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- 저자 : Hao Yuan (검색결과 186 건)
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Mobile Cloud Computation Offloading Switch Based on Decision Value Model
Hao.Yuan,Changbing. Li,Maokang. Du 보안공학연구지원센터 2016 International Journal of Hybrid Information Techno Vol.9 No.9
A method had been constructed for mobile cloud computation offloading switch based on decision value model. In this method, two important ratios had been built: one is the calculation ratio which are offloaded on a proxy server completed tasks time and at the mobile node completed tasks time. Another is the calculation ratio which is offloaded on proxy server completed tasks energy and at the mobile node completed tasks energy. And then, decision value function was produced by combining with these two ratios. Finally, consider the optimization switch problem of computing tasks between different proxy servers. Experimental results show that the proposed method has a smaller time consumption and energy consumption by comparing with random offloading switch and minimum time-based offloading switch, and battery remaining of mobile node can be used rationally.
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HAO YUAN,MAYANK-KUMAR GOLPELWAR 서울대학교 사회발전연구소 2012 Journal of Asian Sociology Vol.41 No.1
Based on an empirical survey in Shanghai, this study tests the effects of four domains of social quality (SQ) viz. economic security, social inclusion, social cohesion, and social empowerment on subjective well-being (SWB). The results show that home ownership and income are important determinants of SWB, though the latter is not as strong a predictor of SWB as the former. Apart from the economic determinants, social cohesion (e.g., political trust) as well as social inclusion (e.g., involvement with social and cultural organizations) can influence peoples SWB to a high degree. Additionally, social alienation and loneliness are negatively related to SWB. Even the degree to which people can express themselves freely relates directly to their SWB level. Results also show that the more people see success as a result of self-effort, the higher their SWB level.
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Hao Yuan,Ximei Zhao 제어·로봇·시스템학회 2023 International Journal of Control, Automation, and Vol.21 No.1
This article presents a novel precision synchronization control method and corresponding control design using adaptive jerk control (AJC) with parameter estimation to improve the synchronous performance for gantry servo system with parametric variations and unknown disturbances. Initially, cross-coupled control (CCC) is provided to realize the synchronous cooperation of two parallel permanent magnet linear synchronous motors (PMLSMs), and the coupled system model is transformed into a state-space form. Consequently, the filtered errors based on synchronous error and position tracking error are established to simultaneously guarantee that both the synchronous error and position tracking error converge to zero asymptotically. Then, AJC is proposed to handle the uncertainty. More specifically, an adaptive feedback gain is involved in the AJC for improving the robustness, without requiring a priori knowledge of the uncertainty. A novel adaptation law is introduced to update the adaptive feedback gain. Moreover, a terminal attractor is incorporated into the adaptation law to improve the convergence even with noise. Therefore, the chattering phenomenon are significantly alleviated. Meanwhile, parameter estimation is employed to address the model parametric variations. Experimental results demonstrate the efficiency and superior performance of the precision synchronization control method.
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Yuan Hao,Li Fupeng,Bai Wenyuan,Chen Wei,Zhang Zhen 대한전기학회 2024 Journal of Electrical Engineering & Technology Vol.19 No.8
Power grid resource planning is the key link of stable power supply and the important engine of smart grid system construction. The same source maintenance of power grid resources is a heavy systematic work, including line loss calculation, load rate analysis, geographical survey, grid optimization and a large number of plates. The project volume is large, and data processing is diffi cult. Aiming at the problem that there may be a lack of data information in the multi-modal data of the same source of power grid resources, an algorithm for disambiguation model is proposed. Based on the idea of multi-instance multi-label learning, the method transforms the multi-modal data of complex objects into multi-modal multi-instance form so that each modal data of an object can be regarded as a package, which is composed of multiple instances. The consistency between diff erent modal data packages of the same object is met so as to eliminate the infl uence caused by the inconsistency between modal examples. According to the multi-marker prediction task of power grid resources, the M3DN is used to propose a method using the correlation between markers based on the optimal transmission theory to improve the accuracy of prediction and mine more hidden relationships between markers. In the experimental analysis, a variety of algorithms are used to compare with the content of this paper. The experimental results show that the performance of this algorithm is 2.5% ahead of other methods in the benchmark data set. The density of data mining is better than other algorithms, and the eff ectiveness of interaction matrix is 5% higher than other methods. This study has a certain theoretical and practical engineering application value. It is of great signifi cance to improve the effi ciency of power data homologous maintenance, operation and maintenance. It enhances the level of power grid resource integration, and better serves the smart grid business.
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Cellular Particle Swarm Scheduling Algorithm for Virtual Resource Scheduling of Cloud Computing
Hao Yuan,Changbing Li,Maokang Du 보안공학연구지원센터 2015 International Journal of Grid and Distributed Comp Vol.8 No.3
The virtual resource scheduling is an important topic in the field of cloud computing. Based on particle swarm scheduling algorithm, this paper introduces cellular automata theory to construct a new cellular particle swarm scheduling algorithm. This approach through mathematical modeling for virtual resource scheduling of cloud computing and complete the final search configuration based on directional optimization objective function. Experimental results show that the proposed method has more excellent scheduling performance, in the case of changes in resources, can be also kept stable scheduling balance.
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Yuan-Hao Chen,Yung-Hsiao Chiang,Hsin-I Ma 대한신경과학회 2014 Journal of Clinical Neurology Vol.10 No.2
Background and Purpose Hypoxia, or ischemia, is a common cause of neurological deficits in the elderly. This study elucidated the mechanisms underlying ischemia-induced brain injury that results in neurological sequelae. Methods Cerebral ischemia was induced in male Sprague-Dawley rats by transient ligationof the left carotid artery followed by 60 min of hypoxia. A two-dimensional differential proteome analysis was performed using matrix-assisted laser desorption ionization-time-of-flightmass spectrometry to compare changes in protein expression on the lesioned side of the cortexrelative to that on the contralateral side at 0, 6, and 24 h after ischemia. Results The expressions of the following five proteins were up-regulated in the ipsilateralcortex at 24 h after ischemia-reperfusion injury compared to the contralateral (i.e., control)side: aconitase 2, neurotensin-related peptide, hypothetical protein XP-212759, 60-kDa heatshock protein, and aldolase A. The expression of one protein, dynamin-1, was up-regulatedonly at the 6-h time point. The level of 78-kDa glucose-regulated protein precursor on the lesioned side of the cerebral cortex was found to be high initially, but then down-regulated by 24 hafter the induction of ischemia-reperfusion injury. The expressions of several metabolic enzymes and translational factors were also perturbed soon after brain ischemia. Conclusions These findings provide insights into the mechanisms underlying the neurodegenerative events that occur following cerebral ischemia.
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