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We have developed AirTransNote, a student notes sharing system to facilitate collaborative and interactive learning in a regular lecture at conventional classrooms. Our former student system employed ultrasonic digital pens to capture student notes on a usual paper sheet. Although the paper-based approach is intuitive for learners, the ultrasonic pen with a PDA created some difficulties when used by senior high school students. In order to eliminate those difficulties, we have introduced anoto-based pens and a data gathering system called "digital pen gateway." Owing to the improved student system, students could easily submit their answers with handling of multiple paper sheets. The teacher could refer the answers to choose students who need assistance during the lecture. Questionnaire results showed that the simpler student interface is quite acceptable, and the system can realize our augmented classroom concept in a practical way. [ABSTRACT FROM AUTHOR]

This paper proposes a neural-based method to map facial expressions between human and robot. We applied the method to a sensitivity communication robot, Ifbot, which has been developed by our industry-university joint research project. The method enables the robot to imitate an arbitrary human facial expression. The paper describes the feature extraction from face image, and proposes neural network based parameter matching between human facial expression and Ifbot's facial expression mechanism. This paper also reports the evaluation of the facial expression transmission performance of Ifbot with the proposed system. The evaluation shows the effectiveness of emphasizing emotional expressions and the possibility of using Ifbot as an agent for distance communication. [ABSTRACT FROM AUTHOR]

This paper presents an improved statistical learning algorithm for feature generation in pattern recognition and signal processing. It is approximately derived from geometrical interpretation of the Fisher linear discriminant analysis (FLDA). The principal component analysis (PCA) is popular for data compression and feature extraction. Furthermore, iterative learning algorithms for obtaining eigenvectors in PCA have been presented in such fields. Their effectiveness has been demonstrated in many applications. However, recently FLDA has been often used in many fields, especially face image recognition. The drawback of FLDA is a long computational time based on a large-sized covariance matrix and the issue that the within-class covariance matrix is usually singular. Generally, in FLDA, the inverse matrix of the within-class covariance matrix cannot be obtained, since data dimension is generally higher than the number of data and then it includes many zero eigenvalues. In order to overcome this difficulty, a new iterative feature generation method, the simple-FLDA was proposed by authors. In this paper, further improvement is introduced into the simple-FLDA and its effectiveness is demonstrated for preliminary personal identification problem. [ABSTRACT FROM AUTHOR]

In this paper, we discuss a robot vision in order to perceive humans and the environment around a mobile robot. We developed a tele-operated mobile robot with a pan-tilt mechanism composed of a camera and a laser range finder (LRF). The output from the camera is color information, and the output of LRF is distance information to objects from the robot. In this paper, we propose a method of sensor fusion to extract a human from the measured data by integrating these outputs based on the concept of synthesis. Finally, we show experimental results of the proposed method. [ABSTRACT FROM AUTHOR]

This paper presents an efficient method of obstacle recognition system and HRI (human robot interaction) system specialized for biped walking robot. This method transmits the information regarding obstacle conditions to a biped walking robot. In the present paper, we describe a cascade of boosted classifier using adaboost algorithm as a obstacle region extracting module from input images. Besides, PCA is applied as a feature extracting module from the obstacle region and a hierarchical support vector machine is applied as an obstacle recognizing module. The data from vision system is combined with information from other sensors and the walking assist commands transmit to the biped walking robot. From the results of experiments, the proposed method can be applied to biped walking robot effectively. [ABSTRACT FROM AUTHOR]

Skill knowledge is important human knowledge as well as symbolic knowledge. Definition of skill knowledge is knowledge on high level technique that human acquire through repeated training. Skill knowledge is needed for arts, sports and crafts. It concerns human body structure, muscles, and joints. Also, skill knowledge concerns process of human interaction with objects, namely, recognition and action. There are many researches on learning support system for describable knowledge, such as mathematics, physics, grammar, etc. However, there is few pieces of research on learning support system for skill such as arts and sports. This paper analyses skills and generalize skill features. Then we describe problems to diagnose skill errors. After that, we introduce a learning support system for sketch as an example of a skill learning support environment. [ABSTRACT FROM AUTHOR]

Several new video and image watermarking proposals are based on Informed Coding and Informed Embedding. However, these systems can be not easily used in fingerprinting schemes because they do not satisfy the marking assumption defined in [1]. In this paper we discuss some guidelines to adapt a watermarking system based on informed coding and informed embedding to a generic fingerprinting code, while keeping up with the marking assumption, that is to say, when as a result of one collusion attack of two users, that have different marks that represent the value 0 in the nth position, we have a pirate mark wich represents the 0 value in this same nth position. This can be achieved modifying the work of Miller, Doër and Cox in [2]. [ABSTRACT FROM AUTHOR]

Bayesian Networks are proven to be a comprehensive model to describe causal relationships among domain attributes with probabilistic measure of conditional dependency. However, depending on a context, many attributes of the model might not be relevant. If a Bayesian Network has been learned across multiple contexts then all uncovered conditional dependencies are averaged over all contexts and cannot guarantee high predictive accuracy when applied to a concrete case. We are considering a context as a set of contextual attributes, which are not directly effect probability distribution of the target attributes, but they effect on "relevance" of the predictive attributes towards target attributes. In this paper we use the Bayesian Metanetwork vision to model context-sensitive feature relevance. Separating contextual and predictive features is an important task. In this paper we also consider three strategies of extracting context from relevant features, which are based on: part_of context, role-based context and interface-based context. [ABSTRACT FROM AUTHOR]

A factor to be considered in browsing of an existing web page to a mobile terminal is the difference in hardware environments between average PCs and terminals. It is necessary to service contents effectively in accordance with diverse environmental information of various terminals caused by the rapid development in communication devices. This various terminal information needs much time to generate the content for a server and much capacity to load in the server. Therefore the method to minimize response time and server capacity is required. This paper proposes a CA(Content Aware Selecting) and HCT(Hyperlink Based Content Transcoding) method to provide a more rapid response time according to requirements of various terminals and illustrates the results of test system. [ABSTRACT FROM AUTHOR]

This paper describes a discussion support function on the intelligent bulletin board system (iBBS), which aim to enhance educative effectiveness of e-Learning programs. Bi-directional communication plays an important role in asynchronous e-Learning systems. The authors have proposed the support functions for activization of communication. The paper proposes implementation and improvement for the iBBS, and demonstrates its performance through an experimental evaluation. [ABSTRACT FROM AUTHOR]

Study on semantic search can be mainly divided into two kinds: one is augmenting traditional keyword-based search engines with semantic techniques like ontology, semantic inference; the other is proposing methods for directly searching on semantic repositories as RDF or OWL files. However, compared with those theoretic-driven approaches, semantic search still lacks applications with real life cases at the moment. By analyzing the scenario of domain resources, this paper proposes a domain-oriented semantic search model, which provides both entity search (concepts and instances) and relationship retrieval (concept2concpet, concept2instance and instance2instance). The search model can be further refined as a generalized and domain independent architecture with inference supports. The supporting semantic inference is gradually achieved by reasoning-rules, formulas and algorithms. With such semantic search model, more exact and meaningful information hidden in the resource repository can be extracted. [ABSTRACT FROM AUTHOR]

Despite the success in the application of ontologies as tools supporting semantic based approaches in various application areas, the lack of simple instruments for their visualization and editing still hinders their diffusion and wide adoption. This paper introduces NavEditOW, a system for the visualization, navigation, updating and maintenance of ontologies through the web. The paper describes the functionalities offered by the system, as well as its internal architecture. A description of its application to the representation and management of archaeological knowledge for the description of publications in an e-library ends the paper. [ABSTRACT FROM AUTHOR]

Ontology mapping is a precondition to achieve interoperability between agents or services using different ontologies. Today, a series of methods for ontology mapping have been reported. However in the existing literature, the focus has so far been on computing similarity and establishing equal mapping relation. In practice, it is possible to have other mapping relations besides equal mapping, such as subclass mapping relation. In this paper a new method for ontology mapping, FCA-Mapping, is presented. FCA-Mapping is based on Formal Concept Analysis (FCA) theory. By computing relation measures between entities of different ontologies, it can automatically establish equal and subclass mapping relations. [ABSTRACT FROM AUTHOR]

The progress of industrialization and civilization accelerates the complexity of traffic system. To solve the problem of increase of traffic volume and complexity of traffic system, the methods that offer real-time traffic information to drivers like Intelligent Transport System(ITS) are proposed and are researched. Also navigation system that can use in a car is being studied. This paper suggests the selection method of route for the driver's assistant system that can become individual system to driver by addition of driver's tendency. Driver's tendency defines as characteristic of the driver's driving pattern and the selected driving route. This paper infers driver's tendency and characteristics of routes by use of fuzzy logic and simulates the proposed algorithm with Personal Computer(PC) and personal Digital Assistant(PDA). [ABSTRACT FROM AUTHOR]

Physical activities beginners encounter difficulties in being accustomed to their new level of activity for lack of constant motivation in regular physical activities. In order to keep a high level of motivation, the selection of a proper training partner is of significant importance. At present, SNS (Social Networking Service) provides a perfect opportunity to successfully find such an appropriate partner. This paper proposes a methodology for organizing an online community based on the real world log. During training, users will have tiny loggers on, such as GPS (Global Positioning System) and/or HRM (Heart Rate Monitor). After training, users will send the log file from the hardware devices to the system. The system aims at automatically organizes the appropriate community to increase or keep their motivation. This paper reports the design and development of the referred system. [ABSTRACT FROM AUTHOR]

In a wireless sensor network (WSN) system, an important problem for the special application, in which the battery of a sensor node cannot be exchanged, is how to extend the life time of the entire WSN system. In the past we proposed an improvement to the LEACH protocol to lengthen the lifetime of a WSN system and showed the superiority of our proposal by simulation. In this paper we set up an experimental WSN system using sensor nodes called "MICAz". We try to measure the lifetime of the WSN systems based on the protocol of our proposal and to compare with the simulation result. We confirm by experiment that the lifetime of our proposal is up to 1.2 times longer than that of the LEACH protocol at one sensor node. The protocol of our proposal is sufficiently effective though the effect of the simulation cannot be achieved. [ABSTRACT FROM AUTHOR]

In this paper we consider the problem of separating source images from linear mixtures with unknown coefficients, in presence of noise and blur. In particular, we consider as a special case the problem of estimating the Cosmic Microwave Background from galactic and extra-galactic emissions. Like many visual inverse problems, this problem results to be ill-posed in Hadamard sense. To solve the non-blind version of the problem a classical edge-preserving regularization technique can be used. Thus, the solution is defined as the argument of the minimum of an energy function. In order to solve the blind inverse problem, in this paper a new function, called target function, is introduced. Such a function can consider constraints as the degree of Gaussianity and correlation of the results. The experimental results, considering the cosmic mixtures, have given accurate estimations. [ABSTRACT FROM AUTHOR]

This paper reports on the unsupervised analysis of seismic signals recorded in Italy, respectively on the Vesuvius volcano, located in Naples, and on the Stromboli volcano, located North of Eastern Sicily. The Vesuvius dataset is composed of earthquakes and false events like thunders, man-made quarry and undersea explosions. The Stromboli dataset consists of explosion-quakes, landslides and volcanic microtremor signals. The aim of this paper is to apply on these datasets three projection methods, the linear Principal Component Analysis (PCA), the Self-Organizing Map (SOM), and the Curvilinear Component Analysis (CCA), in order to compare their performance. Since these algorithms are well known to be able to exploit structures and organize data providing a clear framework for understanding and interpreting their relationships, this work examines the category of structural information that they can provide on our specific sets. Moreover, the paper suggests a breakthrough in the application area of the SOM, used here for clustering different seismic signals. The results show that, among the three above techniques, SOM better visualizes the complex set of high-dimensional data discovering their intrinsic structure and eventually appropriately clustering the different signal typologies under examination, discriminating the explosion-quakes from the landslides and microtremor recorded at the Stromboli volcano, and the earthquakes from natural (thunders) and artificial (quarry blasts and undersea explosions) events recorded at the Vesuvius volcano. [ABSTRACT FROM AUTHOR]

This paper presents an original feature selection method for Emotion Recognition which includes many original elements. Feature selection has some merit regarding pattern recognition performance. Thus, we developed a method called an 'Interactive Feature Selection(IFS)' and 'GA Feature Selection( GAFS)'. Afterwards, the results (selected features) of the IFS and GAFS were applied to an emotion recognition system (ERS), which was also implemented in this research. Especially, our interactive feature selection method was based on a Reinforcement Learning Algorithm since it required responses from human users. By performing the IFS, we were able to obtain three top features and apply them to the ERS. We compared those results from a random selection and Sequential Forward Selection (SFS) and Genetic Algorithm Feature Selection (GAFS). [ABSTRACT FROM AUTHOR]

Localization is one of the important topics in robotics and it is essential to execute a mission. Most problems in the class of localization are due to uncertainties in the modeling and sensors. Therefore, various filters are developed to estimate the states in noisy information. Recently, particle filter is issued widely because it can be applied to a nonlinear model and a non-Gaussian noise. In this paper a fuzzy adaptive particle filter is proposed, whose basic idea is to generate samples at the high-likelihood using a fuzzy logic approach. The method brings out the improvement of an accuracy of estimation. In addition, this paper presents the localization method for a mobile robot with ultrasonic beacon systems. For comparison purposes, we test a conventional particle filter method and our proposed method. Experimental results show that the proposed method has better localization performance. [ABSTRACT FROM AUTHOR]

Access control for semi-structured data is nontrivial, as witnessed by the number of access control approaches in literature. Recently, a case has been made for expressing access constraints at finer levels of granularity on data nodes and extending constraints to structural relationships. In this paper, we introduce a rewrite-based approach for access constraint enforcement, based on the ACXESS framework we developed at Indiana University. The ACXESS framework utilizes virtual security views and introduces a set of rewrite rules that takes advantage of the Security Annotated Schema (SAS) - an internal representation for virtual views. It is capable of rewriting user queries against security views into queries against the source data, while honoring the access constraints. [ABSTRACT FROM AUTHOR]

Context-aware computing that recognizes the context in which a user performs a task is one of the most important techniques for supporting user activity in ubiquitous computing. To realize context-aware computing, a computer needs to recognize the user's location. This paper describes a technique for location detection inside a room using radio waves from a user's computer. The proposed technique has to be sufficiently robust to cater for dynamic environments and should require only ordinary network devices, such as radio signal emitters, without the need for special equipment. We propose performing localization by relative values of RSSI (Received Signal Strength Indicator) among wireless nodes, and also our system support the node mobility. We evaluate the performance of our system in the environment where the node is movable. [ABSTRACT FROM AUTHOR]

In the paper web-based system user interface hybrid recommendation method based on the ant colony metaphor is presented. In this paper we apply the ontology-based user and user interface modeling. The role of ontologies in the user and user interface modeling is determining objects, concepts and relations between them. The user model is represented as a tuple and user interface model is represented by a set of connected nodes. The recommendation is performed using ant colony metaphor for selection the most optimal path in the user interface graph that specifies the user interface parameters for the specified user. The applied hybrid recommendation method is based on: demographic, content-based and collaborative filtering. [ABSTRACT FROM AUTHOR]

Agent technology has been claimed to be a promising tool for creating e-commerce applications. To develop a multi-agent e-commerce system effectively, the developers have to deal with several issues such as agent characteristics, agent functionalities, protocols, communication, cooperation and coordination. JADE (Java Agent Development Environment), an open source software framework, is currently the state-of-the-art tool used for developing multi-agent systems. In this paper, our aim is to present our experience in designing and developing an e-commerce multi-agent system with JADE. Our objective is realised through the presentation of the analysis, design and implementation phases of an agent software system we currently develop in the context of travel industry. We will also discuss some lessons we have learned in using the JADE platform. [ABSTRACT FROM AUTHOR]

Agent coordination and cooperation co-exist in a multiagent system, and are cognitively linked. This link is emphasized further by incorporating their atomic composition with their ability to perceive and gather information from the environment around them. As a result, a new generation of coordination/cooperation architectures is starting to emerge. From each of their definitions and current implementations, we show how the relationship between the Belief-Desire-Intention (BDI) architecture and the Observe-Orient-Decide-Act (OODA) loop can enable the use of Coordinative Cooperation within the Agent Coordination and Cooperation Cognitive Model. More importantly, we show the relationship between coordination, cooperation, BDI and OODA. This paper also discusses the current developments of the model and how the BDI and OODA architectures can affect coordination and cooperation within a Multi-Agent System (MAS). We recommend how these concepts can be designed and implemented in a MAS. [ABSTRACT FROM AUTHOR]

UMTS provides a high mobility two-way multimedia service with a medium bit rate. DVB provides high bit rate mobile reception, but restricted to a unidirectional one-to-one. The convergence of telecommunication and broadcasting networks have problem about how to support mutual authentication between user and broadcasting network. In this paper, we propose a new authentication scheme that authenticates each other. We involve UMTS AKA to share session key between user and converged networks. The AKA is based on symmetric keys, and runs typically in a UMTS subscriber identity mobile, a smart card like device. AKA mechanism is based on a challenge and response authentication protocol conceived in such a way as to achieve maximum compatibility with UMTS subscriber authentication and key establishment protocol.The VLR/SGSN checks user identity such as IMSI with PSI/SI which is transmitted through interface Ii. If the UMTS authentication user corrects PSI/SI table, DVB-H network transmits data with unnecessary authentication. The session key is used in every session to encapsulate the data sent to the user. Our proposed authentication scheme provide a fast and secure authentication for the converged networks. [ABSTRACT FROM AUTHOR]

RFID technology can be found embedded in almost everything from razor blade packages, clothing and books to prescription medicines to parts of an aircraft. Despite the pervasive nature of RFID, surveys have consistently shown a lack of RFID awareness, an overall lack of understanding and general confusion about what it actually is, its capabilities and limitations. This is due in part to a lack of a comprehensive, principles-based and systematic RFID classification scheme. This paper proposes a multi-agent architecture for RFID taxonomy of currently available RFID technology and systems. The taxonomy is based on a sound service-oriented and multi-agent RFID architecture framework. Multi-agent plays a role in the formulation of the taxonomy. It can be used by both novices and RFID practitioners to gain an understanding of the "next big thing" technology, the architectural considerations for designing and implementing a successful RFID system. [ABSTRACT FROM AUTHOR]

Agent-Oriented Software Development is one of the recent contributions to the field of Software Engineering. To date numerous methodologies for agent-oriented software development have been proposed in the literature. However, their application to real-world problems is still limited due to their lack of maturity. Evaluating their strengths and weaknesses is an important step towards developing better methodologies in the future. This paper presents research results obtained by applying three agent-oriented methodologies, namely ROADMAP, MaSE and Prometheus in the context of an E-commerce system. The results are presented and future work is discussed. [ABSTRACT FROM AUTHOR]

The application of various clustering techniques for large-scale gene-expression measurement experiments is an established method in bioinformatics. Clustering is also usually accompanied by functional characterization of gene sets by assessing statistical enrichments of structured vocabularies, such as the Gene Ontology (GO) [1]. If different cluster sets are generated for correlated experiments, a machine learning step termed cluster meta-analysis may be performed, in order to discover relations among the components of such sets. Several approaches have been proposed for this step: in particular, kernel methods may be used to exploit the graphical structure of typical ontologies such as GO. Following up the formulation of such approach [2], in this paper we present and discuss further results about its applicability and its performance, always in the context of the well known Spellman's Yeast Cell Cycle dataset [3]. [ABSTRACT FROM AUTHOR]

The appearance of powerful tools for lightweight metadata creation, such as collaborative tagging systems, is harnessing the power of online communities, although such metadata are limited to human consumption only. In this paper we first propose an abstract model for representing a generic collaborative tagging system which uses RDF as the underlying technology to store metadata created by different online communities. Then, we present a scenario with the purpose of illustrating how a service able to retrieve tags from different folksonomies can support users in the organization of their personal information spaces within the context of a digital library. [ABSTRACT FROM AUTHOR]

Since users want to have proper services in their own position and surrounding circumstance in ubiquitous computing, it is critically important to provide appropriate services by adapting changes of the user requirements and their environments. Most approaches lack considerations for position or preference of users. In this paper, we present an adaptation process model to dynamically select services based on user's preferences according to their contextual changes. We define a conceptual context model and use the adaptation process model to select proper services. The adaptation process consists of the service selection and the service negotiation. Service candidates are selected based on user's and service provider's preferences in the service selection process. The service negotiation process determines the best service among service candidates. [ABSTRACT FROM AUTHOR]

The know-how of critical thinking is tacit and latent, and the importance of training critical thinking skills is widely recognized. For those reasons, it is difficult (i) for learners to develop meta-cognitive skills, (ii) for teachers to externalize their tacit know-how of critical thinking, and (iii) for system developers to embed active learning support functions into the system that follow a learner's thinking processes. To support meta-cognitive learning, CSCL is a promising approach, although we must design functions well to facilitate learner and teacher behaviors (communications). In this paper, we propose a learning-phase model that specifies learning goals and scaffolds for respective learning phases. Furthermore, we illustrate a development system for a nursing domain according to the model. We expect that the model-based system will contribute to encouraging meaningful learning behaviors. [ABSTRACT FROM AUTHOR]

Recently the amount of personal contents which a person has to manage is increasing remarkably. We are working on Experience Web, which is a system for managing personal contents based on experiences of a user. Experience Web provides functions to integrate various types of personal contents in a unified manner, and enable a user to search them based on context. Personal contents represent activities of a user and are taken in an activity of a user. Personal contents are used more efficiently if they are shared in the users who attended the same activity. In this paper, we discuss the search that using personal contents of other users. [ABSTRACT FROM AUTHOR]

This paper describes a learning environment that provides program division patterns for programming education. Receiving source codes drawn by learners, this environment analyzes data flow and detects the information on active variables based on lexical, syntax, and semantic analyses. Then, this environment generates and evaluates module division patterns and finally shows visually to a learner module division patterns, active variables and their active scopes. [ABSTRACT FROM AUTHOR]

In many mission-critical systems, databases are updated by transaction processing, and are queried by batch processing to make statistics and so on. It is necessary that both processing can be executed at the same time for the efficient operation. The method, which manages the history of the data and queries a snapshot of the past time to avoid the influence of the present updating, was proposed. However, there is a problem that even if the error data had been corrected just before querying, it is not reflected in the snapshot. In this paper, we propose a method, by which the correction of the data done after the time of the snapshot is reflected in it, and show the integrity of the querying result maintained even while data are being updated. Moreover, we applied this method to a mission-critical system, and confirmed that it was effective. [ABSTRACT FROM AUTHOR]

This paper describes a characteristic of groups in the information systems design class in which a web-based support system was utilized. The groups were analyzed according to the frequency of the discussion within a group on Bulletin Board System (BBS). We observed significant differences among groups in the use of BBS. In an effective BBS collaborative group, members incorporated feed-back from professor and discussed each other's opinions. [ABSTRACT FROM AUTHOR]

This paper proposes an original approach for detection, localization and quantification of faults appearing in electrical machines. The used method in this work deals with the analysis of the leakage magnetic field of a machine. This approach is already known, but until now, classical methods only detect if a fault is present or not. Thus, we propose a new approach based on the theory of inverse problems. It not only enables us to identify a faulty mode, but also to discriminate several types of defects, to localize them and also to quantify their importance. [ABSTRACT FROM AUTHOR]

The paper deals with an approach that automates the computation of frequential characteristics of passive electronic circuit and their associated sensitivities according to all the components of the circuit. This method enables the designer to focus on the physical behavior of the circuit since the modeling and computing tasks are automatically performed without any computer science skills. It is useful to size circuits with many constraints by using optimization based on gradient algorithm. [ABSTRACT FROM AUTHOR]

The aim of this study is to construct a multi-camera tracking system which recognizes human motions beyond several video scenes. Generally, to recognize a single human motion is easier than to link several human motions. This is because several human motions move different directions, while a single human motion moves one direction in a certain period. Therefore, we need a system that is reliable to track of human motions in every frame. In this paper, a new method is proposed for a human tracking system in order to link human movements in different directions using foot step direction method. The detail outcome and result are discussed using experiments of the method in this paper. [ABSTRACT FROM AUTHOR]

We propose an identification method of fuzzy measures by diamond pairwise comparisons. Right and left side of the diamond means ordinal weights' comparison and up and down means interaction degrees. From the comparisons, we estimate a hierarchy diagram with interaction degrees and weights of evaluation items and the fuzzy measure of the diagram. In this paper, we compare the two interpretations of the diamond, AHP scales and Grabish's graphical interpretation. [ABSTRACT FROM AUTHOR]

A key problem in time series prediction using autoregressive models is to fix the model order, namely the number of past samples required to model the time series adequately. The estimation of the model order using cross-validation is a long process. In this paper we explore faster alternative to cross-validation, based on nonlinear dynamics methods, namely Grassberger-Procaccia, Kégl and False Nearest Neighbors algorithms. Once the model order is obtained, it is used to carry out the prediction, performed by a SVM. Experiments on three real data time series show that nonlinear dynamics methods have performances very close to the cross-validation ones. [ABSTRACT FROM AUTHOR]

For conventional ships, the mono-variable autopilot controls the heading of the ship in the presence of disturbances. During the heading control, there are many moments of time when the rudder command to control the yaw angle has a negative influence on roll oscillations. The prediction of the wave influence on the roll motion can be used to implement an intelligent heading control system, which is added to the mono-variable autopilot, generating only rudder commands with damping or non-increasing effects over roll movements. In this paper, aspects of roll angle and roll rate prediction using feed-forward neural networks are discussed. A neural network predictor of the roll rate, based on measured values of the roll angle, is proposed. The neural architecture is analyzed using different training data sets and noise conditions. The predictor has on-line adaptive characteristics and is working well even if both training and testing sets are affected by measurement noise. [ABSTRACT FROM AUTHOR]

This paper presents a handwritten Greek character recognizer. The recognizer is composed of two modules: the first one is a feature extractor, the second one, the classifier, is performed by means of Learning Vector Quantization. The recognizer, tested on a database of more than 28000 handwritten Greek characters, has shown satisfactory performances. [ABSTRACT FROM AUTHOR]

This paper addresses learning of a reasonably accurate evaluation function of Shogi (Japanese Chess) positions through learning from records of games. Accurate evaluation of a Shogi position is indispensable for a computer Shogi program. A Shogi position is projected into several semantic features characterizing the position. Using such features as input, we employ reinforcement learning with a multi-layer perceptron as a nonlinear function approximator. We prepare two completely different sets of games: games played by computer Shogi programs and games played by professional Shogi players. Then we built two evaluation functions by separate learning based on two different sets of games, and compared the results to find several interesting tendencies. [ABSTRACT FROM AUTHOR]

A new approach of input uncertainty classification is proposed in this paper. This approach develops a new technique which extends the support vector classification (SVC) by incorporating input uncertainties. Kernel functions can be used to generalize this proposed technique to non-linear models and the resulting optimization problem is a second order cone program with a unique solution. Results are shown to demonstrate how the technique is more robust when uncertainty information is available. [ABSTRACT FROM AUTHOR]

In this paper, systematic three-dimensional classification is presented for sets of interneuron slice images of silkworm moths, using self-organizing maps. Fractal dimension values are calculated for target sets to quantify denseness of their branching structures, and are employed as element values in training data for constructing a map. The other element values are calculated from the sets to which labeling and erosion are applied, and they quantifies whether the sets include thick main dendrites. The classification result is obtained as clusters with units in the map. The proposed classification employing only two elements in training data achieves as high accuracy as the manual classification made by neuroscientists. [ABSTRACT FROM AUTHOR]

The human-machine interface is an essential part of intelligent robotic system. Through the human-machine interface, human being can interact with the robot. Especially, in tele-robotics environment, the human-machine interface can be developed with remarkable extended functionality. In this paper, we propose a human-machine interface with augmented reality for the network based mobile robot. Generally, we can take some meaningful information from human's motion such as movement of head or fingers. So, it is very useful to take these motions as input for systems. We synchronize head motion of human being and the camera motion of the mobile robot using visual information. So user of the mobile robot can monitor environment of the mobile robot as eyesight of mobile robot. Then we use gesture recognition for control the mobile robot. In the implemented framework, the user can monitor what happens in environment as eyesight of mobile robot and control the mobile robot easily and intuitively by using gesture. [ABSTRACT FROM AUTHOR]

Recently cars are been equipped with intelligent systems aiding safe driving. However a large percentage of traffic accidents between human and automobile happen on crosswalk. Intelligent functions from road side are also indispensable in order to make crosswalk safer. We propose a quiet navigation system for safe crosswalks by parametric speakers in order to allow pedestrians to safely cross streets for 24 hours and to find an easy way to their destination. In this paper we examine different types of new parametric speakers comparing them with regular traffic signal loudspeakers and propose a useful type of the speakers. [ABSTRACT FROM AUTHOR]

When subscribers watch pay-TV programs, they get keys for decrypting the transmitted content and they are charged a fee, so these schemes enable content providers to get information about the contents that the subscribers watched, and the anonymity disappears. Recently, people have been taking the preservation of privacy seriously, and they do not want their private information to be disclosed even to the content provider of pay-TV. Moreover, content providers require a secure and correct revenue sharing scheme. In this paper, we propose an anonymous pay-TV system with secure revenue sharing to meet such requirements. [ABSTRACT FROM AUTHOR]

Many scenarios require models for access control which consider former accesses to permit or deny access. One such model is the Chinese Wall model (CWM) which was designed to prevent the misuse of insider knowledge in the consulting business. In this paper, we show that our model for history-based access control provides a flexible and expressive method to define access depending on histories, which contain information about former accesses. We demonstrate this by modeling the policies of the CWM in a way that avoids the unnecessary restrictions of the original CWM. [ABSTRACT FROM AUTHOR]