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

Challenges in distributed information search in a semantic digital library

Nowadays an enormous quantity of heterogeneous and distributed information is stored in the current digital libraries. Access to these collections poses a serious challenge, however, because present search techniques based on manually annotated metadata and linear replay of material selected by the user do not scale effectively or efficiently to large collections. The artificial intelligent and semantic Web provides a common framework that allows knowledge to be shared and reused. In this paper we propose a comprehensive approach for discovering information objects in large digital collections based on analysis of recorded semantic metadata in those objects and the application of expert system technologies. We suggest a conceptual architecture for a semantic and intelligent search engine. OntoFAMA is a collaborative effort that proposes a new form of interaction between people and Digital Library, where the latter is adapted to individuals and their surroundings. We have used Case Based-Reasoning methodology to develop a prototype for supporting efficient retrieval knowledge from digital library of Seville University

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

Forecasting Recharging Demand to Integrate Electric Vehicle Fleets in Smart Grids

Electric vehicle fleets and smart grids are two growing technologies. These technologies provided new possibilities to reduce pollution and increase energy efficiency. In this sense, electric vehicles are used as mobile loads in the power grid. A distributed charging prioritization methodology is proposed in this paper. The solution is based on the concept of virtual power plants and the usage of evolutionary computation algorithms. Additionally, the comparison of several evolutionary algorithms, genetic algorithm, genetic algorithm with evolution control, particle swarm optimization, and hybrid solution are shown in order to evaluate the proposed architecture. The proposed solution is presented to prevent the overload of the power grid

Monitoring and Fault Location Sensor Network for Underground Distribution Lines

One of the fundamental tasks of electric distribution utilities is guaranteeing a continuous supply of electricity to their customers. The primary distribution network is a critical part of these facilities because a fault in it could affect thousands of customers. However, the complexity of this network has been increased with the irruption of distributed generation, typical in a Smart Grid and which has significantly complicated some of the analyses, making it impossible to apply traditional techniques. This problem is intensified in underground lines where access is limited. As a possible solution, this paper proposes to make a deployment of a distributed sensor network along the power lines. This network proposes taking advantage of its distributed character to support new approaches of these analyses. In this sense, this paper describes the aquiculture of the proposed network (adapted to the power grid) based on nodes that use power line communication and energy harvesting techniques. In this sense, it also describes the implementation of a real prototype that has been used in some experiments to validate this technological adaptation. Additionally, beyond a simple use for monitoring, this paper also proposes the use of this approach to solve two typical distribution system operator problems, such as: fault location and failure forecasting in power cables.Ministerio de Economía y Competitividad, Government of Spain project Sistema Inteligente Inalámbrico para Análisis y Monitorización de Líneas de Tensión Subterráneas en Smart Grids (SIIAM) TEC2013-40767-RMinisterio de Educación, Cultura y Deporte, Government of Spain, for the funding of the scholarship Formación de Profesorado Universitario 2016 (FPU 2016

Increasing the Efficiency of Rule-Based Expert Systems Applied on Heterogeneous Data Sources

Nowadays, the proliferation of heterogeneous data sources provided by different research and innovation projects and initiatives is proliferating more and more and presents huge opportunities. These developments create an increase in the number of different data sources, which could be involved in the process of decisionmaking for a specific purpose, but this huge heterogeneity makes this task difficult. Traditionally, the expert systems try to integrate all information into a main database, but, sometimes, this information is not easily available, or its integration with other databases is very problematic. In this case, it is essential to establish procedures that make a metadata distributed integration for them. This process provides a “mapping” of available information, but it is only at logic level. Thus, on a physical level, the data is still distributed into several resources. In this sense, this chapter proposes a distributed rule engine extension (DREE) based on edge computing that makes an integration of metadata provided by different heterogeneous data sources, applying then a mathematical decomposition over the antecedent of rules. The use of the proposed rule engine increases the efficiency and the capability of rule-based expert systems, providing the possibility of applying these rules over distributed and heterogeneous data sources, increasing the size of data sets that could be involved in the decision-making process

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

Positioning of "fast food" in Chiclayo-Peru, across the analysis of correspondences

El objetivo de este trabajo es establecer la posición competitiva de los diferentes establecimientos comerciales de comida rápida (fast foods) que operan en el Centro Comercial “Real Plaza” de la ciudad de Chiclayo-Perú. Para esto, se ha aplicado el análisis de correspondencias. Los datos fueron recogidos en 265 entrevistas a los clientes de los fast foods. El cuestionario se dirigía a verificar la percepción del consumidor en atributos como precios, nivel de gasto, frecuencia, lealtad, calidad del servicio, calidad del trato y calidad de la comida. Los resultados indican que Bembos y Pizza Hut son marcas diferenciadas por el consumidor y posicionadas, en el primer caso, en calidad de comida, gasto importante y trato regular, en el segundo caso, el buen servicio y nivel de gasto alto. KFC (Kentucky Fried Chicken) y Chinawok son marcas que figuran en un segundo grupo y comparten el atributo de servicio excelente. Las demás marcas como Nitos, Manos Norteñas y Mi casa no se encuentran diferenciadas y su posicionamiento es escaso. Para complementar se hizo un análisis factorial que descartó al precio como atributo de relevancia para los consumidores. Finalmente las estrategias de mayor impacto para estos negocios, sobre todo los no diferenciados, se relacionan con lograr una percepción de comida y trato excelente, mejorando la variedad de oferta, empleando la gama de precios y elevando el nivel de contacto con el cliente

Una perspectiva innovadora en la formación de administradores: el desarrollo de las inteligencias intra e interpersonales (A new way in training of the managers: development of intra and inter-personal intelligence)

El artículo propone una nueva perspectiva en la formación de los administradores a partir de la identificación de las competencias directivas y de la importancia que en éstas tienen las que derivan de la inteligencia emocional. Después de destacar la importancia de la educación y de la formación en administración en el contexto universitario actual, se definen las competencias requeridas para la administración y se proponen algunas estrategias para mejorar la competitividad de los administradores en las organizaciones. This article lays out a new perspective for training of the managers from the point of view of leadership abilities as well as the emotional intelligence. After stressing the relevance of education and the training in management in the universities, the qualities required for management are noted, and some strategies for improving the competitiveness of the managers are proposed

Estudio comparado

El presente capítulo describe las vinculaciones entre la investigación científica para el estudio de la administración pública y el método comparativo. Se parte de la premisa de que cualquier disciplina científica requiere de un objeto de estudio único y diferente de los demás que integran las ciencias sociales y de que el estudio científico de un objeto, fenómeno o circunstancia requiere también de una metodología sustentada en bases científicas. Para ello se describen brevemente el método científico y el proceso de investigación científica, revisando los tipos de razonamiento y las principales técnicas e instrumentos coadyuvantes a la investigación administrativa. Por último se presentan las características del método comparativo, integrándose dos breves ejemplos de estudio aplicando dicho método al análisis de la competitividad institucional en el caso de tres megaciudades de México (Cd. De México, Guadalajara y Monterrey), y en el caso de 5 municipios urbanos de la zona de Monterrey