bluuebunny/crossref_metadata_2025 huggingface dataset:
ON LEFT AND RIGHT UNINORMS
Authors: MAS M. , MONSERRAT M. , TORRENS J.
Published: May 2003

This paper presents a characterization of a new family of operators. Namely, all non-decreasing, associative binary operators U: [0, 1]2→ [0, 1] with a left (or right) neutral element e ∈ [0, 1], and such that they satisfy an additional hypothesis on continuity which is called here left (or right) pseudocontinuity.
USING STATISTICAL VIEWPOINT IN DEVELOPING CORRELATION OF INTUITIONISTIC FUZZY SETS
Authors: HUNG WEN-LIANG
Published: May 2003

In this paper, we propose a method to calculate the correlation coefficient of intuitionistic fuzzy sets by means of mathematical statistics. This value obtained from our formula tell us not only the strength of relationship between the intuitionistic fuzzy sets, but also whether the intuitionistic fuzzy sets are positively or negatively related. This approach looks better than previous methods which only evaluate the strength of the relation. Furthermore, we extend the proposed method to interval-valued intuitionistic fuzzy sets. The value of the correlation coefficient between interval-valued intuitionistic fuzzy sets lies in the interval [-1, 1], as computed from our formula.
A NOTE ON THE CORRELATION OF FUZZY NUMBERS BY EXPECTED INTERVAL
Authors: HUNG WEN-LIANG , WU JONG-WUU
Published: May 2003

In this paper, we propose a method to calculate the correlation coefficient of fuzzy numbers by means of "expected interval" (see [8], [9]). This value obtained from our formula tell us not only the strength of relationship between the fuzzy numbers, but also whether the fuzzy numbers are positively or negatively related. This approach looks better than previous methods which only evaluate the strength of the relation. Furthermore, we extend the "expected interval" method to interval-valued fuzzy numbers. The value of the correlation coefficient between interval-valued fuzzy numbers lies in the interval [-1,1], as computed from our formula.
INTERVAL METHODS IN KNOWLEDGE REPRESENTATION
Authors: KREINOVICH VLADIK
Published: May 2003

This section is maintained by Vladik Kreinovich. Please send your abstract (or copies of papers that you want to see reviewed here), to vladik@cs.utep.edu, or by regular mail to: Vladik Kreinovich, Department of Computer Science, University of Texas at El Paso, El Paso, TX 79968, USA.
AN ALTERNATIVE APPROACH TO COMPUTING WITH WORDS
Authors: LAWRY JONATHAN
Published: May 2003

An alternative theory of linguistic variables is introduced based on voting model semantics. This theory is then applied to computing with words whereby a calculus is introduced for inference from linguistic facts and rules.
EXTENDING CHOQUET INTEGRALS FOR AGGREGATION OF ORDINAL VALUES
Authors: GODO LLUÍS , TORRA VICENÇ
Published: May 2003

In this paper we study the extension of Choquet integrals to ordinal scales. We show that two different integrals can be defined on the basis of two different but equivalent expressions in the numerical case. We prove some properties of the Choquet integrals and show their application to aggregation.
THE 2-TUPLE LINGUISTIC COMPUTATIONAL MODEL: ADVANTAGES OF ITS LINGUISTIC DESCRIPTION, ACCURACY AND CONSISTENCY
Authors: HERRERA F. , MARTINEZ L.
Published: May 2003

The Fuzzy Linguistic Approach has been applied successfully to different areas. The use of linguistic information for modelling expert preferences implies the use of processes of Computing with Words. To accomplish these processes different approaches has been proposed in the literature: (i) Computational model based on the Extension Principle, (ii) the symbolic one(also called ordinal approach), and (iii) the 2-tuple linguistic computational model. The main problem of the classical approaches, (i) and (ii), is the loss of information and lack of precision during the computational processes. In this paper, we want to compare the linguistic description, accuracy and consistency of the results obtained using each model over the rest ones. To do so, we shall solve a Multiexpert Multicriteria Decision-Making problem defined in a multigranularity linguistic context using the different computational approaches. This comparison helps us to decide what model is more adequated for computing with words.
LINGUISTIC MODIFIERS IN A SYMBOLIC FRAMEWORK
Authors: AKDAG H. , TRUCK I. , BORGI A. , MELLOULI N.
Published: May 2003

In common language, as well as in knowledge–based systems, the truth of a proposition can be evaluated in a qualitative manner using adverbs usually represented on a scale of symbolic degrees. To combine or aggregate such symbolic degrees, we may need scales of different precision levels. We propose to model small variations inside a degree scale using linguistic modifiers in a symbolic framework. We formally define such modifiers and we distinguish three families: reinforcing, weakening and central modifiers. We also introduce the original notion of intensity rate associated to a linguistic degree on a scale base. After that, we propose a generalization of our modifiers, so we obtain more sophisticated tools. These have been used, in particular, in an application on colorimetry that allows us to alter the color slightly. The importance of our work is that most of our linguistic modifiers verify some interesting properties on their intensity rate: notably, they assume a certain order relation.
AN ORDINAL INFORMATION RETRIEVAL MODEL
Authors: BORDOGNA GLORIA , PASI GABRIELLA
Published: May 2003

In this paper an ordinal Information Retrieval model is proposed, which is formalised within fuzzy set theory and is based on the notion of linguistic granules of information. Linguistic expressions are defined to represent and manage the importance of both the index terms as descriptors of the information items and the query terms (content selectors) as descriptors of users' needs. The advantage of this approach with respect to the (numeric) fuzzy IR models is that the query evaluation mechanism and the definition of the importance semantics are simplified.
AN INFORMATION RETRIEVAL MODEL WITH ORDINAL LINGUISTIC WEIGHTED QUERIES BASED ON TWO WEIGHTING ELEMENTS
Authors: HERRERA-VIEDMA E.
Published: May 2003

An Information Retrieval (IR) model defined using an ordinal fuzzy linguistic approach is proposed. It accepts ordinal linguistic weighted queries based on two weighting elements: the query terms and the query sub-expressions. In such a way, users may easily express simultaneously several semantic restrictions in a query. A symmetrical threshold semantic is associated to the weights of the query terms and an importance semantic is associated to the weights of the query sub-expressions. The advantage of this IR model with respect to others is the facility for expressing different semantic restrictions on the desired documents simultaneously, incorporating more flexibility in the user-IR system interaction.
COMPUTING WITH WORDS IN DECISION MAKING THROUGH INDIVIDUAL AND COLLECTIVE LINGUISTIC CHOICE RULES
Authors: KACPRZYK JANUSZ , ZADROZNY S£AWOMIR
Published: May 2003

A fuzzy preference relation is a popular model to represent both individual and group preferences. However, what is often sought is a subset of alternatives that is an ultimate solution of a decision problem. In order to arrive at such a final solution individal and/or group choice rules may be employed. There is a wealth of such rules devised in the context of the classical, crisp preference relations. Originally, most of the popular group decision making rules were conceived for classical (crisp) preference relations (orderings), and then extended to the case of traditional fuzzy preference relations. Moreover, they often differ in their assumptions about the properties o the preference relations to be processed. In the paper we pursue the path towards a universal representation of such rules that provides an effective generalization of the classical rules for the fuzzy case. Moreover, it leads to a meaningful extension to the linguistic preferences, in the spirit of the computing with words paradigm.
APPLYING LINGUISTIC DECISION-MAKING METHOD TO DEAL WITH SERVICE QUALITY EVALUATION PROBLEMS
Authors: CHEN CHEN T.
Published: May 2003

Today the evaluation of service quality is one of the most important management issues for every organization. An important feature of the service process is the degree of customer influence on the service process. A characteristic of service quality evaluation is that it consists of both tangible and intangible factors. In this paper the customers' subjective opinions and the weights of factors are described by linguistic labels which can be expressed in trapezoidal fuzzy numbers. After aggregating these linguistic labels, a linguistic decision–making method is proposed to evaluate the service quality level of each organization. Finally, a numerical example is shown to highlight the procedure of the proposed method at the end of this paper.
LINGUISTIC AND CHOQUET INTEGRAL BASED EVALUATION IN PROCESS PLANNING
Authors: DEVEDŽIĆ G.
Published: May 2003

This paper addresses fuzzy evaluation issues as applied in a decision–making procedure of process planning. General framework of fuzzy partitioning of system variables, evaluation procedure, and system variables, evaluation procedure, and system parameters aggregation have been described in detail for two classes and three distinguishing types of evaluation. Classes of evaluation include (a) linguistic, and (b) fuzzy (Choquet) integral based evaluation. Within these classes we distinguish between: (1) single criterion evaluation, (2) global multicriteria evaluation, and (3) global integral evaluation. First type relates to fuzzification of system parameters and matching procedure of a system's parameters input values to linguistic values in pre–defined dictionary. Multicriteria evaluation provides aggregation protocol of an object's attributes values and their significance yielding its suitability measure. We can use this measure to select the most appropriate linguistic value from pre–defined dictionary for further propagation through reasoning system, as well as for ranking of possible alternatives since it provides their global rank. Both types belong to linguistic evaluation class. Finally, global integral evaluation employs fuzzy integrals (here Choquet integral) for overall assessment of alternatives status. This type of evaluation belongs to fuzzy integral based class. Each type of evaluation is illustrated by an example from the real industrial practice concerning metal cutting process planning. The whole methodology should be seen as an upgrade of traditional expert systems used for this purpose. Relaxation of some system constraints provides more generality to traditional approaches, puts more "naturality" in assessment of parameters values, and reduces knowledge bases.
FUZZY QUEUEING THEORY REVISITED
Authors: BUCKLEY JAMES J. , FEURING THOMAS , HAYASHI YOICHI
Published: May 2003

We first survey the basic results in recent paper on fuzzy queueing theory based on possibility theory. Then we apply this to two application problems: (1) machine servicing problem (optimal size of service crews); and (2) then a queueing decision problem where we find the optimal number of servers.
THE USE OF THE DISCRETE SUGENO INTEGRAL IN DECISION-MAKING: A SURVERY
Authors: DUBOIS D. , MARICHAL J. L. , PRADE H. , ROUBENS M. , SABBADIN R.
Published: May 2003

An overview of the use of the discrete Sugeno integral as either an aggregation tool or a preference functional is presented in the qualitative framework of two decision paradigms: multi-criteria decision-making and decision-making under uncertainty. The parallelism between the representation theorems in both settings is stressed, even if a basic requirement like the idempotency of the aggregation scheme should be explicitely stated in multi-criteria decision-making, while its counterpart is implicit in decision under uncertainty by equating the utility of a constant act with the utility of its consequence. Important particular cases of Sugeno integrals such as prioritized minimum and maximum operators, their ordered versions, and Boolean max-min functions are studied.
UNCERTAINTY AND IMPRECISION IN ANALYTICAL CONTEXT: FUZZY LIMITS AND FUZZY DERIVATIVES
Authors: BURGIN MARK
Published: May 2003

The main goal of the present paper is to extend such classical constructions as limits and derivatives making them appropriate for management of imprecise, vague, uncertain, and incomplete information. In the second part of the paper, going after introduction, elements of the theory of fuzzy limits are presented. The third part is devoted to the construction of fuzzy derivatives of real functions. Two kinds of fuzzy derivatives are introduced: weak and strong ones. It is necessary to remark that the strong fuzzy derivatives are similar to ordinary derivatives of real functions being their fuzzy extensions. The weak fuzzy derivatives generate a new concept of a weak derivative even in a classical case of exact limits. In the fourth part fuzzy differentiable functions are studied. Different properties of such functions are obtained. Some of them are the same or at least similar to the properties of the differentiable functions while other properties differ in many aspects from those of the standard differentiable functions. Many classical results are obtained as direct corollaries of propositions for fuzzy derivatives, which are proved in this paper. Some of the classical results are extended and completed. The fifth part of the paper contains several interpretations of fuzzy derivatives aiming at application of fuzzy differential calculus to solving practical problems. At the end, some open problems are formulated.
TRADE-OFF BETWEEN COMPUTATION TIME AND NUMBER OF RULES FOR FUZZY MINING FROM QUANTITATIVE DATA
Authors: HONG TZUNG-PEI , KUO CHAN-SHENG , CHI SHENG-CHAI
Published: May 2003

Data mining is the process of extracting desirable knowledge or interesting patterns from existing databases for specific purposes. Most conventional data-mining algorithms identify the relationships among transactions using binary values. Transactions with quantitative values are however commonly seen in real-world applications. We proposed a fuzzy mining algorithm by which each attribute used only the linguistic term with the maximum cardinality int he mining process. The number of items was thus the same as that of the original attributes, making the processing time reduced. The fuzzy association rules derived in this way are not complete. This paper thus modifies it and proposes a new fuzzy data-mining algorithm for extrating interesting knowledge from transactions stored as quantitative values. The proposed algorithm can derive a more complete set of rules but with more computation time than the method proposed. Trade-off thus exists between the computation time and the completeness of rules. Choosing an appropriate learning method thus depends on the requirement of the application domains.
MULTI-OBJECTIVE FULLY FUZZIFIED LINEAR PROGAMMING
Authors: BUCKLEY JAMES J. , FEURING THOMAS , HAYASHI YOICHI
Published: May 2003

In this paper we wish to solve multi-objective fully fuzzified linear programming problems which are multi-objective linear programming problems where all the parameters and variables are fuzzy numbers. We change this problem into a single objective fuzzy linear programming problem and then show that our solution procedure can be used to explore the whole undominated set. An evolutionary algorithm is then designed to generate undominated solutions. An example is presented showing our evolutionary algorithm solution.
DECOMPOSITION OF MULTIUNIVERSE FUZZY TRUTH FUNCTIONS
Authors: ALTUNAY DERYA , ÇİFTÇİBAŞI TURHAN
Published: May 2003

This paper focuses on the decomposition problem of fuzzy relations using the concepts of multiuniverse fuzzy propositional logic. Given two fuzzy propositions in different universes, it is always possible to construct a fuzzy relation in the common universe through a prescribed combination. However, the converse is not so obvious, if possible at all. In other words, given a fuzzy relation, how would we know if it really represents a certain relationship between some fuzzy propositions? It is important to recognize whether the given fuzzy relation is a meaningful representation of information according to certain criteria applicable to some fuzzy propositions that constitute the fuzzy relation itself. Two basic structures of decomposition are investigated. Necessary and sufficient conditions for decomposition of multiuniverse fuzzy truth functions in terms of one-universe truth functions are presented. An algorithm for decomposition is proposed.
YAG: A TEMPLATE-BASED TEXT REALIZATION SYSTEM FOR DIALOG
Authors: CHANNARUKUL SONGSAK , MCROY SUSAN W. , ALI SYED S.
Published: May 2003

We present a natural language realization component, called YAG, that is suitable for intelligent tutoring systems that use dialog. Dialog imposes unique requirements on a generation component, namely: dialog systems must interact in real-time; they must be capable of producing fragmentary output; and they may be re-deployed in a number of different domains. Our approach to real-time natural language realization combines a declarative, template-based approach for the representation of text structure with knowledge-based methods for representing semantic content. Possible text structures are defined in a declarative language that is easy to understand, maintain, and re-use. A dialog system can use YAG to realize text structures by specifying a template and content from its knowledge base. Content can be specified in one of two ways: (1) as a sequence of propositions along with some control features; or (2) as a set of feature-value pairs. YAG's template realization algorithm realizes text without any search (in contrast to systems that must find rules that unify with a feature structure).
AN OBJECT LOCATION SPECIFYING METHODOLOGY USING ONE CAMERA
Authors: KESRARAT WIRAT , SORTRAKUL THOTSAPON
Published: May 2003

This research proposed a methodology for specifying the location of an object with image processing. The objectives of this methodology are to capture the target area, and specify the location of the object by using image. In order to locate the dropping object on the image plane efficiently, consecutive images are analyzed and a threshold operation is proposed. Because the accuracy of the dropping objects location on the difference of consecutive images image plane is usually influenced by noise. Moreover, transformation unit is adopted to map the XY coordinate on image plane into the world coordinate for an accuracy of the dropping objects position. After we get the actual XY coordinate of the dropping object, we can find the distance from the target point (center) and clock direction of the dropping object related to the center also. In addition, by using one digital video camera set on the tower and pan to capture the image on the target area to detect the dropping object from the air to the ground. It made the proposed methodology provide easier portability to detect the dropping object in any area.
A COMPETITIVE NEURAL NETWORK APPROACH TO WEB-PAGE CATEGORIZATION
Authors: LIU ZHI-QIANG , ZHANG YA-JUN
Published: May 2003

Recently many techniques, e.g., Google or AltaVista, are available for classifying well-organized, hierarchical crisp categories from human constructed web pages such as that in Yahoo. However, given the current rate of web-page production, there is an urgent need of classifiers that are able to autonomously classify web-page categories that have overlaps. In this paper, we present a competitive learning method for this problem, which based on a new objective function and gradient descent scheme. Experimental results on real-world data show that the approach proposed in this paper gives a better performance in classifying randomly-generated, knowledge-overlapped categories as well as hierarchical crisp categories.
MEASURE OF SIMILARITY BETWEEN FUZZY CONCEPTS FOR IDENTIFICATION OF FUZZY USER'S REQUESTS IN FUZZY SEMANTIC NETWORKS
Authors: OMRI MOHAMED-NAZIH , CHOUIGUI NOUREDDINE
Published: May 2003

This paper presents a method to measure the similarity between different fuzzy concepts in order identify the user's fuzzy requests in a fuzzy semantic networks.
STATISTICAL AND DEMPSTER-SHAFER TECHNIQUES IN TESTING STRUCTURAL INTEGRITY OF AEROSPACE STRUCTURES
Authors: OSEGUEDA ROBERTO A. , SEELAM SEETHARAMI R. , HOLGUIN ANA C. , KREINOVICH VLADIK , TAO CHIN-WANG , NGUYEN HUNG T.
Published: May 2003

We describe the existing statistics-related methods of testing structural integrity for aerospace structures, describe their drawbacks, how they can be overcome, and compare the resulting techniques.
A NEW ADAPTIVE MULTISTAGE FILTER FOR THE REMOVAL OF IMPULSE NOISE
Authors: RODTOOK SITTISAK , MAKHANOV STANISLAV
Published: May 2003

We propose and analyze a new single-pass filter designed to restore images highly corrupted by the impulse noise. The filter involves three stages designed to detect particular patterns of noise. The filter recognizes the "short line like" or the "short curve like" patterns of noise which enables us to preserve fine details. Our simulations show that the proposed new filter overperforms the conventional multilevel median filter, the two-state and the multi-state-median filter.
A NOVEL APPROACH FOR ROBUST, FAST AND ACCURATE FACE DETECTION
Authors: SRISUK SANUN , KURUTACH WERASAK , LIMPITIKEAT KONGSAK
Published: May 2003

In this paper, we propose a novel approach for detecting human faces in a complex background scene. This method is robust and based on our enhanced hausdorff distance. A major aim of this research is to achieve a highly efficient method of face detection that can be used in any real time applications. In addition, our approach produces a very reliable and accurate result. The whole algorithm is composed of three main modules: robust skin detection using Fuzzy HSCC, face similarity measure using RAMHD, and facial feature detection using SVM. Moreover, a technique of automatically updating the size of an elliptical model is also introduced. The results will be shown with real images.
FAULT IMMUNIZATION CONCEPT FOR SELF-ORGANIZING MAPPING NEURAL NETWORKS
Authors: TALUMASSAWATDI R. , LURSINSAP C.
Published: May 2003

Self-Organizing Mapping (SOM) neural network has been widely used in pattern classification, vector quantization, and image compression. We consider the problem of strengthening the reliability of a SOM neural network by the technique of fault immunization of the synaptic links of each neuron which is similar to the concept of biological immunization. Instead of assuming the stuck-at-0 and stuck-at-1 as in those studies, we consider a general case of stuck-at-a, where a is a real value. The only assumption that we consider is only one neuron can be faulty at any time. No restriction on the number of faulty links of the neuron. Let wi,j be the weight of synaptic link j of neuron i obtained after the winner-take-all classification. Weight wi,j is immunized by adding a constant ∊i,j, either positive or negative, to wi,j. A neuron reaches its maximum fault immunization if the value of wi,j + ∊i,j can be either increased or decreased as much as possible without creating any misclassification. Thus, the fault immunization problem is formulated as an optimization problem on finding the value of each ∊i,j. A technique to find the value of wi,j + ∊i,j is proposed and its application to enhance the transmission reliability in image compression area is introduced.
AN OFF-LINE HANDWRITTEN THAI ALPHABET RECOGNITION SYSTEM FOR UNCONSTRAINED HANDWRITING STYLES
Authors: TANPRASERT THITIPONG , JITWONGTRAKUL KAMOLCHOL , TAECHOTANON SARACHAI
Published: May 2003

This paper presents a new off-line character recognition system for handwritten Thai alphabets. Unlike many existing techniques, the proposed system has been developed without any assumption on the way that the characters are written. As the results, the reported recognition rate of the proposed system correlates well with the results from real-world tests.The system consists of two classification phases where the techniques that are appropriate for each phase have been independently developed. The first phase classifies character images based on the overall character structure by a technique that emphasizes high tolerance to noise and shape distortion. The second phase performs local contour analysis using a fuzzy system in order to extract detailed features that distinguishes among similar characters. The recognition engine for both phases are neural network-type enhanced with technique called outpost vector for improved generalization. The experimental results on arbitrary handwriting confirms the effectiveness and practicality of the technique.
SUPPORT VECTOR MACHINES FOR THAI PHONEME RECOGNITION
Authors: THUBTHONG NUTTAKORN , KIJSIRIKUL BOONSERM
Published: May 2003

The Support Vector Machine (SVM) has recently been introduced as a new pattern classification technique. It learns the boundary regions between samples belonging to two classes by mapping the input samples into a high dimensional space, and seeking a separating hyperplane in this space. This paper describes an application of SVMs to two phoneme recognition problems: 5 Thai tones, and 12 Thai vowels spoken in isolation. The best results on tone recognition are 96.09% and 90.57% for the inside test and outside test, respectively, and on vowel recognition are 95.51% and 87.08% for the inside test and outside test, respectively.
TONE RECOGNITION OF CONTINUOUS THAI SPEECH UNDER TONAL ASSIMILATION AND DECLINATION EFFECTS USING HALF-TONE MODEL
Authors: THUBTHONG NUTTAKORN , KIJSIRIKUL BOONSERM
Published: May 2003

This paper presents a method for continuous Thai tone recognition. One of the main problems in tone recognition is that several interacting factors affect F0realization of tones. In this paper, we focus on the tonal assimilation and declination effects. These effects are compensated by the tone information of neighboring syllables, the F0downdrift and the context-dependent tone model. However, the context-dependent tone model is too large and its training time is very long. To overcome these problems, we propose a novel model called the half-tone model. The experiments, which compare all tone features and all tone models, were simulated by feedforward neural networks. The results show that the proposed tone features increase the recognition rates and the half-tone model outperforms conventional tone models, i.e. context-independent and context-dependent tone models, in terms of recognition rate and speed. The best results are 94.77% and 93.82% for the inside test and outside test, respectively.
MEMBERSHIP FUNCTION OPTIMISATION OF A FUZZY LOGIC CONTROLLER FOR A NON-LINEAR SYSTEM
Authors: ZADEH HOSSEIN S.
Published: May 2003

This work is an ongoing investigation of attitude control ([Formula: see text] rad rotation) as well as vibration suppression of a very flexible structure. A nominal fuzzy logic controller was designed and was used as a basis for design of an optimised fuzzy controller. Optimisation algorithm and procedure are explained. Results show a clear improvement in performance of the controller in comparison to that of the nominal system.
RELATIONSHIPS BETWEEN POSSIBILITY MEASURES AND NESTED RANDOM SETS
Authors: MIRANDA ENRIQUE , COUSO INÉS , GIL PEDRO
Published: May 2003

Different authors have observed some relationships between consonant random sets and possibility measures, specially for finite universes. In this paper, we go deeply into this matter and propose several possible definitions for the concept of consonant random set. Three of these conditions are equivalent for finite universes. In that case, the random set considered is associated to a possibility measure if and only if any of them is satisfied. However, in a general context, none of the six definitions here proposed is sufficient for a random set to induce a possibility measure. Moreover, only one of them seems to be necessary.
PIECEWISE LINEAR AGGREGATION FUNCTIONS
Authors: OVCHINNIKOV SERGEI
Published: May 2003

The Choquet and Sugeno (fuzzy) integrals are examples of piecewise linear functions on a finite dimensional space ℝn. In this paper we consider piecewise linear functions as aggregation functions and establish a Max-Min polynomial representation of these functions.
THE ALGORITHM ON KNOWLEDGE REDUCTION IN INCOMPLETE INFORMATION SYSTEMS
Authors: LIANG JIYE , XU ZONGBEN
Published: May 2003

Rough set theory is emerging as a powerful tool for reasoning about data, knowledge reduction is one of the important topics in the research on rough set theory. It has been proven that finding the minimal reduct of an information system is a NP-hard problem, so is finding the minimal reduct of an incomplete information system. Main reason of causing NP-hard is combination problem of attributes. In this paper, knowledge reduction is defined from the view of information, a heuristic algorithm based on rough entropy for knowledge reduction is proposed in incomplete information systems, the time complexity of this algorithm is O(|A|2|U|). An illustrative example is provided that shows the application potential of the algorithm.
PARTIAL CORRELATION COEFFICIENTS OF INTUITIONISTIC FUZZY SETS
Authors: HUNG WEN-LIANG
Published: May 2003

In many applications, partial correlation for three or more intuitionistic fuzzy sets are very important, but Hung [12] do not discuss this problem. In this paper, we propose a method to calculate the partial correlation of intuitionistic fuzzy sets by means of multivariate correlation model. In order to fit into normal framework, we use empirical logit transform (see Agresti [1] and Johnson and Wichern [13]) for the degree of membership of intuitionistic fuzzy set to achive this.
ON GROUP DECISION MAKING UNDER LINGUISTIC ASSESSMENTS
Authors: BUI CONG CUONG
Published: May 2003

In this paper we consider a fuzzy logic-based model in group decision making, with a focus on the set of all alternatives and on the individual lingustic preference relations. Some choice processes are devoted to the model using consensus measures and linguistic ordered weighted averaging (LOWA) operator. A multiple criteria group decision model in linguistic setting and some aggregation processes are also considered. The model and the new processes allow to incorporate human consistency in decision support systems.
FUZZY QUANTUM POSETS
Authors: LE BA LONG
Published: May 2003

This paper discusses three types of fuzzy quantum posets, states and observables on these posets, representations of fuzzy quantum posets, representation of observables, and joint observables.
NAVIGATION CONTROL OF AN INTELLIGENT WHEELCHAIR USING FUZZY LOGIC
Authors: MAEDA MIKIO , NAKAYAMA YASUSHI , MURAKAMI SHUTA
Published: May 2003

Hospital patients, persons of old age, and physically handicapped persons need wheelchairs and helpers. When a helper carries one of these persons, he/she must be attend on the person ridden on a wheelchair. The helpers are busy and have a lot of work. Patients without helpers grow very tired navigating their wheelchairs. To help, we propose an autonomous fuzzy navigation system for an automatic control of a wheelchair. This system consists of a navigation planning part, a navigation control part, and an environment recognition part. In this paper, we describe an intelligent wheelchair with a fuzzy navigation system and discuss experimental results.
MODEL IDENTIFICATION OF A SERVO-TRACKING SYSTEM USING FUZZY CLUSTERING
Authors: NGUYEN ERIC M. , PRASAD NADIPURAM R.
Published: May 2003

This paper investigates the use of Fuzzy Clustering as a means for model identification of a complex and highly non-linear servo-tracking system when only observational data is available. The use of Fuzzy Clustering facilities automatic generation of rules and its antecedent parameters. The consequent of the model is then formulated in the form of Takagi, Sugeno and Kang (TSK), and its parameters determined by the Least Squares Method (LSM).
HEDGE ALGEBRAS, LINGUISTIC-VALUE LOGIC AND THEIR APPLICATION TO FUZZY REASONING
Authors: NGUYEN CAT HO , TRAN DINH KHANG , VAN NAM HUYNH , NGUYEN HAI CHAU
Published: May 2003

People use natural languages to think, to reason, to deduce conclusions, and to make decisions. Fuzzy set theory introduced by L. A. Zadeh has been intensively developed and founded a computational foundation for modeling human reasoning processs. The contribution of this theory both in the theoretical and the applied aspects is well recognized. However, the traditional fuzzy set theory cannot handle linguistic terms directly. In our approach, we have constructed algebraic structures to model linguistic domains, and developed a method of linguistic reasoning, which directly manipulates linguistic terms, In particular, our approach can be applied to fuzzy control problems.

In many applications of expert systems or fuzzy control, there exist numerous fuzzy reasoning methods. Intuitively, the effectiveness of each method depends on how well this method satisfies the following criterion: the similarity degree between the conclusion (the output) of the method and the consequence of an if-then sentence (in the given fuzzy model) should be the "same" as that between the input of the method and the antecedent of this if-then sentence. To formalize this idea, we introduce a "measure function" to measure the similarity between linguistic terms in a domain of any linguistic variable and to build approximate reasoning methods. The resulting comparison between our method and some other methods shows that our method is simple and more effective.
TUBERDIAG: AN EXPERT SYSTEM FOR PULMONARY TUBERCULOSIS DIAGNOSIS
Authors: NGUYEN HOANG PHUONG , DANG HUU HUNG , NGUYEN VIET CO , BUI DUC DUONG , PHAM TIEN THINH , NGUYEN PHUONG HOA , NGUYEN NHAT LINH
Published: May 2003

In this paper, we present an overview of TUBERDIAG, a rule-based expert system for diagnosis of pulmonary tuberculosis. This system was developed as a 2-year joint project by the Institute of Information Technology (National Center for Science and Technology) and the National Institute of Tuberculosis and Lung Diseases, Hanoi. After designing and building a suitable inference engine for this system, we have done a lot of work to create an effective knowledge base; at present, this knowledge base contains more than 1,000 rules. The paper focuses on how the rule base is constructed, managed, and used. We also present here the first evaluation of TUBERDIAG by the doctors at the National Institute of Tuberculosis and Lung Diseases, who have been playing a very important role in the project – providing the system with their knowledge.
A FUZZY DISTRIBUTED EXPERT SYSTEM DESIGN TOOL EXGEN AND ITS APPLICATION TO SENSORY FOODSTUFF EVALUATION
Authors: NGUYEN THANH THUY , NGUYEN TOAN THANG , THAC BINH CUONG , TRAN DINH KHANG
Published: May 2003

Since the appearance of MYCIN, expert systems have been widely and successfully developed for various scientific and technological researches and applications. These applications require more and more fuzzy information resources because of the uncertainty, inexactness in labeling facts using linguistic terms and expressing human expertise. Sensory foodstuff evaluation is among this kind of fuzzy expert system applications.

In the frame of the research project on fuzzy expert systems for science and technology at the Hanoi University of Technology, we have developed an expert system building tool called EXGEN which has the following features:

– Knowledge editing in the form of production rules using Vietnamese in the natural language-like syntax. The tool is also capable to verify the consistency of an acquired knowledge base.

– Inference engine consisting of two principal inference mechanisms (forward and backward inference) and control strategy module. We proposed also some heuristics for choosing a potential inference trace, allowing to get more information about conclusions.

– Possibility of establishing a configuration for a distributed working session.

It would be possible to carry out:

+ a deduction over a shared rule base (RB) in the server, based on information acquired from workstations (common RB and conclusion, distributed fact base (FB))

+ a deduction over a shared RB in the server with different cognitive tasks (including hypotheses fact and conclusions) on workstations (common RB and distributed FB)

+ deductions on workstations with distributed knowledge bases (Distributed RB and FB)

We have already implemented an application expert system SENEXSYS for sensory foodstuff evaluation using the building tool EXGEN. Experimental results have shown that qualification given by the expert system is comparable to evaluation results obtained by following up Vietnamese standard TCVN 3215.79
A MULTIMEDIA INFORMATION ACQUISITION METHOD BASED ON FUZZY INFERENCE
Authors: OH Kabsuk , HIROTA Kaoru
Published: May 2003

A method of multimedia information data acquisition is proposed based on fuzzy rules, where multimedia mean the five human senses. Observed information is characterized by VAGOT (visual, acoustic, gustatory, olfactory and tactile) time series data and the goal is to extract an appropriate subset of VAGOT data based on a given instruction. Here, Multimedia Information centers on image and sound, represented by membership functions. Fuzzy rules based on visual and acoustic information are used to identify the appropriate time interval in three experiments: various cars on a general road, sunny-side-up eggs and fireworks multimedia information.
FUZZY INTERPRETATION OF HUMAN INTELLIGENCE
Authors: SHOURAKI SAEED BAGHERI , HONDA NAKAJI , YUASA GO
Published: May 2003

In this paper, introducing a new hardware concept which has the ability of FUZZY computation in a non-exact naturally FUZZY method, outlines of human brain simulation in hardware level will be presented. It will be shown that a soft computer may be implemented by using unique hardware structures for processor and memory units. Considering the learning procedure of human being and simulating it, using the introduced soft computer, a total energy decreasing trend will be observed in the soft computer structure. The generalization of this trend will be regarded as an equivalent concept for human intelligence. Therefore, complicated concepts such as human intelligence and also imagination and inference procedures may appear as natural abilities of the proposed soft computer. It also will be shown, when starting with observing a phenomenon, the whole procedure, from modeling to controller designing, including the recognition of goal function and effective inputs, may be done automatically and in an intelligent way.
FUZZY IDENTIFICATION OF THE USER'S REQUIREMENTS IN THE HUMAN INTERFACE OF MAN-MACHINE SYSTEMS BY THE GLOBAL LEARNING METHOD
Authors: SUZUKI IZUMI , OHSATO ARIO
Published: May 2003

This paper presents a "Global Learning Method" (G.L.M.) that can be used to construct a human-friendly interface for man-machine systems. The aims of the G.L.M. is to identify, in a user-friendly manner, the user's requirements of the environments by means of a fuzzy set in order to give adequate instructions to the machine to make a desired environment for the user. First, man-machine systems are considered from the viewpoint of human friendly interface. Second, the G.L.M. is proposed, and third, the method is applied to the practical problem of identifying the user's requirements in a color environment of the Graphical User Interface (GUI) of personal computers and the results are shown. Finally, the effectiveness of introducing the G.L.M. to the construction of a human friendly interface is discussed from the viewpoint of man-machine systems.
HIERARCHICAL DECISION MAKING IN STRATEGIC INVESTMENT BY A BOLTZMANN MACHINE
Authors: WATANABE TERUYUKI , WATADA JUNZO , ODA KENJI
Published: May 2003

A conventional portfolio selection problem, which is based on a mean-variance model, is difficult to solve by using mathematical programming techniques. This difficulty is caused by the fact that the corresponding mathematical programming problems are large-dimensional one, since almost all variance-covariances of return rates are, typically, not zeros. In this paper, we propose an efficient method for solving a portfolio selection problem, a method which uses a Boltzmann machine.

In a real-life problem, it is also important to find the optimal combination of a small number of invested securities out of many securities in a market, because of a limited amount of funds to invest into securities. So we also propose a portfolio selection method to obtain the invest ratio of limited number of securities out of huge number of securities using a multi-stage application of the Boltzmann machine.
SHEWHART CHARTS FOR THE DETECTION OF LINEAR TRENDS AND OF SHIFTS IN AN AUTOREGRESSION MODEL
Authors: GÖB RAINER
Published: May 2003

The paper considers a univariate characteristic of a manufacturing process which is measured at discrete time points. The characteristic exhibits a linear trend under an AR(1) disturbance. If the slope of the linear trend and the autoregression coefficient are known, the process characteristic can be adjusted to vary as white noise around its target. However, the adjustment policy is very sensitive to departures from model assumptions and fails to achieve its objective in case of shifted model parameters, e.g., in case of biased estimates or external assignable causes which change the parameters. A discussion of the behaviour of the adjusted process shows that parameter shifts can have harmful consequences. As a protection against parameter shifts, additional statistical monitoring of the process is indispensable. The paper introduces various Shewhart control charts for the detection of shifts in the mean, the trend parameter, or the autoregression parameter. The performance of the charts is analyzed by the average run length criterion.
INTRODUCING DOMAIN KNOWLEDGE FOR SELECTION OF ACTIVE FACTORS IN DESIGNED EXPERIMENTS
Authors: EKDAHL FREDRIK , PERSSON PER , WIKLUND PIA SANDVIK
Published: May 2003

Unreplicated factorial designs are widely used for designed experimentation in industry. In the analysis of designed experiments, the experimental factors influencing the response must be identified and separated from those that do not. An abundance of procedures intended to perform this selection have been introduced in the literature. A recent study indicated that the procedure due to Box and Meyer outperforms the lot of the other selection procedures in terms of efficiency and robustness. The procedure of Box and Meyer rests on a quasi-Bayesian foundation and utilizes generic domain knowledge, in the form of a common-for-all-factors a priori probability, that a factor significantly influences the response, to calculate an a posteriori probability for each factor. This paper suggests a strategy for introducing more elaborate domain knowledge about the experimental factors in the procedure of Box and Meyer, aiming to further improve its performance.
A NOTE ON STATISTICAL MONITORING OF ENGINEERING CONTROLLED PROCESSES
Authors: TSUNG FUGEE
Published: May 2003

The importance of Statistical Process Control (SPC), also called Statistical Process Monitoring (SPM) techniques, for quality improvement is well-recognized in industry. With advances in sensing and data collection technology, large volumes of data are being routinely collected under Engineering Process Control (EPC) or Automatic Process Control (APC). There is a great need for SPC for variation reduction and quality improvement in these environments. This research studies the statistical properties of monitoring the process output and the control action of EPC controlled processes. Several statistical monitoring strategies are introduced and their advantages and disadvantages are discussed.
A SUBJECTIVE SAFETY AND COST BASED DECISION MODEL FOR ASSESSING SAFETY REQUIREMENTS SPECIFICATIONS
Authors: WANG J. , YANG J. B.
Published: May 2003

This paper presents a subjective safety and cost based modeling approach for evaluating safety requirements specifications in the study of safety-critical software. In the approach fuzzy set modeling and evidential reasoning are combined to assess both the safety associated with and the cost incurred in each option of safety requirements specifications. Both safety and cost estimates are combined to obtain the preference degree associated with each option of safety requirements specifications for selecting the best one. An example is presented to demonstrate the proposed approach for safety based on decision-making in safety requirements analysis of safety critical software development.
TESTING THE FIT TO GENERALIZED POISSON DISTRIBUTIONS BASED ON AN EMPIRICAL TRANSFORM
Authors: MEINTANIS SIMOS , KOUTROUVELIS I. A.
Published: May 2003

Generalized Poisson distributions appear as applied-research models in many fields. For example in reliability, the total amount of wear of items, the hazard rate and the total time to failure can be modeled after a Generalized Poisson distribution. Methods of Statistical Inference for such distributions have been scarce since the corresponding distribution functions come in complicated, often not closed form, expressions. In this article, we present a method for testing the goodness-of-fit to any specified member of the family of Generalized Poisson distributions. The proposed method utilizes the general form of the moment generating function of Generalized Poisson distributions. The asymptotic distribution of the test statistics is derived when the parameters of the generalizing distribution are assumed known as well as unknown. The performance of the procedures is investigated by employing real and simulated data.
TESTING PROCESS CAPABILITY USING THE INDEX Cpmk WITH AN APPLICATION
Authors: PEARN W. L. , YANG S. L. , CHEN K. S. , LIN P. C.
Published: May 2003

Numerous process capability indices, including Cp, Cpk, Cpm, and Cpmk, have been proposed to provide measures on process potential and performance. Procedures using the estimators of Cp, Cpk, and Cpm have been proposed for the practitioners to use in judging whether a process meets the capability requirement. In this paper, based on the theory of testing hypothesis, we develop a step-by-step procedure, using estimator of Cpmk for the practitioners to use in making decisions. Then, the proposed procedure is applied to an audio-speaker driver manufacturing process, to demonstrate how we may apply the procedure to actual data collected in the factory.
DESIGN OF THE LIFT-GATE WEDGES IN SPORTS UTILITY VEHICLES FOR IMPROVED RELIABILITY
Authors: IM KEE H. , PARTHASARATHY RAVI
Published: May 2003

Lift-gate is a rear closure system present in sports utility vehicles (SUV) and minivans. It has multiple design variables affecting multiple functional requirements. A wedge is a small piece of hardware used to stabilize the lift-gate especially in cross-car direction by providing the load path from the lift-gate to the surrounding structure. But, a wedge may increase the closing effort due to the reaction force in the swing direction. Furthermore, wedges need to accommodate the gap variation to bridge the lift-gate and the body frame. This paper presents the characteristics of two different types of wedges, their effects on the lift-gate system, and design methodologies to improve the wedge performance.