians to access to the previous and current medical image analysis algorithms using a handful user interface without any access to the algorithm codes and procedures.
Category: Artificial Intelligence

[87] viXra:1301.0107 [pdf] submitted on 2013-01-17 21:56:43

Automatic Tunning of MapReduce Jobs using Uncertain Pattern Matching Analysis

Authors: Nikzad Babaii Rizvandi, Javid Taheri, Reza Moraveji, Albert Y.Zomaya
Comments: 19 Pages.

In this paper, we study CPU utilization time patterns of several MapReduce applications. After extracting running patterns of several applications, the patterns along with their statistical information are saved in a reference database to be later used to tweak system parameters to efficiently execute future unknown applications. To achieve this goal, CPU utilization patterns of new applications along with its statistical information are compared with the already known ones in the reference database to find/predict their most probable execution patterns. Because of different pattern lengths, the Dynamic Time Warping (DTW) is utilized for such comparison; a statistical analysis is then applied to DTWs’ outcomes to select the most suitable candidates. Furthermore, under a hypothesis, we also proposed another algorithm to classify applications under similar CPU utilization patterns. Finally, dependency between minimum distance/maximum similarity of applications and their scalability (in both input size and number of virtual nodes) are studied. Here, we used widely used applications (WordCount, Distributed Grep, and Terasort) as well as an Exim Mainlog parsing application to evaluate our hypothesis in automatic tweaking MapReduce configuration parameters in executing similar applications scalable on both size of input data and number of virtual nodes. Results are very promising and showed the effectiveness of our approach on a private cloud with up to 25 virtual nodes.
Category: Artificial Intelligence

[86] viXra:1301.0024 [pdf] submitted on 2013-01-05 10:07:02

CloudSVM : Training an SVM Classifier in Cloud Computing Systems

Authors: F. Ozgur Catak, M. Erdal Balaban
Comments: 13 Pages.

In conventional distributed machine learning methods, distributed support vector machines (SVM) algorithms are trained over pre-configured in-tranet/internet environments to find out an optimal classifier. These methods are very complicated and costly for large datasets. Hence, we propose a method that is referred as the Cloud SVM training mechanism (CloudSVM) in a cloud computing environment with MapReduce technique for distributed machine learning applications. Accordingly, (i) SVM algorithm is trained in distributed cloud storage servers that work concurrently; (ii) merge all support vectors in every trained cloud node; and (iii) iterate these two steps until the SVM con-verges to the optimal classifier function. Single computer is incapable to train SVM algorithm with large scale data sets. The results of this study are im-portant for training of large scale data sets for machine learning applications. We provided that iterative training of splitted data set in cloud computing envi-ronment using SVM will converge to a global optimal classifier in finite iteration size.
Category: Artificial Intelligence

[85] viXra:1301.0017 [pdf] submitted on 2013-01-03 17:41:06

Statistical Performance Provisioning and Energy Efficiency in Distributed Computing Systems

Authors: Nikzad Babaii Rizvandi
Comments: 47 Pages.

This is a presenation on my PhD thesis about using statistical machine learning techniques to model and provision the performance of MapReduce and also energy efficient slack reclamation in distributed computing systems.
Category: Artificial Intelligence

[84] viXra:1301.0016 [pdf] submitted on 2013-01-03 17:52:51

High Performance Computing of Seismic Data on MapReduce

Authors: Nikzad Babaii Rizvandi
Comments: 1 Page.

After an overview of forward/inverse Prestack Kirchhoff Time Migration (PKTM) algorithm, we will explain our proposed approach to fit this algorithm for running on Google’s MapReduce framework. Toward the end, we will analyse the relation between MapReduce-based PKTM completion time and the number of map/reduce tasks on pseudo-distributed MapReduce mode.
Category: Artificial Intelligence

[83] viXra:1211.0104 [pdf] submitted on 2012-11-18 21:11:04

A Primarily Survey on Energy Efficiency in Cloud and Distributed Computing Systems

Authors: Nikzad Babaii Rizvandi, Albert Y. Zomaya
Comments: 18 Pages.

A survey of available techniques in hardware to reduce energy consumption
Category: Artificial Intelligence

[82] viXra:1211.0098 [pdf] submitted on 2012-11-17 20:07:28

Gu Test: A Progressive Measurement of Generic Intelligence

Authors: Scott Lifan Gu
Comments: 7 Pages. The earliest version of this paper is at: https://ia600801.us.archive.org/29/items/GuTest/GuTest.txt

Do computers already have human level intelligence? Could they understand and process the semantics of irrational numbers without knowing the exact values ? Human can. How about uncountable sets ? These are necessary to build sciences and real world modeling. Does human intelligence exceed the power of Turing Machine? This paper explains that behavior-based Turing Test cannot measure some intrinsic human intelligence, due to the bottleneck in expression, the bottleneck in capacity, and black box issue, etc. And it does not provide a progressive measurement up to human level intelligence. Similar issues exist in other current testing methods, due to the limitations of behavior-based, knowledge-based or task-based, etc. Measurements based on intrinsic mechanisms could provide better testing. This paper identifies several design goals, to further improve the measurement. Gu Test, a progressive generic intelligence measurement with levels and potential structures, is proposed based on these goals, to measure the intrinsic mechanism for semantics, potential and other intelligence. The semantics of irrational numbers and uncountable sets are identified as two test levels. More work need be done to expand the test feature sets and structures, and provide some suggestions for the direction of future Artificial Intelligence (AI) researches.
Category: Artificial Intelligence

[81] viXra:1210.0134 [pdf] submitted on 2012-10-23 18:38:54

Extenics in Higher Dimensions

Authors: Florentin Smarandache
Comments: 112 Pages.

Prof. Florentin Smarandache, during his research period in the Summer of 2012 at the Research Institute of Extenics and Innovation Methods, from Guangdong University of Technology, in Guangzhou, China, has introduced the Linear and Non-Linear Attraction Point Principle and the Network of Attraction Curves, he has generalized the 1D Extension Distance and the 1D Dependent Function to 2D, 3D, and in general to n-D Spaces, and he generalized Qiao-Xing Li’s and Xing-Sen Li’s definitions of the Location Value of a Point and the Dependent Function of a Point on a Single Finite Interval from one dimension (1D) to 2D, 3D, and in general n-D spaces. He used the Extenics, together with Victor Vlădăreanu, Mihai Liviu Smarandache, Tudor Păroiu, and Ştefan Vlăduţescu, in 2D and 3D spaces in technology, philosophy, and information theory. Extenics is the science of solving contradictory problems in many fields set up by Prof. Cai Wen in 1983.
Category: Artificial Intelligence

[80] viXra:1210.0087 [pdf] submitted on 2012-10-17 10:58:57

On the Maneuvering Control of Networks of Moving Vehicles

Authors: Jae Park, Evgeniy Grechnikov, Fang Chen
Comments: 7 Pages.

A maneuvering control algorithm based on the independent all-wheel driving and steering control has been proposed to improve the maneuverability and survivability for special purpose 6WD/6WS vehicles. The control algorithm to perform maneuvering, high speed stability, and fault tolerant controls effectively are derived based on high dynamic characteristics of in-wheel motor and advantages of independent steer and drive. The maneuvering controller applies sliding and optimal control theories considering optimal torque distribution and friction circle related to the vertical tire force.
Category: Artificial Intelligence

[79] viXra:1210.0080 [pdf] submitted on 2012-10-16 13:31:05

SVM-DSmT Combination for Off-Line Signature Verification

Authors: Nassim Abbas, Youcef Chibani
Comments: 5 Pages.

We propose in this work a signature verification system based on decision combination of off-line signatures for managing conflict provided by the SVM classifiers. The system is basically divided into three modules: i) Radon Transform-SVM, ii) Ridgelet Transform-SVM and iii) PCR5 combination rule based on the generalized belief functions of Dezert-Smarandache theory. The proposed framework allows combining the normalized SVM outputs and uses an estimation technique based on the dissonant model of Appriou to compute the belief assignments. Decision making is performed through likelihood ratio. Experiments are conducted on the well known CEDAR database using false rejection and false acceptance criteria. The obtained results show that the proposed combination framework improves the verification accuracy compared to individual SVM classifiers.
Category: Artificial Intelligence

[78] viXra:1210.0079 [pdf] submitted on 2012-10-16 12:24:38

Generalizations in Extenics of the Location Value and Dependent Function from A Single Finite Interval to 2D, 3D, and n-D Spaces

Authors: Florentin Smarandache, Mihai Liviu Smarandache
Comments: 9 Pages.

Qiao-Xing Li and Xing-Sen Li have defined in 2011 the Location Value of a Point and the Dependent Function of a Point on a single finite or infinite interval. In this paper we extend their definitions from one dimension (1D) to 2D, 3D, and in general n-D spaces. Several examples are given in 2D and 3D spaces.
Category: Artificial Intelligence

[77] viXra:1209.0112 [pdf] submitted on 2012-09-30 14:55:09

Three Non-linear α-Discounting MCDM-Method Examples

Authors: Florentin Smarandache
Comments: 5 Pages.

In this paper we present three new examples of using the α-Discounting Multi-Criteria Decision Making Method in solving non-linear problems involving algebraic equations and inequalities in the decision process.
Category: Artificial Intelligence

[76] viXra:1208.0235 [pdf] submitted on 2012-08-30 09:31:38

The Navigation Mobile Robot Systems Using Bayesian Approach Through the Virtual Projection Method

Authors: Luige Vladareanu, Gabriela Tont, Victor Vladareanu, Florentin Smarandache, Lucian Capitanu
Comments: 6 Pages.

The paper presents the navigation mobile walking robot systems for movement in non-stationary and non-structured environments, using a Bayesian approach of Simultaneous Localization and Mapping (SLAM) for avoiding obstacles and dynamical stability control for motion on rough terrain. By processing inertial information of force, torque, tilting and wireless sensor networks (WSN) an intelligent high level algorithm is implementing using the virtual projection method. The control system architecture for the dynamic robot walking is presented in correlation with a stochastic model of assessing system probability of unidirectional or bidirectional transition states, applying the non-homogeneous/non-stationary Markov chains. The rationality and validity of the proposed model are demonstrated via an example of quantitative assessment of states probabilities of an autonomous robot. The results show that the proposed new navigation strategy of the mobile robot using Bayesian approach walking robot control systems for going around obstacles has increased the robot’s mobility and stability in workspace.
Category: Artificial Intelligence

[75] viXra:1208.0110 [pdf] submitted on 2012-08-19 00:10:25

Fabric Inspection System using Artificial Neural Networks

Authors: P. Banumathi, G. M. Nasira
Comments: 8 Pages.

Fabric inspection system is important to maintain the quality of fabric. Fabric inspection is carried out manually with human visual inspection for a long time. The work of inspectors is very tedious and consumes time and cost.To reduce the wastage of cost and time, automatic fabric inspection is required. This paper proposes an approach to recognize fabric defects in textile industry for minimizing production cost and time. The Fabric inspection system first acquires high quality vibration free images of the fabric. Then the acquired images are subjected to defect segmentation algorithm. The output of the processed image is used as an input to the Artificial Neural Network (ANN) which uses back propagation algorithm to calculate the weighted factors and generates the desired classification of defects as an output.
Category: Artificial Intelligence

[74] viXra:1208.0109 [pdf] submitted on 2012-08-19 00:11:50

Experience on re-Engineering Applying with Software Product Line

Authors: Waraporn Jirapanthong
Comments: 10 Pages.

In this paper, we present our experience based on a reengineering project. The software project is to re-engineer the original system of a company to answer the new requirements and changed business functions. Reengineering is a process that involves not only the software system, but also underlying business model. Particularly, the new business model is designed along with new technologies to support the new system. This paper presents our experience that applies with software product line approach to develop the new system supporting original business functions and new ones.
Category: Artificial Intelligence

[73] viXra:1208.0108 [pdf] submitted on 2012-08-19 00:16:35

Tea Insect Pests Classification Based on Artificial Neural Networks

Authors: R. K. Samanta, Indrajit Ghosh
Comments: 13 Pages.

Tea is one of the major health drinks of our society. It is a perennial crop in India and other countries. One of the production barriers of tea is insect pests. This paper presents an automatic diagnosis system for detecting tea insect pests based on artificial neural networks. We apply correlation-based feature selection (CFS) and incremental back propagation network (IBPLN). This is applied on a new database created by the authors based on the records of tea gardens of North Bengal Districts of India. We compare classification results with reduction of dimension and without reduction of dimension. The correct classification rate of the proposed system is 100% in both the cases.
Category: Artificial Intelligence

[72] viXra:1208.0063 [pdf] submitted on 2012-08-15 10:51:00

On the Travelling Salesman Algorithm: An Application

Authors: David Grace, Alessandro Waldron, Tahir Ahmad
Comments: 7 Pages.

The aim of this paper is to set up a simulation model of the production process of an aircraft company in order to obtain a tool for process analysis and decision support. To achieve this object has been used ProModel as simulation software. The advantages of all tools used in a correct and efficient internal movement, the different layouts and the possible usable materials handling system.
Category: Artificial Intelligence

[71] viXra:1208.0049 [pdf] submitted on 2012-08-12 06:17:32

种飞机图像目标多特征信息融合识别方法

Authors: Xin-De Li, Wei-Dong Yang, Jean Dezert
Comments: 10 Pages.

种基于概率神经网络(Probabilistic neural networks, PNN) 和DSmT 推理(Dezert-Smarandache theory) 的飞机图像目标多特征融合识别算法. 针对提取的多个图像特征量, 利用数据融合的思想对来自图像目标各个特征量提供的 信息进行融合处理. 首先, 对图像进行二值化预处理, 并提取Hu 矩、归一化转动惯量、仿射不变矩、轮廓离散化参数和奇异 值特征5 个特征量; 其次, 针对Dezert-Smarandache Theory 理论中信度赋值构造困难的问题, 利用PNN 网络, 构造目标识别率矩阵, 通过目标识 别率矩阵对证据源进行信度赋值; 然后, 用DSmT 组合规则在决策级层进行融合, 从而完成对飞机目标的识别; 最后, 在目标 图像小畸变情形下, 将本文提出的图像多特征信息融合方法和单一特征方法进行了对比测试实验, 结果表明本文方法在同等 条件下正确识别率得到了很大提高, 同时达到实时性要求, 而且具有有效拒判能力和目标图像尺寸不敏感性. 即使在大畸变情 况下, 识别率也能达到89.3 %.
Category: Artificial Intelligence

[70] viXra:1207.0062 [pdf] submitted on 2012-07-16 23:17:12

Generalization of the Dependent Function in Extenics for Nested Sets with Common Endpoints to 2D-Space, 3D-Space, and Generally to N-D-Space

Authors: Florentin Smarandache
Comments: 8 Pages.

In this paper we extend Prof. Yang Chunyan and Prof. Cai Wen’s dependent function of a point P with respect to two nested sets X0 X, for the case the sets X0 and X have common ending points, from 1D-space to n-D-space. We give several examples in 2D- and 3D-spaces. When computing the dependent function value k(.) of the optimal point O, we take its maximum possible value. Formulas for computing k(O), and the geometrical determination the Critical Zone are also given.
Category: Artificial Intelligence

[69] viXra:1207.0058 [pdf] submitted on 2012-07-16 05:14:14

Neutrosophic Masses & Indeterminate Models. Applications to Information Fusion

Authors: Florentin Smarandache
Comments: 7 Pages.

In this paper we introduce the indeterminate models in information fusion, which are due either to the existence of some indeterminate elements in the fusion space or to some indeterminate masses. The best approach for dealing with such models is the neutrosophic logic.
Category: Artificial Intelligence

[68] viXra:1207.0057 [pdf] submitted on 2012-07-16 05:15:50

Extended PCR Rules for Dynamic Frames

Authors: Florentin Smarandache, Jean Dezert
Comments: 8 Pages.

In most of classical fusion problems modeled from belief functions, the frame of discernment is considered as static. This means that the set of elements in the frame and the underlying integrity constraints of the frame are fixed forever and they do not change with time. In some applications, like in target tracking for example, the use of such invariant frame is not very appropriate because it can truly change with time. So it is necessary to adapt the Proportional Conflict Redistribution fusion rules (PCR5 and PCR6) for working with dynamical frames. In this paper, we propose an extension of PCR5 and PCR6 rules for working in a frame having some non-existential integrity constraints. Such constraints on the frame can arise in tracking applications by the destruction of targets for example. We show through very simple examples how these new rules can be used for the belief revision process.
Category: Artificial Intelligence

[67] viXra:1207.0056 [pdf] submitted on 2012-07-16 05:17:47

Comparative Study of Contradiction Measures in the Theory of Belief Functions

Authors: Florentin Smarandache, Deqiang Han, Arnaud Martin
Comments: 7 Pages.

Uncertainty measures in the theory of belief functions are important for the uncertainty representation and reasoning. Many measures of uncertainty in the theory of belief functions have been introduced. The degree of discord (or conflict) inside a body of evidence is an important index for measuring uncertainty degree. Recently, distance of evidence is used to define a contradiction measure for quantifying the degree of discord inside a body of evidence. The contradiction measure is actually the weighted summation of the distance values between a given basic belief assignment (bba) and the categorical bba’s defined on each focal element of the given bba redefined in this paper. It has normalized value and can well characterize the self-discord incorporated in bodies of evidence. We propose here, some numerical examples with comparisons among different uncertainty measures are provided, together with related analyses, to show the rationality of the proposed contradiction measure.
Category: Artificial Intelligence

[66] viXra:1207.0040 [pdf] submitted on 2012-07-11 05:41:10

P Vs. NP Solved

Authors: Gurpinder Singh
Comments: 1 Page. this is only existing proof of this problem

t
Category: Artificial Intelligence

[65] viXra:1207.0026 [pdf] submitted on 2012-07-06 10:56:56

Consensus Seeking on Moving Neighborhood Model of Random Sector Graphs

Authors: Mitra Ganguly, Timothy Eller
Comments: 5 Pages. technical report in NUI, #551

In this paper, we address consensus seeking problem of dynamical agents on random sector graphs. Random sector graphs are directed geometric graphs and have been investigated extensively. Each agent randomly walks on these graphs and communicates with each other if and only if they coincide on a node at the same time. Extensive simulations are performed to show that global consensus can be reached.
Category: Artificial Intelligence

[64] viXra:1206.0014 [pdf] submitted on 2012-06-04 23:37:54

Generalizations of the Distance and Dependent Function in Extenics to 2D, 3D, and n-D

Authors: Florentin Smarandache
Comments: 17 Pages.

Dr. Cai Wen defined in his 1983 paper: - the distance formula between a point x0 and a one-dimensional (1D) interval ; - and the dependence function which gives the degree of dependence of a point with respect to a pair of included 1D-intervals. His paper inspired us to generalize the Extension Set to two-dimensions, i.e. in plane of real numbers R2 where one has a rectangle (instead of a segment of line), determined by two arbitrary points A(a1, a2) and B(b1, b2). And similarly in R3, where one has a prism determined by two arbitrary points A(a1, a2, a3) and B(b1, b2, b3). We geometrically define the linear and nonlinear distance between a point and the 2D- and 3D-extension set and the dependent function for a nest of two included 2D- and 3D-extension sets. Linearly and non-linearly attraction point principles towards the optimal point are presented as well. The same procedure can be then used considering, instead of a rectangle, any bounded 2Dsurface and similarly any bounded 3D-solid, and any bounded n-D-body in Rn. These generalizations are very important since the Extension Set is generalized from onedimension to 2, 3 and even n-dimensions, therefore more classes of applications will result in consequence. Introduction.
Category: Artificial Intelligence

[63] viXra:1204.0081 [pdf] submitted on 2012-04-18 13:14:24

Erasure Techniques in MRD Codes

Authors: W. B. Vasantha Kandasamy, Florentin Smarandache, R. Sujatha, R. S. Raja Duray
Comments: 162 Pages.

In this book the notions of erasure techniques to MRD codes and concatenated MRD codes are introduced. Special type of concatenated supercodes using linear codes are given, which may find its application in networking.
Category: Artificial Intelligence

[62] viXra:1204.0080 [pdf] submitted on 2012-04-18 13:24:29

The Fifth Function of University: “Neutrosophic e-Function” of Communication-Collaboration-Integration of University in the Information Age

Authors: Florentin Smarandache, Stefan Vladutescu
Comments: 18 Pages.

The study is based on the following hypothesis with practical foundation: - Premise 1 - if two members of university on two continents meet on the Internet and initiate interdisciplinary scientific communication; - Premise 2 - subsequently, if within the curricular interests they develop an academic scientific collaboration; - Premise 3 - if the so-called collaboration integrates the interests of other members of the university; - Premise 4 - finally, if the university allows, accepts, validates and promotes such an approach; - Conclusion: then it means the university as a system (the global academic system) has, and it is, exerting a potential function to provide communication, collaboration and integration of research and of academic scientific experience.
Category: Artificial Intelligence

[61] viXra:1204.0002 [pdf] submitted on 2012-04-01 20:23:36

Correction of Inertial Navigation System’s Errors by the Help of Video-Based Navigator Based on Digital Terrarium Map

Authors: Oleg Kupervasser, Vladimir Voronov
Comments: 26 Pages.

This paper deals with the error analysis of a novel navigation algorithm that uses as input the sequence of images acquired from a moving camera and a Digital Terrain (or Elevation) Map (DTM/DEM). More specifically, it has been shown that the optical flow derived from two consecutive camera frames can be used in combination with a DTM to estimate the position, orientation and ego-motion parameters of the moving camera. As opposed to previous works, the proposed approach does not require an intermediate explicit reconstruction of the 3D world. In the present work the sensitivity of the algorithm outlined above is studied. The main sources for errors are identified to be the optical-flow evaluation and computation, the quality of the information about the terrain, the structure of the observed terrain and the trajectory of the camera. By assuming appropriate characterization of these error sources, a closed form expression for the uncertainty of the pose and motion of the camera is first developed and then the influence of these factors is confirmed using extensive numerical simulations. The main conclusion of this paper is to establish that the proposed navigation algorithm generates accurate estimates for reasonable scenarios and error sources, and thus can be effectively used as part of a navigation system of autonomous vehicles.
Category: Artificial Intelligence

[60] viXra:1201.0063 [pdf] submitted on 2012-01-16 05:22:32

Information – Entropy Theory of Artificial Intelligence

Authors: George Rajna
Comments: 2 Pages.

The basic theory on which one chess program can be constructed is that there exists a general characteristic of the game of chess, namely the concept of entropy. We can think about the positive logarithmic values as the measure of entropy and the negative logarithmic values as the measure of information.
Category: Artificial Intelligence

[59] viXra:1109.0042 [pdf] submitted on 19 Sep 2011

Applications of Neutrosophic Logic to Robotics. An Introduction

Authors: Florentin Smarandache, Luige Vladareanu
Comments: 6 pages

In this paper we present the N-norms/N-conorms in neutrosophic logic and set as extensions of T-norms/T-conorms in fuzzy logic and set. Then we show some applications of the neutrosophic logic to robotics.
Category: Artificial Intelligence

[58] viXra:1109.0041 [pdf] submitted on 19 Sep 2011

A Geometric Interpretation of the Neutrosophic Set - A Generalization of the Intuitionistic Fuzzy Set

Authors: Florentin Smarandache
Comments: 5 pages

In this paper we give a geometric interpretation of the Neutrosophic Set using the Neutrosophic Cube. Distinctions between the neutrosophic set and intuitionistic fuzzy set are also presented.
Category: Artificial Intelligence

[57] viXra:1107.0050 [pdf] submitted on 24 Jul 2011

A Methods of Neutrosophic Logia to Answer Queries in Relational Database

Authors: Smita Rajpal, M.N. Doja, Ranjit Biswas
Comments: 10 pages

Today Databases are Deterministic. An item belongs to the database is a probabilistic event, or a tuple is an answer to the query is a probabilistic event and it can be extended to all data models. Here we will discuss probabilistic relational data. Probabilistic relational Data are defined in two ways, Database is deterministic and Query answers are probabilistic or Database is probabilistic and Query answers are probabilistic. Probabilistic relational databases have been studied from the late 80's until today. But today Application Need to manage imprecision's in data. Imprecision can be of many types: non-matching data values, imprecise queries, inconsistent data, misaligned schemas, etc.
Category: Artificial Intelligence

[56] viXra:1106.0032 [pdf] submitted on 14 Jun 2011

Contradiction Measures and Specificity Degrees of Basic Belief Assignments

Authors: Florentin Smarandache, Arnaud Martin, Christophe Osswald
Comments: 8 Pages.

In the theory of belief functions, many measures of uncertainty have been introduced. However, it is not always easy to understand what these measures really try to represent. In this paper, we re-interpret some measures of uncertainty in the theory of belief functions. We present some interests and drawbacks of the existing measures. On these observations, we introduce a measure of contradiction. Therefore, we present some degrees of non-specificity and Bayesianity of a mass. We propose a degree of specificity based on the distance between a mass and its most specific associated mass. We also show how to use the degree of specificity to measure the specificity of a fusion rule. Illustrations on simple examples are given.
Category: Artificial Intelligence

[55] viXra:1101.0073 [pdf] submitted on 22 Jan 2011

Développement de Modèles de Fusion et de Classification Contextuelle D'images Satellitaires Par la Théorie de L'évidence et la Théorie du Raisonnement Plausible et Paradoxal

Authors: Nassim Abbas
Comments: 89 pages

La multiplication des satellites de télédétection et l'utilisation de plusieurs capteurs pour l'observation de la terre ont permis l'acquisition d'une multitude d'images présentant des caractéristiques spatiale, spectrale et temporelle différentes. L'extraction des informations utiles, liées à la nature physique des surfaces observées, fait appel à différentes techniques, approches et méthodes de traitement d'images numériques. Parmi ces procédures figure la fusion de données. Cette méthode permet d'exploiter le caractère redondant et complémentaire contenu dans les données satellitaires et doit prendre en compte des sources d'information de plus en plus nombreuses et variées.
Category: Artificial Intelligence

[54] viXra:1101.0069 [pdf] submitted on 22 Jan 2011

Normalization of Neutrosophic Relational Database

Authors: Smita Rajpal, Pariza Kamboj
Comments: 5 pages

In this paper authors have presented a method of normalizing a relational schema with Neutrosophic attributes into 1NF.This Method is called as Neutrosophic-First Normal Form(1NF(N)) a revision of First normal Form in Relational database. Authors are taking the Neutrosophic Relational database [3, 1] which is the extension of Fuzzy and Vague database to define the Neutrosophic- First Normal form.
Category: Artificial Intelligence

[53] viXra:1012.0013 [pdf] submitted on 3 Dec 2010

An Artificial Volition Architecture for Autonomous Robotics

Authors: T. E. Raptis
Comments: 18 pages

In this short presentation we introduce a new architecture capable of exhibiting a primordial type of volition in a simplified modularized version of M. Minsky's hive-mind. In this model, three relatively independent computational cores which themselves can also be whole multi-agent systems are engaged in an endless interaction each one representing the internal "imaginative" world, the external world interface and the arbitrator or Internal Observer. Volition then is expected to occur as the result of an endless antagonism for control between the internal and the external world models.
Category: Artificial Intelligence

[52] viXra:1010.0039 [pdf] submitted on 25 Oct 2010

Fusion of Imprecise Qualitative Information

Authors: Xin-De Li, Xian-Zhong Dai, Jean Dezert, Florentin Smarandache
Comments: 340 pages

In this paper, we present a new 2-tuple linguistic representation model, i.e. Distribution Function Model (DFM), for combining imprecise qualitative information using fusion rules drawn from Dezert-Smarandache Theory (DSmT) framework. Such new approach allows to preserve the precision and efficiency of the combination of linguistic information in the case of either equidistant or unbalanced label model. Some basic operators on imprecise 2-tuple labels are presented together with their extensions for imprecise 2-tuple labels. We also give simple examples to show how precise and imprecise qualitative information can be combined for reasoning under uncertainty. It is concluded that DSmT can deal efficiently with both precise and imprecise quantitative and qualitative beliefs, which extends the scope of this theory.
Category: Artificial Intelligence

[51] viXra:1009.0025 [pdf] submitted on 14 Mar 2010

Refined Labels for Qualitative Information Fusion in Decision-Making Support System

Authors: Florentin Smarandache, Jean Dezert, Xin-De Li
Comments: 8 pages

This paper introduces the Dezert-Smarandache (DSm) Field and Linear Algebra of Refined Labels (FLARL) useful for dealing accurately with qualitative information expressed in terms of qualitative belief functions. This work extends substantially our previous works done in DSmT framework which were mainly based on approximate qualitative operators. Here, new well justified accurate basic operators on qualitative labels (addition, subtraction, multiplication, division, root, power, etc) are presented. The end of this paper is devoted to an exemples of qualitative fusion rules based on this new FLARL approach for decision-making support.
Category: Artificial Intelligence

[50] viXra:1008.0067 [pdf] submitted on 13 Mar 2010

Target Type Tracking with a new Probabilistic Belief Transformation

Authors: Jean Dezert, Florentin Smarandache, Albena Tchamova, Pavlina Konstantinova
Comments: 8 pages

Abstract-In this paper we analyze the performances of a new probabilistic belief transformation, denoted DSmP, for the sequential estimation of target ID from classifier outputs in the Target Type Tracking problem (TTT). We complicate here a bit the TTT problem by considering three types of targets (Interceptor, Fighter and Cargo) and show through Monte-Carlo simulations the advantages of DSmP over the classical pignistic transformation which is classically used for decision-making under uncertainty when dealing with belief assignments. Based on our previous works for the justification of rules of combination for TTT problem, only the Proportional Conflict Redistribution rule and the hybrid fusion rules are considered in this work for their ability to deal consistently with high conflicting sources of evidence with three different belief assignment modelings.
Category: Artificial Intelligence

[49] viXra:1008.0026 [pdf] submitted on 10 Aug 2010

Threat Assessment of a Possible Vehicle-Borne Improvised Explosive Device Using DSmT

Authors: Jean Dezert, Florentin Smarandache
Comments: 24 pages

This paper presents the solution about the threat of a VBIED (Vehicle-Borne Improvised Explosive Device) obtained with the DSmT (Dezert-Smarandache Theory). This problem has been proposed recently to the authors by Simon Maskell and John Lavery as a typical illustrative example to try to compare the different approaches for dealing with uncertainty for decision-making support. The purpose of this paper is to show in details how a solid justified solution can be obtained from DSmT approach and its fusion rules thanks to a proper modeling of the belief functions involved in this problem.
Category: Artificial Intelligence

[48] viXra:1005.0080 [pdf] submitted on 20 May 2010

Multi-Criteria Decision Making Based on DSmT-Ahp

Authors: Jean Dezert, Jean-Marc Tacnet, Mireille Batton-Hubert, Florentin Smarandache
Comments: 6 pages

In this paper, we present an extension of the multicriteria decision making based on the Analytic Hierarchy Process (AHP) which incorporates uncertain knowledge matrices for generating basic belief assignments (bba's). The combination of priority vectors corresponding to bba's related to each (sub)-criterion is performed using the Proportional Conflict Redistribution rule no. 5 proposed in Dezert-Smarandache Theory (DSmT) of plausible and paradoxical reasoning. The method presented here, called DSmT-AHP, is illustrated on very simple examples.
Category: Artificial Intelligence

[47] viXra:1005.0079 [pdf] submitted on 20 May 2010

Non Bayesian Conditioning and Deconditioning

Authors: Jean Dezert, Florentin Smarandache
Comments: 6 pages

In this paper, we present a Non-Bayesian conditioning rule for belief revision. This rule is truly Non-Bayesian in the sense that it doesn't satisfy the common adopted principle that when a prior belief is Bayesian, after conditioning by X, Bel(X|X) must be equal to one. Our new conditioning rule for belief revision is based on the proportional conflict redistribution rule of combination developed in DSmT (Dezert-Smarandache Theory) which abandons Bayes' conditioning principle. Such Non-Bayesian conditioning allows to take into account judiciously the level of conflict between the prior belief available and the conditional evidence. We also introduce the deconditioning problem and show that this problem admits a unique solution in the case of Bayesian prior; a solution which is not possible to obtain when classical Shafer and Bayes conditioning rules are used. Several simple examples are also presented to compare the results between this new Non-Bayesian conditioning and the classical one.
Category: Artificial Intelligence

[46] viXra:1005.0077 [pdf] submitted on 19 May 2010

Fusion of Masses Defined on Infinite Countable Frames of Discernment

Authors: Florentin Smarandache, Arnaud Martin
Comments: 5 pages

In this paper we introduce for the first time the fusion of information on infinite discrete frames of discernment and we give general results of the fusion of two such masses using the Dempster's rule and the PCR5 rule for Bayesian and non-Bayesian cases.
Category: Artificial Intelligence

[45] viXra:1005.0076 [pdf] submitted on 19 May 2010

Degree of Uncertainty of a Set and of a Mass

Authors: Florentin Smarandache, Arnaud Martin
Comments: 9 pages

In this paper we use extend Harley's measure of uncertainty of a set and of mass to the degree of uncertainty of a set and of a mass (bba).
Category: Artificial Intelligence

[44] viXra:1005.0044 [pdf] submitted on 11 Mar 2010

Fuzzy Interval Matrices, Neutrosophic Interval Matrices and Their Applications

Authors: W. B. Vasantha Kandasamy, Florentin Smarandache
Comments: 304 pages

The new concept of fuzzy interval matrices has been introduced in this book for the first time. The authors have not only introduced the notion of fuzzy interval matrices, interval neutrosophic matrices and fuzzy neutrosophic interval matrices but have also demonstrated some of its applications when the data under study is an unsupervised one and when several experts analyze the problem. Further, the authors have introduced in this book multiexpert models using these three new types of interval matrices. The new multi expert models dealt in this book are FCIMs, FRIMs, FCInMs, FRInMs, IBAMs, IBBAMs, nIBAMs, FAIMs, FAnIMS, etc. Illustrative examples are given so that the reader can follow these concepts easily. This book has three chapters. The first chapter is introductory in nature and makes the book a self-contained one. Chapter two introduces the concept of fuzzy interval matrices. Also the notion of fuzzy interval matrices, neutrosophic interval matrices and fuzzy neutrosophic interval matrices, can find applications to Markov chains and Leontief economic models. Chapter three gives the application of fuzzy interval matrices and neutrosophic interval matrices to real-world problems by constructing the models already mentioned. Further these models are mainly useful when the data is an unsupervised one and when one needs a multi-expert model. The new concept of fuzzy interval matrices and neutrosophic interval matrices will find their applications in engineering, medical, industrial, social and psychological problems. We have given a long list of references to help the interested reader.
Category: Artificial Intelligence

[43] viXra:1004.0139 [pdf] submitted on 10 Mar 2010

Introduction to N-Adaptive Fuzzy Models to Analyze Public Opinion on Aids

Authors: W. B. Vasantha Kandasamy, Florentin Smarandache
Comments: 236 pages.

AIDS is not simply a physical malady, it is also an artifact of social and sexual transgression, violated taboo, fractured identity-political and personal projections. Its key words are primarily the property of the powerful. AIDS: Keywords - is my attempt to identify and contest some of the assumptions underlying our current 'knowledge'. In this effort I am joined by many AIDS activists including people living with AIDS - Acquired Immuno Deficiency Syndrome.
Category: Artificial Intelligence

[42] viXra:1004.0138 [pdf] submitted on 10 Mar 2010

General Combination Rules for Qualitative and Quantitative Beliefs

Authors: Arnaud Martin, Christophie Osswald, Jean Dezert, Florentin Smarandache
Comments: 23 pages.

Martin and Osswald [15] have recently proposed many generalizations of combination rules on quantitative beliefs in order to manage the conflict and to consider the specificity of the responses of the experts. Since the experts express themselves usually in natural language with linguistic labels, Smarandache and Dezert [13] have introduced a mathematical framework for dealing directly also with qualitative beliefs. In this paper we recall some element of our previous works and propose the new combination rules, developed for the fusion of both qualitative or quantitative beliefs.
Category: Artificial Intelligence

[41] viXra:1004.0094 [pdf] submitted on 19 Apr 2010

Neutrosophy in Situation Analysis

Authors: Anne-Laure Jousselme, Patrick Maupin
Comments: 7 pages.

In situation analysis (SA), an agent observing a scene receives information from heterogeneous sources of information including for example remote sensing devices, human reports and databases. The aim of this agent is to reach a certain level of awareness of the situation in order to make decisions. For the purpose of applications, this state of awareness can be conceived as a state of knowledge in the classical epistemic logic sense. Considering the logical connection between belief and knowledge, the challenge for the designer is to transform the raw, imprecise, conflictual and often paradoxical information received from the different sources into statements understandable by both man and machines. Hence, quantitative (i.e. measuring the world) and qualitative (i.e. reasoning about the structure of the world) information processing coexist in SA. A great challenge in SA is the conciliation of both aspects in mathematical and logical frameworks. As a consequence, SA applications need frameworks general enough to take into account the different types of uncertainty and information present in the SA context, doubled with a semantics allowing meaningful reasoning on situations. The aim of this paper is to evaluate the capacity of neutrosophic logic and Dezert- Smarandache theory (DSmT) to cope with the ontological and epistemological problems of SA.
Category: Artificial Intelligence

[40] viXra:1004.0057 [pdf] submitted on 9 Apr 2010

Importance of Sources Using the Repeated Fusion Method and the Proportional Conflict Redistribution Rules #5 and #6

Authors: Florentin Smarandache, Jean Dezert
Comments: 6 pages

We present in this paper some examples of how to compute by hand the PCR5 fusion rule for three sources, so the reader will better understand its mechanism. We also take into consideration the importance of sources, which is different from the classical discounting of sources.
Category: Artificial Intelligence

[39] viXra:1004.0052 [pdf] submitted on 8 Mar 2010

A Simple Proportional Conflict Redistribution Rule

Authors: Florentin Smarandache, Jean Dezert
Comments: 21 pages

One proposes a first alternative rule of combination to WAO (Weighted Average Operator) proposed recently by Josang, Daniel and Vannoorenberghe, called Proportional Conflict Redistribution rule (denoted PCR1). PCR1 and WAO are particular cases of WO (the Weighted Operator) because the conflicting mass is redistributed with respect to some weighting factors. In this first PCR rule, the proportionalization is done for each non-empty set with respect to the non-zero sum of its corresponding mass matrix - instead of its mass column average as in WAO, but the results are the same as Ph. Smets has pointed out. Also, we extend WAO (which herein gives no solution) for the degenerate case when all column sums of all non-empty sets are zero, and then the conflicting mass is transferred to the non-empty disjunctive form of all non-empty sets together; but if this disjunctive form happens to be empty, then one considers an open world (i.e. the frame of discernment might contain new hypotheses) and thus all conflicting mass is transferred to the empty set. In addition to WAO, we propose a general formula for PCR1 (WAO for non-degenerate cases). Several numerical examples and comparisons with other rules for combination of evidence published in literature are presented too. Another distinction between these alternative rules is that WAO is defined on the power set, while PCR1 is on the hyper-power set (Dedekind's lattice). A nice feature of PCR1, is that it works not only on non-degenerate cases but also on degenerate cases as well appearing in dynamic fusion, while WAO gives the sum of masses in this cases less than 1 (WAO does not work in these cases). Meanwhile we show that PCR1 and WAO do not preserve unfortunately the neutrality property of the vacuous belief assignment though the fusion process. This severe drawback can however be easily circumvented by new PCR rules presented in a companion paper.
Category: Artificial Intelligence

[38] viXra:1004.0009 [pdf] submitted on 8 Mar 2010

Neutrosophic Set - A Generalization of the Intuitionistic Fuzzy Set

Authors: Florentin Smarandache
Comments: 7 pages

In this paper one generalizes the intuitionistic fuzzy set (IFS), paraconsistent set, and intuitionistic set to the neutrosophic set (NS). Many examples are presented. Distinctions between NS and IFS are underlined.
Category: Artificial Intelligence

[37] viXra:1004.0008 [pdf] submitted on 8 Mar 2010

Neutrosophic Logic - A Generalization of the Intuitionistic Fuzzy Logic

Authors: Florentin Smarandache
Comments: 7 pages

In this paper one generalizes the intuitionistic fuzzy logic (IFL) and other logics to neutrosophic logic (NL). The differences between IFL and NL (and the corresponding intuitionistic fuzzy set and neutrosophic set) are pointed out.
Category: Artificial Intelligence

[36] viXra:1004.0005 [pdf] submitted on 8 Mar 2010

Uniform and Partially Uniform Redistribution Rules

Authors: Florentin Smarandache, Jean Dezert
Comments: 4 pages

This short paper introduces two new fusion rules for combining quantitative basic belief assignments. These rules although very simple have not been proposed in literature so far and could serve as useful alternatives because of their low computation cost with respect to the recent advanced Proportional Conflict Redistribution rules developed in the DSmT framework.
Category: Artificial Intelligence

[35] viXra:1004.0004 [pdf] submitted on 8 Mar 2010

Neutrosophic Logic Based Semantic Web Services Agent

Authors: Haibin Wang, Yan-Qing Zhang, Rajshekhar Sunderraman, Florentin Smarandache
Comments: 15 pages

In this paper we propose a framework called Semanic Web Services (see paper for full abstract)
Category: Artificial Intelligence

[34] viXra:1003.0257 [pdf] submitted on 8 Mar 2010

α-Discounting Method for Multi-Criteria Decision Making

Authors: Florentin Smarandache
Comments: 26 pages

In this paper we introduce a new procedure called α-Discounting Method for Multi-Criteria Decision Making (α-D MCDM), which is as an alternative and extension of Saaty's Analytical Hierarchy Process (AHP). It works for any set of preferences that can be transformed into a system of homogeneous linear equations. A degree of consistency (and implicitly a degree of inconsistency) of a decision-making problem are defined. α-D MCDM is generalized to a set of preferences that can be transformed into a system of linear and/or non-linear homogeneous and/or non-homogeneous equations and/or inequalities. Many consistent, weak inconsistent, and strong inconsistent examples are given.
Category: Artificial Intelligence

[33] viXra:1003.0252 [pdf] submitted on 26 Mar 2010

Ornamental Sign Language in the First Order Tracery Belts

Authors: Modris Tenisons, Dainis Zeps
Comments: 18 pages

We consider ornamental sign language of first order where principles of sieve displacement, of asymmetric building blocks as base of ornament symmetry, color exchangeability and side equivalence principles work. The generic aspects of sieve and genesis of ornamental pattern and ornament sign in it are discussed. The hemiolia principle for ornamental genesis is introduced. The discoverer of most of these principles were artist Modris Tenisons [4, 5, 6, 7 (refs. 23, 24), 8 (ref. 65)]. Here we apply systematical research using simplest mathematical arguments. We come to conclusions that mathematical argument in arising ornament is of much more significance than simply symmetries in it as in image. We are after to inquire how ornament arises from global aspects intertwinned with these local. We raise argument of sign's origin from code rather from image, and its eventual impact on research of ornamental patterns, and on research of human prehension of sign and its connection with consciousness.
Category: Artificial Intelligence

[32] viXra:1003.0232 [pdf] submitted on 7 Mar 2010

Fuzzy Cognitive Maps and Neutrosophic Cognitive Maps

Authors: W. B. Vasantha Kandasamy, Florentin Smarandache
Comments: 213 pages

In a world of chaotic alignments, traditional logic with its strict boundaries of truth and falsity has not imbued itself with the capability of reflecting the reality. Despite various attempts to reorient logic, there has remained an essential need for an alternative system that could infuse into itself a representation of the real world. Out of this need arose the system of Neutrosophy, and its connected logic, Neutrosophic Logic. Neutrosophy is a new branch of philosophy that studies the origin, nature and scope of neutralities, as well as their interactions with different ideational spectra. This was introduced by one of the authors, Florentin Smarandache. A few of the mentionable characteristics of this mode of thinking are [90-94]: It proposes new philosophical theses, principles, laws, methods, formulas and movements; it reveals that the world is full of indeterminacy; it interprets the uninterpretable; regards, from many different angles, old concepts, systems and proves that an idea which is true in a given referential system, may be false in another, and vice versa; attempts to make peace in the war of ideas, and to make war in the peaceful ideas! The main principle of neutrosophy is: Between an idea and its opposite , there is a continuum-power spectrum of Neutralities. This philosophy forms the basis of Neutrosophic logic.
Category:
Artificial Intelligence

[31] viXra:1003.0209 [pdf] submitted on 6 Mar 2010

Advances and Applications of DSmT for Information Fusion Collected Works Volume 2

Authors: Florentin Smarandache, Jean Dezert
Comments: 461 pages

This second book devoted on advances and applications of Dezert-Smarandache Theory (DSmT) for information fusion collects recent papers from different researchers working in engineering and mathematics. Part 1 of this book presents the current state-of-the-art on theoretical investigations while, Part 2 presents several applications of this new theory. Some ideas in this book are still under current development or improvements, but we think it is important to propose them in order to share ideas and motivate new debates with people interested in new reasoning methods and information fusion. So, we hope that this second volume on DSmT will continue to stir up some interests to researchers and engineers working in data fusion and in artificial intelligence.
Category: Artificial Intelligence

[30] viXra:1003.0208 [pdf] submitted on 6 Mar 2010

Advances and Applications of DSmT for Information Fusion Collected Works Volume 1

Authors: Florentin Smarandache, Jean Dezert
Comments: 438 pages

This book is devoted to an emerging branch of Information Fusion based on new approach for modelling the fusion problematic when the information provided by the sources is both uncertain and (highly) conflicting. This approach, known in literature as DSmT (standing for Dezert-Smarandache Theory), proposes new useful rules of combinations. We gathered in this volume a presentation of DSmT from the beginning to the latest development. Part 1 of this book presents the current state-of-the-art on theoretical investigations while Part 2 presents several applications of this new theory. We hope that this first book on DSmT will stir up some interests to researchers and engineers working in data fusion and in artificial intelligence. Many simple but didactic examples are proposed throughout the book. As a young emerging theory, DSmT is probably not exempt from improvements and its development will continue to evolve over the years. We just want through this book to propose a new look at the Information Fusion problematic and open a new track to attack the combination of information.
Category: Artificial Intelligence

[29] viXra:1003.0197 [pdf] submitted on 6 Mar 2010

Application of Probabilistic PCR5 Fusion Rule for Multisensor Target Tracking

Authors: Aloïs Kirchnera, Frédéric Dambrevilleb, Francis Celeste, Florentin Smarandache, Jean Dezert
Comments: 9 pages

This paper defines and implements a non-Bayesian fusion rule for combining densities of probabilities estimated by local (non-linear) filters for tracking a moving target by passive sensors. This rule is the restriction to a strict probabilistic paradigm of the recent and efficient Proportional Conflict Redistribution rule no 5 (PCR5) developed in the DSmT framework for fusing basic belief assignments. A sampling method for probabilistic PCR5 (p-PCR5) is defined. It is shown that p-PCR5 is more robust to an erroneous modeling and allows to keep the modes of local densities and preserve as much as possible the whole information inherent to each densities to combine. In particular, p-PCR5 is able of maintaining multiple hypotheses/modes after fusion, when the hypotheses are too distant in regards to their deviations. This new p-PCR5 rule has been tested on a simple example of distributed non-linear filtering application to show the interest of such approach for future developments. The non-linear distributed filter is implemented through a basic particles filtering technique. The results obtained in our simulations show the ability of this p-PCR5-based filter to track the target even when the models are not well consistent in regards to the initialization and real cinematic. Keywords: Filtering, Robust estimation, non-Bayesian fusion rule, PCR5, Particle filtering.
Category: Artificial Intelligence

[28] viXra:1003.0196 [pdf] submitted on 6 Mar 2010

Qualitative Belief Conditioning Rules (QBCR)

Authors: Florentin Smarandache, Jean Dezert
Comments: 13 pages

In this paper we extend the new family of (quantitative) Belief Conditioning Rules (BCR) recently developed in the Dezert-Smarandache Theory (DSmT) to their qualitative counterpart for belief revision. Since the revision of quantitative as well as qualitative belief assignment given the occurrence of a new event (the conditioning constraint) can be done in many possible ways, we present here only what we consider as the most appealing Qualitative Belief Conditioning Rules (QBCR) which allow to revise the belief directly with words and linguistic labels and thus avoids the introduction of ad-hoc translations of quantitative beliefs into quantitative ones for solving the problem.
Category: Artificial Intelligence

[27] viXra:1003.0195 [pdf] submitted on 6 Mar 2010

Enrichment of Qualitative Beliefs for Reasoning Under Uncertainty

Authors: Xin-De Li, Xinhan Huang, Florentin Smarandache, Jean Dezert
Comments: 12 pages

This paper deals with enriched qualitative belief functions for reasoning under uncertainty and for combining information expressed in natural language through linguistic labels. In this work, two possible enrichments (quantitative and/or qualitative) of linguistic labels are considered and operators (addition, multiplication, division, etc) for dealing with them are proposed and explained. We denote them qe-operators, qe standing for "qualitative-enriched" operators. These operators can be seen as a direct extension of the classical qualitative operators (q-operators) proposed recently in the Dezert-Smarandache Theory of plausible and paradoxist reasoning (DSmT). q-operators are also justified in details in this paper. The quantitative enrichment of linguistic label is a numerical supporting degree in [0,∞), while the qualitative enrichment takes its values in a finite ordered set of linguistic values. Quantitative enrichment is less precise than qualitative enrichment, but it is expected more close with what human experts can easily provide when expressing linguistic labels with supporting degrees. Two simple examples are given to show how the fusion of qualitative-enriched belief assignments can be done.
Category: Artificial Intelligence

[26] viXra:1003.0181 [pdf] submitted on 6 Mar 2010

Proportional Conflict Redistribution Rules for Information Fusion

Authors: Florentin Smarandache, Jean Dezert
Comments: 41 pages

In this paper we propose five versions of a Proportional Conflict Redistribution rule (PCR) for information fusion together with several examples. From PCR1 to PCR2, PCR3, PCR4, PCR5 one increases the complexity of the rules and also the exactitude of the redistribution of conflicting masses. PCR1 restricted from the hyper-power set to the power set and without degenerate cases gives the same result as the Weighted Average Operator (WAO) proposed recently by Jøsang, Daniel and Vannoorenberghe but does not satisfy the neutrality property of vacuous belief assignment. That's why improved PCR rules are proposed in this paper. PCR4 is an improvement of minC and Dempster's rules. The PCR rules redistribute the conflicting mass, after the conjunctive rule has been applied, proportionally with some functions depending on the masses assigned to their corresponding columns in the mass matrix. There are infinitely many ways these functions (weighting factors) can be chosen depending on the complexity one wants to deal with in specific applications and fusion systems. Any fusion combination rule is at some degree ad-hoc.
Category: Artificial Intelligence

[25] viXra:1003.0174 [pdf] submitted on 6 Mar 2010

Redesigning Decision Matrix Method with an Indeterminacy-Based Inference Process

Authors: Jose L. Salmeron, Florentin Smarandache
Comments: 12 pages

For academics and practitioners concerned with computers, business and mathematics, one central issue is supporting decision makers. In this paper, we propose a generalization of Decision Matrix Method (DMM), using Neutrosophic logic. It emerges as an alternative to the existing logics and it represents a mathematical model of uncertainty and indeterminacy. This paper proposes the Neutrosophic Decision Matrix Method as a more realistic tool for decision making. In addition, a de-neutrosophication process is included.
Category: Artificial Intelligence

[24] viXra:1003.0165 [pdf] submitted on 6 Mar 2010

A Neutrosophic Description Logic

Authors: Haibin Wang, André Rogatko, Florentin Smarandache, Rajshekhar Sunderraman
Comments: 19 pages

Description Logics (DLs) are appropriate, widely used, logics for managing structured knowledge. They allow reasoning about individuals and concepts, i.e. set of individuals with common properties. Typically, DLs are limited to dealing with crisp, well defined concepts. That is, concepts for which the problem whether an individual is an instance of it is a yes/no question. More often than not, the concepts encountered in the real world do not have a precisely defined criteria of membership: we may say that an individual is an instance of a concept only to a certain degree, depending on the individual's properties. The DLs that deal with such fuzzy concepts are called fuzzy DLs. In order to deal with fuzzy, incomplete, indeterminate and inconsistent concepts, we need to extend the capabilities of fuzzy DLs further. In this paper we will present an extension of fuzzy ALC, combining Smarandache's neutrosophic logic with a classical DL. In particular, concepts become neutrosophic (here neutrosophic means fuzzy, incomplete, indeterminate and inconsistent), thus, reasoning about such neutrosophic concepts is supported. We will define its syntax, its semantics, describe its properties and present a constraint propagation calculus for reasoning in it.
Category: Artificial Intelligence

[23] viXra:1003.0161 [pdf] submitted on 6 Mar 2010

DSmT: a New Paradigm Shift for Information Fusion

Authors: Jean Dezert, Florentin Smarandache
Comments: 11 pages

The management and combination of uncertain, imprecise, fuzzy and even paradoxical or high conflicting sources of information has always been and still remains of primal importance for the development of reliable information fusion systems. In this short survey paper, we present the theory of plausible and paradoxical reasoning, known as DSmT (Dezert-Smarandache Theory) in literature, developed for dealing with imprecise, uncertain and potentially highly conflicting sources of information. DSmT is a new paradigm shift for information fusion and recent publications have shown the interest and the potential ability of DSmT to solve fusion problems where Dempster's rule used in Dempster-Shafer Theory (DST) provides counter-intuitive results or fails to provide useful result at all. This paper is focused on the foundations of DSmT and on its main rules of combination (classic, hybrid and Proportional Conflict Redistribution rules). Shafer's model on which is based DST appears as a particular and specific case of DSm hybrid model which can be easily handled by DSmT as well. Several simple but illustrative examples are given throughout this paper to show the interest and the generality of this new theory.
Category: Artificial Intelligence

[22] viXra:1003.0159 [pdf] submitted on 6 Mar 2010

An Introduction to the DSm Theory for the Combination of Paradoxical, Uncertain, and Imprecise Sources of Information

Authors: Florentin Smarandache, Jean Dezert
Comments: 21 pages

The management and combination of uncertain, imprecise, fuzzy and even paradoxical or high conflicting sources of information has always been, and still remains today, of primal importance for the development of reliable modern information systems involving artificial reasoning. In this introduction, we present a survey of our recent theory of plausible and paradoxical reasoning, known as Dezert-Smarandache Theory (DSmT) in the literature, developed for dealing with imprecise, uncertain and paradoxical sources of information. We focus our presentation here rather on the foundations of DSmT, and on the two important new rules of combination, than on browsing specific applications of DSmT available in literature. Several simple examples are given throughout the presentation to show the efficiency and the generality of this new approach.
Category: Artificial Intelligence

[21] viXra:1003.0157 [pdf] submitted on 6 Mar 2010

Fusion of Qualitative Beliefs Using DSmT

Authors: Florentin Smarandache, Jean Dezert
Comments: 13 pages

This paper introduces the notion of qualitative belief assignment to model beliefs of human experts expressed in natural language (with linguistic labels). We show how qualitative beliefs can be efficiently combined using an extension of Dezert-Smarandache Theory (DSmT) of plausible and paradoxical quantitative reasoning to qualitative reasoning. We propose a new arithmetic on linguistic labels which allows a direct extension of classical DSm fusion rule or DSm Hybrid rules. An approximate qualitative PCR5 rule is also proposed jointly with a Qualitative Average Operator. We also show how crisp or interval mappings can be used to deal indirectly with linguistic labels. A very simple example is provided to illustrate our qualitative fusion rules.
Category: Artificial Intelligence

[20] viXra:1003.0156 [pdf] submitted on 6 Mar 2010

Target Type Tracking with PCR5 and Dempster's Rules: a Comparative Analysis

Authors: Jean Dezert, Albena Tchamova, Florentin Smarandache, Pavlina Konstantinova
Comments: 10 pages

In this paper we consider and analyze the behavior of two combinational rules for temporal (sequential) attribute data fusion for target type estimation. Our comparative analysis is based on Dempster's fusion rule proposed in Dempster-Shafer Theory (DST) and on the Proportional Conflict Redistribution rule no. 5 (PCR5) recently proposed in Dezert-Smarandache Theory (DSmT). We show through very simple scenario and Monte-Carlo simulation, how PCR5 allows a very efficient Target Type Tracking and reduces drastically the latency delay for correct Target Type decision with respect to Demspter's rule. For cases presenting some short Target Type switches, Demspter's rule is proved to be unable to detect the switches and thus to track correctly the Target Type changes. The approach proposed here is totally new, efficient and promising to be incorporated in real-time Generalized Data Association - Multi Target Tracking systems (GDA-MTT) and provides an important result on the behavior of PCR5 with respect to Dempster's rule. The MatLab source code is provided in [5].
Category: Artificial Intelligence

[19] viXra:1003.0155 [pdf] submitted on 6 Mar 2010

Processing Uncertainty and Indeterminacy in Information Systems Projects Success Mapping

Authors: Jose L. Salmeron, Florentin Smarandache
Comments: 13 pages

IS projects success is a complex concept, and its evaluation is complicated, unstructured and not readily quantifiable. Numerous scientific publications address the issue of success in the IS field as well as in other fields. But, little efforts have been done for processing indeterminacy and uncertainty in success research. This paper shows a formal method for mapping success using Neutrosophic Success Map. This is an emerging tool for processing indeterminacy and uncertainty in success research. EIS success have been analyzed using this tool.
Category: Artificial Intelligence

[18] viXra:1003.0154 [pdf] submitted on 6 Mar 2010

The Combination of Paradoxical, Uncertain and Imprecise Sources of Information based on DSmT and Neutro-Fuzzy Inference

Authors: Florentin Smarandache, Jean Dezert
Comments: 20 pages

The management and combination of uncertain, imprecise, fuzzy and even paradoxical or high conflicting sources of information has always been, and still remains today, of primal importance for the development of reliable modern information systems involving artificial reasoning. In this chapter, we present a survey of our recent theory of plausible and paradoxical reasoning, known as Dezert-Smarandache Theory (DSmT) in the literature, developed for dealing with imprecise, uncertain and paradoxical sources of information. We focus our presentation here rather on the foundations of DSmT, and on the two important new rules of combination, than on browsing specific applications of DSmT available in literature. Several simple examples are given throughout the presentation to show the efficiency and the generality of this new approach. The last part of this chapter concerns the presentation of the neutrosophic logic, the neutro-fuzzy inference and its connection with DSmT. Fuzzy logic and neutrosophic logic are useful tools in decision making after fusioning the information using the DSm hybrid rule of combination of masses.
Category: Artificial Intelligence

[17] viXra:1003.0152 [pdf] submitted on 6 Mar 2010

The Generalized Pignistic Transformation

Authors: Jean Dezert, Florentin Smarandache, Milan Daniel
Comments: 11 pages

This paper presents in detail the generalized pignistic transformation (GPT) succinctly developed in the Dezert-Smarandache Theory (DSmT) framework as a tool for decision process. The GPT allows to provide a subjective probability measure from any generalized basic belief assignment given by any corpus of evidence. We mainly focus our presentation on the 3D case and provide the complete result obtained by the GPT and its validation drawn from the probability theory.
Category: Artificial Intelligence

[16] viXra:1003.0150 [pdf] submitted on 6 Mar 2010

On the Tweety Penguin Triangle Problem

Authors: Jean Dezert, Florentin Smarandache
Comments: 17 pages

In this paper, one studies the famous well-known and challenging Tweety Penguin Triangle Problem (TPTP or TP2) pointed out by Judea Pearl in one of his books. We first present the solution of the TP2 based on the fallacious Bayesian reasoning and prove that reasoning cannot be used to conclude on the ability of the penguin-bird Tweety to fly or not to fly. Then we present in details the counter-intuitive solution obtained from the Dempster-Shafer Theory (DST). Finally, we show how the solution can be obtained with our new theory of plausible and paradoxical reasoning (DSmT)
Category: Artificial Intelligence

[15] viXra:1003.0149 [pdf] submitted on 6 Mar 2010

Infinite Classes of Counter-Examples to the Dempster's Rule of Combination

Authors: Jean Dezert, Florentin Smarandache
Comments: 13 pages

This paper presents several classes of fusion problems which cannot be directly attacked by the classical mathematical theory of evidence, also known as the Dempster-Shafer Theory (DST) either because the Shafer's model for the frame of discernment is impossible to obtain or just because the Dempster's rule of combination fails to provide coherent results (or no result at all). We present and discuss the potentiality of the DSmT combined with its classical (or hybrid) rule of combination to attack these infinite classes of fusion problems.
Category: Artificial Intelligence

[14] viXra:1003.0148 [pdf] submitted on 6 Mar 2010

Combining Uncertain and Paradoxical Evidences for DSm Hybrid Models

Authors: Jean Dezert, Florentin Smarandache
Comments: 33 pages

This paper presents a general method for combining uncertain and paradoxical source of evidences for a wide class of fusion problems. From the foundations of the Dezert-Smarandache Theory (DSmT) we show how the DSm rule of combination can be adapted to take into account all possible integrity constraints (if any) of the problem under consideration due to the true nature of elements/concepts involved into it. We show how the Shafer's model can be considered as a specific DSm hybrid model and be easily handled by our approach and a new efficient rule of combination different from the Dempster's rule is obtained. Several simple examples are also provided to show the efficiency and the generality of the approach proposed in this work.
Category: Artificial Intelligence

[13] viXra:1003.0147 [pdf] submitted on 6 Mar 2010

On the Generation of Hyper-Powersets for the DSmT

Authors: Jean Dezert, Florentin Smarandache
Comments: 11 pages

The recent theory of plausible and paradoxical reasoning (DSmT) developed by the authors appears to be a nice promising theoretical tools to solve many information fusion problems where the Shafer's model cannot be used due to the intrinsic paradoxical nature of the elements of the frame of discernment and where a strong internal conflict between sources arises. The main idea of DSmT is to work on the hyper-powerset of the frame of discernment of the problem under consideration. Although the definition of hyper-powerset is well established, the major difficulty in practice is to generate such hyper-powersets in order to implement DSmT fusion rule on computers. We present in this paper a simple algorithm for generating hyper-powersets and discuss the limitations of our actual computers to generate such hyper-powersets when the dimension of the problem increases.
Category: Artificial Intelligence

[12] viXra:1003.0146 [pdf] submitted on 6 Mar 2010

Partial Ordering of Hyper-Powersets and Matrix Representation of Belief Functions Within DSmT

Authors: Jean Dezert, Florentin Smarandache
Comments: 13 pages

In this paper, we examine several issues for ordering or partially ordering elements of hyperpowertsets involved in the recent theory of plausible, uncertain and paradoxical reasoning (DSmT) developed by the authors. We will show the benefit of some of these issues to obtain a nice and useful matrix representation of belief functions.
Category: Artificial Intelligence

[11] viXra:1003.0114 [pdf] submitted on 6 Mar 2010

On Rugina's System of Thought

Authors: Florentin Smarandache
Comments: 30 pages

In this article one investigates Rugina's Orientation Table and one gives particular examples for several of its seven models. Leon Walras's Economics of Stable Equilibrium and Keynes's Economics of Disequilibrium are combined in Rugina's Orientation Table in systems which are s% stable and 100-s% unstable, where s may be 100, 95, 65, 50, 35, 5, and 0. The Classical Logic and Modern Logic are united in Rugina's Integrated Logic, and then generalized in the Neutrosophic Logic.
Category: Artificial Intelligence

[10] viXra:1003.0110 [pdf] submitted on 6 Mar 2010

Comments on "A New Combination of Evidence Based on Compromise"

Authors: Jean Dezert, Arnaud Martin, Florentin Smarandache
Comments: 5 pages

Comments on "A new combination of evidence based on compromise"
Category: Artificial Intelligence

[9] viXra:1003.0108 [pdf] submitted on 6 Mar 2010

A Class of DSm Conditioning Rules

Authors: Florentin Smarandache, Mark Alford
Comments: 9 pages

In this paper we introduce two new DSm fusion conditioning rules with example, and as a generalization of them a class of DSm fusion conditioning rules, and then extend them to a class of DSm conditioning rules.
Category: Artificial Intelligence

[8] viXra:1003.0101 [pdf] submitted on 6 Mar 2010

A New Class Fusion Rule for Solving Blackman's Association Problem

Authors: Albena Tchamova, Jean Dezert, Florentin Smarandache
Comments: 6 pages

This paper presents a new approach for solving the paradoxical Blackman's Association Problem. It utilizes the recently defined new class fusion rule based on fuzzy Tconorm/ T-norm operators together with Dezert-Smarandache theory based, relative variations of generalized pignistic probabilities measure of correct associations, defined from a partial ordering function of hyper-power set. The ability of this approach to solve the problem against the classical Dempster-Shafer's method, proposed in the literature is proven. It is shown that the approach improves the separation power of the decision process for this association problem.
Category: Artificial Intelligence

[7] viXra:1003.0100 [pdf] submitted on 6 Mar 2010

On the Blackman's Association Problem

Authors: Jean Dezert, Florentin Smarandache, Albena Tchamova
Comments: 11 pages

Modern multitarget-multisensor tracking systems involve the development of reliable methods for the data association and the fusion of multiple sensor information, and more specifically the partioning of observations into tracks. This paper discusses and compares the application of Dempster-Shafer Theory (DST) and the Dezert-Smarandache Theory (DSmT) methods to the fusion of multiple sensor attributes for target identification purpose. We focus our attention on the paradoxical Blackman's association problem and propose several approaches to outperfom Blackman's solution. We clarify some preconceived ideas about the use of degree of conflict between sources as potential criterion for partitioning evidences.
Category: Artificial Intelligence

[6] viXra:1003.0094 [pdf] submitted on 6 Mar 2010

Belief Conditioning Rules

Authors: Florentin Smarandache, Jean Dezert
Comments: 27 pages

In this paper we propose a new family of Belief Conditioning Rules (BCR) for belief revision. These rules are not directly related with the fusion of several sources of evidence but with the revision of a belief assignment available at a given time according to the new truth (i.e. conditioning constraint) one has about the space of solutions of the problem.
Category: Artificial Intelligence

[5] viXra:1003.0083 [pdf] submitted on 5 Mar 2010

Artificial Intelligence and Responsive Optimization

Authors: M. Khoshnevisan, Sukanto Bhattacharya, Florentin Smarandache
Comments: 87 pages

The purpose of this book is to apply the Artificial Intelligence and control systems to different real models.
Category: Artificial Intelligence

[4] viXra:1003.0064 [pdf] submitted on 6 Mar 2010

Adaptative Combination Rule and Proportional Conflict Redistribution Rule for Information Fusion

Authors: M. C. Florea, J. Dezert, P. Valin, Florentin Smarandache, Anne-Laure Jousselme
Comments: 8 pages

This paper presents two new promising combination rules for the fusion of uncertain and potentially highly conflicting sources of evidences in the theory of belief functions established first in Dempster-Shafer Theory (DST) and then recently extended in Dezert-Smarandache Theory (DSmT). Our work is to provide here new issues to palliate the well-known limitations of Dempster's rule and to work beyond its limits of applicability. Since the famous Zadeh's criticism of Dempster's rule in 1979, many researchers have proposed new interesting alternative rules of combination to palliate the weakness of Dempster's rule in order to provide acceptable results specially in highly conflicting situations. In this work, we present two new combination rules: the class of Adaptive Combination Rules (ACR) and a new efficient Proportional Conflict Redistribution (PCR) rule. Both rules allow to deal with highly conflicting sources for static and dynamic fusion applications. We present some interesting properties for ACR and PCR rules and discuss some simulation results obtained with both rules for Zadeh's problem and for a target identification problem.
Category: Artificial Intelligence

[3] viXra:1003.0060 [pdf] submitted on 6 Mar 2010

DSmT Qualitative Reasoning Based on 2-Tuple Linguistic Representation Model

Authors: Xin-De Li, Xian-Zhong Dai, Jean Dezert, Florentin Smarandache
Comments: 6 pages

Most of modern systems for information retrieval, fusion and management have to deal more and more with information expressed quatitatively (by linguistic labels) since human reports are better and easier expressed in natural language than with numbers. In this paper, we propose to use Herrera-Martínez' 2-Tuple linguistic representation model (i.e. equidistant linguistic labels with a numeric value assessment) for reasoning with uncertain and qualitative information in Dezert-Smarandache Theory (DSmT) framework to preserve the precision and the efficiency of the fusion of linguistic information expressing the expert's qualitative beliefs. We present operators to deal with the 2-Tuples and show from a simple example how qualitative DSmT-based fusion rules can be used for qualitative reasoning and fusioning under uncertainty.
Category: Artificial Intelligence

[2] viXra:1003.0059 [pdf] submitted on 6 Mar 2010

Combination of Qualitative Information with 2-Tuple Linguistic Representation in Dezert-Smarandache Theory

Authors: Xin-De Li, Florentin Smarandache, Xian-Zhong Dai
Comments: 12 pages

Modern systems for information retrieval, fusion and management need to deal more and more with information coming from human experts usually expressed qualitatively in natural language with linguistic labels. In this paper, we propose and use two new 2-Tuple linguistic representation models (i.e., a distribution function model (DFM) and an improved Herrera-Martínez's model) jointly with the fusion rules developed in Dezert-Smarandache Theory (DSmT), in order to combine efficiently qualitative information expressed in term of qualitative belief functions. The two models both preserve the precision and improve the efficiency of the fusion of linguistic information expressing the global expert's opinion. However, DFM is more general and efficient than the latter, especially for unbalanced linguistic labels. Some simple examples are also provided to show how the 2-Tuple qualitative fusion rules are performed and their advantages.
Category: Artificial Intelligence

[1] viXra:0703.0026 [pdf] submitted on 25 Mar 2007

Unification of Fusion Theories (UFT)

Authors: Florentin Smarandache
Comments: recovered from sciprint.org

Since no fusion theory neither rule fully satisfy all needed applications, the author proposes a Unification of Fusion Theories and a combination of fusion rules in solving problems/applications. For each particular application, one selects the most appropriate model, rule(s), and algorithm of implementation. We are working in the unification of the fusion theories and rules, which looks like a cooking recipe, better we'd say like a logical chart for a computer programmer, but we don't see another method to comprise/unify all things. The unification scenario presented herein, which is now in an incipient form, should periodically be updated incorporating new discoveries from the fusion and engineering research.
Category: Artificial Intelligence

Replacements of recent Submissions

[27] viXra:1312.0191 [pdf] replaced on 2014-02-19 02:31:52

Device Search and Selection

Authors: Charith Perera, Chi Harold Liu, Peter Christen
Comments: 42 Pages. Book Chapter abstract for public reference. In Book the Cyber-Physical Systems: Architectures, Protocols and Applications, CRC Press, Taylor & Francis Group, USA, 2014

Cyber-physical systems (CPS) represent the expansion in computerized interconnectivity. This phenomenon is also moving towards the Internet of Things (IoT) paradigm. Searching functionality plays a vital role in this domain. Many different types of search capabilities are required to build a comprehensive CPS architecture. In CPS, users may want to search smart devices and services. In this chapter, we discuss concepts and techniques related to device search and selection. We briefly discuss different types of device searching approaches where each has its own objectives and applications. One such device searching technique is context-aware searching. In this chapter, we present context-aware sensor search, selection and ranking model called CASSARAM in detail. This model addresses the challenge of efficiently selecting a subset of relevant sensors out of a large set of sensors with similar functionality and capabilities. CASSARAM takes into account user preferences and considers a broad range of sensor characteristics, such as reliability, accuracy, location, battery life, and many more. Later in the chapter, we discuss three different techniques that can be used to improve the efficiently of CASSARAM. We implemented the proof of concept software using Java. Testing and performance evaluation results are also discussed. We also highlight open research challenges and opportunities in order to support future research directions.
Category: Artificial Intelligence

[26] viXra:1312.0116 [pdf] replaced on 2014-02-19 02:40:51

Mobile Sensing Devices and Platforms

Authors: Charith Perera, Prem Prakash Jayaraman, Srimal Jayawardena, Chi Harold Liu, Peter Christen
Comments: 41 Pages. Book Chapter abstract for public reference. In Book the Cyber-Physical Systems: Architectures, Protocols and Applications, CRC Press, Taylor & Francis Group, USA, 2014

A cyber-physical system (CPS) is a system of collaborating computational elements con- trolling physical entities. CPS represents the next stage on the road to the creation of smart cities through the creation of an Internet of Things, data and services. Mobility is one of the major characteristic of both CPS and IoT. In this Chapter, we discuss mobile sensing platforms and their applications towards dierent but interrelated paradigms such as IoT, sensing as a service, and smart cities. We highlight and brie y discuss dierent types of mobile sensing platforms and functionalities they oer. Mobile sensing platforms are more oftenly integrated with smart phones and tablet devices. The resource constrained nature of the mobile devices requires dierent types of designs and architectural implementations. We proposed a software-based mobile sensing platform called Mobile Sensor Data Engine (MOSDEN). It is a plug-in-based scalable and extendible IoT middleware for mobile devices that provide an easy way to collect sensor data from both internal and external sensors. MOSDEN act as intermediary device that collects data from external sensors and upload to the cloud in real-time or on demand. We evaluate MOSDEN in both stand-alone and collaborative environments. The proof of concept is developed on Android platform.
Category: Artificial Intelligence

[25] viXra:1309.0149 [pdf] replaced on 2013-09-22 15:16:09

A Complexity of Bridge Double Dummy Problem

Authors: Piotr Beling
Comments: 10 Pages.

This paper presents an analysis of complexity of a bridge double dummy problem. Values of both, a state-space (search-space) complexity and a game tree complexity have been estimated.
Category: Artificial Intelligence

[24] viXra:1305.0080 [pdf] replaced on 2013-07-13 08:24:25

Reduction of Logic to Arithmetic

Authors: Ranganath G Kulkarni
Comments: 13 Pages.

It is possible to make decisions mathematically of first order predicate calculus. A new mathematical formula is found for the solution of decision problem. We can reduce a logical algorithm into simple algorithm without logical trees.
Category: Artificial Intelligence

[23] viXra:1305.0080 [pdf] replaced on 2013-06-18 01:41:59

Reduction of Logic to Arithmetic

Authors: Ranganath G Kulkarni
Comments: 13 Pages.

It is possible to make decisions mathematically of first order predicate calculus. A new mathematical formula is found for the solution of decision problem. We can reduce a logical algorithm into simple algorithm without logical trees.
Category: Artificial Intelligence

[22] viXra:1305.0080 [pdf] replaced on 2013-05-29 01:46:27

Reduction of Logic to Arithmetic

Authors: Ranganath G Kulkarni
Comments: 10 Pages.

It is possible to make decisions mathematically of first order predicate calculus. A new mathematical formula is found for the solution of decision problem. We can reduce a logical algorithm into simple algorithm without logical trees.
Category: Artificial Intelligence

[21] viXra:1304.0133 [pdf] replaced on 2013-05-02 12:13:40

An Indicator of Inclusion with Applications in Computer Vision

Authors: Ovidiu Ilie Şandru, Florentin Smarandache
Comments: 3 Pages.

In this paper we present an algorithmic process of necessary operations for the automatic movement of a predefined object from a video image in the target region of that image, intended to facilitate the implementation of specialized software applications in solving this kind of problems.
Category: Artificial Intelligence

[20] viXra:1304.0133 [pdf] replaced on 2013-04-25 07:09:59

An Indicator of Inclusion with Applications in Computer Vision

Authors: Ovidiu Ilie Şandru, Florentin Smarandache
Comments: 3 Pages.

In this paper we present an algorithmic process of necessary operations for the automatic movement of a predefined object from a video image in the target region of that image, intended to facilitate the implementation of specialized software applications in solving this kind of problems.
Category: Artificial Intelligence

[19] viXra:1303.0202 [pdf] replaced on 2013-03-26 16:10:09

Mobile Robot Navigation Using Artificial Landmarks and GPS

Authors: Kimihiro OKUYAMA, Mohd ANASRI, Florentin SMARANDACHE, Valeri KROUMOV
Comments: 6 Pages.

移動ロボットのナビゲーションを行うにはロボットが 十分に現在位置と周囲の環境を認識する必要がある。そ のために、ロボットにレーザーレンジスキャナや超音波 センサ、カメラ、オドメトリ、GPS (Global Positioning System) 等のセンサを搭載することで、ロボットは現在 位置・姿勢、周囲の様子、移動距離、周囲の物との距離 等を知ることができるようになる。しかし、センサか らの情報には誤差が含まれており、移動している環境 や搭載しているセンサにより生じる誤差が累積される ことで、現在の位置がわからなくなり、走行経路から 外れて、目的地へたどりつけなくなることがある。正 しい位置を認識するには、定期的に誤差を解消し、位 置の校正を行う必要がある。位置校正を向上させるた めに、ロボットにSLAM (Simultaneous Localization and Mapping)[1] アルゴリズムやKalman Filter[2] などの制 御技術が導入される。
Category: Artificial Intelligence

[18] viXra:1303.0192 [pdf] replaced on 2013-06-22 12:53:25

NP!=P

Authors: Liu Ran
Comments: 12 Pages.

Any NP problem can reduce to P problem, any P problem can reduce to instructions. If NP=P, it violate information entropy principle.
Category: Artificial Intelligence

[17] viXra:1303.0192 [pdf] replaced on 2013-05-03 10:56:24

NP!=P

Authors: Liu Ran
Comments: 12 Pages.

Any NP problem can reduce to P problem, any P problem can reduce to instructions. If NP=P, it violate information entropy principle.
Category: Artificial Intelligence

[16] viXra:1303.0192 [pdf] replaced on 2013-04-24 11:47:43

NP!=P

Authors: Liu Ran
Comments: 11 Pages.

Any NP problem can reduce to P problem, any P problem can reduce to instructions. If NP=P, it violate information entropy principle.
Category: Artificial Intelligence

[15] viXra:1303.0072 [pdf] replaced on 2013-05-15 19:27:07

On Godel's Incompleteness Theorem(s), Artificial Intelligence/Life, and Human Mind

Authors: Victor Christianto, Florentin Smarandache
Comments: 4 Pages. submitted to IAT 2013

In the present paper we discuss Gödel’s incompleteness theorem(s) and plausible implications to artificial intelligence/life and human mind. Perhaps we should agree with Sullins III, that the value of this finding is not to discourage certain types of research in AL, but rather to help move us in a direction where we can more clearly define the results of that research. Gödel’s incompleteness theorems have their own limitations, but so do Artificial Life (AL)/AI systems. Based on our experiences so far, human mind has incredible abilities to interact with other part of human body including heart, which makes it so difficult to simulate in AI/AL. However, it remains an open question to predict whether in the future AI research including robotics science can bring this gap closer or not. In this regard, fuzzy logic and its generalization –neutrosophic logic- offer a way to improve significantly AI/AL research.
Category: Artificial Intelligence

[14] viXra:1303.0072 [pdf] replaced on 2013-04-02 23:21:06

On Godel's Incompleteness Theorem(s), Artificial Intelligence/Life, and Human Mind

Authors: Victor Christianto, Florentin Smarandache
Comments: 8 Pages. This paper is not yet submitted to any journal.

In the present paper we discussed Godel’s incompleteness theorem(s) and plausible implications to artificial intelligence/life and human mind. Perhaps we should agree with Sullins III, that the value of this finding is not to discourage certain types of research in AL/AI, but rather to help move us in a direction where we can more clearly define the results of that research. Godel’s incompleteness theorems have their own limitations, but so do Artificial Life (AL)/AI systems. Based on our experiences so far, human mind has incredible abilities to interact with other part of human body including heart, which makes it so difficult to simulate in AI/AL. However, it remains an open question to predict whether the future of AI including robotics science can bring this gap closer or not. In this regard, fuzzy logic and its generalization –neutrosophic logic- offer a way to improve significantly AI/AL research.
Category: Artificial Intelligence

[13] viXra:1303.0072 [pdf] replaced on 2013-03-13 22:54:55

On Godel's Incompleteness Theorem(s), Artificial Intelligence/Life, and Human Mind

Authors: Victor Christianto, Florentin Smarandache
Comments: 8 Pages. This paper is not yet submitted to any journal.

In the present paper we discussed Godel’s incompleteness theorem(s) and plausible implications to artificial intelligence/life and human mind. Perhaps we should agree with Sullins III, that the value of this finding is not to discourage certain types of research in AL/AI, but rather to help move us in a direction where we can more clearly define the results of that research. Godel’s incompleteness theorems have their own limitations, but so do Artificial Life (AL)/AI systems. Based on our experiences so far, human mind has incredible abilities to interact with other part of human body including heart, which makes it so difficult to simulate in AI/AL. However, it remains an open question to predict whether the future of AI including robotics science can bring this gap closer or not. In this regard, fuzzy logic and its generalization –neutrosophic logic- offer a way to improve significantly AI/AL research.
Category: Artificial Intelligence

[12] viXra:1301.0107 [pdf] replaced on 2013-01-20 20:57:23

Automatic Tuning of MapReduce Jobs using Uncertain Pattern Matching Analysis

Authors: Nikzad Babaii Rizvandi, Javid Taheri, Reza Moraveji, Albert Y. Zomaya
Comments: 19 Pages.

In this paper, we study CPU utilization time patterns of several MapReduce applications. After extracting running patterns of several applications, the patterns along with their statistical information are saved in a reference database to be later used to tweak system parameters to efficiently execute future unknown applications. To achieve this goal, CPU utilization patterns of new applications along with its statistical information are compared with the already known ones in the reference database to find/predict their most probable execution patterns. Because of different pattern lengths, the Dynamic Time Warping (DTW) is utilized for such comparison; a statistical analysis is then applied to DTWs’ outcomes to select the most suitable candidates. Furthermore, under a hypothesis, we also proposed another algorithm to classify applications under similar CPU utilization patterns. Finally, dependency between minimum distance/maximum similarity of applications and their scalability (in both input size and number of virtual nodes) are studied. Here, we used widely used applications (WordCount, Distributed Grep, and Terasort) as well as an Exim Mainlog parsing application to evaluate our hypothesis in automatic tweaking MapReduce configuration parameters in executing similar applications scalable on both size of input data and number of virtual nodes. Results are very promising and showed the effectiveness of our approach on a private cloud with up to 25 virtual nodes.
Category: Artificial Intelligence

[11] viXra:1208.0065 [pdf] replaced on 2012-09-04 03:12:32

Determining Wind Velocity from Images of Raindrops

Authors: Kuhan Muniam
Comments: Pages.

This study develops the method of determining wind velocity from images of raindrops. The motivation of this study was to develop a new method of finding wind velocity. In this new method, digital images or videos of raindrops are processed using computer stereo vision to extract information about the rain inclination. The rain inclination is then used to compute the wind velocity. The rain inclination changes with height (and time) due to acceleration from the force exerted by the wind on the raindrops. A simple experiment was conducted to demonstrate that it is possible to determine rain inclination from digital images. The inclination of falling water was found using two perpendicular two-dimensional digital images. This implies that it is possible to determine rain inclination from digital images. Some equations relating wind velocity and the trajectory of a raindrop are derived using Stokes’ Law. Extensive use of fluid mechanics is required to derive accurate equations. Some hypothetical setups of systems that use this method are described. Wind velocity can also be determined from stereoscopic videos of raindrop trajectory. Disdrometers may be used instead of digital cameras when applying this method. Keywords: rain inclination, raindrop, wind velocity, camera, digital images, stereoscopic vision, computer stereo vision, epipolar geometry, wind force, disdrometer, pinhole camera model, fluid mechanics.
Category: Artificial Intelligence

[10] viXra:1206.0043 [pdf] replaced on 2012-06-11 04:21:17

Applications of Extenics to 2D-Space and 3D-Space

Authors: Florentin Smarandache, Victor Vladareanu
Comments: 12 Pages.

In this article one proposes several numerical examples for applying the extension set to 2D- and 3D-spaces. While rectangular and prism geometrical figures can easily be decomposed from 2D and 3D into 1D linear problems, similarly for the circle and the sphere, it is not possible in general to do the same for other geometrical figures.
Category: Artificial Intelligence

[9] viXra:1204.0002 [pdf] replaced on 2012-12-18 22:39:33

Correction of Inertial Navigation System's Errors by the Help of Video-Based Navigator Based on Digital Terrarium Map

Authors: Kupervasser O. Yu., Voronov V.V.
Comments: 6 Pages. PRESENTED AT XIX ST.-PETERSBURG INTERNATIONAL CONFERENCE ON THE INTEGRATED NAVIGATIONAL SYSTEMS (MKINS2012)

This paper deals with the error analysis of a novel navigation algorithm that uses as input the sequence of images acquired from a moving camera and a Digital Terrain (or Elevation) Map (DTM/DEM). More specifically, it has been shown that the optical flow derived from two consecutive camera frames can be used in combination with a DTM to estimate the position, orientation and ego-motion parameters of the moving camera. As opposed to previous works, the proposed approach does not require an intermediate explicit reconstruction of the 3D world. In the present work the sensitivity of the algorithm outlined above is studied. The main sources for errors are identified to be the optical-flow evaluation and computation, the quality of the information about the terrain, the structure of the observed terrain and the trajectory of the camera. By assuming appropriate characterization of these error sources, a closed form expression for the uncertainty of the pose and motion of the camera is first developed and then the influence of these factors is confirmed using extensive numerical simulations. The main conclusion of this paper is to establish that the proposed navigation algorithm generates accurate estimates for reasonable scenarios and error sources, and thus can be effectively used as part of a navigation system of autonomous vehicles.
Category: Artificial Intelligence

[8] viXra:1204.0002 [pdf] replaced on 2012-04-25 12:17:56

Correction of Inertial Navigation System's Errors by the Help of Video-Based Navigator Based on Digital Terrarium Map

Authors: Kupervasser O. Yu., Voronov V.V.
Comments: 61 Pages. PRESENTED AT XIX ST.-PETERSBURG INTERNATIONAL CONFERENCE ON THE INTEGRATED NAVIGATIONAL SYSTEMS (MKINS2012)

This paper deals with the error analysis of a novel navigation algorithm that uses as input the sequence of images acquired from a moving camera and a Digital Terrain (or Elevation) Map (DTM/DEM). More specifically, it has been shown that the optical flow derived from two consecutive camera frames can be used in combination with a DTM to estimate the position, orientation and ego-motion parameters of the moving camera. As opposed to previous works, the proposed approach does not require an intermediate explicit reconstruction of the 3D world. In the present work the sensitivity of the algorithm outlined above is studied. The main sources for errors are identified to be the optical-flow evaluation and computation, the quality of the information about the terrain, the structure of the observed terrain and the trajectory of the camera. By assuming appropriate characterization of these error sources, a closed form expression for the uncertainty of the pose and motion of the camera is first developed and then the influence of these factors is confirmed using extensive numerical simulations. The main conclusion of this paper is to establish that the proposed navigation algorithm generates accurate estimates for reasonable scenarios and error sources, and thus can be effectively used as part of a navigation system of autonomous vehicles.
Category: Artificial Intelligence

[7] viXra:1201.0063 [pdf] replaced on 2012-05-25 05:44:11

Information – Entropy Theory of Artificial Intelligence

Authors: George Rajna
Comments: 2 Pages.

The basic theory on which one chess program can be constructed is that there exists a general characteristic of the game of chess, namely the concept of entropy. We can think about the positive logarithmic values as the measure of entropy and the negative logarithmic values as the measure of information.
Category: Artificial Intelligence

[6] viXra:1201.0063 [pdf] replaced on 2012-05-23 06:06:01

Information – Entropy Theory of Artificial Intelligence

Authors: George Rajna
Comments: 2 Pages.

The basic theory on which one chess program can be constructed is that there exists a general characteristic of the game of chess, namely the concept of entropy. We can think about the positive logarithmic values as the measure of entropy and the negative logarithmic values as the measure of information.
Category: Artificial Intelligence

[5] viXra:1008.0026 [pdf] replaced on 15 Aug 2010

Threat Assessment of a Possible Vehicle-Borne Improvised Explosive Device Using DSmT

Authors: Jean Dezert, Florentin Smarandache
Comments: 26 pages

This paper presents the solution about the threat of a VBIED (Vehicle-Borne Improvised Explosive Device) obtained with the DSmT (Dezert-Smarandache Theory). This problem has been proposed recently to the authors by Simon Maskell and John Lavery as a typical illustrative example to try to compare the different approaches for dealing with uncertainty for decision-making support. The purpose of this paper is to show in details how a solid justified solution can be obtained from DSmT approach and its fusion rules thanks to a proper modeling of the belief functions involved in this problem.
Category: Artificial Intelligence

[4] viXra:1004.0009 [pdf] replaced on 31 Aug 2010

Neutrosophic Set - A Generalization of the Intuitionistic Fuzzy Set

Authors: Florentin Smarandache
Comments: 7 pages

In this paper one generalizes the intuitionistic fuzzy set (IFS), paraconsistent set, and intuitionistic set to the neutrosophic set (NS). Many examples are presented. Distinctions between NS and IFS are underlined.
Category: Artificial Intelligence

[3] viXra:1004.0008 [pdf] replaced on 31 Aug 2010

Neutrosophic Logic - A Generalization of the Intuitionistic Fuzzy Logic

Authors: Florentin Smarandache
Comments: 7 pages

In this paper one generalizes the intuitionistic fuzzy logic (IFL) and other logics to neutrosophic logic (NL). The differences between IFL and NL (and the corresponding intuitionistic fuzzy set and neutrosophic set) are pointed out.
Category: Artificial Intelligence

[2] viXra:1004.0005 [pdf] replaced on 21 Jul 2011

Uniform and Partially Uniform Redistribution Rules

Authors: Florentin Smarandache, Jean Dezert
Comments: 4 pages

This short paper introduces two new fusion rules for combining quantitative basic belief assignments. These rules although very simple have not been proposed in literature so far and could serve as useful alternatives because of their low computation cost with respect to the recent advanced Proportional Conflict Redistribution rules developed in the DSmT framework.
Category: Artificial Intelligence

[1] viXra:1003.0252 [pdf] replaced on 2013-04-22 14:06:13

Ornamental Sign Language in the First Order Tracery Belts

Authors: Modris Tenisons, Dainis Zeps
Comments: 19 Pages. Corrected version

We consider an ornamental sign language of first order where principles of sieve displacement, of asymmetric building blocks as a base of ornament symmetry, color exchangeability and side equivalence principles work. Generic aspects of sieve and a genesis of ornamental pattern and ornament signs in it are discussed. Hemiolia principle for ornamental genesis is introduced. The discoverer of most of these principles were artist Modris Tenisons [4, 5, 6, 7 (refs. 23, 24), 8 (ref. 65)]. Here we apply a systematical research using simplest mathematical arguments. We come to conclusions that mathematical argument in arising ornament is of much more significance than simply symmetries in it as in an image. We are after to inquire how ornament arises from global aspects intertwined with these local. We raise an argument of sign’s origin from code rather from image, and its eventual impact on research of ornamental patterns, and on research of human prehension of sign and its connection with consciousness.
Category: Artificial Intelligence