• Journal of Korea Multimedia Society
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• v.13 no.1
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• pp.30-37
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• 2010

Many embedded real - lime systems have adopted processors supported with dynamic voltage scal-ing(DVS) recently. Power is one of the important metrics for Optimization in the design and operation of embedded real-time systems. We can save considerable energy by using slowdown of processor sup-ported with DVS. In this paper, we improved the previous algorithm at a point of view of time complexity to calculate task slowdown factors for an efficient energy consumption in embedded real-time systems with task synchronization. We grasped the properties of the previous algorithm having $O(n^{2})$ time complexity through mathematical analysis and s simulation. Using its properties we proposed the improved algorithms with O(nlogn) and O(n) time complexity which have the same performance as the previous algorithm has.

• The Journal of Korean Physical Therapy
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• v.29 no.2
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• pp.55-61
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• 2017

Purpose: The purpose of this study was to investigate the effects of a task-oriented upper arm exercise performed in a sitting position on either an unstable support surface or a stable support surface for children with cerebral palsy. Methods: We prospectively evaluated 18 children with cerebral palsy. Eight subjects were randomly assigned to each of the stable and unstable support surface groups. We performed the upper arm exercise three times a week for 6 weeks. To confirm the effects of the intervention, the berg balance scale test, modified functional reaching test (MFRT), timed up and go test (TUG), and Jebsen-Taylor hand function test were conducted before and after the study. Results: Significant differences were observed in MFRT and TUG between the experimental and control groups (p<0.05). In the Jebsen-Taylor hand function test, there were significant differences between the groups for the items picking up small objects, stacking checkers, lifting large light objects, and lifting large heavy objects (p<0.05), but not for writing and stimulation of feeding. Significant differences were observed between the groups in items of card turning, lifting large light objects, and lifting heavy objects. Conclusion: The purpose of this study was to evaluate the effectiveness of a task-oriented upper extremity exercise program for dynamic balance and hand function performed in a sitting position with either stable or unstable support by cerebral palsy patients. There were improvements in the two groups, but performing the exercise while sitting on an unstable support surface had a greater effect on dynamic balance and hand function than exercise while sitting on a stable supporting surface. The results of this study can be used to improve the daily lives of cerebral palsy patients.

• Journal of Internet Computing and Services
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• v.17 no.6
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• pp.103-111
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• 2016

Offloading tasks from mobile devices to available cloud servers were improved since the introduction of the cloudlet. With the implementation of dynamic offloading algorithms, mobile devices can choose the appropriate server for the set of tasks. However, current task distribution approaches do not consider the number of VM, which can be a critical factor in the decision making. This paper proposes a dynamic task distribution on clustered data centers. A proportional VM migration approach is also proposed, where it migrates virtual machines to the cloud servers proportionally according to their allocated CPU, in order to prevent overloading of resources in servers. Moreover, we included the resource capacity of each data center in terms of the maximum CPU in order to improve the migration approach in cloud servers. Simulation results show that the proposed mechanism for task distribution greatly improves the overall performance of the system.

• The KIPS Transactions:PartA
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• v.14A no.6
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• pp.357-362
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• 2007

In distributed systems like cluster systems, in order to get more performance improvement, the initial task placement system precisely estimates and correctly assigns the resource requirement by the process. The resource-based initial job placement scheme needs the prediction of resource usage of a task in order to fit it to the most suitable hosts. However, the wrong prediction of resource usage causes serious performance degradation in dynamic load balancing systems. Therefore, in this paper, to resolve the problem due to the wrong prediction, we propose a new load metric. By the new load metric, the resource-based initial job placement scheme can work without priori knowledge about the type of process. Simulation results show that the dynamic load balancing system using the proposed approach achieves shorter execution times than the conventional approaches.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3663-3679
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• 2020

Scheduling plays a dynamic role in cloud computing in generating as well as in efficient distribution of the resources of each task. The principle goal of scheduling is to limit resource starvation and to guarantee fairness among the parties using the resources. The demand for resources fluctuates dynamically hence the prearranging of resources is a challenging task. Many task-scheduling approaches have been used in the cloud-computing environment. Security in cloud computing environment is one of the core issue in distributed computing. We have designed a deep learning-based security model for scheduling tasks in cloud computing and it has been implemented using CloudSim 3.0 simulator written in Java and verification of the results from different perspectives, such as response time with and without security factors, makespan, cost, CPU utilization, I/O utilization, Memory utilization, and execution time is compared with Round Robin (RR) and Waited Round Robin (WRR) algorithms.

• Journal of Information Processing Systems
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• v.7 no.4
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• pp.613-626
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• 2011

In this paper, we focus on the pinwheel task model with a variable voltage processor with d discrete voltage/speed levels. We propose an intra-task DVS algorithm, which constructs a minimum energy schedule for k tasks in O(d+k log k) time We also give an inter-task DVS algorithm with O(d+n log n) time, where n denotes the number of jobs. Previous approaches solve this problem by generating a canonical schedule beforehand and adjusting the tasks' speed in O(dn log n) or O($n^3$) time. However, the length of a canonical schedule depends on the hyper period of those task periods and is of exponential length in general. In our approach, the tasks with arbitrary periods are first transformed into harmonic periods and then profile their key features. Afterward, an optimal discrete voltage schedule can be computed directly from those features.

• Asia pacific journal of information systems
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• v.24 no.2
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• pp.115-140
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• 2014

In a dynamic business environment, the enterprise mobility solution for a mobile office (EMS) has been adopted to increase the competitive edge of organizations. By using an EMS, performance is expected to be enhanced. However, the related literature has paid little interest to the impact of system quality in an EMS on the information quality produced by the system. On the basis of socio-technical theory, we posited that the system quality in an EMS influences information quality. In addition, we investigated the relationships between the above two qualities, use and job performance by considering task mobility and task inter-dependence as control variables. Survey respondents were from many industries using EMSs. The result of structural equation modeling shows that system quality positively affects information quality, and other relationships in the model are proven statistically significant. We also found that system quality has stronger impacts on use and job performance than information quality does in EMS. However, system quality does not affect use in case both task mobility and task inter-dependence exist. The theoretical and practical implications of the result are discussed in the paper.

• Physical Therapy Korea
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• v.16 no.3
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• pp.16-23
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• 2009

The purpose of this study was to investigate the effects of a repetitive lifting task on the level of activation and median frequency of the paraspinal muscles, and to provide basic data of the maximal acceptable duration of the lifting task to avoid muscle fatigue. Ten healthy male subjects were recruited as participants and they repetitively (12 lifts/min) lifted a box ($46cm{\times}30cm{\times}30cm$, 15 kg) for 10 minutes. Electromyographic data (muscle activation and median frequency), heart rate, and Borg CR10 score were recorded at 1, 3, 5, 7, and 9 minutes after the lifting task. Electromyographic data was recorded from the elector spinalis, mutifidus, external oblique abdominis, and rectus abdominis for 1 minute. The results showed that as the repetitive lifting task progressed, the heart rate and Borg CR10 score significantly increased. In addition, activation of the muscles increased. The median frequency significantly decreased over time in the elector spinalis, mutifidus, and external oblique abdominis (right side), except for the external oblique abdominis (left side) and rectus abdominis. It is suggested that the median frequency recorded from a dynamic task is used to monitor muscle fatigue. Furthermore, the repetitive lifting task (15 kg, 12 lifts/min) should not continue for more than 3 minutes in order to avoid muscle fatigue.

• International Journal of Precision Engineering and Manufacturing
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• v.7 no.1
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• pp.62-66
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• 2006

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized learning control based on adaptive control method. The original motivation of the learning control field was learning in robots doing repetitive tasks such as an assembly line works. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Some techniques will show up in the numerical simulation for vertical dynamic robot. The methods of learning system are shown for the iterative precision of each link.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.4
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• pp.92-98
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• 2005

The learning control develops controllers that learn to improve their performance at executing a given task, based on experience performing this specific task. In a previous work, the authors presented an iterative precision of linear decentralized learning control based on p-integrated learning method for the vertical dynamic multiple systems. This paper develops an indirect decentralized teaming control based on adaptive control method. The original motivation of the teaming control field was loaming in robots doing repetitive tasks such as on an assembly line. This paper starts with decentralized discrete time systems, and progresses to the robot application, modeling the robot as a time varying linear system in the neighborhood of the nominal trajectory, and using the usual robot controllers that are decentralized, treating each link as if it is independent of any coupling with other links. Some techniques will show up in the numerical simulation for vertical dynamic robot. The methods of learning system are shown up for the iterative precision of each link.