10 resultados para DDM Data Distribution Management testbed benchmark design implementation instance generator

em Universidad de Alicante


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The purpose of this paper is twofold. First, the paper analyzes the relationship between quality management and environmental management and their effects on hotel performance. Second, the article examines the relationship between these two management systems and organizational design. The paper uses an exploratory, qualitative approach based on interviews with managers and experts in the hotel industry. Based on a content analysis of interviews, the results lead to several propositions. Specifically, quality and environmental management influence hotel performance through mediating variables. Moreover, the implementation of quality management facilitates the implementation of environmental management. Furthermore, the implementation of these two management systems is associated with an increase of formalization and decentralization. The paper contributes to the analysis of quality management, environmental management, organizational design and performance in a joint manner, which has not been attempted before in the hotel industry. In addition, it helps extend the findings about these links in manufacturing and service organizations to the hotel industry.

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The construction industry has long been considered as highly fragmented and non-collaborative industry. This fragmentation sprouted from complex and unstructured traditional coordination processes and information exchanges amongst all parties involved in a construction project. This nature coupled with risk and uncertainty has pushed clients and their supply chain to search for new ways of improving their business process to deliver better quality and high performing product. This research will closely investigate the need to implement a Digital Nervous System (DNS), analogous to a biological nervous system, on the flow and management of digital information across the project lifecycle. This will be through direct examination of the key processes and information produced in a construction project and how a DNS can provide a well-integrated flow of digital information throughout the project lifecycle. This research will also investigate how a DNS can create a tight digital feedback loop that enables the organisation to sense, react and adapt to changing project conditions. A Digital Nervous System is a digital infrastructure that provides a well-integrated flow of digital information to the right part of the organisation at the right time. It provides the organisation with the relevant and up-to-date information it needs, for critical project issues, to aid in near real-time decision-making. Previous literature review and survey questionnaires were used in this research to collect and analyse data about information management problems of the industry – e.g. disruption and discontinuity of digital information flow due to interoperability issues, disintegration/fragmentation of the adopted digital solutions and paper-based transactions. Results analysis revealed efficient and effective information management requires the creation and implementation of a DNS.

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Frequently, population ecology of marine organisms uses a descriptive approach in which their sizes and densities are plotted over time. This approach has limited usefulness for design strategies in management or modelling different scenarios. Population projection matrix models are among the most widely used tools in ecology. Unfortunately, for the majority of pelagic marine organisms, it is difficult to mark individuals and follow them over time to determine their vital rates and built a population projection matrix model. Nevertheless, it is possible to get time-series data to calculate size structure and densities of each size, in order to determine the matrix parameters. This approach is known as a “demographic inverse problem” and it is based on quadratic programming methods, but it has rarely been used on aquatic organisms. We used unpublished field data of a population of cubomedusae Carybdea marsupialis to construct a population projection matrix model and compare two different management strategies to lower population to values before year 2008 when there was no significant interaction with bathers. Those strategies were by direct removal of medusae and by reducing prey. Our results showed that removal of jellyfish from all size classes was more effective than removing only juveniles or adults. When reducing prey, the highest efficiency to lower the C. marsupialis population occurred when prey depletion affected prey of all medusae sizes. Our model fit well with the field data and may serve to design an efficient management strategy or build hypothetical scenarios such as removal of individuals or reducing prey. TThis This sdfsdshis method is applicable to other marine or terrestrial species, for which density and population structure over time are available.

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In this study, a methodology based in a dynamical framework is proposed to incorporate additional sources of information to normalized difference vegetation index (NDVI) time series of agricultural observations for a phenological state estimation application. The proposed implementation is based on the particle filter (PF) scheme that is able to integrate multiple sources of data. Moreover, the dynamics-led design is able to conduct real-time (online) estimations, i.e., without requiring to wait until the end of the campaign. The evaluation of the algorithm is performed by estimating the phenological states over a set of rice fields in Seville (SW, Spain). A Landsat-5/7 NDVI series of images is complemented with two distinct sources of information: SAR images from the TerraSAR-X satellite and air temperature information from a ground-based station. An improvement in the overall estimation accuracy is obtained, especially when the time series of NDVI data is incomplete. Evaluations on the sensitivity to different development intervals and on the mitigation of discontinuities of the time series are also addressed in this work, demonstrating the benefits of this data fusion approach based on the dynamic systems.

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One of the most relevant subjects for the intellectual formation of elementary school students is Mathematics where its importance goes back to ancient civilizations and which its importance is underestimated nowadays. This phenomenon occurs in Mexico, where 63.1% of the total population of elementary school students between the third and sixth grade have insufficient/elemental level of mathematics knowledge. This has resulted in the need to use a new mechanism to complement student’s classroom learning. With the rapid growth of wireless and mobile technologies, the mobile learning has been gradually considered as a novel and effective form of learning due to it inherits all the advantages of e-learning as well as breaks the limitations of learning time and space occurring in the traditional classroom teaching. This project proposes the use of a Mathematics Game e-Library integrated by a set of games for mobile devices and a distribution/management tool. The games are developed for running on mobile devices and for cover the six competencies related with the mathematics learning approach established in Mexico. The distribution/management tool allows students to reach contents according to their needs; this is achieved through a core engine that infers, from an initial profile, the games that cover the user’s knowledge gaps.

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The present is marked by the availability of large volumes of heterogeneous data, whose management is extremely complex. While the treatment of factual data has been widely studied, the processing of subjective information still poses important challenges. This is especially true in tasks that combine Opinion Analysis with other challenges, such as the ones related to Question Answering. In this paper, we describe the different approaches we employed in the NTCIR 8 MOAT monolingual English (opinionatedness, relevance, answerness and polarity) and cross-lingual English-Chinese tasks, implemented in our OpAL system. The results obtained when using different settings of the system, as well as the error analysis performed after the competition, offered us some clear insights on the best combination of techniques, that balance between precision and recall. Contrary to our initial intuitions, we have also seen that the inclusion of specialized Natural Language Processing tools dealing with Temporality or Anaphora Resolution lowers the system performance, while the use of topic detection techniques using faceted search with Wikipedia and Latent Semantic Analysis leads to satisfactory system performance, both for the monolingual setting, as well as in a multilingual one.

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In this paper, parallel Relaxed and Extrapolated algorithms based on the Power method for accelerating the PageRank computation are presented. Different parallel implementations of the Power method and the proposed variants are analyzed using different data distribution strategies. The reported experiments show the behavior and effectiveness of the designed algorithms for realistic test data using either OpenMP, MPI or an hybrid OpenMP/MPI approach to exploit the benefits of shared memory inside the nodes of current SMP supercomputers.

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Business Intelligence (BI) applications have been gradually ported to the Web in search of a global platform for the consumption and publication of data and services. On the Internet, apart from techniques for data/knowledge management, BI Web applications need interfaces with a high level of interoperability (similar to the traditional desktop interfaces) for the visualisation of data/knowledge. In some cases, this has been provided by Rich Internet Applications (RIA). The development of these BI RIAs is a process traditionally performed manually and, given the complexity of the final application, it is a process which might be prone to errors. The application of model-driven engineering techniques can reduce the cost of development and maintenance (in terms of time and resources) of these applications, as they demonstrated by other types of Web applications. In the light of these issues, the paper introduces the Sm4RIA-B methodology, i.e., a model-driven methodology for the development of RIA as BI Web applications. In order to overcome the limitations of RIA regarding knowledge management from the Web, this paper also presents a new RIA platform for BI, called RI@BI, which extends the functionalities of traditional RIAs by means of Semantic Web technologies and B2B techniques. Finally, we evaluate the whole approach on a case study—the development of a social network site for an enterprise project manager.

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The organocatalytic activities of highly substituted proline esters obtained through asymmetric [3+2] cycloadditions of azomethine ylides derived from glycine iminoesters have been analyzed by 19F NMR and through kinetic isotope effects. Kinetic rate constants have been determined for unnatural proline esters incorporating different substituents. It has been found that exo-L and endo-L unnatural proline methyl esters yield opposite enantiomers in aldol reactions between cyclic ketones and aromatic aldehydes. The combined results reported in this study show subtle and remote effects that determine the organocatalytic behavior of these synthetic but readily available amino acid derivatives. These data can be used as design criteria for the development of new pyrrolidine-based organocatalysts.

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Background: Despite the existence of ample literature dealing, on the one hand, with the integration of innovations within health systems and team learning, and, on the other hand, with different aspects of the detection and management of intimate partner violence (IPV) within healthcare facilities, research that explores how health innovations that go beyond biomedical issues—such as IPV management—get integrated into health systems, and that focuses on healthcare teams’ learning processes is, to the best of our knowledge, very scarce if not absent. This realist evaluation protocol aims to ascertain: why, how, and under what circumstances primary healthcare teams engage (if at all) in a learning process to integrate IPV management in their practices; and why, how, and under what circumstances team learning processes lead to the development of organizational culture and values regarding IPV management, and the delivery of IPV management services. Methods: This study will be conducted in Spain using a multiple-case study design. Data will be collected from selected cases (primary healthcare teams) through different methods: individual and group interviews, routinely collected statistical data, documentary review, and observation. Cases will be purposively selected in order to enable testing the initial middle-range theory (MRT). After in-depth exploration of a limited number of cases, additional cases will be chosen for their ability to contribute to refining the emerging MRT to explain how primary healthcare learn to integrate intimate partner violence management. Discussion: Evaluations of health sector responses to IPV are scarce, and even fewer focus on why, how, and when the healthcare services integrate IPV management. There is a consensus that healthcare professionals and healthcare teams play a key role in this integration, and that training is important in order to realize changes. However, little is known about team learning of IPV management, both in terms of how to trigger such learning and how team learning is connected with changes in organizational culture and values, and in service delivery. This realist evaluation protocol aims to contribute to this knowledge by conducting this project in a country, Spain, where great endeavours have been made towards the integration of IPV management within the health system.