Search

In this paper we propose a novel personalized paper search system using the relevance among user's queried keywords and user's behaviors on a searched paper list. The proposed system builds user's individual relevance network from analyzing the appearance frequencies of keywords in the searched papers. The relevance network is personalized by providing weights to the appearance frequencies of keywords according to users' behaviors on the searched list, such as "downloading," "opening," and "no-action." In the experimental section, we demonstrate our method using 100 faculties' search information in the University of Suwon. [ABSTRACT FROM AUTHOR]

This is a summary of the papers presented at the Active Conceptual Modeling of Learning (ACM-L) Workshop, November 8, 2006, Tucson, Arizona, USA, and several invited papers. [ABSTRACT FROM AUTHOR]

This paper addresses a Korean-English machine translation system for scientific papers. The MT system is supported by CL (Controlled Language)-guided source language rewriting. After analyzing the translation errors of the system, we defined Korean rewriting rules to avoid the linguistic obstacles that may affect the translation accuracy. To support this, a Korean CL-checker was implemented. We showed that this CL-guided MT system can improve the translation accuracy by about 13% by adopting CL rewriting rules. However, this improvement is still not enough for various purposes, because most of the users of the MT system may want to submit the translated texts to a conference or an academic journal. As the MT output contains erroneous expressions, a language model module was added to the pattern-based MT engine. The system automatically detects expressions with low frequency and asks the authors to examine the translation. By adopting CL rewriting rules and language model module to the existing MT engine, almost "professional" translations can be obtained. [ABSTRACT FROM AUTHOR]

The Lost Cosmonaut is an interactive narrative based on digitally enhanced paper. This technology uses an electronic pen to mediate between paper and computer. Thus any actions of the pen on the paper can be captured and manipulated by a computer as well as we can map digitally controlled events onto paper. The story in this narrative environment reveals itself partially through written text and images on the paper surface just as any other printed story. However, additional information in form of digitally controlled outputs such as sound, light and projections can be accessed through interaction with pen and paper. Furthermore the audience is not only supposed to read and otherwise perceive information, we also want them to actively produce content for this environment by writing onto the paper. By doing so they also add content to the database containing the digital output at the same time. Hence we produce a complex multimedia environment that works on three levels: On paper, in a digitally controlled visual and acoustic environment and in the combination of both worlds. Last but not least this environment is an open system, which grows as a collaborative effort over time as each user adds his own entries to paper and database. We argue that using paper as an integrated part of a digital environment is a best-of-both-world approach that opens up new possibilities for producing and perceiving narrative. [ABSTRACT FROM AUTHOR]

We study the problem of predicting the popularity of items in a dynamic environment in which authors post continuously new items and provide feedback on existing items. This problem can be applied to predict popularity of blog posts, rank photographs in a photo-sharing system, or predict the citations of a scientific article using author information and monitoring the items of interest for a short period of time after their creation. As a case study, we show how to estimate the number of citations for an academic paper using information about past articles written by the same author(s) of the paper. If we use only the citation information over a short period of time, we obtain a predicted value that has a correlation of r = 0.57 with the actual value. This is our baseline prediction. Our best-performing system can improve that prediction by adding features extracted from the past publishing history of its authors, increasing the correlation between the actual and the predicted values to r = 0.81. [ABSTRACT FROM AUTHOR]

This paper describes an approach to the use of citation links to improve the scientific paper classification performance. In this approach, we develop two refinement functions, a linear label refinement (LLR) and a probabilistic label refinement (PLR), to model the citation link structures of the scientific papers for refining the class labels of the documents obtained by the content-based Naive Bayes classification method. The approach with the two new refinement models is examined and compared with the content-based Naive Bayes method on a standard paper classification data set with increasing training set sizes. The results suggest that both refinement models can significantly improve the system performance over the content-based method for all the training set sizes and that PLR is better than LLR when the training examples are sufficient. [ABSTRACT FROM AUTHOR]

We present a framework for generating paper-cutting effects on mesh models. Our system involves the construction of model defined paper-cutting patterns, extraction of the medial axis (MA) from the mesh models and position location for patterns on the mesh surface based on MA. Patch sets for placing patterns on the mesh surface are determined by the region growing algorithm. After patch sets parameterization, patterns are drawn on the parameterized domain and mapped onto the mesh surface by inverse sampling. [ABSTRACT FROM AUTHOR]

Active Learning in the classroom domain presents an interesting case for integrating physical and digital affordances. Traditional physical handouts and transparencies are giving way to new digital slides and PCs, but the fully digital systems still lag behind the physical artifacts in many aspects such as readability and tangibility. To better understand the interplay between physical and digital affordances in this domain, we developed PaperCP, a paper-based interface for a Tablet PC-based classroom interaction system (Classroom Presenter), and deployed it in an actual university course. This paper reports on an exploratory experiment studying the use of the system in a real-world scenario. The experiment confirms the feasibility of the paper interface in supporting student-instructor communication for Active Learning. We also discuss the challenges associated with creating a physical interface such as print layout, the use of pen gestures, and logistical issues. [ABSTRACT FROM AUTHOR]

This paper presents way of generation color documents from elements extracted from an original document image. This scheme yields synthetic documents of similar visual information to the original one. This method has several advantages as it allows a far more efficient way of storing and transmitting the information. Its rationale is to decompose a color document into paper and ink texture parameters and textual information. The textual information may be either typed or handwritten and is stored as a compressed monochromatic image. [ABSTRACT FROM AUTHOR]

In this paper we present our work about personalized search in digital libraries. Unlike other researches which use content-based methods, we focus on citation-based methods for this purpose. We propose a practical approach to estimate the co-citation relatedness between scientific papers using the Google search engine. We conducted some experiments to evaluate performance of different citation-based methods. The experimental results show that our approach is promising and applicable for personalized search in digital libraries. [ABSTRACT FROM AUTHOR]

This paper presents the advantage that knowledge-intensive activities, such as Scientific Conference Management, can take by the exploitation of expert components in the key tasks. Typically, in this domain the task of scheduling the activities and resources or the assignment of reviewers to papers is performed manually leading therefore to time-consuming procedures with high degree of inconsistency due to many parameters and constraints to be considered. The proposed systems, evaluated on real conference datasets, show good results compared to manual scheduling and assignment, in terms of both accuracy and reduction of runtime. [ABSTRACT FROM AUTHOR]

Finding the right material on the Web could be a worthwhile result. Users waste too much time to discover the useful information. Recommender system can provide some shortcuts to the user, but if the recommendation is based on people's opinion, one question remains — how relevant is a user's opinion? This paper presents a model to define the user's relevance opinion in a recommender system. This metric aims to help the target user to decide in what recommendation he should focus his attention. Beyond the model, we present a real experiment using an e-government database. Keywords: User modeling, Authority, Recommender System. [ABSTRACT FROM AUTHOR]

The techniques for organizing and retrieving the artifacts from digital libraries (DLs) semantically are discussed, which include letting the taxonomies and semantic relations work in tandem to index the artifacts in DLs; integrating the techniques used in natural language processing and taxonomies to help users to start their retrieval processes; and ranking scientific papers on similarity in terms of contents or ranking the relevant papers on multi-factors. These techniques are verified through the design and implementation of a prototype of DLs for scientific paper management. [ABSTRACT FROM AUTHOR]

Typically, personalized information recommendation services automatically infer the user profile, a structured model of the user interests, from documents that were already deemed relevant by the user. We present an approach based on Word Sense Disambiguation (WSD) for the extraction of user profiles from documents. This approach relies on a knowledge-based WSD algorithm, called JIGSAW, for the semantic indexing of documents: JIGSAW exploits the WordNet lexical database to select, among all the possible meanings (senses) of a polysemous word, the correct one. Semantically indexed documents are used to train a naïve Bayes learner that infers "semantic", sense-based user profiles as binary text classifiers (user-likes and user-dislikes). Two empirical evaluations are described in the paper. In the first experimental session, JIGSAW has been evaluated according to the parameters of the Senseval-3 initiative, that provides a forum where the WSD systems are assessed against disambiguated datasets. The goal of the second empirical evaluation has been to measure the accuracy of the user profiles in selecting relevant documents to be recommended. Performance of classical keyword-based profiles has been compared to that of sense-based profiles in the task of recommending scientific papers. The results show that sense-based profiles outperform keyword-based ones. [ABSTRACT FROM AUTHOR]

Vertical Search Engines (VSEs), which usually work on specific domains, are designed to answer complex queries of professional users. VSEs usually have large repositories of structured instances. Traditional instance ranking methods do not consider the categories that instances belong to. However, users of different interests usually care only the ranking list in their own communities. In this paper we design a ranking algorithm -ZRank, to rank the classified instances according to their importances in specific categories. To test our idea, we develop a scientific paper search engine-CPaper. By employing instance classifying and ranking algorithms, we discover some helpful facts to users of different interests. [ABSTRACT FROM AUTHOR]

The tenth year of the annual International Conference on Research in Computational Biology (RECOMB) provides an opportunity to reflect on its history. RECOMB has been held across the world, including 6 different countries spanning 3 continents (Table 1). Over its 10 year history, RECOMB has published 373 papers and 170 individuals have served on its various committees. While there are many new faces in RECOMB each year, a significant number of researchers have participated over many years forming the core of the RECOMB community. [ABSTRACT FROM AUTHOR]

Collaborative tagging has grown on the Internet as a new paradigm for web information discovering, filtering and retrieval. In the physical world, we use visual tags: labels readable by smartphones with cameras. While visual tags are usually related to a web site address, collaborative tagging, instead, provides updated, recommended information contributed and shared by users. In this paper we investigate the combination of collaborative tagging systems with visual tags. We present a prototype of a semiautomatic system generating visual tags which gather information from collaborative tagging. The user can interact with a list of relevant tags (built by clustering closely related tags) that can be further encoded in a visual tag, according to user's preferences. The user experience is enriched by retrieving multimedia content linked to the selected tags, present on the web. We finally show a case study illustrating our approach. [ABSTRACT FROM AUTHOR]

The regulation of multiagent systems may be approached from different stand-points. In this paper I will take the perspective of using a certain type of devices, electronic institutions, to regulate agent interactions. Furthermore, in this paper I am concerned with the tasks of design and construction of actual electronic institutions and I will explore some of the empirical aspects that one may encounter in such activities. More specifically, I will focus on those empirical aspects that are characteristic of electronic institutions rather than those that may be typical of multi-agent systems development in general or other types of software engineering. I use three examples of actual electronic institutions that show different and complementary features in order to motivate a number of distinctions that may be used to treat empirical features in a systematic way. [ABSTRACT FROM AUTHOR]

Organic computing is an upcoming research area with strong relationships to the ideas and concepts of agent-based systems. In this paper, we therefore will have a closer look at agent systems, organic computing systems (as well as autonomic computing systems) and state commonalities and divergences between them. We then propose a common view on these technologies and show, how they can benefit from each other with regard to software engineering. [ABSTRACT FROM AUTHOR]

In this paper, we discuss importance and usefulness of interpersonal network in a community support system. We built a scheduling support system for an academic conference. Our system supports information exchange among participants and information discovery with generating participants' interpersonal network. This system was used in an academic conference called JSAI2003 involving 276 active users. The analysis of the networks reveals that interpersonal networks can promote information exchange among people by indicating existence of people to the others, and that it can also support information discovery by recommendation. [ABSTRACT FROM AUTHOR]

In spite of the importance of natural drawing with input device, the interface between the device and virtual brush's status has been dealt less in literatures. Through this paper, we present a natural interface between pen-tablet device and virtual brush. Proposed system uses pressure instead of z-coordinate of pen to allow drawing with the similar feeling to the real brush. The contribution of this paper is as follows: first, a brush model interacting with pressure is generated. Second, 3D brush model is allowed to be folded back decreasing droplet size intensively according to pen direction changes. [ABSTRACT FROM AUTHOR]

The research community plays a very important role in helping researchers undertake new research topics. The authors propose a community mining system that helps to find communities of researchers by using bibliography data. The basic concept of this system is to provide interactive visualization of communities both local and global communities. We implemented this concept using actual bibliography data and present a case study using the proposed system. [ABSTRACT FROM AUTHOR]

Capturing and understanding mathematics from print form is an important task in translating written mathematical knowledge into electronic form. While the problem of syntactically recognising mathematical formulas from scanned images has received attention, very little work has been done on semantic validation and correction of recognised formulas. We present a first step towards such an integrated system by combining the Infty system with a semantic analyser for matrix expressions. We applied the combined system in experiments on the semantic analysis of matrix images scanned from textbooks. While the first results are encouraging, they also demonstrate many ambiguities one has to deal with when analysing matrix expressions in different contexts. We give a detailed overview of the problems we encountered that motivate further research into semantic validation of mathematical formula recognition. [ABSTRACT FROM AUTHOR]

Automatic evaluation of visual print quality is addressed in this study. Due to many complex factors of perceived visual quality its evaluation is divided to separate parts which can be individually evaluated using standardized assessments. Most of the assessments however require active evaluation by trained experts. In this paper one quality assessment, missing dot detection from printed dot patterns, is addressed by defining sufficient hardware for image acquisition and method for detecting and counting missing dots from a test strip. The experimental results are evidence how the human assessment can be automated with the help of machine vision, thus making the test more repeatable and accurate. [ABSTRACT FROM AUTHOR]

Although ontologies as an important component are widely used for different purpose in different communities and a number of approaches have been reported for developing ontologies, few works have been done to clarify the concept of knowledge science as far as we know. This paper presents a novel attempt to create an ontology characterizing a research program "Technology Creation Based on Knowledge Science" from a Knowledge Science perspective. We address a combination of bottom-up and top-down approaches to ontology creation, which is a first time to put forward a perspective of combining explicit knowledge with tacit, intuitive and experiential knowledge for constructing an ontology. An example of application of this ontology, related to a software tool named adaptive hermeneutic agent (AHA), is also given in the paper. [ABSTRACT FROM AUTHOR]

Today the proliferation of the availability of the information of scientific events on the Web has created the necessity to offer a quickly access to up-to-date information about the quality of these events. This requirement demands for (semi) automatic tools to speedily provide this information. The human-performed activity of the information quality evaluation is extremely time consuming and easily leads to failures. The application OntoQualis here described was motivated to support the quality evaluation of Scientific Conferences, in the Computer Science area, based on the graduated programs evaluation protocol of the Brazilian agency CAPES. The evaluation mechanism is specified in the QUALIS document specifically designed to assess journals and conferences ranking. This paper presents a brief vision of the ongoing process of domain analysis and ontology prototyping aiming to classify Scientific Conferences: the OntoQualis project. Some results of OntoQualis preliminary evaluation have shown a satisfactory classification level in comparison with CAPES-QUALIS ranking. [ABSTRACT FROM AUTHOR]

Ukiyo-e is one famous traditional woodblock type Japanese drawing. Some pattern printed by special print techniques can only be seen from some special direction. This phenomenon relate to the reflection properties on the surface of Ukiyo-e. In this paper, we propose a method to measure these reflection properties of Ukiyo-e. Fitstly, the normal on the surface and the direction of the fiber in Japanese paper are computed from photos which are taken by a measuring machine named OGM. Then, fit the reflection model to the measured data and the reflection properties of Ukiyo-e can be obtained. Based on these parameters, the the appearance of Ukiyo-e can be rendered on real-time. [ABSTRACT FROM AUTHOR]

Real-world data often involves objects that exhibit multiple relationships; for example, ‘papers' and ‘authors' exhibit both paper-author interactions and paper-paper citation relationships. A typical learning problem requires one to make inferences about a subclass of objects (e.g. ‘papers'), while using the remaining objects and relations to provide relevant information. We present a simple, unified mechanism for incorporating information from multiple object types and relations when learning on a targeted subset. In this scheme, all sources of relevant information are marginalized onto the target subclass via random walks. We show that marginalized random walks can be used as a general technique for combining multiple sources of information in relational data. With this approach, we formulate new algorithms for transduction and ranking in relational data, and quantify the performance of new schemes on real world data—achieving good results in many problems. [ABSTRACT FROM AUTHOR]

We develop a novel user-centric modeling technology, which can dynamically describe and update a person's expertise profile. In an enterprise environment, the technology can enhance employees' collaboration and productivity by assisting in finding experts, training employees, etc. Instead of using the traditional search methods, such as the keyword match, we propose to use relational and evolutionary graph models, which we call ExpertiseNet, to describe and find experts. These ExpertiseNets are used for mining, retrieval, and visualization. We conduct experiments by building ExpertiseNets for researchers from a research paper collection. The experiments demonstrate that expertise mining and matching are more efficiently achieved based on the proposed relational and evolutionary graph models. [ABSTRACT FROM AUTHOR]

This paper provides a survey and analysis of applications of Agent Based Simulation (ABS). A framework for describing and assessing the applications is presented and systematically applied. A general conclusion from the study is that even if ABS seems a promising approach to many problems involving simulation of complex systems of interacting entities, it seems as the full potential of the agent concept and previous research and development within ABS often is not utilized. We illustrate this by providing some concrete examples. Another conclusion is that important information of the applications, in particular concerning the implementation of the simulator, was missing in many papers. As an attempt to encourage improvements we provide some guidelines for writing ABS application papers. [ABSTRACT FROM AUTHOR]

Knowledge visualization is a creative process, but difficult to formalize. This paper presents a system that is capable of analyzing voluminous citation data and visualizing the result. The system offers visualizations of trends by clustering scientific papers taken from the web (CiteSeer papers). Two methods are implemented: factor analysis and PFNET. An experiment has been carried out with the literature in knowledge management. A deep analysis of current trends in KM is then performed to check the relevance of these results. While the topical content is specific to knowledge engineering, semantic web, and related sub-areas, the approach could be applied to any general topic area in AI. [ABSTRACT FROM AUTHOR]

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]

The aim of this paper is to give theoretical and experimental tools for measuring the driving force in evolving complex networks. First a discrete-time stochastic model framework is introduced to state the question of how the dynamics of these networks depend on the properties of the parts of the system. Then a method is presented to determine this dependence in the possession of the required data about the system. This measurement method is applied to the citation network of high energy physics papers to extract the in-degree and age dependence of the dynamics. It is shown that the method yields close to "optimal" results. [ABSTRACT FROM AUTHOR]

TSP is a problem finding out the shortest distance out of possible courses where one starts a certain city and turns back to a starting city, visiting every city only once among N cities. This paper proposes the new method using both population initialization and sequential transformation method at the same time and then proves the improvement of capability by comparing them with existing methods. Keywords: Genetic Algorithm, GA, TSP, Initialization. [ABSTRACT FROM AUTHOR]

Changes and adaptations are always necessary after the deployment of a multiagent system (MAS), as well as of any other type of software systems. Some of these changes may be simply perfective and have local impact only. However, adaptive changes to meet changed situations in the operational environment of the MAS may have global impact on the overall design. In this paper, we analyze the issue of continuous design change/adaptation in a MAS organization, and the specific problem of how to properly model/design a MAS so as to make it ready to adaptation. Following, the paper focuses on the Gaia methodology and analyzes - also with the help of an illustrative example - its suitability in supporting and facilitating adaptive changes in MASs organizations, and its advantages and limitations with this regard over a number of different agent-oriented methodologies. Keywords: Agent Oriented Methodologies, Design for Change, Adaptive Organizations, Methodologies Evaluation. [ABSTRACT FROM AUTHOR]

Nowadays amount of information on Internet is dramatically increasing. The ability of facilitating users to achieve useful information is more and more important for search field. CDSE, a model for the domain-based intelligent search engine is proposed in this paper. The model can help users to retrieve what they need by combining text classification with keywords extraction. Several algorithms that use key technologies are proposed, such as statistics, data mining and agents. Then a new criterion named ranking error is contributed to solve the problem of evaluation ranking inefficiency in traditional performance evaluation methodologies. The experimental results indicate that the proposed model can effectively improve retrieval precision and solve the problem of relevant document ranking behind in current search engine. [ABSTRACT FROM AUTHOR]

Spatial structure supporting applications offer an abstract level of what can be found in the real world. However, in many systems, objects are aligned straight, rotation is not possible, they can be resized easily and can hold more text than is visible on the screen. Paper and structures created with paper seem to be more limited: Straight alignment is not possible without spending much time; paper can hardly be resized without damaging it; and piles may fall down if they become too tall. However, a closer look shows that paper structures offer much more attributes and dependencies than any current spatial structure supporting application. In this article, we compare paper structures to a selection of computer applications. We argue that the observed small additions with paper carry information which improves finding and organizing. [ABSTRACT FROM AUTHOR]

Semantic Web conferences such as ESWC and ISWC offer prime opportunities to test and showcase semantic technologies. Conference metadata about people, papers and talks is diverse in nature and neither too small to be uninteresting or too big to be unmanageable. Many metadata-related challenges that may arise in the Semantic Web at large are also present here. Metadata must be generated from sources which are often unstructured and hard to process, and may originate from many different players, therefore suitable workflows must be established. Moreover, the generated metadata must use appropriate formats and vocabularies, and be served in a way that is consistent with the principles of linked data. This paper reports on the metadata efforts from ESWC and ISWC, identifies specific issues and barriers encountered during the projects, and discusses how these were approached. Recommendations are made as to how these may be addressed in the future, and we discuss how these solutions may generalize to metadata production for the Semantic Web at large. [ABSTRACT FROM AUTHOR]

This paper introduces an indexing technique for fuzzy numerical data which relies on the classical, well-known and well-spread B+tree index data structure. The proposed indexing technique is specifically devised to increase the performance of query processing when a possibility measured flexible condition is involved. The proposal relies on the use of an indexing data structure implemented in virtually every database management system. This feature makes the proposal a good candidate to be used, with very low implementation effort, in a fuzzy database management system created as an extension of a classical one. The paper includes a performance analysis of the proposed indexing technique in contrast with other purpose equivalent techniques in order to evaluate the suitability of the proposal. [ABSTRACT FROM AUTHOR]

Request Processing Systems should exhibit predictable behavior by guaranteeing Quality-of-Service parameters. One of the important requirements of predictability is that requests should have maximum acceptable response time thresholds, denoted as deadlines in this paper. In order to provide QoS, the system should try to guarantee these deadlines. This way, it is desirable to use a load-balancing algorithm that tries to both maximize the throughput and minimize the missed deadlines. Assuming that all requests durations are known a priori, this paper shows, with the help of a simulator, how the control over the big tasks plays a crucial role in the pursuit of the objective. Finally, this paper presents a derived form of the traditional Least-Work-Remaining algorithm, named Task Assignment by Isolating Big Tasks, that proved to be a better alternative in such scenarios. [ABSTRACT FROM AUTHOR]

UML is being increasing used for the analysis and design of Web Information Systems. At the same time, many XML-based languages are cornerstones in the development of this kind of system. As a consequence of the predominance of these languages, there are many works in the literature devoted to exploring the relationships between UML and XML. In this paper we present a survey of current approaches to the transformation of UML models into XML schemas. The study is focused on the case of transformation of UML class diagrams to XML schemas, since we have not found any proposal regarding other kinds of UML diagrams. [ABSTRACT FROM AUTHOR]

The paper discusses a distributed approach for monitoring and diagnosing the execution of a plan where concurrent actions are performed by a team of cooperating agents. The paper extends the notion of plan diagnosis(introduced by Roos et al. for the execution of a multi-agent plan) with the notion of agent diagnosis. While plan diagnosis is able to capture the distinction between primary and secondary failures, the agent diagnosis makes apparent the actual health status of the agents. The paper presents a mechanism of failure propagation which captures the interplay between agent diagnosis and plan diagnosis; this mechanism plays a critical role in the understanding at what extent a fault affecting the functionalities of an agent affects the global plan too. A relational formalism is adopted for modeling both the nominal and the abnormal execution of the actions. [ABSTRACT FROM AUTHOR]

In order to discover services in business-driven Web service composition conveniently, accurately, and efficiently, this paper proposes a business process-oriented service discovery approach. In order to link business property with services, this paper proposes a business related description model of operations. Based on the business related relation model proposed in this paper, a relation-driven discovering algorithm for business process-oriented service discovery is presented. Compared with other discovering approach, the proposed discovering approach considers the business relation between operations and can solve the problem of discovering services with meaningful business relation. The experimentation shows the better performance of this algorithm. [ABSTRACT FROM AUTHOR]

In this paper, we suggest a postal RFID application model that can be used for real time trace and tracking system implementation of parcel processing and pallet management. This paper also shows the tag recognition performance of parcels by speed and mounting tag material such as thin cans, water bottles, and paper using an implemented postal RFID system to find the best solution for RFID adaptation in postal logistics. [ABSTRACT FROM AUTHOR]

Generally, it is difficult to find constant patterns on identifiers in a container image, since the identifiers are not normalized in color, size, and position, etc. and their shapes are damaged by external environmental factors. This paper distinguishes identifier areas from background noises and removes noises by using an ART2-based quantization method and general morphological information on the identifiers such as color, size, ratio of height to width, and a distance from other identifiers. Individual identifier is extracted by applying the 8-directional contour tracking method to each identifier area. This paper proposes a refined ART2-based RBF network and applies it to the recognition of identifiers. Through experiments with 300 container images, the proposed algorithm showed more improved accuracy of recognizing container identifiers than the others proposed previously, in spite of using shorter training time. [ABSTRACT FROM AUTHOR]

Reading and literature exploration are important tasks of scientific research. However, conventional retrieval systems provide limited support for these tasks by concentrating on identifying relevant materials. New generation systems should provide additional support functionality by focusing on analyzing and organizing the retrieved materials. A framework of literature exploration support systems is proposed. Techniques of granular computing are used to construct granular knowledge structures from the contents, structures, and usages of scientific documents. The granular knowledge structures provide a high level understanding of scientific literature and hints regarding what has been done and what needs to be done. As a demonstration, we examine granular knowledge structures obtained from an analysis of papers from two rough sets related conferences. [ABSTRACT FROM AUTHOR]

The present paper is an attempt to construct a theoretical model of the context of social action based on a reinterpretation of the sociological theory of social fields as developed by Pierre Bourdieu. Using his notions of different types of capital and other tools, a multidimensional model of context is presented in which dimensions are defined as fields affected by (and affecting) a given social action. Focus in the paper is on discursive behaviour, but following the assumptions of linguistic pragmatics, discourse is considered here just as a specific form of broadly defined social action. Thus an attempt is made at linking studies on context from linguistics with those from sociology. Social action is theorized, as in Bourdieu's models, as a process of conversion of different types of capital. The strategic use of particular types of capital is considered as another dimension of contextualization of social action. [ABSTRACT FROM AUTHOR]

We are glad to present the papers of the special session on Performance in Industrial Holonic Systems (Pi-HolS 2007) at the 3d International Conference on Industrial Applications of Holonic and Multi-Agent Systems (HoloMAS 2007). The session brought together researchers and practitioners in the areas of holonic and multi-agent systems, knowledge engineering, and performance management to share their views and experience in design, development, deployment, and application of technologies for measuring, assessing and optimizing the performance of industrial systems based on holonic principles. [ABSTRACT FROM AUTHOR]

In this paper we propose a two-pass classification method and apply it to face recognitions. The method is obtained by integrating together two approaches, the hyper-ellipsoid neural networks (HENN's) and the SVM's with error correcting codes. This method realizes a classification operation in two passes: the first one is to get an intermediate classification result for an input sample by using the HENN's, and the second pass is followed by using the SVM's to re-classify the sample based on both the input data and the intermediate result. Simulations conducted in the paper for applications to face recognition showed that the two-pass method can maintain the advantages of both the HENN's and the SVM's while remedying their disadvantages. Compared with the HENN's and the SVM's, a significant improvement of recognition performance over them has been achieved by the new method. [ABSTRACT FROM AUTHOR]

The neuron based nonlinear PID control method for plant with uncertainties is proposed in this paper. In this control system, the neuron based nonlinear PID controller is constructed by selecting the neuron inputs, and the control action of the nonlinear PID controller are determined by modifying the neuron weights on-line. The neuron based nonlinear PID controller produces the control signal in model-free way. With an example of the basis weight control of a paper machine, the experiments are made. The simulation results show that the neuron model-free controller has good control performance, fast transient response and strong robustness. [ABSTRACT FROM AUTHOR]