Conjugate Gradient (CG) method is an iterative linear solver which is used by many scientific and engineering applications to solve a linear system of algebraic equations. CG generates a heavy load of computation and ...
详细信息
Conjugate Gradient (CG) method is an iterative linear solver which is used by many scientific and engineering applications to solve a linear system of algebraic equations. CG generates a heavy load of computation and therefore it slows the performance of the applications using it. Parallelizing CG is considered as a way to increase its performance. However, CG suffers from communication dependencies among its divisible loads. Most of the studies to parallelize CG concentrate on parallelizing its matrix-vector multiplication. In this paper, we answer the following questions: 1) what are the divisible loads in the CG, and 2) where is communication involved in the parallel CG. To answer 1), we highlight the different divisible data blocks in CG. To answer 2), we introduce a dependency graph among the different data blocks. We conduct experiments on a parallel CG implementation and evaluate communication cost.
This paper presented a new prediction model for Pressure-Volume-Temperature (PVT) properties based on the recently introduced learning algorithm called Sensitivity Based Linear Learning Method (SBLLM) for two-layer fe...
详细信息
Needle operation is one of the fundamental operations in many surgeries such as acupuncture, liver biopsy and anesthesia. During such procedure, the haptic perception is especially important for surgeons to manipulate...
详细信息
Gaze visualizations represent an effective way for gaining fast insights into eye tracking data. Current approaches do not adequately support eye tracking studies for three-dimensional (3D) virtual environments. Hence...
详细信息
Humancomputer Interaction (HCI) research groups have recently attracted to the issue of emotion or affect especially in the examination of interaction and design. With recent technological advances, human users are ab...
详细信息
Humancomputer Interaction (HCI) research groups have recently attracted to the issue of emotion or affect especially in the examination of interaction and design. With recent technological advances, human users are able to interact with computers in ways which are almost impossible. New modalities for computer interaction with human emotion such as skin conductivity, heart rate, brain signals and physiological signals are emerging. It shows that emotion plays an important role in human communication and interaction, therefore allow people to express emotion beyond the verbal domain. This issue motivates the investigation of two modals of emotional processing in the application of HCI and User Interface Design (UID) areas. The result of this study is directed to the development of an affective interaction design storyboard tool called SCOUT. The paper addresses significant roles of Multimodal Emotional Processing methods for SCOUT, which includes different types of Psychometric usability methods and Physiological emotional processing methods. The application of Psychometrics and Multimodal Emotional Processing are then, analyzed. The results of the analysis revealed that the use of both processing methods would enrich the evaluation of emotion in humancomputer interaction study.
A New Opposition-based Compact Genetic Algorithm with Fluctuation (OFCGA) is proposed to overcome premature convergence of compact genetic algorithm. The key points of OFCGA lie in: 1) the probability vector is fluctu...
详细信息
Epilepsy is caused by sudden flurries of electrochemical activity in the brain, which interrupt the 'conversation' among neurons. Consciousness, memory, sense, speech, mood, movement, and motions can all be af...
详细信息
ISBN:
(纸本)9781424469925;9780769540436
Epilepsy is caused by sudden flurries of electrochemical activity in the brain, which interrupt the 'conversation' among neurons. Consciousness, memory, sense, speech, mood, movement, and motions can all be affected during the one or two minutes that the seizure lasts. Walking, jogging, running and stationary bicycling are particularly safe, but especially "Prayer type yoga exercise" clearly benefits epileptic inhabitants to control epilepsy because it often reduces seizure frequency, relieves depression, decreases social segregation, and promotes cardiac and general health. This paper proposes the study about yoga "Prayer", which is not really an exercise but similar to yoga, helping in controlling of epilepsy and also physically, mentally, spiritually relaxation can also be achieved through this method. Spiritual religious believe and practices have an important impact on both physical and mental health.
From the strong point of XML that allows document owners to describe their documents in their own format, it is difficult to search information if those XML documents use different formats. Moreover, users might not r...
详细信息
ISBN:
(纸本)9781424455690
From the strong point of XML that allows document owners to describe their documents in their own format, it is difficult to search information if those XML documents use different formats. Moreover, users might not retrieve all relevant information from differently formatted XML documents. To allow users to retrieve all relevant results, users need to have as many as queries for all possible formats. SXER (Semantic Ranking for XML Element Recommendation) is an idea to make XML documents easier for searching. It receives XML document as an input, checks all possible semantics for each element, and checks those semantic elements to find which element (word) should be used. The output is a recommendation for each element of input XML document.
In this research, we have extended the use of Kernel Dimensionality Reduction (KDR) in the context of semi supervised learning in particular for micro-array DNA clustering application. We have proposed a new model cal...
详细信息
In this research, we have extended the use of Kernel Dimensionality Reduction (KDR) in the context of semi supervised learning in particular for micro-array DNA clustering application. We have proposed a new model call K-means-KDR for survival analysis which we aimed to improve the genes classification performance and study the dimension of effective subspaces in cancer patient survival analysis. KDR method was extended and combined with the K-means clustering technique, Cox's proportional hazards regression model and log rank test where KDR contributes in gene classification to determine subgroups from the patient's group. Results from the experiments have indicated that our model has outperformed Support Vector Machines (SVM) in gene classification. We also observed that the best value for dimension of effective subspaces (K) for microarray DNA data is between 10%-20% of the total patients.
暂无评论