The aim of this paper is to present the affective multimedia learning framework of the MENTOR as well as the web and multimedia technologies which were used for its implementation. The MENTOR is an affective web-based adaptive educational system for distance learning. The basic concern of MENTOR is to retain the student|s emotional state positive during the learning process. To achieve this, MENTOR incorporates an affective module which enhances the traditional learning practices with an affective multimedia dimension. The foremost and endmost goal of MENTOR is to provide the learner with a more personalised and friendly multimedia environment for learning, according to his personality, mood and emotions.

Intelligent agents that seek to automate various stages of the negotiation process are often enhanced with models of computational intelligence extending the cognitive abilities of the parties they represent. This paper is focused on predictive strategies employed by automated negotiators, and particularly those based on forecasting the counterpart’s responses. In this context a strategy supporting negotiations over multiple issues is presented and assessed. Various behaviors emerge with respect to negotiator’s attitude towards risk, resulting to different utility gains. Forecasting is conducted with the use of Multilayer Perceptrons (MLPs) and the training set is extracted online during the negotiation session. Two cases are examined: in the first separate MLPs are used for the estimations of each negotiable attribute, whereas in the second a single MLP is used to estimate the counterpart’s response. Experiments are conducted to search the architecture of the MLPs.

In this paper, we present a new text line detection method for handwritten documents. The proposed technique is based on a strategy that consists of three distinct steps. The first step includes image binarization and enhancement, connected component extraction, partitioning of the connected component domain into three spatial sub-domains and average character height estimation. In the second step, a block-based Hough transform is used for the detection of potential text lines while a third step is used to correct possible splitting, to detect text lines that the previous step did not reveal and, finally, to separate vertically connected characters and assign them to text lines. The performance evaluation of the proposed approach is based on a consistent and concrete evaluation methodology.

The aim of this paper is to present an Affective Educational Module for distance learning which is called MENTOR. MENTOR constitutes of three main components, the Emotional Component, the Teacher Component and the Visualization Component and its main purpose is to motivate appropriately the student in order to accomplish his learning goals. The basic concern of MENTOR is to retain the student's emotional state positive during the learning process. To achieve this, it recognizes the emotions of the students and takes them under consideration to provide them with the suitable learning strategy. This kind of strategy is based both on the cognitive abilities and the affective preferences of the student and is stored in the student's model. The Student model supplies the educational system with necessary information with the aim to adapt itself successfully to the Student's needs.

The need for effective ontology visualization for design, management and browsing has arisen as a result of the progress in the areas of semantic Web and personal information management. There are several ontology visualizations available through existing ontology management tools, but not as many evaluations to determine their advantages and disadvantages and their suitability for various ontologies and user groups. This work presents selected results of an evaluation of four visualization methods in Protege.

Having realised the benefits resulting from delivering on-line public services in the context of electronic government, administrations strive to extend the spectrum of services offered to citizens and enterprises, as well as to engage multiple communication channels in service delivery, in order to increase the target audience and, consequently, the service effectiveness. Insofar, however, only the web channel has been sufficiently used for service delivery, whereas other channels have not been adequately exploited. One of the main reasons of this lag is the cost incurred for the development and maintenance of multiple versions of an electronic service, each version targeted to a different platform. In this paper, we present an approach and the associated tools for developing and maintaining electronic services that allows the automated production of different versions of the electronic service, each targeted to a specific platform.

Most ontology development methodologies and tools for ontology management deal with ontology snapshots, i. e. they model and manage only the most recent version of ontologies, which is inadequate for contexts where the history of the ontology is of interest, such as historical archives. This work presents a modeling for entity and relationship timelines in the Protégé tool, complemented with a visualization plug-in, which enables users to examine entity evolution along the timeline.

Today's nanometer technology trends have a very negative impact on the reliability of semiconductor products. Intermittent faults constitute the largest part of reliability failures that are manifested in the field during the semiconductor product operation. Since Software-Based Self-Test (SBST) has been proposed as an effective strategy for on-line testing of processors integrated in non-safety critical low-cost embedded system applications, optimal test period specification is becoming increasingly challenging.In this paper we first introduce a reliability analysis for optimal periodic testing of intermittent faults that minimizes the test cost incurred based on a two-state Markov model for the probabilistic modeling of intermittent faults. Then, we present for the first time an enhanced SBST strategy for on-line testing of complex pipelined embedded processors. Finally, we demonstrate the effectiveness of the proposed optimal periodic SBST strategy by applying it to a fully-pipelined RISC embedded processor and providing experimental results.

Digital libraries and historical archives are increasingly employing visualization systems to facilitate the information retrieval and knowledge extraction tasks of their users. Typically, each organization employs a single visualization system, which may not suit best the needs of certain user groups, specific tasks, or properties of document collections to be visualized. In this paper, we present a context-based adaptive visualization environment, which embeds a set of visualization methods into a visualization library, from which the most appropriate one is selected for presenting information to the user. Methods are selected by examining parameters related to the user profile, system configuration and the set of data to be visualized, and employing a set of rules to assess the suitability of each method. The presented environment additionally monitors user behavior and preferences to adapt the visualization method selection criteria

In this article, we describe the Massively AGent Execution system (MAGE), whose purpose is to facilitate the implementation of multiagent applications in a massively parallel environment. MAGE is a parallel programming environment that supports the implementation of each agent in a Prolog system extended with communication primitives used for the cooperation and the interaction among the agents.

A new design method of TSC m-out-of-2m code checkers is presented. The design is composed basically of two full-adder/half-adder trees, each summing-up the one's of m input lines, and a k-variable 2-pair two-rail code tree that compares the outputs of the two adder trees. The only modules used are full-adders, half-adders and two-rail T2. This method is well suited for VLSI MOS implementation and compared to previous methods it results in significant circuit cost reduction and smaller test set, without sacrificing performance. At the same time the proposed design has all added advantages of a modular design.

With the need for electronic services to be developed and deployed more and more rapidly, it is imperative that concrete models of electronic services are developed, to facilitate systematic work of electronic service stakeholders, concrete semantics, and coherent representations across services developed within an organisation. Using the XML language to develop such a model offers a number of additional advantages, such as rich semantics, facilitation of data interchange, extensibility, high abstraction levels, and possibility for mechanical processing. In this paper, we present the design aspects of an XML model for electronic services, which has been used for building a repository of interlinked elements representing e-services. A web-based interface for the management of this repository and a tool for automatically compiling e-service descriptions into executable images have been developed alongside. The model has been evaluated by a mixture of electronic service stakeholders, and the results of this evaluation are also presented.

In this paper we present eg-GRIDS, an algorithm for inducing context-free grammars that is able to learn from positive sample sentences. The presented algorithm, similar to its GRIDS predecessors, uses simplicity as a criterion for directing inference, and a set of operators for exploring the search space. In addition to the basic beam search strategy of GRIDS, eg-GRIDS incorporates an evolutionary grammar selection process, aiming to explore a larger part of the search space. Evaluation results are presented on artificially generated data, comparing the performance of beam search and genetic search. These results show that genetic search performs better than beam search while being significantly more efficient computationally.

In this paper we present a new computationally efficient algorithm for inducing context-free grammars that is able to learn from positive sample sentences. This new algorithm uses simplicity as a criterion for directing inference, and the search process of the new algorithm has been optimised by utilising the results of a theoretical analysis regarding the behaviour and complexity of the search operators. Evaluation results are presented on artificially generated data, while the scalability of the algorithm is tested on a large textual corpus. These results show that the new algorithm performs well and can infer grammars from large data sets in a reasonable amount of time.

Constructive methods obtain solutions to constraint satisfaction problem instances by iteratively extending consistent partial assignments. In this research, we study the solution paths in the search space of constructive methods and examine their distribution among the assignments of the search space. By properly employing the entropy of this distribution, we derive measures of the average amount of choice available within the search space for constructing a solution. The derived quantities directly reflect both the number and the distribution of solutions, an "open question" in the phase transition literature. We show that constrainedness, an acknowledged predictor of computational cost, is an aggregate measure of choice deficit. This establishes a connection between an algorithm-independent property of the search space, such as the inherent choice available for constructing a solution, and the algorithm-dependent amount of resources required to actually construct a solution.

In this paper an algorithm for the generation of single input change (SIC) pairs is presented, termed the accumulator-based SIC pair generation (ASG) algorithm; SIC pairs have been effectively utilised for testing robustly detectable sequential faults. ASG is implemented in hardware utilising an accumulator whose inputs are driven by a barrel shifter. Since such structures (accumulators whose inputs are driven by barrel shifters) are commonly found in current, high-speed signal processing VLSI circuits, the presented schema provides a practical solution for the built-in testing of such circuits for testing delay and stuck-open faults. Utilisation of ASG to applying SIC pairs to adjacent pairs of inputs of the CUT, resulting in pseudoexhaustive schemes, is also addressed.

Our aim is to investigate the factors which determine the intrinsic hardness of constructing a solution to any particular constraint satisfaction problem instance, regardless of the algorithm employed. The line of reasoning is roughly the following: There exists a set of distinct, possibly overlapping, trajectories through the states of the search space, which start at the unique initial state and terminate at complete feasible assignments. These trajectories are named solution paths. The entropy of the distribution of solution paths among the states of each level of the search space provides a measure of the amount of choice available for selecting a solution path at that level. This measure of choice is named solution path diversity. Intrinsic instance hardness is identified with the deficit in solution path diversity and is shown to be linked to the distribution of instance solutions as well as constrainedness, an established hardness measure.

Databases use and design has utilitarian and pedagogical educational interest. The utilitarian interest for database design education is determined by their economic impact. Databases pedagogical interest rises from their view as models and the possibility to use them for the design of general knowledge learning activities. The utilitarian and learning advantages rationalize the database design instruction in secondary education rising educational research questions. In this paper we report some key research findings about 11 th grade students' difficulties in database design, focusing especially in the representation of relationships. For the clarification of students' difficulties research activities were designed and implemented that asked students to transform given ER schemata to the corresponding logical and vice-versa. The analysis of students' solutions resulted in a systematic categorization of their difficulties and the proposition of specific action strategies for database design instruction improvement.

PETINA is a PErsonalized Tourist INformation Advisor system about Greece aiming to help tourists to construct tours satisfying speci ed constraints PETINA is going to be implemented in the ElipSys language a parallel logic programming language under develop ment As it tries to solve a combinatorial searching problem various ElipSys features such as data parallelism data driven computation and constraint satisfaction techniques can be exploited e ciently Moreover as it consults a large database containing tourist data the external database connection facility of ElipSys is exploitable as well