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This paper introduces the invited session of "Intelligent Agents and their Applications" being presented at the 10th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems. This session concentrates on discussing Intelligent Agents and uses some applications to demonstrate the theories reported. An update on last years session [1] is included to report on several key advances in technology that further enable the ongoing development of multi-agent systems. A brief summary of the impediments presented to researchers is also provided to highlight why innovation must be used to sustain the evolution of Artificial Intelligence. This year a variety of challenges and concepts are presented, together with a collection of thoughts about the direction and vision of Intelligent Agents ands their Applciations. [ABSTRACT FROM AUTHOR]

This paper proposes a method for sensitivity communication robots which infer their dialogist's emotion. The method is based on the Bayesian approach: by using a Bayesian modeling for prosodic features. In this research, we focus the elements of emotion included in dialogist's voice. Thus, as training datasets for learning Bayesian networks, we extract prosodic feature quantities from emotionally expressive voice data. Our method learns the dependence and its strength between dialogist's utterance and his emotion, by building Bayesian networks. Bayesian information criterion, one of the information theoretical model selection method, is used in the building Bayesian networks. The paper finally proposes a reasoner to infer dialogist's emotion by using a Bayesian network for prosodic features of the dialogist's voice. The paper also reports some empirical reasoning performance. [ABSTRACT FROM AUTHOR]

In this paper, we evaluate the feasibility of distributed control of shared resources in user-managed networks. This paradigm has become possible with the advent of broadband wireless networking technologies such as IEEE 802.11. One of the most popular applications in these networks is peer-to-peer (P2P) file exchange. Node cooperation can optimize the usage of shared "external" accesses to the Internet (set of links between the user network and the Internet). In a previous paper, we evaluated different agent-oriented distributed control schema, based on the concept of credit limits, on ideal mesh networks subject to uniform traffic. Each node in the mesh network chooses to behave as a cooperator or a defector. Cooperators may assist in file exchange, whereas defectors try to get advantage of network resources without providing help in return. Before this paper was completed, we observed that popular P2P protocols like eMule, Kazaa and BitTorrent were evolving towards the same credit-oriented strategies we previously proposed. Now, we realistically model both user network traffic and topology, and evaluate a new advanced agent-based distributed control scheme. The simulation results in this paper confirm on realistic networks the main conclusion in our previous research: autonomous node agents become cooperators in their permanent state when they take decisions from local information, checking that file exchange services offered to neighbor nodes do not exceed appropriate credit limits. Keywords: P2P, agents, network management, mesh networks. [ABSTRACT FROM AUTHOR]

Trust plays a fundamental role in multi-agent systems in which tasks are delegated or agents must rely on others to perform actions that they themselves cannot do. Dating from the mid-1980s, the Belief-Desire-Intention architecture (BDI) is the longest-standing model of intelligent agency used in multi-agent systems. Part of the attraction of BDI is that it is amenable to logical formalisms such as Wooldridge's Logic Of Rational Agents (LORA). In a previous paper the present authors introduced a model of trust, here named the Ability-Belief-Commitment-Desire (ABCD) model, that could be implemented within the BDI framework. This paper explores the definition of the ABCD model within the LORA formalism. [ABSTRACT FROM AUTHOR]

In this paper we model the concept of "coarseness", typically used in texture image descriptions, by means of fuzzy sets. Specifically, we relate representative measures of this kind of texture with its presence degree. To obtain these "presence degrees", we collect assessments from polls filled by human subjects, performing an aggregation of these assessments by means of OWA operators. Using this collected data, and some statistics as reference set, the membership function corresponding to the fuzzy set "coarseness" is modelled. Keywords: Image features, texture features, fuzzy texture, visual coarseness. [ABSTRACT FROM AUTHOR]

This paper presents a consensus-based algorithm for resolving inconsistency in Web-based recommendation systems. In such systems it is possible that a user have his own usage path (the way of usage of the system) and system can recommend individual usage path for new user. The problem of determining a new path for a new user is the subject of this paper. An algorithm for solving this problem will be described below and some results of the experiments with this algorithm will be presented. [ABSTRACT FROM AUTHOR]

In data mining, hybrid intelligent systems present a synergistic combination of multiple approaches to develop the next generation of intelligent systems. Our paper presents an integration of a Combined Multiple Models (CMM) technique with an evolutionary approach that is used for tuning of parameters. Proposed hybrid classifier was tested in microarray analysis domain. This domain was chosen intentionally, because of the nature of Combined Multiple Models classifiers that are specialized in solving problems with high dimensionality and contain low number of samples. Evolutionary tuning of parameters in combination with validation dataset enables fine tuning of parameters that are usually set to pre-defined values. Using this technique we made another step in leveling the accuracy of comprehensible classifiers to those represented by ensembles of classifiers. [ABSTRACT FROM AUTHOR]

In previous papers we introduced HeCaSe2, a multi-agent system that helps doctors to follow the automatic application of clinical guidelines to patients. In this paper we show how aggregation operators, based on fuzzy logic, may be integrated in this system in order to personalize some of its tasks. These operators take into account the patient preferences when several medical services propose different conditions under which a specific medical test can be performed. The paper describes how different proposals can be rated and ranked, and discusses the influence of two parameters (the set of linguistic preference values and the rating policy) on the results of the aggregation procedure. [ABSTRACT FROM AUTHOR]

INADA is an enhanced C++ persistent programming language and compliant with the ODMG standard. INADA provides multiple-type object which enables any persistent objects to be extended by obtaining any type and by losing any unnecessary types. Furthermore, INADA provides virtual type which enables any persistent objects to be accessed through a virtual type derivable from other base/virtual types. However, it does not allow the type which a virtual type is derived from to be a repeating one. To overcome this constraint, this paper proposes extended virtual type which allows a virtual type to be derived from a repeating one and shows a method of implementing it in INADA. [ABSTRACT FROM AUTHOR]

This paper studies the direction relations between two spatial objects and presents the reasoning model of spatial direction relation based on Voronoi diagram. The algorithm of the reasoning is described detailedly and an example is analyzed. This paper also discusses the six typical circumstances about spatial direction relation based on Voronoi diagram. These include the direction relations of point-point, point-line, point-region, line-line, line-region and region-region. At last, the advantages and disadvantages about the model are summarized. [ABSTRACT FROM AUTHOR]

The contents of multimedia data has complex relationships including deeply nested whole-part and the many-to-many relationships. This paper proposes a data model incorporating the concepts of directed graphs, recursive graphs, and hypergraphs in order to represent the contents of multimedia data. In the proposed data model, an instance is represented with a directed recursive hypergraph called an instance graph. The logic-based operation called rewrite is introduced. It gives us powerful querying capability because regular expressions on paths can be specified in retrieving instance graphs from collection graphs. [ABSTRACT FROM AUTHOR]

Recently, much attention has been paid to manage amount of personal contents effectively. Private photo is one of the most important types of personal contents. In many of conventional approaches for private photo searching, a user is required to assign annotations manually to the private photos of the user by oneself. However, assigning annotations is tedious for a user. This paper introduces an automatic indexing approach for private photo searching based on e-mail message archive. Many of e-mail messages of a user may describe some experiences of the user. In this approach, the temporal expressions are extracted from an e-mail message, and they are used for estimate the relativity between a term in the e-mail message and a temporal interval in the personal time space of a user. The weight of a term to a private photo is calculated on the basis of the relativity and the granularity of the temporal interval. [ABSTRACT FROM AUTHOR]

The scheduling problem of transport vehicles is one of the important issues in our international society. Such a problem should be solved optimally and instantaneously to keep high profitability and conveniency. However, it is hard to find an optimal solution in such a transport problem because transport requests occur constantly and the optimal solution changes according to the requests. Therefore, the strategy to find a near-optimal solution is a practical way to solve the problem at low calculation cost. In this paper, we focus on the range constraints of the optimization problem. The assignment of requests is optimized by request exchange between transport vehicles in their belonging group (i.e., range constraint) to keep the calculation cost low. The group of transport vehicles should be dynamically changed on the basis of their positions. Hence, we introduce an indexing tree called R-Tree and re-construct the tree in certain intervals to index moving transport vehicles dynamically. In the last of this paper, we report the influence of group size and the update interval on the performance of transport vehicles and then show the effectiveness of our optimization algorithm. [ABSTRACT FROM AUTHOR]

We have been developing a system AirTransNote, a computer-mediated learning system that employs digital pen to realize paper-centric augmented classroom. Although the approach was sophisticated, it restricted feedback effects which potentially improve learning. To maximize the feedback effects of the system, we present a hybrid approach of augmented classroom environment. We classified the type of feedback loops in terms of the hybrid approach and improved the system to accomplish the functions by adding (1) note browsing interface for handheld, (2) worksheet editor for teachers, (3) handwriting character recognition engine for versatile use, and (4) HTTP embedded server function for flexible reference of collective results and notes. We also conducted a feasibility study and investigated the effectiveness of the immediate feedback under the hybrid approach. [ABSTRACT FROM AUTHOR]

Self-directed learning often finishes with incomplete knowledge. It is hard for learners to be aware of the knowledge incompleteness. The main issue addressed in this paper is how to enhance their awareness. Our approach to this issue is to enable learners to publish knowledge obtained from their learning process to review it. The most important point towards knowledge publishing is how to represent knowledge so that the learners can reflect on it from another perspective. However, such knowledge representation would be troublesome for the learners. This paper discusses how to promote learners' knowledge publishing by automatically generating a hypertext with TOC (Table Of Contents) as representation of knowledge they have learned in their learning process. Publishing the hypertext enables the learners to gain not only their own reviews but also the reviews from the peers. [ABSTRACT FROM AUTHOR]

Security systems need be tested on the network, when they are developed, for their security test and performance evaluation. Even though the security tests have to be done on the real network but, it is usually tested in a virtual test environment. APS (Attack Packet Simulator) is one of tools for performance test of security system on the virtual environment. In this paper, the development of an attack packet generator extracts the attack information from Snort rule and creates attack information in the Database using the extracted information applying intelligent APS. Also, the proposed generator generates high speed network attack packets to closely assimilate the real network for security system tests using an NP (Network Processor). [ABSTRACT FROM AUTHOR]

In this paper, we propose a uiH-PMAC (ubi-intelligent Home - Privilege Management Access Control) model which is suitable to access control of ubiquitous intelligent environment. The model considers the temporary limit conditions as access control of home device or user location information considering the characteristics of members who could limit the use of resource. In addition, the model provides authentication policy which authenticates not only devices but also domains and access control policy which considers inheritance of role. Finally, the model can be applied various and scalable access control policies which are suitable to the characteristics of intelligent digital environment as considering the user location information as a temporary limit condition. [ABSTRACT FROM AUTHOR]

Artificial Intelligence techniques are increasingly extending and enriching decision support through such means as coordinating data delivery, analyzing data trends, providing forecasts, developing data consistency, quantifying uncertainty, anticipating the user's data needs, providing information to the user in the most appropriate forms, and suggesting courses of action. This session of the 10th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems focuses on the use of Artificial Intelligence to enhance decision making. [ABSTRACT FROM AUTHOR]

This paper describes preliminary work performed to gain an understanding of how to implement collaboration between intelligent agents in a multi-agent system and/or humans. The paper builds on previous research where an agent-development software framework was implemented based on a cognitive hybrid reasoning and learning model. Agent relationships are formed using a three-layer process involving communication, negotiation and trust. Cooperation is a type of relationship that is evident within structured teams when an agent is required to cooperate with and explicitly trust instructions and information received from controlling agents. Collaboration involves the creation of temporary relationships between different agents and/or humans that allows each member to achieve their own goals. Due to the inherent physical separation between humans and agents, the concept of collaboration has been identified as the means of realizing human-agent teams. A preliminary demonstration used to confirm this research is also presented. [ABSTRACT FROM AUTHOR]

This paper outlines the abridged history of agent reasoning theories as ‘agent mind' from the perspective of its implementation inspired by new trends such as ‘teaming' and ‘learning'. This paper covers how the need for such new notions in agent technology introduced a change in fundamental agent theories and how it can be balanced by inducing some original cognitive notions from the field of ‘artificial mind'. This paper concentrates on the popular agent reasoning notion of Belief Desire Intention (BDI) and outlines the importance of the human-centric agent reasoning model as a step towards the next generation of agents to bridge the gap between human and agent. The current trend including the human-centric nature of agent mind and humanagent teaming is explained, and its needs and characteristics are also explained. This paper reports add-on implementation on BDI in order to facilitate humancentric nature of agent mind. This human-centric nature and concepts such as teaming agreements are utilised to aid human-agent teaming in a simulated environment. The issues in order to make agents more human-like or receptive are outlined. [ABSTRACT FROM AUTHOR]

Where customers with different membership and position, use computers as in the university network systems, it often takes much time and efforts for them to cope with the change of the system management. This is because the requirements for the respective computer usage are different in the network and security policies. In this paper, a new destination addressing control system (DACS) scheme for the university network services is proposed. The DACS Scheme performs the network services efficiently through the communication management of a client. As the characteristic of DACS Scheme, only the setup modification is required by a system administrator, when the configuration change is needed in the network server. Then, the setup modification is unnecessary by a customer, which shows a merit for both a system administrator and a customer. This paper describes the instruction and the prototype for DACS Protocol as the implementation of DACS Scheme. Then, the simplicity of the system management in DACS Scheme, is examined from the customer and the system administrator viewpoints. [ABSTRACT FROM AUTHOR]

This paper addresses the extraction of small group configurations and activities in an intelligent meeting environment. The proposed approach takes a continuous stream of observations coming from different sensors in the environment as input. The goal is to separate distinct distributions of these observations corresponding to distinct group configurations and activities. In this paper, we explore an unsupervised method based on the calculation of the Jeffrey divergence between histograms over observations. The obtained distinct distributions of observations can be interpreted as distinct segments of group configuration and activity. To evaluate this approach, we recorded a seminar and a cocktail party meeting. The observations of the seminar were generated by a speech activity detector, while the observations of the cocktail party meeting were generated by both the speech activity detector and a visual tracking system. We measured the correspondence between detected segments and labelled group configurations and activities. The obtained results are promising, in particular as our method is completely unsupervised. [ABSTRACT FROM AUTHOR]

On the basis of Markov Random Field (MRF), which uses context information, in this paper, a robust image segmentation method is proposed. The relationship between observed pixel intensities and distance between pixels are introduced to the traditional neighbourhood potential function, which described the probability of pixels being classified into one class. To perform an unsupervised segmentation, the Bayes Information Criterion (BIC) is used to determine the class number. The K-means is employed to initialise the classification and calculate the mean values and variances of the classes. The segmentation is transformed to maximize a posteriori (MAP) procedure. Then, the Iterative Conditional Model (ICM) is employed to solve the MAP problem. In the experiments, the proposed method is adopted with K-means, traditional Expectation-Maximization (EM) and MRF image segmentation techniques, for noisy image segmentation applying on synthetic and real images. The experiment results and the histogram of signal to noise ratio (SNR)-miss classification ratio (MCR) showed that the proposed algorithm is the better choice. [ABSTRACT FROM AUTHOR]

The amount of data is growing at an exponential rate. We are faced with a challenge to analyze, process and extract useful information from the vast amount of data. Traditional data analysis techniques have contributed immensely in the area of data analysis but we believe that the soft data analysis techniques, based on soft computing techniques, can be complementary and can process complicated data sets. This paper provides an introduction to the soft data analysis paradigms. It summarizes the successful and possible applications of the soft computing analysis paradigms. The merits and demerits of these paradigms are included. A number of resources available are listed and the future vision is discussed. This paper also provides a brief summary of the papers included in the session on "Innovation in Soft Data Analysis". [ABSTRACT FROM AUTHOR]

In this paper, we present an extended boids model for simulating the aggregate moving of fish schools in a complex environment. Three behavior rules are added to the extended boids model: following a feed; avoiding obstacle; avoiding enemy boids. The moving vector is a linear combination of every behavior rule vector, and the coefficients should be optimized. We also proposed a genetic algorithm to optimize the coefficients. Experimental results show that by using the GA-based optimization, the aggregate motions of fish schools become more realistic and similar to behaviors of real fish world. [ABSTRACT FROM AUTHOR]

Blur identification is usually necessary in image restoration. In this paper, a novel blur identification algorithm based on Support Vector Machines (SVM) is proposed. In this method, blur identification is considered as a multi-classification problem. First, Sobel operator and local variance are used to extract feature vectors that contain information about the Point Spread Functions (PSF). Then SVM is used to classify these feature vectors. The acquired mapping between the vectors and corresponding blur parameter provides the identification of the blur. Meanwhile, extension of this method to blind super-resolution image restoration is achieved. After blur identification, a super-resolution image is reconstructed from several low-resolution images obtained by different foci. Simulation results demonstrate the feasibility and validity of the method. [ABSTRACT FROM AUTHOR]

Handheld devices, which have been widely adopted to clinical environments for medical data archiving, have revolutionized error-prone manual processes of the past. Meanwhile, the use of devices has been reported to be limited to data entries and archiving, without fully leveraging their computing and retrieval capabilities. This paper studies a hybrid system which complements current state-of-art, by combining intelligent retrieval techniques developed over middleware environments for retrieval effectiveness and flash-aware data management techniques for retrieval efficiency. By enabling intelligent ranked retrieval, the limited resources of handheld devices, eeg., limited display and computation capabilities, can be utilized effectively, by selectively retrieving the few most relevant results. However, to achieve this goal, we need a hybrid approach, bridging middleware-based ranked retrieval techniques to optimize for flash memory storage, as typically adopted by handheld devices. We address this newly emerging challenge and propose a flash-aware framework H3, which we empirically validate its effectiveness over baseline alternatives. [ABSTRACT FROM AUTHOR]

In this paper, we present the design, implementation and evaluation of HIGAS, a hybrid intelligent system that deals with diagnosis and treatment consultation of acid-base disturbances based on blood gas analysis data. The system mainly consists of a fuzzy expert system that incorporates an evolutionary algorithm in an off-line mode. The diagnosis process, the input variables and their values were modeled based on expert's knowledge and existing literature. The fuzzy rules are organized in groups to be able to simulate the diagnosis process. Differential evolution algorithm is used to fine-tune the membership functions of the fuzzy variables. Medium scale experimental results show that HIGAS does better than its non-hybrid version, non-experts and other previous computer-based approaches. Keywords: acid-base disturbances, hybrid expert systems, fuzzy-evolutionary synergism, computer diagnosis. [ABSTRACT FROM AUTHOR]

This paper addresses a geographic information management to model various kinds of geographic objects with respect to the space and time features. In this model, an event represents the geographic situation in which geographic objects change, and represented as a set of geographic objects which are concerned to the event. It is possible to easily divide an event into sub-events along space and time criteria. Using this model, our geographic information system can provide users with a capability to manipulate an event from various viewpoints. [ABSTRACT FROM AUTHOR]

When we look for locations, we use the names of geographical objects (e.g., landmarks, rivers, lakes). However, we often memorize the locations by using relations among landmarks like remarkable buildings. For this reason, we focus on spatial relations among geographical objects, and we define spatial relations based on the geographical proximity. In this paper, we manipulate two types of geographical proximities: a vertical proximity and a horizontal proximity. The vertical proximity shows two geographical objects are overlapping, and the horizontal proximity shows two geographical objects are adjacent. In order to represent these proximities, we introduce two spatial relations: "overlapping" and "neighboring". "Overlapping" represents the vertical proximity, and "neighboring" represents the horizontal proximity. Furthermore, we propose a spatial relational graph which is generated by connecting geographical objects with these two spatial relations. In addition, we search maps by inclusive relations among spatial relational graphs, and implement the prototype system to find out locations by using a map. [ABSTRACT FROM AUTHOR]

Intelligent interactive systems have begun to adopt knowledge and software engineering technologies in an attempt to effective development. Feature models have been widely used in knowledge and software engineering for the reuse purpose. However, due to the lack of a formal semantics of feature models, it is rather difficult to perform rigorous consistency reasoning on them. Without guaranteed consistency of feature models, the quality of interactive systems based on them, can not be guaranteed. In this paper, how to formalize feature models with Description Logics is investigated. Following the proposed translation principles, each feature model is formalized into an $\mathcal{ALCQI}$ knowledge base. Hence the consistency reasoning on the feature model turns into the consistency reasoning on the corresponding $\mathcal{ALCQI}$ knowledge base. Especially, the latter reasoning can be automatically performed via the description logic reasoner RACER. [ABSTRACT FROM AUTHOR]

This paper presents a system that integrates news from multiple sources on the Web and delivers in a personalized fashion to the reader. The presented service integrates automatic information extraction from various news sources and presentation of information according to the user's interests. The system consists of source-specific information extraction programs (wrappers) that extract highlights of news items from the various sources, organize them according to pre-defined news categories and present them to the user through a personal Web-based interface. Dynamic personalization is used based on the user's reading history, as well as the preferences of other similar users. User models are maintained by statistical analysis and machine learning algorithms. Results of an initial user study have confirmed the value of the service and indicated ways in which it should be improved. Keywords: Personalization, Information Extraction, Machine Learning. [ABSTRACT FROM AUTHOR]

This paper proposes an evacuation support method, based on routing panels, and evaluates analytically this method by means of computer simulation. For this simulation, the multi-agent paradigm is adopted as our basic modeling view. On this modeling, we focus on the behaviors of agents promoted instructively by routing panels. As a result, two characteristic suggestions are derived: one is that routing panels set on critical sections, in which were estimated by Monte Carlo method, can support the rapid and safe evacuation; and another is that the route finding way to be applicable by the global disaster information is better than that of the local disaster information. [ABSTRACT FROM AUTHOR]

This paper presents an intelligent systematic methodology for enhancing diagnosability of discrete event systems by adding sensors. The methodology consists of the following iteractive steps. First, Petri nets are used to model the target system. Then, an algorithm of polynomial complexity is adopted to analyze a sufficient condition of diagnosability of the modeled system. Here, diagnosability is defined in the context of the discrete event systems theory, which was first introduced by Sampath [3]. If the system is found to be possibly non-diagnosable, T-components of the Petri net model are computed to find a location in the system for adding a sensor. The objective is to distinguish multiple T-components with the same observable event sequences. The diagnosability-checking algorithm is used again to see if the system with the newly added sensor is diagnosable. The process is repeated until either the system is diagnosable or diagnosability of the system cannot be enhanced. [ABSTRACT FROM AUTHOR]

In order to perform effective synchronous online classes with multimedia educational materials, we have developed interactive instruction system named IMPRESSION, which facilitates interactive presentation of various multimedia materials provided by web server on the Internet. In this paper, we clarify the design concept of our system, and show the design and implementation of it. And we discuss the effectiveness of our system through the practical use in the online class for high school students with high-bandwidth networks. [ABSTRACT FROM AUTHOR]

In information ages, a computer is our active intelligent collaborator to work and learn something, so that learner's intelligent ability must be taken into consideration even in education of information technologies (IT). Aim of this paper is to propose quantitative evaluation of the intelligent ability in computer usage. The author discusses some elements in the intelligent ability (such as quickness, logics, accuracy, memory, discernment, patience, decision, and inference), and formulates quantitative evaluation method of the elements with computer games. A tutor of IT education will be able to apply result of the research to computer assisted education for supporting learner's intelligent activities. [ABSTRACT FROM AUTHOR]

In this paper, we use maximal itemsets to represent itemsets in a database. We show that the set of supreme covers, which are the maximal itemsets whose proper subsets are not maximal itemsets, induces an equivalence relation on the set itemsets. Based on maximal itemsets, we propose a large itemset generation algorithm with dynamic support, which runs in time O(M′2N+M′logM), where N is the maximum number of items in a maximal itemset, M′ is the number of the maximal itemsets with minimum support greater than the required support, and M is the number of the maximal itemsets. [ABSTRACT FROM AUTHOR]

O-glycosylation is one of the main types of the mammalian protein glycosylation, which is serine or threonine specific, though any consensus sequence is still unknown. In this paper, a layered neural network and a support vector machine are used for the prediction of O-glycosylation sites. Three types of encoding for a protein sequence within a fixed size window are used as the input to the network, that is, a sparse coding which distinguishes all 20 amino acid residues, 5-letter coding and hydropathy coding. In the neural network, one output unit gives the prediction whether a particular site of serine or threonine is glycosylated, while SVM classifies into the 2 classes. The performance is evaluated by the Matthews correlation coefficient. The preliminary results on the neural network show the better performance of the sparse and 5-letter codings compared with the hydropathy coding, while the improvement according to the window size is shown to be limited to a certain extent by SVM. [ABSTRACT FROM AUTHOR]

Decision makers may present their preferences over alternatives as fuzzy preference relations. Usually, there exist inconsistencies in the preference relation given by decision makers. In this paper, we propose methods based on goal programming to obtain fuzzy preference relations that satisfy additive consistency from the subjective preference relations given by decision makers. [ABSTRACT FROM AUTHOR]

This paper presents a fuzzy multiple criteria decision making model to the evaluation of airline competitiveness over a period. The evaluation problem is formulated as a fuzzy multiple criteria decision making problem and solved by our strength-weakness based approach. After the strength and weakness matrices for airlines are derived, the weights of criteria, strength matrix and weakness matrix can be aggregated into strength indices and weakness indices for airlines, by which each airline can identify his own strength and weakness. The strength and weakness indices can be further integrated into an overall performance indices, by which airlines can identify their competitiveness ranking. [ABSTRACT FROM AUTHOR]

In this paper, we propose a visualization architecture that constructs a map suggesting clusters in sequence that involve classification utilizing the class label information for the display method of the map. This architecture is based on Self-Organizing Maps (SOM) that are to create clusters and to arrange the similar clusters near within the low dimensional map. This proposed method consists of three steps, firstly the winner neuron trajectories are obtained by SOM, secondly, connectivity weights are obtained by a single layer perceptron based on the winner neuron trajectories, finally, the map is visualized by reversing the obtained weights into the map. In the experiments using time series of real-world medical data, we evaluate the visualization and classification performance by comparing the display method by the number of sample ratio for classes belonging to each cluster. [ABSTRACT FROM AUTHOR]

In this paper, an Intelligent Content Management System with Chaotic Copyright Protection scheme called iJADE CMS is presented. iJADE CMS focuses on how web mining techniques can be effectively applied on Chinese content, with the integration of various AI techniques including intelligent agents, agent ontology and fuzzy logic based data mining scheme. Through the adoption of chaotic encryption scheme, iJADE CMS demonstrates how agentbased copyright protection can be successfully applied to digital media publishing industry. From the application perspective, iJADETM CMS provides the state-of-the-art content management function by the integration of iJADETM Technology with the Ontological Agent Technology. iJADETM CMS assists user to organize the content in the most semantic way. Moreover, the web mining information retrieval method such as Term Frequency Times Inverse Document Frequency (TFIDF) scheme is adopted to mine the linguistic meaning of the information content. [ABSTRACT FROM AUTHOR]

In this paper, we proposed a high precision location estimation algorithm using an intelligent coordination scheme in 2.45GHz RTLS and analyzed an average estimation error distance at 2D coordinates searching-area (300m×300m and 250m×250m). An average error distance was reduced as the number of available reader and received sub-blink increased. Proposed location estimation algorithm satisfied the RTLS specification requirements, 3m radius accuracy when the number of available reader is greater than 3 and the received sub-blink number exceeds 2 times in 250m×250m. Also, an average error distance was saturated within 0.5m~2.5m in case of 250m×250m when the number of available reader is greater than 4 regardless of the number of sub-blink. Also we confirmed that the 3m radius accuracy is 78 percent, and the 2.348m radius accuracy is 72 percent in 300m×300m searching-area when the number of available reader and received sub-blink was 8 and 4 times, respectively. In that case, we confirmed that 3m radius accuracy is 99 percent, and the 2.348m radius accuracy is 97 percent in 250m×250m searching-area. [ABSTRACT FROM AUTHOR]

WWW (World Wide Web) has incurred the problem that users are not necessarily provided with the information they want to receive, at a time when the amount of information is explosively increasing. Therefore, Tim Berners-Lee proposed the Semantic Web as the new web paradigm to solve this problem. But there is always a security problem in Semantic Web such as WWW and the study about this is insufficient. Therefore, the authors of this paper propose that the Security Intelligence system should be used to present semantic information using ontology and prevents that users flow out the information. This system is an ACM(Access Control Matrix) based access control model basically, and It is a system that prevent information leakage by user's deliberation and by user's mistake. It can be also used for WWW. [ABSTRACT FROM AUTHOR]

Agent technology becomes more and more importance in Business Intelligence domain. The concepts and technology have been brought to a stage where they are useable in real applications, and there is a growing understanding of how to apply them to practical problems. Component methodologies have proved to be successful in increasing speed to market of software development projects, lowering the development cost and providing better quality. In this paper, we propose systemical development process using component and UML(Unified Modeling Language) technology to analysis, design and develop e-business agent for business intelligence. The ebA-CBD(e-business Agent-Component Based Development) process is an attempt to consider all of the best features of existing AOSE(Agent Oriented Software Engineering) methodologies while grounding agent-oriented concepts in the same underlying semantic framework used by UML, the standard modeling language for Object Oriented Software Engineering. Finally we describe how these concepts may assist in increasing the efficiency and reusability in business intelligence application and e-business agent development in business intelligence environment. Keywords: e-Business Agent, Business Intelligence, ebA-CBD Reference Architecture, ebA-Spec, Component Based Development. [ABSTRACT FROM AUTHOR]

Broadcast encryption has been applied to transmit digital information such as multimedia, software and paid TV programs on the open networks. One of key factors in the broadcast encryption is that only previously authorized users can access the digital information. If the broadcast message is sent, first of all, the privileged users will decode the session key by using his or her personal key, which the user got previously. The user will get the digital information through this session key. As shown above, the user will obtain messages or session keys using the keys transmitted from a broadcaster, which process requires effective ways for the broadcaster to generate and distribute keys. In addition, when a user wants to withdraw or sign up, an effective process to renew a key is required. It is also necessary to chase and check users' malicious activities or attacking others. This paper presents a method called Traitor Tracing to solve all these problems. Traitor tracing can check attackers and trace them. It also utilizes a proactive scheme for each user to have effective and intelligence renewal cycle to generate keys. [ABSTRACT FROM AUTHOR]

One of the important services that intelligent home networks provide is to remotely control home appliances in home network. However, the remote control service causes intelligent home networks to have various security threats. Thus, for the service, intelligent home networks should provide strong security services, especially user authentication. In this paper, we provide a public key based one-time password authentication scheme for secure remote access in intelligent home networks. To provide 2-factor strong authentication conveniently and cost effectively, we adopt and enhance YEH-SHEN-HWANG's authentication scheme. Since our scheme uses a server-side public key to addresses the vulnerabilities of YEH-SHEN-HWANG's scheme, it can securely perform user authentication, server authentication and session key distribution without any pre-shared secret, while defending against server compromise. [ABSTRACT FROM AUTHOR]

Multi-sensor data fusion techniques combine data from multiple sensors in order to get more accurate and efficient meaningful information through several intelligent process levels that may not be possible from a single sensor alone. One of the most important parts in the intelligent data fusion system is the identification fusion, and it can be categorized into physical models, parametric classification and cognitive-based models. In this paper, we present a novel identification fusion method by integrating two fusion approaches such as the parametric classification techniques and the cognitive-based models for achieving high intelligent decision support. We also have confirmed that the reliability and performance of two-phase identification algorithm never fall behind other fusion methods. We thus argue that our heuristics are required for effective decision making in real time for intelligent military situation assessment. [ABSTRACT FROM AUTHOR]

Mining of association rules is to find associations among data items that appear together in some transactions or business activities. As of today, algorithms for association rule mining, as well as for other data mining tasks, are mostly applied to relational databases. As XML being adopted as the universal format for data storage and exchange, mining associations from XML data becomes an area of attention for researchers and developers. The challenge is that the semi-structured data format in XML is not directly suitable for traditional data mining algorithms and tools. In this paper we present an intelligent encoding method to encode XML tree-nodes. This method is used to store the XML data in 2-dimensional tables that can be easily accessed via indexing using knowledge. The hierarchical relationship in the original XML tree structure is embedded in the encoding. We applied this method in some applications, such as mining of association rules. [ABSTRACT FROM AUTHOR]

Various selection processes are present in the real world. Among them, some processes are open to everyone and others allow only members to validate them. These choice and selection types have been developed using cryptography protocol model. But, further study of definite anonymous secure selection protocols based on a cryptography is needed. In this paper, we propose the 'Intelligent Magic Sticker' scheme which is anonymous secure selection to get the anonymity of an originator, and which blinds the selection result from other entities on the open network. Because this approach protects a selection result of an originator using one-way anonymous authentication service, although the selection information is opened, the Magic Sticker scheme can be used in electronic voting, fair E-money and electronic bidding etc. Keyword: Anonymous Secure Selection, Intelligent Magic Sticker, Anonymous Authentication. [ABSTRACT FROM AUTHOR]