617,699 research outputs found

    Search Process as Transitions Between Neural States

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    Search is one of the most performed activities on the World Wide Web. Various conceptual models postulate that the search process can be broken down into distinct emotional and cognitive states of searchers while they engage in a search process. These models significantly contribute to our understanding of the search process. However, they are typically based on self-report measures, such as surveys, questionnaire, etc. and therefore, only indirectly monitor the brain activity that supports such a process. With this work, we take one step further and directly measure the brain activity involved in a search process. To do so, we break down a search process into five time periods: a realisation of Information Need, Query Formulation, Query Submission, Relevance Judgment and Satisfaction Judgment. We then investigate the brain activity between these time periods. Using functional Magnetic Resonance Imaging (fMRI), we monitored the brain activity of twenty-four participants during a search process that involved answering questions carefully selected from the TREC-8 and TREC 2001 Q/A Tracks. This novel analysis that focuses on transitions rather than states reveals the contrasting brain activity between time periods – which enables the identification of the distinct parts of the search process as the user moves through them. This work, therefore, provides an important first step in representing the search process based on the transitions between neural states. Discovering more precisely how brain activity relates to different parts of the search process will enable the development of brain-computer interactions that better support search and search interactions, which we believe our study and conclusions advance

    APPLICATIONS OF GRAPH THEORY FOR REUSE OF MODEL BASED SYSTEMS ENGINEERING DESIGN DATA

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    This dissertation contributes to systems engineering (SE) by introducing and demonstrating a novel graph-based design repository (GBDR) tool. GBDR enables engineers to leverage system design information from a heterogenous set of system models created using multiple model based systems engineering (MBSE) software tools as an integrated body of knowledge. Specifically, the research provides a set of approaches that allow the use of system models described in Systems Modeling Language and Lifecycle Modeling Language as an integrated body of design information. The coalesced body of system design information serves to support concept ideation and analysis within SE. The research accomplishes this by using a graph database to store system model information imported from digital artifacts created by MBSE tools and applying principles from graph theory and semantic web technologies to identify likely connections and equivalent concepts across system models, modeling languages, and metamodels. The research demonstrates that the presented tool can import, store, synthesize, search, display, distribute, and export information from multiple MBSE tools. As a practical demonstration, feasible subsystem design alternatives for a small unmanned aircraft system government reference architecture are identified from within a set of existing system models.OSD CAPECivilian, Office of the Secretary of DefenseApproved for public release. Distribution is unlimited

    ON USING GRAPHICAL MODELS FOR SUPPORTING CONTEXT AWARE INFORMATION RETRIEVAL

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    International audienceIt is well known that with the increasing of information volumes across the Web, it is increasingly difficult for search engines to deal with ambiguous queries. In order to overcome this limit, a key challenge in information retrieval nowadays consists in enhancing an information seeking process with the user's context in order to provide accurate results in response to a user query. The underlying idea is that different users have different backgrounds, preferences and interests when seeking information and so a same query may cover different specific information needs according to who submitted it. This paper investigates the use of graphical models to respond to the challenge of context aware information retrieval. The first contribution consists in using CP-Nets as formalism for expressing qualititative queries. The approach for automatically computing the preference weights is based on the predominance property embedded within such graphs. The second contribution focuses on another aspect of context, namely the user's interests. An influence-diagram based retrieval model is presented as a theoretical support for a personalized retrieval process. Preliminary experimental results using enhanced TREC collections show the effectiveness of our approach

    Adaptive personal information environment based on the semantic web

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    In order to support knowledge workers during their tasks of searching, locating and manipulating information, a system that provides information suitable for a particular user’s needs, and that is also able to facilitate the sharing and reuse information is essential. This paper presents Adaptive Personal Information Environment (a-PIE); a service-oriented framework using Open Hypermedia and Semantic Web technologies to provide an adaptive web-based system. a-PIE models the information structures (data and links), context and behaviour as Fundamental Open Hypermedia Model (FOHM) structures which are manipulated by using the Auld Linky contextual link service. a-PIE provides an information environment that enables users to search an information space based on ontologically defined domain concepts. The users can add and manipulate (delete, comment, etc) interesting data or parts of information structures into their information space, leaving the original published data or information structures unchanged. a-PIE facilitates the shareability and reusability of knowledge according to users’ requirements

    Towards a search engine for functionally appropriate, Web-enabled models and simulations

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 2006.Includes bibliographical references (p. 100-104).New emerging modeling and simulation environments have the potential to provide easy access to design models and simulations on the Internet, much as the World Wide Web (WWW) has provided easy access to information. To support sharing, integration and reuse of web-enabled applications (design models and simulations), a search engine for functionally appropriate/similar models is needed. There are ongoing efforts to develop ontological descriptions for web content and simulation model functionality, where semantics of available services are explicitly represented using a shared knowledge representation of concepts and rules. Simulation publishers are responsible of semantically marking up the interfaces with such ontological annotations. In contrast to such an approach, this work proposes a flexible, implicit, pattern matching solution that does not require any extra annotations to accompany, the models, much as the way current web search engines operate. A learning-through-association, similarity-based approach was developed. It uses only pre-existing low-level information in web-enabled simulation interfaces-such as model and parameters names, parameter units, parameter scale, input/output structure, causality, and documentation - to synthesize templates that become archetypes for functional concepts.(cont.) Then, different interfaces are matched against templates and are classified based on how they are similar to a certain template. Newly found functionally similar interfaces can be merged into the original template, thereby both generalizing the pattern for a functional role and strengthening the most critical aspects of the pattern. This thesis also developed algorithms based on graph theory and pre-defined heuristic attributes similarity metrics. The information from model interfaces is represented using Attributed Relational Graphs (ARG), where nodes represent parameters and arcs represent causality relationships. Templates are represented as Fuzzy Attributed Relational Graphs, which are extended ARGs whose node attributes are fuzzy sets. Then, a bipartite graph-matching algorithm is used to compare graphs and the similarity between an interface and a template. Graph merging algorithm is also designed for template generalization. A prototype implementation of proposed algorithms is developed and applied to a suite of real-life engineering models. Results validate the hypothesis and demonstrated the plausibility of the approach.by Qing Cao.Ph.D

    Γ (Gamma): cloud-based analog circuit design system

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    Includes bibliographical references.2016 Summer.With ever increasing demand for lower power consumption, lower cost, and higher performance, designing analog circuits to meet design specifications has become an increasing challenging task, On one hand, analog circuit designers must have intimate knowledge about the underlining silicon process technology's capability to achieve the desired specifications. On the other hand, they must understand the impact of tweaking circuits to satisfy a given specification on all circuit performance parameters. Analog designers have traditionally learned to tackle design problems with numerous circuit simulations using accurate circuit simulators such as SPICE, and have increasingly relied on trial-and-error approaches to reach a converging point. However, the increased complexity with each generation of silicon technology and high dimensionality of searching for solutions, even for some simple analog circuits, have made trial-and-error approaches extremely inefficient, causing long design cycles and often missed market opportunities. Novel rapid and accurate circuit evaluation methods that are tightly integrated with circuit search and optimization methods are needed to aid design productivity. Furthermore, the current design environment with fully distributed licensing and supporting structures is cumbersome at best to allow efficient and up-to-date support for design engineers. With increasing support and licensing costs, fewer and fewer design centers can afford it. Cloud-based software as a service (SaaS) model provides new opportunities for CAD applications. It enables immediate software delivery and update to customers at very low cost. SaaS tools benefit from fast feedback and sharing channels between users and developers and run on hardware resources tailored and provided for them by software vendors. However, web-based tools must perform in a very short turn-around schedule and be always responsive. A new class of analog design tools is presented in this dissertation. The tools provide effective design aid to analog circuit designers with a dash-board control of many important circuit parameters. Fast and accurate circuit evaluations are achieved using a novel lookup-table transistor models (LUT) with novel built-in features tightly integrated with the search engine to achieve desired speed and accuracy. This enables circuit evaluation time several orders faster than SPICE simulations. The proposed architecture for analog design attempts to break the traditional analog design flow using SPICE based trial-and-error methods by providing designers with useful information about the effects of prior design decisions they have made and potential next steps they can take to meet specifications. Benefiting from the advantages offered by web-hosted architectures, the proposed architecture incorporates SaaS as its operating model. The application of the proposed architecture is illustrated by an analog circuit sizer and optimizer. The Γ (Gamma) sizer and optimizer show how web-based design-decision supporting tool can help analog circuit designers to reduce design time and achieve high quality circuit

    Semantic web service architecture for simulation model reuse

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    COTS simulation packages (CSPs) have proved popular in an industrial setting with a number of software vendors. In contrast, options for re-using existing models seem more limited. Re-use of simulation component models by collaborating organizations is restricted by the same semantic issues however that restrict the inter-organization use of web services. The current representations of web components are predominantly syntactic in nature lacking the fundamental semantic underpinning required to support discovery on the emerging semantic web. Semantic models, in the form of ontology, utilized by web service discovery and deployment architecture provide one approach to support simulation model reuse. Semantic interoperation is achieved through the use of simulation component ontology to identify required components at varying levels of granularity (including both abstract and specialized components). Selected simulation components are loaded into a CSP, modified according to the requirements of the new model and executed. The paper presents the development of ontology, connector software and web service discovery architecture in order to understand how such ontology are created, maintained and subsequently used for simulation model reuse. The ontology is extracted from health service simulation - comprising hospitals and the National Blood Service. The ontology engineering framework and discovery architecture provide a novel approach to inter- organization simulation, uncovering domain semantics and adopting a less intrusive interface between participants. Although specific to CSPs the work has wider implications for the simulation community

    A Nine Month Report on Progress Towards a Framework for Evaluating Advanced Search Interfaces considering Information Retrieval and Human Computer Interaction

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    This is a nine month progress report detailing my research into supporting users in their search for information, where the questions, results or even thei
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