T-overlap query is the basis of set similarity query and has been applied in many important fields. Most existing approaches employ a pruning-and-verification framework, thus in low efficiency. Modern GPU has much hig...
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T-overlap query is the basis of set similarity query and has been applied in many important fields. Most existing approaches employ a pruning-and-verification framework, thus in low efficiency. Modern GPU has much higher parallelism as well as memory bandwidth than CPU and can be used to accelerate T-overlap query. In this paper, we use hash segmentation to divide inverted lists into segments, then design an efficient inverted index called GHSII on GPU using hash segmentation. Based on GHSII, a new segmentation parallel T-overlap algorithm, GSPS, is proposed. GSPS uses segment at a time to scan segments and uses shared memory to decrease the number of accesses to device memory. Furthermore, an optimized algorithm called GSPS-TLLO using a heuristic query order is proposed to solve the problem of load *** are carried out on two real datasets and the results show that GSPS-TLLO outperforms the state-of-the-art GPU parallel T-overlap algorithms.
Focusing on the background of utilizing magnetic compass in the air-ground amphibious robot system,this paper explores error compensation of magnetic compass in the process of moving on the ground and the *** on the e...
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ISBN:
(纸本)9781509009107
Focusing on the background of utilizing magnetic compass in the air-ground amphibious robot system,this paper explores error compensation of magnetic compass in the process of moving on the ground and the *** on the error analysis on the air-ground amphibious robot magnetic compass,this paper applies the ellipsoid fitting algorithm for error identification of this model coefficient and thus calibration of magnetic compass is realized in the ***,through the processing of three sets of data together with the comparison of the traditional empirical Calibration methods,the effectiveness of the proposed method is verified.
In this paper, we address the control problem of an uncertain robotic manipulator with input saturations, unknown input scalings and disturbances. For this purpose, a model reference adaptive control like （MRAC-like...
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In this paper, we address the control problem of an uncertain robotic manipulator with input saturations, unknown input scalings and disturbances. For this purpose, a model reference adaptive control like （MRAC-like） is used to handle the input saturations. The model reference is input to state stable （ISS） and driven by the errors between the required control signals and input saturations. The uncertain parameters are dealt with by using linear-in-the-parameters property of robotic dynamics, while unknown input scalings and disturbances are handled by non-regressor based approach. Our design ensures that all the signals in the closed-loop system are bounded, and the tracking error converges to the compact set which depends on the predetermined bounds of the control inputs. Simulation on a planar elbow manipulator with two joints is provided to illustrate the effectiveness of the proposed controller.
In this paper, we discuss a possible navigation solution for two autonomous marine robots, of which one is submerged. The situation is a sub task of the overall mission scenario of a recent research project. The goal ...
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In previous work on joint multiple point sets registration, the multiple point sets are often formulated by a Gaussian mixture model (GMM) and the registration is then cast to a clustering problem, which aims to explo...
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In previous work on joint multiple point sets registration, the multiple point sets are often formulated by a Gaussian mixture model (GMM) and the registration is then cast to a clustering problem, which aims to exploit global relationships on the multiple point sets. However, local relationships on the multiple point sets are ignored in the state-of-the-art joint multiple point sets registration techniques. In this paper, the multiple point sets are assumed to be generated from a GMM. Local features of the multiple point sets, such as shape context, are proposed to infer the membership probabilities of the GMM. The problem of joint multiple point sets registration can be performed by maximum likelihood of the GMM. The parameters of GMM and registration are estimated by an expectation maximization algorithm. Comprehensive experiments demonstrate that our proposed method has better performance than the state-of-the-art methods.
Medium voltage drives (MVDs) are commonly used in high-power applications and show significant impact on the overall system dynamics due to their large size and high power demand. Although detailed switching models fo...
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To solve the false correlation caused by negative influence in selecting opinion leader, a micro-blog opinion leader selection method using emotional contribution model is proposed. When the retweeters and reviewers o...
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To solve the false correlation caused by negative influence in selecting opinion leader, a micro-blog opinion leader selection method using emotional contribution model is proposed. When the retweeters and reviewers of the tracked object is made, there is not all positive content but kinds of contents of negative, thus they are divided into effective influence or ineffective, which means the all contents made by retweeters and reviewers are taken as an emotional contribution model. In the process of object tracking by using emotional contribution model, messages dissemination occurs mostly in the early, so the early spread the greater influence. As the result, when the tracked object has negative forwarding or reply, the proposed method can infer the polarity of emotion based on variant LSTM. Then, we get the effective influence ranking of opinion leader by each object's coverage rate. The experimental results show coverage rate of proposed model has improved 4.9% than the Page Rank algorithm.
In order to solve the scheduling problems of Re-entrant Hybrid Flowshop (RHFS), this paper investigates the mathematical programming model of RHFS, and proposes the wolf pack based algorithm (WPA) as a global optimiza...
In order to solve the scheduling problems of Re-entrant Hybrid Flowshop (RHFS), this paper investigates the mathematical programming model of RHFS, and proposes the wolf pack based algorithm (WPA) as a global optimization method. Multi-Sticking Crape Masking procedure scheduling problems in painting workshop of a bus manufacturing enterprise are of typical features of RHFS. We regard it as an application objective of the proposed algorithm, applying WPA and multiple evolutionary algorithms to solve the problems. The results show that the algorithm can solve re-entrant scheduling problems of hybrid flowshop more effectively compared with other conventional methods.
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