279 research outputs found

    The design and implementation of fuzzy query processing on sensor networks

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    Sensor nodes and Wireless Sensor Networks (WSN) enable observation of the physical world in unprecedented levels of granularity. A growing number of environmental monitoring applications are being designed to leverage data collection features of WSN, increasing the need for efficient data management techniques and for comparative analysis of various data management techniques. My research leverages aspects of fuzzy database, specifically fuzzy data representation and fuzzy or flexible queries to improve upon the efficiency of existing data management techniques by exploiting the inherent uncertainty of the data collected by WSN. Herein I present my research contributions. I provide classification of WSN middleware to illustrate varying approaches to data management for WSN and identify a need to better handle the uncertainty inherent in data collected from physical environments and to take advantage of the imprecision of the data to increase the efficiency of WSN by requiring less information be transmitted to adequately answer queries posed by WSN monitoring applications. In this dissertation, I present a novel approach to querying WSN, in which semantic knowledge about sensor attributes is represented as fuzzy terms. I present an enhanced simulation environment that supports more flexible and realistic analysis by using cellular automata models to separately model the deployed WSN and the underlying physical environment. Simulation experiments are used to evaluate my fuzzy query approach for environmental monitoring applications. My analysis shows that using fuzzy queries improves upon other data management techniques by reducing the amount of data that needs to be collected to accurately satisfy application requests. This reduction in data transmission results in increased battery life within sensors, an important measure of cost and performance for WSN applications

    Big Data Management Challenges, Approaches, Tools and their limitations

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    International audienceBig Data is the buzzword everyone talks about. Independently of the application domain, today there is a consensus about the V's characterizing Big Data: Volume, Variety, and Velocity. By focusing on Data Management issues and past experiences in the area of databases systems, this chapter examines the main challenges involved in the three V's of Big Data. Then it reviews the main characteristics of existing solutions for addressing each of the V's (e.g., NoSQL, parallel RDBMS, stream data management systems and complex event processing systems). Finally, it provides a classification of different functions offered by NewSQL systems and discusses their benefits and limitations for processing Big Data

    An office document retrieval system with the capability of processing incomplete and vague queries

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    TEXPROS (TEXt PROcessing System) is an intelligent document processing system. The system is a combination of filing and retrieval systems, which supports storing, classifying, categorizing, retrieving and reproducing documents, as well as extracting, browsing, retrieving and synthesizing information from a variety of documents. This dissertation presents a retrieval system for TEXPROS, which is capable of processing incomplete or vague queries and providing semantically meaningful responses to the users. The design of the retrieval system is highly integrated with various mechanisms for achieving these goals. First, a system catalog including a thesaurus is used to store the knowledge about the database. Secondly, there is a query transformation mechanism which consists of context construction and algebraic query formulation modules. Given an incomplete query, the context construction module searches the system for the required terms and constructs a query that has a complete representation. The resulting query is then formulated into an algebraic query. Thirdly, in practice, the user may not have a precise notion of what he is looking for. A browsing mechanism is employed for such situations to assist the user in the retrieval process. With the browser, vague queries can be entered into the system until sufficient information is obtained to the extent that the user is able to construct a query for his request. Finally, when processing of queries responds with an empty answer to the user, a query generalization mechanism is used to give the user a cooperative explanation for the empty answer. The generalizations of any given failed queries (i.e., with an empty answer) are derived by applying both the folder and type substitutions and weakening the search criteria in the original query. An efficient way is investigated for determining whether the empty answer is genuine and whether the original query reflects erroneous presuppositions, and therefore answering any failed query with a meaningful and cooperative response. It incorporates with a methodical approach to reducing the search space of generalized subqueries by analyzing the results of executing the query generalization and by efficiently applying the possible substitutions in a query to generate a small subset of relevant subqueries which are to be evaluated

    TravelBuddy: a closed-community carpooling system as a case study for web development with focus on usability, design and infrastructure

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    The Web and the technologies that revolve around it are on a rapid rise. As the use and utilization of Web grows broader, so does the dependency on Web technologies. If a web site aims to survive and mature, in a world where 10.000 web sites per day are published, the web designer/developer must assess the factors associated with Web site success during the development process. While a web site's long-term success is dependant on many factors, this thesis's focus is on its initial development which consists of three interconnected factors; usability, design and responsiveness provided with infrastructure. Usability, design and responsiveness provided with infrastructure are the three primary factors needed to establish a quality and complex web site. While each factor has its own priorities and requirements, they are all dependant on each other. Establishing a balance between these factors are key to success. This thesis will discuss how to utilize the three factors to create a successfull web site. The concluded information will be used with the aid of research on carpooling, to create "TravelBuddy", a closed-community carpooling system prototype. The thesis will also discuss the development process in association with Web site success factors and planned future work

    Data bases and data base systems related to NASA's Aerospace Program: A bibliography with indexes

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    This bibliography lists 641 reports, articles, and other documents introduced into the NASA scientific and technical information system during the period January 1, 1981 through June 30, 1982. The directory was compiled to assist in the location of numerical and factual data bases and data base handling and management systems

    Functional inferences over heterogeneous data

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    Inference enables an agent to create new knowledge from old or discover implicit relationships between concepts in a knowledge base (KB), provided that appropriate techniques are employed to deal with ambiguous, incomplete and sometimes erroneous data. The ever-increasing volumes of KBs on the web, available for use by automated systems, present an opportunity to leverage the available knowledge in order to improve the inference process in automated query answering systems. This thesis focuses on the FRANK (Functional Reasoning for Acquiring Novel Knowledge) framework that responds to queries where no suitable answer is readily contained in any available data source, using a variety of inference operations. Most question answering and information retrieval systems assume that answers to queries are stored in some form in the KB, thereby limiting the range of answers they can find. We take an approach motivated by rich forms of inference using techniques, such as regression, for prediction. For instance, FRANK can answer “what country in Europe will have the largest population in 2021?" by decomposing Europe geo-spatially, using regression on country population for past years and selecting the country with the largest predicted value. Our technique, which we refer to as Rich Inference, combines heuristics, logic and statistical methods to infer novel answers to queries. It also determines what facts are needed for inference, searches for them, and then integrates the diverse facts and their formalisms into a local query-specific inference tree. Our primary contribution in this thesis is the inference algorithm on which FRANK works. This includes (1) the process of recursively decomposing queries in way that allows variables in the query to be instantiated by facts in KBs; (2) the use of aggregate functions to perform arithmetic and statistical operations (e.g. prediction) to infer new values from child nodes; and (3) the estimation and propagation of uncertainty values into the returned answer based on errors introduced by noise in the KBs or errors introduced by aggregate functions. We also discuss many of the core concepts and modules that constitute FRANK. We explain the internal “alist” representation of FRANK that gives it the required flexibility to tackle different kinds of problems with minimal changes to its internal representation. We discuss the grammar for a simple query language that allows users to express queries in a formal way, such that we avoid the complexities of natural language queries, a problem that falls outside the scope of this thesis. We evaluate the framework with datasets from open sources

    Music Encoding Conference Proceedings 2021, 19–22 July, 2021 University of Alicante (Spain): Onsite & Online

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    Este documento incluye los artículos y pósters presentados en el Music Encoding Conference 2021 realizado en Alicante entre el 19 y el 22 de julio de 2022.Funded by project Multiscore, MCIN/AEI/10.13039/50110001103
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