bluuebunny/crossref_metadata_2025 huggingface dataset:
An Efficient Conflict–Resolution Approach to Support Read/Write Operations in a Video Server
Authors: Lee Chien-I , Chang Ye-In , Yang Wei-Pang
Published: October 2003

In this paper, we propose an efficient conflict-resolution approach based on the multi-disk architecture for the insertion/deletion operations on continuous media that are split up into blocks and placed in various locations on the disk, without reorganizing the whole data. When a new subobject is inserted after subobject i, it will be assigned with an identification number (i + 1) and be inserted into a disk in which the retrieval of the new subobject does not conflict with the retrieval of any other subobject, where a conflict means a pair of two consecutive subobjects that are stored in the same disk have to be retrieved simultaneously. However, a new conflict on the same disk may occur since all the identification numbers of subobjects after subobject i are increased by one. Only when such a new conflict occurs, one movement operation is required, so does the case of a deletion operation. Moreover, to reduce those additional movement cost, a deferring approach is proposed at the cost of an additional buffer. In this approach, n data insertions are deferred and stored in a buffer. Then, the system starts to insert those data after an optimal insertion sequence is determined. Based on this approach, two strategies are proposed: the conflict-resolved-first-deferring strategy (the CRFD strategy) and the conflict-resolved-last-deferring strategy (the CRLD strategy). From our performance analysis, we will prove that the CRLD strategy with an insertion sequence according to the ascending order of identification numbers is an optimal strategy based on the proposed deferring approach.
User Control and Dynamic Reorganization of Multimedia Presentations During Playout
Authors: Hakkoymaz Veli , Znati F. , Dogdu E.
Published: October 2003

A methodology to dynamically adjust the multimedia presentations as a result of user interactions during the playout is introduced. A constraint-driven approach is described for the automated assembly, organization and playout of presentations from multimedia databases. To allow interactive user control over the playout of an automatically generated presentation, a set of control buttons are provided. Using these buttons, the user can control and change the flow of the presentation in a variety of ways. Interactive user control during the presentation playout, however, can introduce new delays in the original presentation schedule of multimedia segments and possibly change playout constraints. To account for these delays and changes, strategies to (a) dynamically reorganize the subpresentations into a presentation, (b) replace segments with their compacted clips, and (c) delete segments on the presentation graph are proposed.
Application of Graph Grammars in an Educational Software Engineering Game: A Case Study in Pragmatic Adoption
Authors: Schneider Kurt
Published: October 2003

This paper introduces an approach to modeling software project dynamics using an attributed graph grammar formalism. A project situation is modeled and presented to a "player" who is supposed to act as project manager of a simulated project. Events and internal processes of the simulated project are modeled using a custom-designed formalism that integrates attributed graph grammar concepts with a quantitative simulation mechanism resembling System Dynamics. Both ingredients were pragmatically selected and blended based on (1) their comparative simplicity, (2) their expressive power, and (3) their intuitive appeal for bridging the cognitive gap between real-world software engineering experiences and an executable simulation model.

This modeling formalism was applied in the SESAM educational software engineering game. The modeling formalism was supported by a family of graphical SESAM editors. Resulting models could be animated and served as simulated projects in the game runs. SESAM was applied in graduate courses on software project management at the University of Stuttgart. Experiences with the modeling approach are reported. The design history and design rationale that led to using graph grammars as the underlying formalism are described and discussed. The design of the SESAM modeling formalism is presented as an (involuntary) case study in adopting a graph grammar approach.
Nested Graph Transformation Units
Authors: Kreowski Hans-Jörg , Kuske Sabine , Schürr Andy
Published: October 2003

In this paper, we introduce a new concept for the structured development of rule-based graph transformation systems that allows to build up large systems from small pieces in a modular way. The concept is called nested graph transformation unit and consists of a network of local graph transformation units. While each local unit provides a set of rules and control conditions (including input and output descriptions), the net reflects the import structure of the system where each local unit can use its direct neighbours without any restrictions. In particular, the import structure may contain cycles. It is shown that nested graph transformation units have a reasonable operational semantics by iterating the so-called interleaving operator, which interleaves local rule applications with calls of used units according to the local control conditions. It turns out that the iterated interleaving semantics is the smallest fixed point of the interleaving operator provided that the involved control conditions are continuous in a certain sense.
Generating an Algebraic Specification from an ER-Model
Authors: Doberkat Ernst-Erich
Published: October 2003

Entity-Relationship modelling is a visual, hence a rather intuitive technique for specifying the structure of complex data. The technique is popular in part because the structure of an ER-model is easily grasped, and it is usually supported by diagrams or other visualizing tools. This paper deals with a detailed analysis of ER-modelling with the goal of deriving an algebraic specification for a given ER-model. This is motivated by considerations regarding program specification for data intensive applications. We indicate how the technique demonstrated here may be combined with formal techniques for specifying the functional behavior of a system.
A Polynomial Function Discovery System — FFS
Authors: Tzafestas Spyros , Ma Zhifang
Published: October 2003

This paper presents a function discovery system FFS that has two core parts: FFS-0-CORE and FFS-1-CORE. Both cores are with polynomial time complexity in discovering functions of either a•f(x)+b form or a1f1(x)+…+anfn(x)+b form. FFS-0-CORE allows users to define their own models. FFS-1-CORE uses novel principles to increase information which helps the function discovery procedures. Three computational examples are included.
Use of a System of Recurrent Neural Networks for Solving the Cell Placement Problem in VLSI Design
Authors: Singh Kirti , George Suju M. , Rambabu P.
Published: October 2003

Cell placement in VLSI design is an NP-complete problem. In this paper, we have tried to solve the standard cell placement problem using the Hopfield neural network model. Furthermore, a new system of coupled recurrent neural networks, which was designed to eliminate the drawbacks of the Hopfield neural network, is introduced.

The performance of Hopfield networks with discrete and graded neurons is also investigated. The energy function corresponding to the chosen representation is given and the weight matrix and the inputs needed for the network are also computed in this work. Several different combinations of parameters were examined to find the optimum set of parameters which results in better and faster convergence.

To show the effectiveness of our methods, cell placement problems up to 30 cells are considered and the results are compared with the results obtained by a genetic algorithm. Our results show that a system of coupled neural networks could be an efficient way to overcome the limitation of recurrent neural networks which consider only bilinear forms of the energy function.
A Rulebase Management System Using Conceptual Rule Modeling
Authors: Bouziane M'Hamed , Hsu Cheng
Published: October 2003

Conceptual modeling is a fundamental concept in information management. Although originated in the theory and practice of databases, its significance as a guiding principle reaches all areas of information integration efforts dealing with heterogeneous uses. In the field of knowledge-based systems, an emerging need is for expert system shells to be able to manage triggers that change frequently and to support heterogeneous applications which use the same rulebase simultaneously but in different ways. A conceptual schema is clearly in order for this new capability. In addition, it is central to integrating databases with knowledge bases as well as providing interoperability to multiple (heterogeneous and distributed) knowledge-based systems.

This paper presents a rulebase management system (RBMS) featuring a conceptual schema. The model of the conceptual schema is developed using the Two-Stage Entity-Relationship approach, which is compatible with most common methods and requires only standard data and rules processing technology to implement. The architecture and execution model of RBMS are discussed in details. Its specific implementation design is applicable to managing rules both in the usual rule-based systems and in the systems where rules are embedded into objects or entities. The processing methods are verified with a prototype, which is also discussed in this paper. The RBMS design is being implemented for Samsung Electronics Corporation.
An ILP Based Knowledge Discovery System
Authors: Chen Po-Chi , Hsueh Ru-Fang , Hwang Shu-Yuen
Published: October 2003

Interest in research into knowledge discovery in databases (KDD) has been growing continuously because of the rapid increase in the amount of information embedded in real-world data. Several systems have been proposed for studying the KDD process. One main task in a KDD system is to learn important and user-interesting knowledge from a set of collected data. Most proposed systems use simple machine learning methods to learn the pattern. This may result in efficient performance but the discovery quality is less useful.

In this paper, we propose a method to integrated a new and complicated machine learning method called inductive logic programming (ILP) to improve the KDD quality. Such integration shows how this new learning technique can be easily applied to a KDD system and how it can improve the representation of the discovery. In our system, we use user's queries to indicate the importance and interestingness of the target knowledge. The system has been implemented on a SUN workstation using the Sybase database system. Detailed examples are also provided to illustrate the benefit of integrating the ILP technique with the KDD system.
Efficiency Mechanisms for a Class of Blackboard Systems
Authors: Hewett Rattikorn , Hewett Micheal
Published: October 2003

This paper presents efficient mechanisms for activation, execution and rating that are suitable for use in BB1-style blackboard architectures. We describe a knowledge source compiler that produces match networks and demons for efficient activation and rating while compiling the entire system for increased execution speed. Experiments using the enhancements in a general-purpose blackboard shell illustrate approximately a doubling of run time speed, including an increase in activation speed by a factor of 7.6 on the average.

We have also resolved a subclass of blackboard systems that can be compiled down to the machine level by using a condensed representation where low-level blackboard accesses are replaced by vector references. Our analysis shows that the time complexity of the execution cycle of a condensed system is faster than the conventional approach by the ratio of the time required for blackboard retrievals to the time required for vector element retrievals. In practice, this ratio is approximately four orders of magnitude.
HighLAP: A High Level System for Generating, Representing, and Evaluating Assembly Sequences
Authors: Röhrdanz F. , Mosemann H. , Wahl F. M.
Published: October 2003

In this paper we present our high level assembly planning system HighLAP·HighLAP generates and evaluates all assembly sequences of a mechanical assembly with minimal user interaction. For the evaluation of all feasible assembly sequences several criteria are taken into account. HighLAP considers for example the separability and the manipulability of the generated (sub)assemblies. Furthermore, the necessity of reorientation for a mating operation and parallelism during plan execution is considered. Another important criterion is the stability of the generated (sub)assemblies. Most of the assembly planners developed up to date use heuristics or user defined criteria to determine assembly stability for plan evaluation. In order to bring automatic assembly planning closer to reality HighLAP performs a powerful geometrical and physical reasoning. The presented system is the first assembly planning system taking into account the range of all stable orientations of an assembly considering friction for plan evaluation.
Fast and Sound Two-Step Algorithms for Multiple Alignment of Nucleic Sequences
Authors: Abdeddaim Said
Published: October 2003

We report here on our work on multiple alignment of biological sequences. The observation of actual alignments has lead us to formulate heuristics from which we have derived new and efficient algorithms. These two algorithms are very fast and give reasonably good results. They work in two steps: blocks are found in the sequences, and then the sequences are aligned between the blocks. Strong and sound hypotheses made at every step, as well as a new representation of blocks, yield high efficiency of the resulting algorithms.
Fuzzy CPU Scheduling
Authors: Zhang Yan-Qing , Kandel Abraham
Published: October 2003

In this paper, the methodology of using fuzzy logic techniques to improve the performance of CPU scheduling is concisely proposed. To make CPU work efficiently in the multiple-factor environment, we developed a fuzzy CPU scheduling algorithm to deal with the fuzziness of CPU scheduling. The simulations of different CPU scheduling algorithms have shown that the fuzzy CPU scheduling algorithm is an efficient scheme for compromising multiple factors.
Disorientation and Cognitive Overhead in Hypertext Systems
Authors: Ransom Stephen , Wu Xindong , Schmidt Heinz
Published: October 2003

Disorientation and cognitive overhead are two interrelated problems that may in fact ultimately limit the usefulness of hypertext. Cognitive overhead upon the author arises from a viewpoint that sees the author as the person solely responsible for inserting all links within her work. This includes all links between the anchors in her own work and those in external frames, as well as cross-links between the anchors within her own work. The need for an author to be aware, for each anchor within her work, of all possible other anchors makes the insertion of such links an O(N2) problem where N is the number of possible anchors in the hypertext universe. To reduce this to an O(N) problem this paper proposes the use of bi-directional intelligent anchors. These are anchors that have both a knowledge of the concepts that a potential reader would be seeking were she to arrive at the anchor, together with a knowledge of the concepts that a reader would be seeking were she to jump from that anchor to another within the hypertext.

Disorientation or the lost in hyperspace effect on the reader can be addressed in many cases by a fundamental re-definition of the relationship between hypertext authors and their readers. To address this issue, this paper proposes a unit of authorship based more on the treatise than on the traditional fragmented model of hypertext that we call a scenic route and which is based loosely on Bush (1945)'s Trails and Trigg (1988 and 1991)'s Guided Tours.
TCGD: A Time-Constrained Approximate Guided Depth-First Search Algorithm
Authors: Wah Benjamin W. , Chu Lon-Chan
Published: October 2003

In this paper, we develop TCGD, a problem-independent, time-constrained, approximate guided depth-first search (GDFS) algorithm. The algorithm is designed to achieve the best ascertained approximation degree under a fixed time constraint. We consider only searches with finite search space and admissible heuristic functions. We study NP-hard combinatorial optimization problems with polynomial-time computable feasible solutions. For the problems studied, we observe that the execution time increases exponentially as approximation degree decreases, although anomalies may happen. The algorithms we study are evaluated by simulations using the symmetric traveling-salesperson problem.
Incremental Updates of Discovered Multi-Level Association Rules
Authors: Cheung David W. , Ng Vincent T. , Tam Benjamin W.
Published: October 2003

Update of the single- and multi-level association rules discovered in large databases is inherently costly. The straight forward approach of re-running the discovery algorithm on the entire updated database to re-discover the association rules is not cost-effective. An incremental algorithm FUP have been proposed for the update of discovered single-level association rules. In this study, we have shown that the incremental technique in FUP can be generalized to other data mining systems. An efficient algorithm MLUp has been proposed for the updating of discovered multi-level association rules. Our performance study shows that MLUp has a superior performance over the representative mining algorithm such as ML-T2 in updating discovered multi-level association rules.
Representation Shifts Using Knowledge Compilation
Authors: Ho F. , Kamel M.
Published: October 2003

Tractability versus expressiveness is a problem underlying the current generation of problem solvers. It is desirable to specify the problem, along with knowledge required for its solution, in the most expressive means possible. However, from the perspective of the solver, the most efficient representation is the least expressive one. One solution to this problem is to devise a means of transforming an expressive problem description into an efficient problem solver. Knowledge compilation is the process of transforming a domain theory into a form specialized for the solution of a given problem set. This paper will present OPCOMP, a system devised to compile a first order quantifier free predicate calculus domain theory into a problem reduction solver.
Modeling User Requirements with a Front-End Analysis
Authors: Lee Jonathan , Kuo Jong-Yih , Liu Alan
Published: October 2003

In this paper, we propose a front-end analysis approach to specifying vague requirements and identifying implicit user requirements for early validation. First, functional requirements are arranged into a function-subfunction hierarchy based on functional decomposition approach; whereas, nonfunctional requirements are decomposed into two types of hierarchy: a classification hierarchy through IS-A relationship, and an aggregation hierarchy using IS-PART-OF relationship. Second, constraint networks are built from the hierarchies. Propagation rules are then applied to derive implicit requirements. Finally, the derived requirements are represented using Zadeh's canonical forms14.
Compiling Knowledge-Based Systems to Ada: The PrkAda ProTalk Compiler
Authors: Filman Robert E. , Morris Paul H.
Published: October 2003

This paper describes the implementation of the ProTalk compiler for PrkAda. An important component of the ProKappa system is its multi-paradigm, mixed-rule/imperative language, ProTalk. ProTalk combines elements of backtracking AI languages such as Prolog with imperative constructs such as conditionals, iteration, assignment, and subprogram invocation. Our implementation illustrates the use of generators to achieve a Prolog-like semantics, and the possibility (and difficulties) of employing such mechanisms in Ada.
Compiling Knowledge-Based Systems to Ada: The PrkAda Core
Authors: Filman Robert E. , Morris Paul H.
Published: October 2003

This paper describes the implementation of PrkAda, a system for delivering, in Ada, Artificial Intelligence and object-oriented applications developed using the ProKappa system. (ProKappa is a modern, multi-paradigm knowledge-based–system development tool. It includes facilities for dynamic object management, rule-based processing, daemons, and graphical developer and end-user interfaces. ProKappa is a successor system to KEE.) Creating PrkAda required creating a run-time, Ada-language, object-system "core," and developing a compiler to Ada from ProTalk (ProKappa's high-level, backtracking-based language). We describe PrkAda ProTalk compiler in a companion paper [5]. This paper concentrates on the issues involved in implementing an AI application delivery core, particularly with respect to Ada, including

• Automatic storage management (garbage collection) without either the cooperation of the compiler or access to the run-time stack,

• Dynamic (weak) typing in a strongly-typed language,

• Dynamic objects (objects that can change their slots and parentage as the program is executing)

• Dynamic function binding in a language designed to preclude "self-modifying programs," and

• Implementation trade-offs in object-oriented knowledge-based systems development environments
Neurofuzzy Anticipatory Systems: A New Approach to Intelligent Control
Authors: Tsoukalas Lefteri H.
Published: October 2003

Anticipatory systems are systems whose change of state is based on information about present as well as future states. Planning and acting on the basis of anticipations of the future is an omnipresent feature of human control strategies, deeply permeating our daily experience and considered as the hallmark of natural intelligence. Yet, as the eminent mathematical biologist Robert Rosen has pointed out in his book Anticipatory Systems (1985), such control strategies are curiously absent from existing formal approaches to automatic control and decision-making processes. Recent developments in biology, ethology and cognitive sciences, however, as well as advancements in the technology of computer-based predictive models, compel us to reconsider the role of anticipation in intelligent systems and to the extent possible incorporate it in our formal approaches to control. Significant improvements in neural predictive computing when combined with the flexibility of fuzzy systems, supports the development of neurofuzzy anticipatory control architectures that integrate planning and control sequencing functions with feedback control algorithms. A review of the role of anticipation in intelligent systems and a new approach for neurofuzzy anticipatory control using radial basis neural predictive models and fuzzy if/then rules is presented.
An Application of a Recurrent Neural Model for Parsing Natural Language
Authors: Salerno John J.
Published: October 2003

Neural models for dealing with symbolic processing are in their infancy. Success thus far can be defined by the parsing of very simple phrases and a small set of words into small, fixed size frames. Many of these systems do not scale well as one increases the number of words or the phrase length. These models are limited with respect to the large number of epochs required to train and the error rates. In the discussion that follows we will address the issue of training. We will present an analysis which will provide a lower bound on the error rate. The approach presents simple extensions to the basic learning algorithm and make use of a closest neighbor algorithm for correctness. Other issues such as generalization versus memorization, optimum hidden layer size and teaching the network after the initial training phase are also discussed.
Order in Space: A General Formalism for Spatial Reasoning
Authors: El-Geresy Baher A. , Abdelmoty Alia I.
Published: October 2003

In this paper we propose a general approach for reasoning in space. The approach is composed of a set of two general constraints to govern the spatial relationships between objects in space, and two rules to propagate relationships between those objects. The approach is based on a novel representation of the topology of the space as a connected set of components using a structure called adjacency matrix which can capture the topology of objects of different complexity in any space dimension. The formalism is used to explain spatial compositions resulting in indefinite and definite relations and it is shown to be applicable to reasoning in the temporal domain. The main contribution of the formalism is that it provides means for constructing composition tables for objects with arbitrary complexity in any space dimension. A new composition table between spatial objects of different types is presented. A major advantage of the method is that reasoning between objects of any complexity can be achieved in a defined limited number of steps. Hence, the incorporation of spatial reasoning mechanisms in spatial information systems becomes possible.
The Integration of Qualitative Orientation and Named Distances: Application to a Qualitative Navigation Simulator
Authors: Escrig M. Teresa , Toledo Francisco
Published: October 2003

Human beings reason about different aspects of space (such as relative orientation, cardinal directions, distance, size and shape of objects) quite easily. With the aim of simulating human behavior, several models for these spatial concepts have been developed in the recent years. Cognitive considerations have made these frameworks qualitative, because they seem to deal better with the imprecision that human perception provides. However, an operational model to reason with all these spatial aspects in an integrated way has not been developed, up to now. The first aim of our research work has been the integration of different spatial concepts into the same spatial model which has been accomplished thanks to the definition of an operational model based on Constrain Logic Programming extended with Constraint Handling Rules. Although other aspects of space have been successfully represented by these techniques [2], in this paper we focus our attention in positional information, that is, orientation integrated with distance information. The Constraint Solver developed for managing positional information has a temporal complexity of O(n) 3, where n is the number of spatial landmarks considered in the reasoning process. The second aim of our work is to apply qualitative spatial reasoning to develop a Qualitative Navigation Simulator.
Mixed-Level Knowledge Representations and Variable-Depth Inference in Natural Language Processing
Authors: Hess Michael
Published: October 2003

A system is described that uses a mixed-level knowledge representation based on standard Horn Clause Logic to represent (part of) the meaning of natural language documents. A variable-depth search strategy is outlined that distinguishes between the different levels of abstraction in the knowledge representation to locate specific passages in the documents. A detailed description of the linguistic aspects of the system is given. Mixed-level representations as well as variable-depth search strategies are applicable in fields outside that of NLP.
Improving Performance of Case-Based Classification Using Context-Based Relevance
Authors: Jurisica Igor , Glasgow Janice
Published: October 2003

Classification involves associating instances with particular classes by maximizing intra-class similarities and minimizing inter-class similarities. Thus, the way similarity among instances is measured is crucial for the success of the system. In case-based reasoning, it is assumed that similar problems have similar solutions. The case-based approach to classification is founded on retrieving cases from the case base that are similar to a given problem, and associating the problem with the class containing the most similar cases.

Similarity-based retrieval tools can advantageously be used in building flexible retrieval and classification systems. Case-based classification uses previously classified instances to label unknown instances with proper classes. Classification accuracy is affected by the retrieval process – the more relevant the instances used for classification, the greater the accuracy.

The paper presents a novel approach to case-based classification. The algorithm is based on a notion of similarity assessment and was developed for supporting flexible retrieval of relevant information. Case similarity is assessed with respect to a given context that defines constraints for matching. Context relaxation and restriction is used for controlling the classification accuracy. The validity of the proposed approach is tested on real-world domains, and the system's performance, in terms of accuracy and scalability, is compared to that of other machine learning algorithms.
Data Mining Using $\mathcal{MLC}++$ a Machine Learning Library in C++
Authors: Kohavi Ron , Sommerfield Dan , Dougherty James
Published: October 2003

Data mining algorithms including maching learning, statistical analysis, and pattern recognition techniques can greatly improve our understanding of data warehouses that are now becoming more widespread. In this paper, we focus on classification algorithms and review the need for multiple classification algorithms. We describe a system called [Formula: see text], which was designed to help choose the appropriate classification algorithm for a given dataset by making it easy to compare the utility of different algorithms on a specific dataset of interest. [Formula: see text] not only provides a workbench for such comparisons, but also provides a library of C++ classes to aid in the development of new algorithms, especially hybrid algorithms and multi-strategy algorithms. Such algorithms are generally hard to code from scratch. We discuss design issues, interfaces to other programs, and visualization of the resulting classifiers.
A Novel Search Technique for Solving Over-Constrained Problems
Authors: Marchiori Elena , Marchiori Massimo , Kok Joost N.
Published: October 2003

In many applications, such as decision support, negotiation, planning, scheduling, etc., one needs to express requirements that can be only partially satisfied. In order to express such requirements, we propose a technique called forward-tracking. Intuitively, forward-tracking is a kind of dual of chronological back-tracking: if a program globally fails to find a solution, then a new execution is started from a program point and a state 'forward' in the computation tree. This search technique is applied to the specific paradigm of constraint logic programming, obtaining a powerful extension that preserves all the useful properties of the original scheme. We report on the successful practical application of forward-tracking to the evolutionary training of (constrained) neural networks, and discuss other interesting applications.
Artificial Neurogenesis: Applications to the Cart-Pole Problem and to an Autonomous Mobile Robot
Authors: Michel Olivier , Clergue Manuel , Collard Philippe
Published: October 2003

A lot of recent research papers focus on the challenging problem of the combination of genetic algorithms and artificial neural networks. Developmental and molecular biology may be a source of inspiration for designing powerful artificial neurogenesis systems allowing the generation of complex modular structures. This paper describes in details such a neurogenesis model associated with an evolutionary process and its applications to the cart-pole problem and to the control of a mobile robot. Early results demonstrate the surprising efficiency of this methodology and give hints to continue the research towards the generation of more complex adaptive neural networks.
A Purely Symbolic Model for Dynamic Scene Interpretation
Authors: Chaudron Laurent , Cossart Corine , Maille Nicolas , Tessier Catherine
Published: October 2003

The symbolic level of a dynamic scene interpretation system is presented. This symbolic level is based on plan prototypes represented by Petri nets whose interpretation is expressed thanks to 1st order cubes, and on a reasoning aiming at instantiating the plan prototypes with objects delivered by the numerical processing of sensor data. A purely symbolic meta-structure, grounded on the lattice theory, is then proposed to deal with the symbolic uncertainty issues. Examples on real world data are given.
A Framework for Epidemic Models
Authors: Gielen J. L. W.
Published: October 2003

A framework is developed that enables the modeling of the various mechanisms of epidemic processes. A model within the framework is completely characterized by a set of transmission functions. These functions support the modeling of the infectivity of a new infective as a function of its age-of-infection. They also support the presence of a, possible time-dependent, outside source of infection and allow for the introduction of an inhibitor function that accounts for the decreasing number of available susceptibles in the course of the epidemic. In addition this inhibitor function could describe the effects of an inoculation program, or a governmental information campaign, or improvements in general health care on the course of the epidemic. The proposed models deliver a complete stochastic description of the infectious-age structure of the population at any moment of time. In particular the size of the epidemic, that is the probability distribution of the number of new infectives, is worked out. By letting time tend to infinity an analytical expression for the final size of the epidemic is found. This leads to new recursive procedures for the determination of this final size. Ludwig's recursive scheme for this purpose is considerably extended. Finally, using a specific type of model from within the framework as a building block, a compound model is introduced that describes an epidemic with a structured population of infectives. Although such a compound model goes beyond the boundaries of the framework, still important characteristics present in the framework are preserved in such a model. The size of the epidemic at a certain moment of time, according to a compound model, as well as its final size are easily found. Moreover, for the infinite case simple expressions for the final size distribution and its first moment are found. This leads to a precise quantitative threshold theorem, that discriminates between a minor outbreak or a major build-up for such an epidemic.
An Optimal Treatment Strategy for Diabetes
Authors: Nyabadza Farai , Lungu Edward M.
Published: October 2003

Consider a system on n variables involved in the regulation of glucose in the body, whose concentrations are given by stochastic differential equations driven by m-dimensional Brownian motion. We formulate a stochastic control problem and give sufficient conditions for the existence of an optimal treatment strategy. We study the following problem: what treatment strategy for the n variables, maximizes the expected benefit from treatment.
William Bateson, Richard Goldschmidt, and Non-Genic Modes of Speciation
Authors: Forsdyke D. R.
Published: October 2003

Sometimes a cross between two individuals that appear to belong to the same species produces a sterile offspring (i.e., their hybrid is sterile). Thus, the two individuals appear reproductively isolated from each other. If each could find a compatible mate, then new species might emerge. At issue is whether the form of hybrid sterility that precedes sympatric differentiation into species is, in the general case, of genic or non-genic origin. Several recent papers lend the authority of William Bateson to the genic hypothesis, referring to the "Bateson–Dobzhansky–Muller hypothesis". All these papers cite a 1996 paper that, in turn, cites a 1909 paper of Bateson. However, from 1902 until 1926 the latter espoused a non-genic hypothesis that today would be classified as "chromosomal". Analysis of Bateson's 1909 text reveals no recantation. Bateson's non-genic view was similar to that advanced by Richard Goldschmidt in the 1940s. However, Bateson proposed a contribution from parents of abstract factors that, together in their hybrids, complement to bring about a negative effect (hybrid sterility). In contrast, Goldschmidt proposed that normally parents contribute complementary factors making parental chromosomes compatible at meiosis in their hybrids, which hence are fertile (i.e., the parental factors work together to produce a positive effect). When the factors are not sufficiently complementary the parental chromosomes are incompatible in their hybrids, which hence are sterile. The non-genic Batesonian–Goldschmidtian abstractions are now being fleshed-out chemically in terms of DNA base-composition differences.
Oscillation and Persistence in a Mangrove Ecosystem in Presence of Delays
Authors: Bhattacharyya Rakhi , Mukhopadhyay Banibrata
Published: October 2003

In this paper, we have considered a resource based model of the Sunderban Mangrove ecosystem with detritus recycling. The criteria of stability and persistence with constant detritus input and instantaneous detritus recycling is obtained. We also studied the delay effect on recycling of detritus and maturation of detritivores and performed bifurcation analysis in the presence of delays.
On the Comparisons of OWA Operators and Ordinal OWA Operators
Authors: Fan Taihe , Ralescu Dan A.
Published: October 2003

In this paper, comparisons of OWA operators and ordinal OWA operators are carried out by using lattice theoretic methods. It is proved first that in both cases, the set of all aggregation operators forms a lattice, then the concept of positive valuation is used to measure the "orness" of aggregation operators and the structures of all such possible "orness" measures are determined.
On-Line Chinese Character Recognition by Incorporating Human Knowledge
Authors: Liu Jianzhuang , Cham W. K. , Chang Michael M. Y.
Published: October 2003

A stroke order and number free method for on-line recognition of Chinese characters is proposed. Both input characters and the model characters are represented with complete attributed relational graphs (ARGs). The ARGs of the model base are built according to the human knowledge of the segment relation structure of Chinese characters. For the recognition purpose, an optimal matching measure between two ARGs is defined, and the graph matching is formulated as a search problem of finding the minimum cost path in a state space tree, using the A * algorithm. Moreover, to reduce the search time of the A *, besides a heuristic estimate, a novel strategy is employed which again uses the human knowledge of the segment position structure of Chinese characters to prune the tree. Our experimental results demonstrate the efficiency of the proposed method.
A Simple Procedure for Pattern Pre-Recognition Based on Fuzzy Logic Analysis
Authors: Novák Vilém , Zorat Alessandro , Fedrizzi Mario
Published: October 2003

In this paper a simple procedure for pattern pre-recognition is presented. The task is to recognize whether a given pattern should be interesting for further analysis or not. The description of the procedure presented in this paper is based on formal theory of fuzzy logic in narrow sense so that the procedure – being general – can be used for many other purposes where patterns are to be recognized.
A Knowledge-Based Controller Used in Process Control Systems
Authors: Wang Jin , Wang Fuli , Li Mingzhong , Yang Yingha
Published: October 2003

A knowledge-based controller(KBC) used in process control systems is presented. It has three features: first, it does not need the mathematical model; secondly, the adjustable parameters of KBC have practical meanings, so they can be determined easily using human experience, and thirdly, the contribution of KBC to a controlled plant is separated into two parts: steady states contribution and transient contribution. A simple fuzzy reasoning is employed to tune the KBC parameters. The experimental and simulation results show that KBC is very effective especially when there are variations in the process dynamics.
On the Integrable Solution of a Class of Fuzzy Functional Equations
Authors: Subrahmanyam P. V. , Sudarsanam S. K.
Published: October 2003

This paper proves the existence of Lp solution to the fuzzy functional equation [Formula: see text] where a and y are fuzzy functions and h is a given deterministic function. This functional equation is fuzzified using Zadeh's extension principle and the existence theorem is proved using the contraction principle, Castaing representation theorem and Negoita and Ralescu's representation theorem. This supplements and earlier existence theorem we obtained for bounded fuzzy solutions.
Interval Methods in Knowledge Representation
Authors: Kreinovich Vladik
Published: October 2003

Please send your abstracts 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 Approach to Modelling and Simulation of Uncertain Dynamical Systems
Authors: Hüllermeier Eyke
Published: October 2003

Coping with uncertainty in dynamical systems has recently received some attention in artificial intelligence (AI), particularly in the fields of qualitative and model-based reasoning. In this paper, we propose an approach to modelling and simulation of uncertain dynamics which is based on the following ideas: We consider (linguistic) descriptions of uncertain functional relationships characterizing the behavior of some dynamical system. Based on a certain interpretation of such rule-based models, we derive a fuzzy function [Formula: see text]. It will be shown that all (reasonable) fuzzy functions can be approximated to any degree of accuracy in this way. The function [Formula: see text] is then used as the "fuzzy" right hand side of a set of differential equations, which leads us to consider fuzzy initial value problems. We are going to propose an interpretation of such problems. Moreover, several aspects of simulation methods for characterizing the set of all system behaviors compatible with this interpretation will be discussed.
PFB-Integrals and PFA-Integrals with Respect to Monotone Set Functions
Authors: Wang Zhenyuan , Klir George J.
Published: October 2003

A pair of new integrals, a PFB-integral and a PFA-integral, are introduced. Given a measurable space, these integrals are defined for nonnegative functions with respect to monotone set functions, and they are generalizations of both the Lebesgue integral and the fuzzy integral. Some primary properties of the PFB-integral and PFA-integral are discussed and an inequality between them is established in this paper.
Normalized Conditional Possibility Distributions and Informational Connection Between Fuzzy Variables
Authors: Gwét Henri
Published: October 2003

In this article, we introduce a general concept of fuzzy operators. These operators are then used to generalize the possibilistic conditioning formulation proposed by Nguyen [1]. This generalization depends on the relation which exists between this conditioning and the probabilistic t-norm. By using other t-norms, other conditionings are obtained, and their properties are studied. One application of normalized possibilistic conditioning is the measure of the dependency between two fuzzy statistical variables. The measure constructed can be considered as the possibilistic counterpart of mutual information commonly used in statistics.
Interval Methods in Knowledge Representation
Authors: Kreinovich Vladik
Published: October 2003

This section is maintained by Vladik Kreinovich. Please send your abstracts 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.
From Intervals to Fuzzy Truth-Values: Adding Flexibility to Reasoning Under Uncertainty
Authors: Mantaras Ramon Lopez De , Godo Lluis
Published: October 2003

In dealing with representing knowledge under uncertainty there is a sustained tendency to increase flexibility in order to avoid problems of inconsistency in the knowledge. Early uncertainty management systems dealt with single real values within a predefined range, soon interval valued approaches were proposed and more recently we have witnessed the introduction of fuzzy-interval valued approaches, i.e., possibility distributions and fuzzy truth-values. In this paper we describe these fuzzy set based approaches with an emphasis on the concept of fuzzy truth-value.
On Capacity Functionals in Interval Probabilities
Authors: Nguyen Hung T. , Nguyen Nhu T. , Wang Tonghui
Published: October 2003

This paper addresses some basic issues concerning set-functions which are endpoints in interval probabilities. The property of alternating of infinite order of set-functions is investigated in detail. Generalizing a result of Graf (1980), we establish a necessary and sufficient condition for the existence of the Radon-Nikodym derivatives for a larger class of set functions, called submeasures.
Interval Methods in Knowledge Representation
Authors: Kreinovich Vladik
Published: October 2003

This section is maintained by Vladik Kreinovich. Please send your abstracts (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.
On Some Classes of Idempotent Operators
Authors: Mayor G. , Torrens J.
Published: October 2003

In this paper we deal with the idempotency equation H(x,x)=x for all x∈[0,1]. In particular we solve it for two special cases. First when H is a convex linear combination of a strict t-norm and its (1-j)-dual and second, when H is a convex linear combination of a special kind of aggregation functions F=<(f,N)> and its N-dual, being these aggregation functions, called L-representable aggregation functions, a kind of functions verifying a similar representation theorem to the classical representation theorem for non strict Archimedean t-norms.
Management of Uncertainty and Vagueness in Databases: The Firms Point of View
Authors: Mouaddib N. , Subtil P.
Published: October 2003

In this paper, we present an approach to model and retrieve nuanced information (i.e. uncertain, fuzzy and incomplete information). The particularities of the model we propose are:

• the introduction of the nuanced value concept to distinguish between a value (ex: young) and a nuance which is a complement on value and either expresses uncertainty (e.g. probably, …) or linguistic quantifiers/modifiers (e.g. very, often,…).

• the possibility to represent aggregate attributes (i.e. attribute composed with a set of attributes) and to generate their values from nuanced value of the component attributes.

• the advantage to define nuanced domain which is the set of all possible associations value/nuance for an attribute. We will show that a nuanced domain is an extension of the linguistic variable notion introduced by Zadeh.

• the use of: (i) the fuzzy thesaurus concept to constraint values of discret attributes; (ii) an associated grammar of Chomsky to generate automatically the characteristic functions of the thesaurus terms.

An interactive and progressive process is proposed to retrieve information taking into account fuzzy thesaurus and nuanced information. These propositions are implemented into FIRMS system that we realize in Smalltalk language.
Fuzziness: From Epistemic Considerations to Terminological Clarification
Authors: Toth Herbert
Published: October 2003

Using some semantical considerations and results from basic philosophy and some basic mathematical concepts we try to fix suitable explanations for some fundamental notions of fuzzy set theory on a semiformal level. This will – to the author's knowledge for the first time at all – lead us to a proposal for a definition of what is to be understood by the term 'fuzziness', simultaneously clarifying its epistemic rôle.