4 resultados para Issues for Managing Tourism Information

em Universitätsbibliothek Kassel, Universität Kassel, Germany


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Presentation at the 1997 Dagstuhl Seminar "Evaluation of Multimedia Information Retrieval", Norbert Fuhr, Keith van Rijsbergen, Alan F. Smeaton (eds.), Dagstuhl Seminar Report 175, 14.04. - 18.04.97 (9716). - Abstract: This presentation will introduce ESCHER, a database editor which supports visualization in non-standard applications in engineering, science, tourism and the entertainment industry. It was originally based on the extended nested relational data model and is currently extended to include object-relational properties like inheritance, object types, integrity constraints and methods. It serves as a research platform into areas such as multimedia and visual information systems, QBE-like queries, computer-supported concurrent work (CSCW) and novel storage techniques. In its role as a Visual Information System, a database editor must support browsing and navigation. ESCHER provides this access to data by means of so called fingers. They generalize the cursor paradigm in graphical and text editors. On the graphical display, a finger is reflected by a colored area which corresponds to the object a finger is currently pointing at. In a table more than one finger may point to objects, one of which is the active finger and is used for navigating through the table. The talk will mostly concentrate on giving examples for this type of navigation and will discuss some of the architectural needs for fast object traversal and display. ESCHER is available as public domain software from our ftp site in Kassel. The portable C source can be easily compiled for any machine running UNIX and OSF/Motif, in particular our working environments IBM RS/6000 and Intel-based LINUX systems. A porting to Tcl/Tk is under way.

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Context awareness, dynamic reconfiguration at runtime and heterogeneity are key characteristics of future distributed systems, particularly in ubiquitous and mobile computing scenarios. The main contributions of this dissertation are theoretical as well as architectural concepts facilitating information exchange and fusion in heterogeneous and dynamic distributed environments. Our main focus is on bridging the heterogeneity issues and, at the same time, considering uncertain, imprecise and unreliable sensor information in information fusion and reasoning approaches. A domain ontology is used to establish a common vocabulary for the exchanged information. We thereby explicitly support different representations for the same kind of information and provide Inter-Representation Operations that convert between them. Special account is taken of the conversion of associated meta-data that express uncertainty and impreciseness. The Unscented Transformation, for example, is applied to propagate Gaussian normal distributions across highly non-linear Inter-Representation Operations. Uncertain sensor information is fused using the Dempster-Shafer Theory of Evidence as it allows explicit modelling of partial and complete ignorance. We also show how to incorporate the Dempster-Shafer Theory of Evidence into probabilistic reasoning schemes such as Hidden Markov Models in order to be able to consider the uncertainty of sensor information when deriving high-level information from low-level data. For all these concepts we provide architectural support as a guideline for developers of innovative information exchange and fusion infrastructures that are particularly targeted at heterogeneous dynamic environments. Two case studies serve as proof of concept. The first case study focuses on heterogeneous autonomous robots that have to spontaneously form a cooperative team in order to achieve a common goal. The second case study is concerned with an approach for user activity recognition which serves as baseline for a context-aware adaptive application. Both case studies demonstrate the viability and strengths of the proposed solution and emphasize that the Dempster-Shafer Theory of Evidence should be preferred to pure probability theory in applications involving non-linear Inter-Representation Operations.

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Water is the very essential livelihood for mankind. The United Nations suggest that each person needs 20-50 litres of water a day to ensure basic needs of drinking, cooking and cleaning. It was also endorsed by the Indian National Water Policy 2002, with the provision that adequate safe drinking water facilities should be provided to the entire population both in urban and in rural areas. About 1.42 million rural habitations in India are affected by chemical contamination. The provision of clean drinking water has been given priority in the Constitution of India, in Article 47 conferring the duty of providing clean drinking water and improving public health standards to the State. Excessive dependence of ground water results in depletion of ground water, water contamination and water borne diseases. Thus, access to safe and reliable water supply is one of the serious concerns in rural water supply programme. Though government takes certain serious steps in addressing the drinking water issues in rural areas, still there is a huge gap between demand and supply. The Draft National Water Policy 2012 also states that Water quality and quantity are interlinked and need to be managed in an integrated manner and with Stakeholder participation. Water Resources Management aims at optimizing the available natural water flows, including surface water and groundwater, to satisfy competing needs. The World Bank also emphasizes on managing water resources, strengthening institutions, identifying and implementing measures of improving water governance and increasing the efficiency of water use. Therefore stakeholders’ participation is viewed important in managing water resources at different levels and range. This paper attempts to reflect up on portray the drinking water issues in rural India, and highlights the significance of Integrated Water Resource Management as the significant part of Millennium Development Goals, and Stakeholders’ participation in water resources management.

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Web services from different partners can be combined to applications that realize a more complex business goal. Such applications built as Web service compositions define how interactions between Web services take place in order to implement the business logic. Web service compositions not only have to provide the desired functionality but also have to comply with certain Quality of Service (QoS) levels. Maximizing the users' satisfaction, also reflected as Quality of Experience (QoE), is a primary goal to be achieved in a Service-Oriented Architecture (SOA). Unfortunately, in a dynamic environment like SOA unforeseen situations might appear like services not being available or not responding in the desired time frame. In such situations, appropriate actions need to be triggered in order to avoid the violation of QoS and QoE constraints. In this thesis, proper solutions are developed to manage Web services and Web service compositions with regard to QoS and QoE requirements. The Business Process Rules Language (BPRules) was developed to manage Web service compositions when undesired QoS or QoE values are detected. BPRules provides a rich set of management actions that may be triggered for controlling the service composition and for improving its quality behavior. Regarding the quality properties, BPRules allows to distinguish between the QoS values as they are promised by the service providers, QoE values that were assigned by end-users, the monitored QoS as measured by our BPR framework, and the predicted QoS and QoE values. BPRules facilitates the specification of certain user groups characterized by different context properties and allows triggering a personalized, context-aware service selection tailored for the specified user groups. In a service market where a multitude of services with the same functionality and different quality values are available, the right services need to be selected for realizing the service composition. We developed new and efficient heuristic algorithms that are applied to choose high quality services for the composition. BPRules offers the possibility to integrate multiple service selection algorithms. The selection algorithms are applicable also for non-linear objective functions and constraints. The BPR framework includes new approaches for context-aware service selection and quality property predictions. We consider the location information of users and services as context dimension for the prediction of response time and throughput. The BPR framework combines all new features and contributions to a comprehensive management solution. Furthermore, it facilitates flexible monitoring of QoS properties without having to modify the description of the service composition. We show how the different modules of the BPR framework work together in order to execute the management rules. We evaluate how our selection algorithms outperform a genetic algorithm from related research. The evaluation reveals how context data can be used for a personalized prediction of response time and throughput.