Improving Knowledge Retrieval in Digital Libraries Applying Intelligent Techniques

Nowadays an enormous quantity of heterogeneous and distributed information is stored in the digital University. Exploring online collections to find knowledge relevant to a user’s interests is a challenging work. The artificial intelligence and Semantic Web provide a common framework that allows knowledge to be shared and reused in an efficient way. In this work we propose a comprehensive approach for discovering E-learning objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. We have used Case Based-Reasoning methodology to develop a prototype for supporting efficient retrieval knowledge from online repositories. We suggest a conceptual architecture for a semantic search engine. OntoUS is a collaborative effort that proposes a new form of interaction between users and digital libraries, where the latter are adapted to users and their surroundings

Hybrid consumption paths in the attribute space: A model and application with scanner data

This paper presents and estimates a dynamic choice model in the attribute space considering rational consumers. In light of the evidence of several state-dependence patterns, the standard attribute-based model is extended by considering a general utility function where pure inertia and pure variety-seeking behaviors can be explained in the model as particular linear cases. The dynamics of the model are fully characterized by standard dynamic programming techniques. The model presents a stationary consumption pattern that can be inertial, where the consumer only buys one product, or a variety-seeking one, where the consumer shifts among varied products. We run some simulations to analyze the consumption paths out of the steady state. Under the hybrid utility assumption, the consumer behaves inertially among the unfamiliar brands for several periods, eventually switching to a variety-seeking behavior when the stationary levels are approached. An empirical analysis is run using scanner databases for three different product categories: fabric softener, saltine cracker, and catsup. Non-linear specifications provide the best fit of the data, as hybrid functional forms are found in all the product categories for most attributes and segments. These results reveal the statistical superiority of the non-linear structure and confirm the gradual trend to seek variety as the level of familiarity with the purchased items increases.Dynamic Choice Model, Rational Consumers, Inertia, Variety Seeking, Hybrid Behavior, Scanner Data

Intelligent Integrated Management for Telecommunication Networks

As the size of communication networks keeps on growing, faster connections, cooperating technologies and the divergence of equipment and data communications, the management of the resulting networks gets additional important and time-critical. More advanced tools are needed to support this activity. In this article we describe the design and implementation of a management platform using Artificial Intelligent reasoning technique. For this goal we make use of an expert system. This study focuses on an intelligent framework and a language for formalizing knowledge management descriptions and combining them with existing OSI management model. We propose a new paradigm where the intelligent network management is integrated into the conceptual repository of management information called Managed Information Base (MIB). This paper outlines the development of an expert system prototype based in our propose GDMO+ standard and describes the most important facets, advantages and drawbacks that were found after prototyping our proposal

Teaching Innovation in Order to Integrate Self-Learning and Self-Evaluation in the Webct Platform

El concepto de docencia universitaria tradicional se ha visto modificado por los principios definidos en el Espacio Europeo de Educación Superior. Un cambio metodológico que motiva el concepto de autoevaluación y promueve todas aquellas actividades académicas que faciliten el autoaprendizaje. En este escenario, es fundamental que los estudiantes adquieran nuevos hábitos autoformativos. Nuestro trabajo presenta un método de enseñanza-aprendizaje para que ésta pase a ser más activa y participativa. Este proyecto permite al alumno disponer de un conjunto de recursos, que favorecen la autoevaluación y autoformación, a la vez que facilita su trabajo personal y en equipo.In the European Higher Education Area (EHEA) the traditional teaching university concept has changed. EHEA has introduced a methodological change in order to motivate selfevaluation and to promote self learning academic activities. In this way students must acquire new self learning practices. Our work presents a method to make more active and participatory the teaching-learning process. This project provides students different tools in order to promote the self-learning and self-evaluation. A set of teaching resources are presented to facilitate both individual and collective students' work

The Evolution of OSI Network Management by Integrated the Expert Knowledge

The management of modern telecommunications networks must satisfy ever-increasing operational demands. Operation and quality service requirements imposed by the users are also an important aspect to consider. In this paper we have carried out a study for the improvement of intelligent administration techniques in telecommunications networks. This task is achieved by integrating knowledge base of expert system within the management information used to manage a network. For this purpose, an extension of OSI management framework specifications language has been added and investigated in this study. A new property named RULE has also been added, which gathers important aspects of the facts and the knowledge base of the embedded expert system. Networks can be managed easily by using this proposed integration

Embedment of metal nanoparticles in GaAs and Si for plasmonic absorption enhancement in intermediate band solar cells

The high near-field enhancement occurring in the vicinity of metallic nanoparticles (MNPs) sustaining surface plasmons can only be fully exploited in photovoltaic devices if the MNPs are placed inside their semiconducting material, in the photoactive region. In this work an experimental procedure is studied to embed MNPs in gallium arsenide (GaAs) and silicon (Si), which can be applied to other semiconductor host materials. The approach consists in spin-coating colloidal MNPs dispersed in solution onto the substrate surface. Then a capping layer of the same material as the substrate is deposited on top to embed the MNPs in the semiconductor. The extinction spectra of silver (Ag) and gold (Au) MNPs embedded in GaAs and Si is modeled with Mie theory for comparison with optical measurements. This contribution constitutes the initial step towards the realization of quantum-dot intermediate band solar cells (QD-IBSC) with MN

Intelligent information processing in a digital library using semantic web

With the explosive growth of information, it is becoming increasingly difficult to retrieve the relevant documents with current search engine only. The information is treated as an ordinary database that manages the contents and positions. To the individual user, there is a great deal of useless information in addition to the substantial amount of useful information. This begets new challenges to docent community and motivates researchers to look for intelligent information retrieval approach and ontologies that search and/or filter information automatically based on some higher level of understanding are required. We study improving the efficiency of search methods and classify the search patrons into several models based on the profiles of agent based on ontology. We have proposed a method to efficiently search for the target information on a Digital Library network with multiple independent information sources. This paper outlines the development of an expert prototype system based in an ontology for retrieval information of the Digital Library University of Seville. The results of this study demonstrate that by improving representation by incorporating more metadata from within the information and the ontology into the retrieval process, the effectiveness of the information retrieval is enhanced. We used Jcolibri and Prótége for developing the ontology and creation the expert system respectively

Expert knowledge management based on ontology in a digital library

The architecture of the future Digital Libraries should be able to allow any users to access available knowledge resources from anywhere and at any time and efficient manner. Moreover to the individual user, there is a great deal of useless information in addition to the substantial amount of useful information. The goal is to investigate how to best combine Artificial Intelligent and Semantic Web technologies for semantic searching across largely distributed and heterogeneous digital libraries. The Artificial Intelligent and Semantic Web have provided both new possibilities and challenges to automatic information processing in search engine process. The major research tasks involved are to apply appropriate infrastructure for specific digital library system construction, to enrich metadata records with ontologies and enable semantic searching upon such intelligent system infrastructure. We study improving the efficiency of search methods to search a distributed data space like a Digital Library. This paper outlines the development of a CaseBased Reasoning prototype system based in an ontology for retrieval information of the Digital Library University of Seville. The results demonstrate that the used of expert system and the ontology into the retrieval process, the effectiveness of the information retrieval is enhanced

Intelligent Techniques for Knowledge Recovery in University Education

El desarrollo de sistemas de búsqueda que faciliten la gestión del conocimiento académico en un espacio distribuido como son las Bibliotecas digitales universitarias, es uno de los principales objetivos de instituciones y proveedores de información. Estos nuevos retos motivan a los investigadores y a la comunidad docente a buscar nuevos enfoques en la recuperación eficiente de la información. El presente estudio supone un esfuerzo en innovación educativa, y propone un enfoque pragmático en la aplicación de la recuperación del conocimiento en las bibliotecas digitales. Para ello utilizamos un enfoque ontológico y técnicas de la inteligencia artificial.The main goal of the academic institutions and information providers is to development a search engine to retrieval information in a super distributed data space like digital university libraries. This begets new challenges to docent community and motivates researchers to look for intelligent information retrieval approach that search and/or filter information automatically. We make an effort in innovation education in this direction and we propose a semantic method for efficient information search. This paper suggests a pragmatic approach to the implementation of intelligent techniques and ontologies for efficient knowledge retrieval in the academic digital libraries

Spacecraft magnetic attitude control using approximating sequence Riccati equations

This paper presents the results of a spacecraft attitude control system based on magnetic actuators designed for low Earth orbits. The control system is designed by using a nonlinear control technique based on the approximating sequence of Riccati equations. The behavior of the satellite is discussed under perturbations and model uncertainties. Simulation results are presented when the control system is able to guide the spacecraft to the desired attitude in a variety of different conditions