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RISS 인기검색어
- 검색키워드
- 저자 : ( Mohsen Sharifi ) (검색결과 4 건)
- 무료
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Mohsen Sharifi,Morteza Okhovvat 한국전자통신연구원 2012 ETRI Journal Vol.34 No.3
In many applications of wireless sensor actor networks (WSANs) that often run in harsh environments, the reduction of completion times of tasks is highly desired. We present a new time-aware, energy-aware, and starvation-free algorithm called Scate for assigning tasks to actors while satisfying the scalability and distribution requirements of WSANs with semi-automated architecture. The proposed algorithm allows concurrent executions of any mix of small and large tasks and yet prevents probable starvation of tasks. To achieve this, it estimates the completion times of tasks on each available actor and then takes the remaining energies and the current workloads of these actors into account during task assignment to actors. The results of our experiments with a prototyped implementation of Scate show longer network lifetime, shorter makespan of resulting schedules,and more balanced loads on actors compared to when one of the three well-known task-scheduling algorithms,namely, the max-min, min-min, and opportunistic load balancing algorithms, is used. In many applications of wireless sensor actor networks (WSANs) that often run in harsh environments, the reduction of completion times of tasks is highly desired. We present a new time-aware, energy-aware, and starvation-free algorithm called Scate for assigning tasks to actors while satisfying the scalability and distribution requirements of WSANs with semi-automated architecture. The proposed algorithm allows concurrent executions of any mix of small and large tasks and yet prevents probable starvation of tasks. To achieve this, it estimates the completion times of tasks on each available actor and then takes the remaining energies and the current workloads of these actors into account during task assignment to actors. The results of our experiments with a prototyped implementation of Scate show longer network lifetime, shorter makespan of resulting schedules,and more balanced loads on actors compared to when one of the three well-known task-scheduling algorithms,namely, the max-min, min-min, and opportunistic load balancing algorithms, is used.
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An investigation on the supersonic ejectors working with mixture of air and steam
Maziar Shafaee,Mohsen Tavakol,Rouzbeh Riazi,Navid Sharifi 대한기계학회 2015 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.29 No.11
This study evaluated the performance of an ejector using two streams of fluids as suction flow. Three motive flow pressures were consideredwhen investigating ejector performance; the suction flow pressure was assumed to be constant. The suction flow consisted of amixture of air and steam and the mass fraction of air in this mixture varied from 0 to 1. The ejector performance curves were analyzed fordifferent mass fractions of air. The results indicate that variation of the mass fraction of air in the suction flow mixture had a significanteffect on ejector performance. At all motive flow pressures, the ejector entertainment ratio increased as the mass fraction of air in thesuction flow increased. The results also show that the sensitivity of ejector performance to variation in the mass fraction of air in the suctionflow decreases at higher motive flow pressures. An increase in motive flow pressure caused the transition from supersonic to subsonicflow to occur at higher ejector discharge pressures.
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Buckling capacity of uniformly corroded steel members in terms of exposure time
Reza Rahgozar,Yasser Sharifi,Mohsen Malekinejad 국제구조공학회 2010 Steel and Composite Structures, An International J Vol.10 No.6
Most of steel structures in various industries are subjected to corrosion due to environmental exposure. Corrosion damage is a serious problem for these structures which may reduce their carrying capacity. These aging structures require maintenance and in many cases, replacement. The goal of this research is to consider the effects of corrosion by developing a model that estimates corrosion loss as a function of exposure time. The model is formulated based on average measured thickness data collected from three severely corroded I-beams (nearly 30 years old). Since corrosion is a time-dependent parameter. Analyses were performed to calculate the lateral buckling capacity of steel beam in terms of exposure time. Minimum curves have been developed for assessment of the remaining lateral buckling capacity of ordinary I-beams based on the loss of thicknesses in terms of exposure time. These minimum curves can be used by practicing engineers for better estimates on the service life of corrosion damaged steel beams.
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Human Activity Recognition in Smart Homes Based on a Difference of Convex Programming Problem
( Vahid Ghasemi ),( Ali A. Pouyan ),( Mohsen Sharifi ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.1
Smart homes are the new generation of homes where pervasive computing is employed to make the lives of the residents more convenient. Human activity recognition (HAR) is a fundamental task in these environments. Since critical decisions will be made based on HAR results, accurate recognition of human activities with low uncertainty is of crucial importance. In this paper, a novel HAR method based on a difference of convex programming (DCP) problem is represented, which manages to handle uncertainty. For this purpose, given an input sensor data stream, a primary belief in each activity is calculated for the sensor events. Since the primary beliefs are calculated based on some abstractions, they naturally bear an amount of uncertainty. To mitigate the effect of the uncertainty, a DCP problem is defined and solved to yield secondary beliefs. In this procedure, the uncertainty stemming from a sensor event is alleviated by its neighboring sensor events in the input stream. The final activity inference is based on the secondary beliefs. The proposed method is evaluated using a well-known and publicly available dataset. It is compared to four HAR schemes, which are based on temporal probabilistic graphical models, and a convex optimization-based HAR procedure, as benchmarks. The proposed method outperforms the benchmarks, having an acceptable accuracy of 82.61%, and an average F-measure of 82.3%.
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