Previous months:
2007 - 0703(1)
2010 - 1003(33) - 1004(9) - 1005(5) - 1008(2) - 1009(1) - 1010(1) - 1012(1)
2011 - 1101(2) - 1106(1) - 1107(1) - 1109(2)
2012 - 1201(1) - 1204(3) - 1206(2) - 1207(6) - 1208(7) - 1209(1) - 1210(4) - 1211(2) - 1212(4)
2013 - 1301(6) - 1302(2) - 1303(6) - 1304(9) - 1305(1)
Any replacements are listed further down
[108] viXra:1305.0080 [pdf] submitted on 2013-05-13 07:19:22
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
[107] viXra:1304.0155 [pdf] submitted on 2013-04-27 09:28:39
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
[106] viXra:1304.0139 [pdf] submitted on 2013-04-25 07:02:03
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
[105] viXra:1304.0133 [pdf] submitted on 2013-04-24 11:58:17
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
[104] viXra:1304.0101 [pdf] submitted on 2013-04-20 11:05:18
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
[103] viXra:1304.0091 [pdf] submitted on 2013-04-19 06:08:36
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
[102] viXra:1304.0085 [pdf] submitted on 2013-04-18 02:30:46
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
[101] viXra:1304.0084 [pdf] submitted on 2013-04-18 02:35:31
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
[100] viXra:1304.0064 [pdf] submitted on 2013-04-14 07:10:21
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
[99] viXra:1304.0011 [pdf] submitted on 2013-04-02 21:49:41
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
[98] viXra:1303.0202 [pdf] submitted on 2013-03-26 07:59:36
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
[97] viXra:1303.0192 [pdf] submitted on 2013-03-25 10:36:22
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
[96] viXra:1303.0072 [pdf] submitted on 2013-03-09 21:04:02
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
[95] viXra:1303.0069 [pdf] submitted on 2013-03-09 11:52:15
Authors: H. Wang, Y. Zhang, R. Sunderraman, F. Song
Comments: 14 Pages.
We define set-operators on DNS.
Category: Artificial Intelligence
[94] viXra:1303.0068 [pdf] submitted on 2013-03-09 11:54:52
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
[93] viXra:1303.0066 [pdf] submitted on 2013-03-09 11:13:19
Authors: Matteo Ceriotti, Massimiliano Vasile, Mauro Massari
Comments: 28 Pages.
Dezert-Smarandache Theory (DSmT) used for the planetary rover.
Category: Artificial Intelligence
[92] viXra:1302.0175 [pdf] submitted on 2013-02-28 09:32:15
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
[91] viXra:1302.0015 [pdf] submitted on 2013-02-03 10:52:56
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
[90] viXra:1301.0183 [pdf] submitted on 2013-01-29 17:59:27
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
[89] viXra:1301.0107 [pdf] submitted on 2013-01-17 21:56:43
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
[88] viXra:1301.0024 [pdf] submitted on 2013-01-05 10:07:02
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
[87] viXra:1301.0017 [pdf] submitted on 2013-01-03 17:41:06
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
[86] viXra:1301.0016 [pdf] submitted on 2013-01-03 17:52:51
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
[85] viXra:1212.0111 [pdf] submitted on 2012-12-27 18:52:11
Authors: Charith Perera, Arkady Zaslavsky, Peter Christen, Dimitrios Georgakopoulos
Comments: 8 Pages.
Internet of Things (IoT) will connect billions of sensors deployed around the world together. This will create an ideal opportunity to build a sensing-as-a-service platform. Due to large number of sensor deployments, there would be number of sensors that can be used to sense and collect similar information. Further, due to advances in sensor hardware technology, new methods and measurements will be introduced continuously. In the IoT paradigm, selecting the most appropriate sensors which can provide relevant sensor data to address the problems at hand among billions of possibilities would be a challenge for both technical and non-technical users. In this paper, we propose the Context Awareness for Internet of Things (CA4IOT) architecture to help users by automating the task of selecting the sensors according to the problems/tasks at hand. We focus on automated configuration of filtering, fusion and reasoning mechanisms that can be applied to the collected sensor data streams using selected sensors. Our objective is to allow the users to submit their problems, so our proposed architecture understands them and produces more comprehensive and meaningful information than the raw sensor data streams generated by individual sensors.
Category: Artificial Intelligence
[84] viXra:1212.0093 [pdf] submitted on 2012-12-27 18:53:31
Authors: Charith Perera, Arkady Zaslavsky, Peter Christen, Ali Salehi, Dimitrios Georgakopoulos
Comments: 8 Pages.
Internet of Things (IoT) will create a cyberphysical world where all the things around us are connected to the Inter net, sense and produce "big data" that has to be stored, processed and communicated with minimum human intervention. With the ever increasing emergence of new sensors, interfaces and mobile devices, the grand challenge is to keep up with this race in developing software drivers and wrappers for IoT things. In this paper, we examine the approaches that automate the process of developing middleware drivers/wrappers for the IoT things. We propose ASCM4GSN architecture to address this challenge efficiently and effectively. We demonstrate the proposed approach using Global Sensor Network (GSN) middleware which exemplifies a cluster of data streaming engines. The ASCM4GSN architecture significantly speeds up the wrapper development and sensor configuration process as demonstrated for Android mobile phone based sensors as well as for Sun SPOT sensors.
Category: Artificial Intelligence
[83] viXra:1211.0104 [pdf] submitted on 2012-11-18 21:11:04
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
Category: Artificial Intelligence
[63] viXra:1204.0081 [pdf] submitted on 2012-04-18 13:14:24
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
Category: Artificial Intelligence
[31] viXra:1003.0209 [pdf] submitted on 6 Mar 2010
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
[23] viXra:1304.0133 [pdf] replaced on 2013-05-02 12:13:40
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
[22] viXra:1304.0133 [pdf] replaced on 2013-04-25 07:09:59
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
[21] viXra:1303.0202 [pdf] replaced on 2013-03-26 16:10:09
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
[20] viXra:1303.0192 [pdf] replaced on 2013-05-03 10:56:24
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
[19] viXra:1303.0192 [pdf] replaced on 2013-04-24 11:47:43
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
[18] viXra:1303.0072 [pdf] replaced on 2013-05-15 19:27:07
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
[17] viXra:1303.0072 [pdf] replaced on 2013-04-02 23:21:06
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
[16] viXra:1303.0072 [pdf] replaced on 2013-03-13 22:54:55
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
[15] viXra:1301.0107 [pdf] replaced on 2013-01-20 20:57:23
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
[14] viXra:1301.0035 [pdf] replaced on 2013-01-07 08:43:57
Authors: Charith Perera, Prem Jayaraman, Arkady Zaslavsky, Peter Christen, Dimitrios Georgakopoulos
Comments: 6 Pages.
Internet of Things (IoT) envisions billions of sensors to be connected to the Internet. By deploying intelligent lowlevel computational devices such as mobile phones in-between sensors and cloud servers, we can reduce data communication with the use of intelligent processing such as fusing and filtering sensor data, which saves significant amount of energy. This is also ideal for real world sensor deployments where connecting sensors directly to a computer or to the Internet is not practical. Most of the leading IoT middleware solutions require manual and labour intensive tasks to be completed in order to connect a mobile phone to them. In this paper we present a mobile application called Mobile Sensor Hub (MoSHub). It allows variety of different sensors to be connected to a mobile phone and send the data to the cloud intelligently reducing network communication. Specifically, we explore techniques that allow MoSHub to be connected to cloud based IoT middleware solutions autonomously. For our experiments, we employed Global Sensor Network (GSN) middleware to implement and evaluate our approach. Such automated configuration reduces significant amount of manual labour that need to be performed by technical experts otherwise. We also evaluated different methods that can be used to automate the configuration process.
Category: Artificial Intelligence
[13] viXra:1212.0112 [pdf] replaced on 2012-12-28 03:33:05
Authors: Arkady Zaslavsky, Charith Perera, Dimitrios Georgakopoulos
Comments: 8 Pages.
Internet of Things (IoT) will comprise billions of devices that can sense, communicate, compute and potentially actuate. Data streams coming from these devices will challenge the traditional approaches to data management and contribute to the emerging paradigm of big data. This paper discusses emerging Internet of Things (IoT) architecture, large scale sensor network applications, federating sensor networks, sensor data and related context capturing techniques, challenges in cloud-based management, storing, archiving and processing of sensor data.
Category: Artificial Intelligence
[12] viXra:1212.0044 [pdf] replaced on 2012-12-27 18:55:49
Authors: Charith Perera, Arkady Zaslavsky, Peter Christen, Ali Salehi, Dimitrios Georgakopoulos
Comments: 6 Pages.
Mobile phones play increasingly bigger role in our everyday lives. Today, most smart phones comprise a wide variety of sensors which can sense the physical environment. The Internet of Things vision encompasses participatory sensing which is enabled using mobile phones based sensing and reasoning. In this research, we propose and demonstrate our DAM4GSN architecture to capture sensor data using sensors built into the mobile phones. Specifically, we combine an open source sensor data stream processing engine called ‘Global Sensor Network (GSN)’ with the Android platform to capture sensor data. To achieve this goal, we proposed and developed a prototype application that can be installed on Android devices as well as a AndroidWrapper as a GSN middleware component. The process and the difficulty of manually connecting sensor devices to sensor data processing middleware systems are examined. We evaluated the performance of the system based on power consumption of the mobile client.
Category: Artificial Intelligence
[11] viXra:1208.0065 [pdf] replaced on 2012-09-04 03:12:32
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
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
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
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
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
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
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
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
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
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
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