4 research outputs found

    Air Force Institute of Technology Research Report 2012

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    This report summarizes the research activities of the Air Force Institute of Technology鈥檚 Graduate School of Engineering and Management. It describes research interests and faculty expertise; lists student theses/dissertations; identifies research sponsors and contributions; and outlines the procedures for contacting the school. Included in the report are: faculty publications, conference presentations, consultations, and funded research projects. Research was conducted in the areas of Aeronautical and Astronautical Engineering, Electrical Engineering and Electro-Optics, Computer Engineering and Computer Science, Systems and Engineering Management, Operational Sciences, Mathematics, Statistics and Engineering Physics

    BIM in the construction industry

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    En las 煤ltimas d茅cadas, el t茅rmino modelado de informaci贸n de construcci贸n (BIM) se ha mencionado en una amplia gama de esfuerzos de investigaci贸n de la construcci贸n. BIM es una nueva soluci贸n para la recesi贸n sin precedentes en la industria de la construcci贸n, es decir, p茅rdida de productividad, escasez de mano de obra, sobrecostos y competitividad severa. La tecnolog铆a BIM proporciona muchos beneficios: detecci贸n r谩pida de conflictos de dise帽o, regulaci贸n autom谩tica de dise帽o algoritmo de verificaci贸n, visualizaci贸n de realidad virtual/aumentada y entorno de trabajo de colaboraci贸n. BIM los expertos, as铆 como los profesionales de la industria, enfatizan la importancia de las aplicaciones BIM en el campo de construcci贸n. Dado el r谩pido desarrollo y adopci贸n de BIM en la arquitectura, ingenier铆a, y construcci贸n (AEC), est谩n surgiendo nuevas tendencias relevantes para la investigaci贸n de BIM, siendo sumamente 煤til no s贸lo para los acad茅micos sino tambi茅n para los profesionales.In recent decades, the term building information modeling (BIM) has been mentioned in a wide range of construction research endeavors. BIM is a new solution for unprecedented recession in the construction industry, i.e., productivity loss, labor shortage, cost overrun, and severe competitiveness. BIM technology provides many benefits: prompt design clash detection, automatic deign regulatory check algorithm, augmented/virtual reality visualization, and collaboration work environment. BIM experts as well as industry practitioners are stressing the importance of BIM applications in the field of construction. Given the rapid development and adoption of BIM in the architecture, engineering, and construction (AEC) industry, new trends relevant to the research of BIM are emerging, being exceedingly helpful not only for academics but also for practitioners

    Design and Experimental Evaluation of a Hybrid Wheeled-Leg Exploration Rover in the Context of Multi-Robot Systems

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    With this dissertation, the electromechanic design, implementation, locomotion control, and experimental evaluation of a novel type of hybrid wheeled-leg exploration rover are presented. The actively articulated suspension system of the rover is the basis for advanced locomotive capabilities of a mobile exploration robot. The developed locomotion control system abstracts the complex kinematics of the suspension system and provides platform control inputs usable by autonomous behaviors or human remote control. Design and control of the suspension system as well as experimentation with the resulting rover are in the focus of this thesis. The rover is part of a heterogeneous modular multi-robot exploration system with an aspired sample return mission to the lunar south pole or currently hard-to-access regions on Mars. The multi-robot system pursues a modular and reconfigurable design methodology. It combines heterogeneous robots with different locomotion capabilities for enhanced overall performance. Consequently, the design of the multi-robot system is presented as the frame of the rover developments. The requirements for the rover design originating from the deployment in a modular multi-robot system are accentuated and summarized in this thesis

    Personality Identification from Social Media Using Deep Learning: A Review

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    Social media helps in sharing of ideas and information among people scattered around the world and thus helps in creating communities, groups, and virtual networks. Identification of personality is significant in many types of applications such as in detecting the mental state or character of a person, predicting job satisfaction, professional and personal relationship success, in recommendation systems. Personality is also an important factor to determine individual variation in thoughts, feelings, and conduct systems. According to the survey of Global social media research in 2018, approximately 3.196 billion social media users are in worldwide. The numbers are estimated to grow rapidly further with the use of mobile smart devices and advancement in technology. Support vector machine (SVM), Naive Bayes (NB), Multilayer perceptron neural network, and convolutional neural network (CNN) are some of the machine learning techniques used for personality identification in the literature review. This paper presents various studies conducted in identifying the personality of social media users with the help of machine learning approaches and the recent studies that targeted to predict the personality of online social media (OSM) users are reviewed
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