• Progress in Superconductivity and Cryogenics
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• v.17 no.4
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• pp.34-37
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• 2015

Developing Magnetoencephalography (MEG) based on Superconducting Quantum Interference Device (SQUID) facilitates to observe the human brain functions in non-invasively and high temporal and high spatial resolution. By using this MEG, we studied alpha rhythm (8-13 Hz) that is one of the most predominant spontaneous rhythm in human brain. The 8-13 Hz rhythm is observed in several sensory region in the brain. In visual related region of occipital, we call to alpha rhythm, and auditory related region of temporal call to tau rhythm, sensorimotor related region of parietal call to mu rhythm. These rhythms are decreased in task related region and increased in task irrelevant regions. This means that these rhythms play a pivotal role of inhibition in task irrelevant region. It may be helpful to attention to the task. In several literature about the alpha-band inhibition in multi-sensory modality experiment, they observed this effect in the occipital and somatosensory region. In this study, we hypothesized that we can also observe the alpha-band inhibition in the auditory cortex, mediated by the tau rhythm. Before that, we first investigated the existence of the alpha and tau rhythm in occipital and temporal region, respectively. To see these rhythms, we applied the visual and auditory stimulation, in turns, suppressed in task relevant regions, respectively.

• Journal of Biomedical Engineering Research
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• v.30 no.4
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• pp.306-310
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• 2009

The purpose of this study is to observe the change in gamma-band cortical activities (GBAs) due to task difficulty. Event-related potential and gamma-band activity were investigated using electroencephalograms recorded during auditory oddball tasks with two difficulty levels. For more difficult task, the amplitude of P300 decreased and the peak latency of P300 was delayed significantly compared to easier task. The induced GBA decreased considerably during the P300 latency period and the peak latency of the induced GBA was delayed for more difficult task. The results imply that the difficulty-related change in cortical information processing may be implemented as a change in the strength of local neuronal association.

• Physical Therapy Korea
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• v.2 no.2
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• pp.40-45
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• 1995

The purpose of this study was to investigate the effectiveness of mental practice in increasing accuracy of performance during motor task. Forty healthy students aged 17 years were randomly assigned to two groups. The experimental group(n=20) performed mental practice; the control group(n=20) performed nothing. The task was dotting. No significant change was seen between pre and post test subtest results following mental practice sessions(p>0.05). The experimental group's accuracy improved a little but this was not valuable statistically(p>0.05). We could not prove that mental practice was effective in increasing accuracy of motor task performance.

• The Journal of Korea Robotics Society
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• v.7 no.3
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• pp.194-204
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• 2012

Measuring task complexity of movement skill is an important factor to evaluate a difficulty of learning and/or imitating a task for autonomous robots. Although many complexity-measures are proposed in research areas such as neuroscience, physics, computer science, and biology, there have been little attention on the robotic tasks. To cope with measuring complexity of robotic task, we propose an information-theoretic measure for task complexity of movement skills. By modeling proprioceptive as well as exteroceptive sensor data as multivariate Gaussian distribution, movements of a task can be modeled as probabilistic model. Additionally, complexity of temporal variations is modeled by sampling in time and modeling as individual random variables. To evaluate our proposed complexity measure, several experiments are performed on the real robotic movement tasks.

• Annual Conference of KIPS
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• 2021.11a
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• pp.128-130
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• 2021

Smart cities collect data from thousands of IoT-based sensor devices for intelligent application-based services. Centralized cloud servers support application tasks with higher computation resources but introduce network latency. Fog layer-based data centers bring data processing at the edge, but fewer available computation resources and poor task allocation strategy prevent real-time data analysis. In this paper, tasks generated from devices are distributed as high resource and low resource intensity tasks. The novelty of this research lies in deploying a virtual node assigned to each cluster of IoT sensor machines serving a joint application. The node allocates tasks based on the task intensity to either cloud-computing or fog computing resources. The proposed Task Allocation Strategy provides seamless allocation of jobs based on process requirements.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1992.04b
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• pp.559-568
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• 1992

MODAPTS는 1966년 호주에서 MTM을 기초로 하여 개발되었으며, 이 시스템은 학습과 사용이 용이해서 널리 사용되고 있다. 그러나 본 논문의 연구결과, MODAPTS의 시간단위는 동작구간의 쇠대치를 기준으로 하고 MTM의 동작시간을 합성하여 설정된 것이 증명되었으며, MTM의 동작시간은 "낮은 과업 표준(Low Task Standard)"을 기준으로 하였기 때문에 MODAPTS는 그 정확성에 대하여 검증을 필요로 한다. 본 논문에서는 "높은 과업 표준(High Task Standard)"을 기준으로 하여 설정된 WF를 기초로 하여 MODAPTS의 구성과 정확성에 대하여 분석하였으며, "High Task MODAPTS"의 동작시간을 설정하였다. "High Task MODAPTS"(약칭 HITMAP)는 WF에 대한 정확도가 95%이상으로서 성과급용 표준시간 설정에 충분하므로 생산활동의 생산성을 측정하고 개선하는데 이바지할 것으로 기대된다.하므로 생산활동의 생산성을 측정하고 개선하는데 이바지할 것으로 기대된다.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.89-100
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• 2022

With the advancement in the Internet of things Technology (IoT) cloud computing, billions of physical devices have been interconnected for sharing and collecting data in different applications. Despite many advancements, some latency - specific application in the real world is not feasible due to existing constraints of IoT devices and distance between cloud and IoT devices. In order to address issues of latency sensitive applications, fog computing has been developed that involves the availability of computing and storage resources at the edge of the network near the IoT devices. However, fog computing suffers from many limitations such as heterogeneity, storage capabilities, processing capability, memory limitations etc. Therefore, it requires an adequate task scheduling method for utilizing computing resources optimally at the fog layer. This work presents a comprehensive review of different task scheduling methods in fog computing. It analyses different task scheduling methods developed for a fog computing environment in multiple dimensions and compares them to highlight the advantages and disadvantages of methods. Finally, it presents promising research directions for fellow researchers in the fog computing environment.

• Physical Therapy Rehabilitation Science
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• v.5 no.3
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• pp.143-148
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• 2016

Objective: This study aimed to quantify one of the useful upper extremity movements to evaluate motor control abilities between the groups of people with mild and moderate arm impairments performing a door handling task. Design: Cross-sectional study. Methods: Twenty-one healthy participants and twenty-one persons with chronic stroke (9 mild stroke and 12 moderate stroke) were recruited for this study. Stroke participants were divided into 2 groups based on Fugle-Meyer Assessment scores of 58-65 (mild arm) and 38-57 (moderate arm). All they performed door handling task including the pronation and supination phases 3 times. We measured some movement factors which were reaction time, movement time, hand of peak velocity, hand of movement units to perform door handling task using the three-dimensional motion analysis. Results: The majority of kinematic variables showed significant differences among study groups (p<0.05). The reaction time, total and phase of movement time, hand of peak velocity, the number of movement units discriminated between healthy participants and persons with moderate upper limb stroke (p<0.05). In addition, reaction time, total and phase of movement time, the number of movement units discriminated between those with moderate and mild upper limbs of stroke patients (p<0.05). Conclusions: Three-dimensional kinematic motion analysis in this study was a useful tool for assessing the upper extremity function in different subgroups of people with stroke during the door handling task. These kinematic variables may help clinicians understand the arm movements in door handling task and consist of discriminative therapeutic interventions for stroke patients on upper extremity rehabilitation.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.112-118
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• 2005

Workflow is a collection of tasks organized to accomplish some business processes. It also defines the order of task invocation or conditions under which task must be invoked, task synchronization, and information flow. And activity based costing(ABC) provides accurate cost information for decision making. In ABC systems, costs must be separable into cost pools each of which corresponding to a single cost driver. These two systems are closely related to each other. But recent research deals with workflows and ABC systems separately. Thus, this research proposes an extended workflow model which is expressed cost information using activity based costing.

• International Journal of Computer Science & Network Security
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• v.22 no.3
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• pp.163-172
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• 2022

The interconnection of an enormous number of devices into the Internet at a massive scale is a consequence of the Internet of Things (IoT). As a result, tasks offloading from these IoT devices to remote cloud data centers become expensive and inefficient as their number and amount of its emitted data increase exponentially. It is also a challenge to optimize IoT device energy consumption while meeting its application time deadline and data delivery constraints. Consequently, Fog Computing was proposed to support efficient IoT tasks processing as it has a feature of lower service delay, being adjacent to IoT nodes. However, cloud task offloading is still performed frequently as Fog computing has less resources compared to remote cloud. Thus, optimized schemes are required to correctly characterize and distribute IoT devices tasks offloading in a hybrid IoT, Fog, and cloud paradigm. In this paper, we present a detailed survey and classification of of recently published research articles that address the energy efficiency of task offloading schemes in IoT-Fog-Cloud paradigm. Moreover, we also developed a taxonomy for the classification of these schemes and provided a comparative study of different schemes: by identifying achieved advantage and disadvantage of each scheme, as well its related drawbacks and limitations. Moreover, we also state open research issues in the development of energy efficient, scalable, optimized task offloading schemes for Fog computing.