2,894 research outputs found
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
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