به نام خدا
Title: An efficient parallel architecture for ray-tracing
Authors: Alexandre S Nery Nadia Nedjah Felipe M G Franca
Abstract: Real time rendering of three-dimensional scenes in high photorealistic details is a hard task, such as in the ray tracing rendering algorithm. In general, the performance achieved by a sequential software-based implementation of ray tracing is far from satisfactory. However, parallel implementations of ray tracing have been enabling reasonable real time performance, as the algorithm is embarrassingly parallel. Thus, a custom parallel design in hardware is likely to achieve an even higher performance. In this paper, we propose a hardware parallel architecture capable of dealing with the main desirable features of ray tracing, such as shadows and reflection effects, imposing low area cost and a promising rendering performance. Such architecture, called Grid RT, is based on the Uniform Grid acceleration structure and is intended to deliver massive parallelism through parallel ray-triangle intersection tests as well as parallel processing of many rays. A hardware implementation of the proposed architecture is presented, together with some performance results and resources requirements. The rendering is reduced by 80% using a grid configuration of eight processing elements.
Publish Year: 2012
Published in: Analog Integrated Circuits and Signal Processing - Journal of Springer
Number of Pages: 14
موضوع: پردازش موازی
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به نام خدا
Title: A Machine Learning-based Usability Evaluation Method for eLearning Systems
Authors: Asil Oztekin, Dursun Delen, Ali Turkyilmaz, Selim Zaim
Abstract: The research presented in this paper proposes a new machine learning-based evaluation method for assessing the usability of eLearning systems. Three machine learning methods (support vector machines, neural networks and decision trees) along with multiple linear regression are used to develop prediction models in order to discover the underlying relationship between the overall eLearning system usability and its predictor factors. A subsequent sensitivity analysis is conducted to determine the rank-order importance of the predictors. Using both sensitivity values along with the usability scores, a metric (called severity index) is devised. By applying a Pareto-like analysis, the severity index values are ranked and the most important usability characteristics are identified. The case study results show that the proposed methodology enhances the determination of eLearning system problems by identifying the most pertinent usability factors. The proposed method could provide an invaluable guidance to the usability experts as to what measures should be improved in order to maximize the system usability for a targeted group of end-users of an eLearning system.
Publish Year: 2013
Published in: Decision Support Systems - Science Direct
Number of Pages: 4
موضوع: یادگیری ماشین (Machine Learning) – آموزش الکترونیک (eLearning)
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به نام خدا
Title: Bluetooth Positioning using RSSI and Triangulation Methods
Authors: Yapeng Wang, Xu Yang Yutian Zhao
Abstract: Location based services are the hottest applications on mobile devices nowadays and the growth is continuing. Indoor wireless positioning is the key technology to enable location based services to work well indoors, where GPS normally could not work. Bluetooth has been widely used in mobile devices like phone, PAD etc. therefore Bluetooth based indoor positioning has great market potential. Radio Signal Strength (RSS) is a key parameter for wireless positioning. New Bluetooth standard (since version 2.1) enables RSS to be discovered without time consuming pre-connection. In this research, general wireless positioning technologies are firstly analysed. Then RSS based Bluetooth positioning using the new feature is studied. The mathematical model is established to analyse the relation between RSS and the distance between two Bluetooth devices. Three distance-based algorithms are used for Bluetooth positioning: Least Square Estimation, Three-border and Centroid Method. Comparison results are analysed and the ways to improve the positioning accuracy are discussed.
Publish Year: 2013
Published in: CCNC - IEEE
Number of Pages: 6
موضوع: بلوتوث
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به نام خدا
Title: Electron repulsion integrals for self-energy calculations
Authors: Y Pavlyukh , J Berakdar
Abstract: A fast algorithm for the calculation of the electron repulsion integrals in an atomic basis is a prerequisite of any ab initio quantum chemistry method. Unlike the case of a self-consistent field (SCF) approach, correlated methods often require a full or partial integral transformation to the molecular basis. The run- time of such an algorithm scales unfavorably as O(N ? where N ? is the number of the basis function, and additionally poses high requirements on the computer memory. The problem is aggravated in the case of large highly symmetric molecules which can only be modeled by fully taking the symmetry into account (as was recently demonstrated by us in J. Chem. Phys. 135 (2011) 201103). Wedescribe here the algorithm for the calculation of the electron repulsion integrals, the transformation and their use in the correlated Green s function approach for systems with icosahedral symmetry.
Publish Year: 2013
Published in: Computer Physics Communications - Science Direct
Number of Pages: 9
موضوع: فیزیک
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به نام خدا
Title: Clustering via geometric median shift over Riemannian manifolds
Authors: Yang Wang, Xiaodi Huang, Lin Wu
Abstract: The mean shift algorithms have been successfully applied to many areas, such as data clustering, feature analysis, and image segmentation. However, they still have two limitations. One is that they are ineffective in clustering data with low dimensional manifolds because of the use of the Euclidean distance for calculating distances. The other is that they some- times produce poor results for data clustering and image segmentation. This is because a mean may not be a point in a data set. In order to overcome the two limitations, we pro- pose a novel approach for the median shift over Riemannian manifolds that uses the geo- metric median and geodesic distances. Unlike the mean, the geometric median of a data set is one of points in the set. Compared to the Euclidean distance, the geodesic distances can better describe data points distributed on Riemannian manifolds. Based on these two facts, we first present a novel density function that characterizes points on a manifold with the geodesic distance. The shift of the geometric median over the Riemannian manifold is derived from maximizing this density function. After this, we present an algorithm for geo- metric median shift over Riemannian manifolds, together with theoretical proofs of its cor- rectness. Extensive experiments have demonstrated that our method outperforms the state-of-the-art algorithms in data clustering, image segmentation, and noise filtering on both synthetic data sets and real image databases.
Publish Year: 2013
Published in: Information Sciences - Science Direct
Number of Pages: 14
موضوع: منیفولد (Manifold )
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