143 resultados para Hybrid reality
Resumo:
Over the past few years a number of research studies, mainly involving desktop-based or head-mounted Virtual Reality (VR) systems, have been undertaken to determine what VR can contribute to the education process. In our study we have used the findings from a number of these studies to help in formulating a new study into the perceived merits and limitations of using VR in general, and immersive CAVE-like systems in particular, as an education tool. We conducted our study with a group of final year undergraduate students who were registered on a module that described VR in terms of the scientific issues, application areas, and strengths and weaknesses of the technology.
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One of the essential needs to implement a successful e-Government web application is security. Web application firewalls (WAF) are the most important tool to secure web applications against the increasing number of web application attacks nowadays. WAFs work in different modes depending on the web traffic filtering approach used, such as positive security mode, negative security mode, session-based mode, or mixed modes. The proposed WAF, which is called (HiWAF), is a web application firewall that works in three modes: positive, negative and session based security modes. The new approach that distinguishes this WAF among other WAFs is that it utilizes the concepts of Artificial Intelligence (AI) instead of regular expressions or other traditional pattern matching techniques as its filtering engine. Both artificial neural networks and fuzzy logic concepts will be used to implement a hybrid intelligent web application firewall that works in three security modes.
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Post Traumatic Stress Disorder (PTSD) is reported to be caused by traumatic events that are outside the range of usual human experience including (but not limited to) military combat, violent personal assault, being kidnapped or taken hostage and terrorist attacks. Initial data suggests that at least 1 out of 6 Iraq War veterans are exhibiting symptoms of depression, anxiety and PTSD. Virtual Reality (VR) delivered exposure therapy for PTSD has been used with reports of positive outcomes. The aim of the current paper is to present the rationale and brief description of a Virtual Iraq PTSD VR therapy application and present initial findings from its use with PTSD patients. Thus far, Virtual Iraq consists of a series of customizable virtual scenarios designed to represent relevant Middle Eastern VR contexts for exposure therapy, including a city and desert road convoy environment. User-centered design feedback needed to iteratively evolve the system was gathered from returning Iraq War veterans in the USA and from a system deployed in Iraq and tested by an Army Combat Stress Control Team. Results from an open clinical trial at San Diego Naval Medical Center of the first 18 treatment completers indicate that 14 no longer meet PTSD diagnostic criteria at post-treatment, with only one not maintaining treatment gains at 3 month follow-up. Clinical tests are also currently underway at Ft. Lewis, Emory University, Weill Cornell Medical College, Walter Reed Army Medical Center and 10 other sites. Other sites are preparing to use the application for a variety of PTSD and VR research purposes.
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In this work a hybrid technique that includes probabilistic and optimization based methods is presented. The method is applied, both in simulation and by means of real-time experiments, to the heating unit of a Heating, Ventilation Air Conditioning (HVAC) system. It is shown that the addition of the probabilistic approach improves the fault diagnosis accuracy.
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The proceedings of the conference
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The proceedings of the conference
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In this paper we consider hybrid (fast stochastic approximation and deterministic refinement) algorithms for Matrix Inversion (MI) and Solving Systems of Linear Equations (SLAE). Monte Carlo methods are used for the stochastic approximation, since it is known that they are very efficient in finding a quick rough approximation of the element or a row of the inverse matrix or finding a component of the solution vector. We show how the stochastic approximation of the MI can be combined with a deterministic refinement procedure to obtain MI with the required precision and further solve the SLAE using MI. We employ a splitting A = D – C of a given non-singular matrix A, where D is a diagonal dominant matrix and matrix C is a diagonal matrix. In our algorithm for solving SLAE and MI different choices of D can be considered in order to control the norm of matrix T = D –1C, of the resulting SLAE and to minimize the number of the Markov Chains required to reach given precision. Further we run the algorithms on a mini-Grid and investigate their efficiency depending on the granularity. Corresponding experimental results are presented.