We propose the new framework of the distributed tabu search metaheuristic designed to be executed using a multi-GPU cluster, i.e. cluster of nodes equipped with GPU computing units. We propose a hybrid single-walk par...
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We propose the new framework of the distributed tabu search metaheuristic designed to be executed using a multi-GPU cluster, i.e. cluster of nodes equipped with GPU computing units. We propose a hybrid single-walk parallelization of the tabu search, where hybridization consists in examining a number of solutions from a neighborhood concurrently by several GPUs (multi-GPU). The methodology is designed to solve the flexible job shop scheduling problem, diffcult problem of discrete optimization.
Currently, unmanned aerial vehicles (UAVs) are applied to routine inspection tasks of electric distribution networks. As an important information source, machine vision attracts much attention in the area of the UAV...
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ISBN:
(纸本)9781467316439
Currently, unmanned aerial vehicles (UAVs) are applied to routine inspection tasks of electric distribution networks. As an important information source, machine vision attracts much attention in the area of the UAV's autonomous control. To this end, real-time algorithms are studied-in this paper to detect the power lines in the UAV video images. First, video images are converted into binary images through an adaptive thresholding approach. Then, Hough Transform is used to detect line candidates in the binary images. Finally, a fuzzy C- means (FCM) clustering algorithm is used to discriminate the power lines from the detected line candidates. The properties of power lines are used to remove the spurious lines, and the length and slope of the detected lines are used as features to establish the clustering data set. Experimental results show that the algorithms proposed are effective and able to tolerate noises from complicated terrain background and various illuminations.
This paper extends the RAS-based approach to conflict resolution in multi-vehicle systems presented in Reveliotis and Roszkowska (2008). Similar to that earlier work, the employed model assumes the tesselation of the ...
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Information sharing, exchanging and archiving is the backbone of any organized activity, regardless if it is performed in the sphere of business, home or administration. Semantic Web technologies allow controlling the...
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The paper introduces accuracy boosting extension to a novel induction of fuzzy rules from raw data using Artificial Immune System methods. Accuracy boosting relies on fuzzy partition learning. The performance, in term...
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The paper introduces accuracy boosting extension to a novel induction of fuzzy rules from raw data using Artificial Immune System methods. Accuracy boosting relies on fuzzy partition learning. The performance, in terms of classification accuracy, of the proposed approach was compared with traditional classifier schemes: C4.5, Naïve Bayes, K, Meta END, JRip, and Hyper Pipes. The result accuracy of these methods are significantly lower than accuracy of fuzzy rules obtained by method presented in this study (paired t-test, P
Our aim is to propose an extension of nD systems by treating uncertain parameters of a system as additional independent variables. We recall known results on deriving equations for the sensitivity of the system state ...
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In the paper we want to present a problem of path following for nonholonomic mobile manipulators. In our consideration we restrict ourself to doubly nonholonomic mobile manipulators. Nonholonomic constraints appear du...
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This paper compares two methodologically different approaches to gene set analysis applied for selection of features for sample classification based on microarray studies. We analyze competitive and self-contained met...
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In this work we use the Fourier expansion to characterize and model many-core processor workloads for the purpose of computing accurate predictions of individual core thermal statuses. We demonstrate, that even if the...
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This paper focuses on the theoretical aspects of clustering in wireless sensor networks, as a mean to improve network lifetime. We investigate whether clustering itself (with no data aggregation) can improve network l...
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ISBN:
(纸本)9781424487042
This paper focuses on the theoretical aspects of clustering in wireless sensor networks, as a mean to improve network lifetime. We investigate whether clustering itself (with no data aggregation) can improve network lifetime in particular application when compared to non-clustered networks. We use integer linear programming to analyse 1D and 2D networks, taking into account capabilities of real-life nodes. Our results show that clustering itself cannot improve network lifetime so additional techniques and means are required to be used in synergy with clustering.
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