Matching medical image data is a key factor for appropriate computer aided diagnosis. For the past several decades, many image processing technologies have been developed and discussed. However, most of the methods ar...
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Matching medical image data is a key factor for appropriate computer aided diagnosis. For the past several decades, many image processing technologies have been developed and discussed. However, most of the methods are only of theoretical interest because the time complexity of the matching methods is too high for realistic handling of huge amounts of existing medical images. This paper presents a parallel processing model for matching huge amounts of MR images. A feature vector of an MR image is defined by professionals specifically in the area of neuroscience. Then a matching algorithm is developed based on matching the feature vectors. The algorithm is shown to be suitable for parallel process, and provides acceptable results. The experiments show that the overhead of synchronizing the parallel process is less significant than the improvement of the overall efficiency.
作者：
Morosan, CristianUniv Houston
Conrad N Hilton Coll Global Hospitality Leadership 4800 Calhoun Rd Houston TX 77204 USA
A critical, yet understudied aspect of generative AI functionality in hotels is consumers' disclosure of personal information, which carries significant risks. By expanding the Extended parallel Process model, thi...
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A critical, yet understudied aspect of generative AI functionality in hotels is consumers' disclosure of personal information, which carries significant risks. By expanding the Extended parallel Process model, this research investigates the role of trust in hotels in impacting consumers' perceptions of threat and coping efficacy. These perceptions, in turn, influence consumers' fear perceptions and drive both adaptive behaviors (e.g., protective action and seeking help) and maladaptive behaviors (e.g., avoidance). Ultimately, the disclosure of personal information is strongly influenced by avoidance and, to some extent, by seeking help behaviors, but not by protective action behaviors. As the first study to examine consumers' disclosure of personal information to generative AI, it extends the literature on processing arguments related to opaque systems like generative AI. Additionally, it provides insightful managerial implications, especially at a time when the hotel industry lacks clear guidance regarding the use of consumers' personal information within generative AI.
The numerical solution of the dense linear complex valued system of equations generated by the method of moments (MoMs) generally proceeds by factoring the impedance matrix into LU decomposition. Depending on availabl...
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The numerical solution of the dense linear complex valued system of equations generated by the method of moments (MoMs) generally proceeds by factoring the impedance matrix into LU decomposition. Depending on available hardware resources, the LU algorithm can be executed either on sequential or parallel computers. A straightforward parallel implementation of LU factorisation does not yield a well distributed workload, and therefore it is the computationally most expensive step of the MoMs process, especially when adapting to the GPU technology. Some performance improvement of LU decomposition can be achieved by applying a hybrid approach to the parallel processing model. In this reported work, the problem of accelerating an out-of-core-like LU solver on a heterogeneous low-cost single GPU/CPU computing platform is addressed. For this, a variable panel-width tuning scheme combined with a hybrid panel-based LU decomposition method is employed, which is something of a novelty in the development of dense linear algebra software. To demonstrate the efficiency of the proposed approach some numerical results are provided.
This paper deals with the functional correlates of the gamma response of the brain. A critical review of the literature findings reveals the existence of two types of gamma responses: an early gamma that fulfills sens...
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This paper deals with the functional correlates of the gamma response of the brain. A critical review of the literature findings reveals the existence of two types of gamma responses: an early gamma that fulfills sensory functions and a late gamma that fulfills perceptual-cognitive functions. However, even the early gamma shows individual differences. Such a finding points to the existence of top-down influences on sensory processes and to a parallel-processingmodel for brain function. (C) 2001 Elsevier Science B.V. All rights reserved.
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