45,013 research outputs found

    EGO: a personalised multimedia management tool

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    The problems of Content-Based Image Retrieval (CBIR) sys- tems can be attributed to the semantic gap between the low-level data representation and the high-level concepts the user associates with images, on the one hand, and the time-varying and often vague nature of the underlying information need, on the other. These problems can be addressed by improving the interaction between the user and the system. In this paper, we sketch the development of CBIR interfaces, and introduce our view on how to solve some of the problems of the studied interfaces. To address the semantic gap and long-term multifaceted information needs, we propose a "retrieval in context" system. EGO is a tool for the management of image collections, supporting the user through personalisation and adaptation. We will describe how it learns from the user's personal organisation, allowing it to recommend relevant images to the user. The recommendation algorithm is detailed, which is based on relevance feedback techniques

    Wearable Computing for Health and Fitness: Exploring the Relationship between Data and Human Behaviour

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    Health and fitness wearable technology has recently advanced, making it easier for an individual to monitor their behaviours. Previously self generated data interacts with the user to motivate positive behaviour change, but issues arise when relating this to long term mention of wearable devices. Previous studies within this area are discussed. We also consider a new approach where data is used to support instead of motivate, through monitoring and logging to encourage reflection. Based on issues highlighted, we then make recommendations on the direction in which future work could be most beneficial

    Troping the Enemy: Metaphor, Culture, and the Big Data Black Boxes of National Security

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    This article considers how cultural understanding is being brought into the work of the Intelligence Advanced Research Projects Activity (IARPA), through an analysis of its Metaphor program. It examines the type of social science underwriting this program, unpacks implications of the agency’s conception of metaphor for understanding so-called cultures of interest, and compares IARPA’s to competing accounts of how metaphor works to create cultural meaning. The article highlights some risks posed by key deficits in the Intelligence Community\u27s (IC) approach to culture, which relies on the cognitive linguistic theories of George Lakoff and colleagues. It also explores the problem of the opacity of these risks for analysts, even as such predictive cultural analytics are becoming a part of intelligence forecasting. This article examines the problem of information secrecy in two ways, by unpacking the opacity of “black box,” algorithm-based social science of culture for end users with little appreciation of their potential biases, and by evaluating the IC\u27s nontransparent approach to foreign cultures, as it underwrites national security assessments

    El potencial de la teoría cognitiva en la enseñanza de la contabilidad y auditoría

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    El artículo examina la asimilación de dos conceptos contables complejos: la imagen fiel (TFV) y el valor razonable (FV) en una muestra de estudiantes de Contabilidad Financiera. El objetivo es evaluar la opinión de los estudiantes sobre TFV y FV durante su educación y detectar si las percepciones cambian con su nivel académico y madurez. La metodología utilizada es una encuesta de opinión. Las respuestas obtenidas muestran que los estudiantes consideran que la TFV es un concepto superior a otros principios contables. Además, en el estudio se observa que las respuestas de los estudiantes dependen del nivel académico y la madurez. Por último, se considera que los postulados que establece la teoría cognitiva podrían servir a los instructores en materia de contabilidad y organismos reguladores para mejorar el proceso de aprendizaje así como la calidad de la información financiera.This paper examines the understanding of two complex accounting concepts: true and fair view (TFV) and fair value (FV) by students in Financial Accounting. The correct assimilation of these concepts is assessed as to whether there are differences in concept perception due to academic level and maturity. We use a survey to examine the perception and assimilation of the TFV and FV. The evidence suggests that accounting students consider that TFV is a superior accounting concept over other accounting principles. Additionally, the study identifies a pattern of change depending on the academic level and maturity of the participants. On discovering differences, a proposal is made to use the Cognitive Load Theory (CLT) by standard setters and instructors in accounting and auditing to improve the learning process and the quality of financial information.Ministerio de Innovación y Ciencia DER2009-09539 ECO2010-17463 ECO2010-21627 DER2012-33367 DER2015-67918PConsejería de Educacion y Ciencia Castilla-La Mancha POII10-0134-5011Universidad de Alcalá CCG20014/HUM-03

    Investigating the influence of situations and expectations on user behavior : empirical analyses in human-robot interaction

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    Lohse M. Investigating the influence of situations and expectations on user behavior : empirical analyses in human-robot interaction. Bielefeld (Germany): Bielefeld University; 2010.Social sciences are becoming increasingly important for robotics research as work goes on to enable service robots to interact with inexperienced users. This endeavor can only be successful if the robots learn to interpret the users' behavior reliably and, in turn, provide feedback for the users, which enables them to understand the robot. In order to achieve this goal, the thesis introduces an approach to describe the interaction situation as a dynamic construct with different levels of specificity. The situation concept is the starting point for a model which aims to explain the users' behavior. The second important component of the model is the expectations of the users with respect to the robot. Both the situation and the expectations are shown to be the main determinants of the users' behaviors. With this theoretical background in mind, the thesis examines interactions from a home tour scenario in which a human teaches a robot about rooms and objects within them. To analyze the human expectations and behaviors in this situation, two main novel methods have been developed. In particular, a quantitative method for the analysis of the users' behavior repertoires (speech, gesture, eye gaze, body orientation, etc.) is introduced. The approach focuses on the interaction level, which describes the interplay between the robot and the user. In the second novel method, also the system level is taken into account, which includes the robot components and their interplay. This method serves for a detailed task analysis and helps to identify problems that occur in the interaction. By applying these methods, the thesis contributes to the identification of underlying expectations that allow future behavior of the users to be predicted in particular situations. Knowledge about the users' behavior repertoires serves as a cue for the robot about the state of the interaction and the task the users aim to accomplish. Therefore, it enables robot developers to adapt the interaction models of the components to the situation, actual user expectations, and behaviors. The work provides a deeper understanding of the role of expectations in human-robot interaction and contributes to the interaction and system design of interactive robots

    A Personalized System for Conversational Recommendations

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    Searching for and making decisions about information is becoming increasingly difficult as the amount of information and number of choices increases. Recommendation systems help users find items of interest of a particular type, such as movies or restaurants, but are still somewhat awkward to use. Our solution is to take advantage of the complementary strengths of personalized recommendation systems and dialogue systems, creating personalized aides. We present a system -- the Adaptive Place Advisor -- that treats item selection as an interactive, conversational process, with the program inquiring about item attributes and the user responding. Individual, long-term user preferences are unobtrusively obtained in the course of normal recommendation dialogues and used to direct future conversations with the same user. We present a novel user model that influences both item search and the questions asked during a conversation. We demonstrate the effectiveness of our system in significantly reducing the time and number of interactions required to find a satisfactory item, as compared to a control group of users interacting with a non-adaptive version of the system

    Making intelligent systems team players: Case studies and design issues. Volume 1: Human-computer interaction design

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    Initial results are reported from a multi-year, interdisciplinary effort to provide guidance and assistance for designers of intelligent systems and their user interfaces. The objective is to achieve more effective human-computer interaction (HCI) for systems with real time fault management capabilities. Intelligent fault management systems within the NASA were evaluated for insight into the design of systems with complex HCI. Preliminary results include: (1) a description of real time fault management in aerospace domains; (2) recommendations and examples for improving intelligent systems design and user interface design; (3) identification of issues requiring further research; and (4) recommendations for a development methodology integrating HCI design into intelligent system design
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