• Proceedings of the KIEE Conference
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• 1995.11a
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• pp.219-221
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• 1995

This paper proposes a model for simulation and performance evaluation of distributed computer systems(DCS). The model is composed of operating system(OS), resource, task, environment submodel. Task Flow Graph(TFG) is suggested to describe the relation between tasks. This paper considers task response time, the scheduler's ready queue length, utilization of each resource as performance indices. The distributed system of Continuous Annealing Line(CAL) in iron process is simulated with the proposed model.

• Anxiety and mood
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• v.18 no.1
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• pp.32-37
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• 2022

Objective : Impaired working memory has been known to play an important role in the pathophysiology of obsessive-compulsive disorder (OCD) with growing evidence. Delayed matching-to-sample task (DMST) is a working memory task which have an advantage in analyzing several different working memory processes in one task. However, most of the studies have failed to reveal the working memory impairment with the DMST. The aim of this study was to identify whether working memory deficit in OCD can be evaluated with the DMST. Methods : The participants included 20 OCD patients and 20 healthy volunteers. Working memory was evaluated with the DMST with two different working memory loads. Accuracy of response and mean response time were measured. Results : OCD patients showed a significantly longer reaction time and lower accuracy in DMST compared to healthy controls in the task with high working memory loads. Moreover, the difference in accuracy showed interaction with the working memory load. Conclusion : The present results indicate that working memory deficit in patients with OCD can be evaluated with the DMST. The findings also suggest that previous negative behavioral results using the DMST were from low working memory load of the task.

• Journal of KIISE:Software and Applications
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• v.29 no.11
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• pp.837-850
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• 2002

In this paper, we propose an EEG-based response time prediction method during a yes/no cognitive decision task. In the experimental task, a subject goes through responding of visual stimulus, understanding the given problem, controlling hand motions, and hitting a key. Considering the subject's varying brain activities, we model subjects' mental states with defining CT (cut time), ST (selection time), and RP (repeated period). Based on the assumption between ST and RT in the mental model, we predict subjects' response time by detection of selection time. To recognize the subjects' selection time ST, we extract 3 types of feature from the filtered brain waves at frequency bands of $\alpha$, $\beta$, ${\gamma}$ waves in 4 electrode pairs combined by spatial relationships. From the extracted features, we construct specific rules for each subject and meta rules including common factors in all subjects. Applying the ST detection rules to 8 subjects gives 83% success rates and also shows that the subjects will hit a key in 0.73 seconds after ST detected. To validate the detection rules and parameters, we test the rules for 2 subjects among 8 and discuss about the experimental results. We expect that the proposed detection method can be a basic technology for brain-computer-interface by combining with left/right hand movement or yes/no discrimination methods.

• Anxiety and mood
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• v.11 no.1
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• pp.33-37
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• 2015

Objective : Impaired response inhibition has been suggested to play an important role in the pathophysiology of obsessive-compulsive disorder (OCD). The aim of this study was to evaluate the response inhibition in patients with OCD, by using the Go/NoGo paradigm, and to better understand its associations with clinical symptoms. Methods : The participants included 63 OCD patients and 80 healthy volunteers matched in age and sex. response inhibition was evaluated using computerized Go/NoGo task, in which their commission error rates, omission error rates, and mean response times were measured. The severity of clinical symptoms in the OCD patients was assessed using Montgomery-Asberg Depression Scale and Yale-Brown Obsessive Compulsive Scale. Result : OCD patients showed significantly impaired inhibition and higher omission errors rates despite their slower response time, compared to normal controls. Clinical symptoms were not correlated with commission errors and omission errors. Conclusion : The present results indicate that impairment in response inhibition may play a critical role in the pathophysiology of OCD as a trait. These findings suggest that deficit of response inhibition may contribute to developing and maintaining clinical symptoms such as compelling need to repeat certain actions in patients with OCD.

• Industrial Engineering and Management Systems
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• v.4 no.2
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• pp.176-183
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• 2005

The theory of signal detection has been applied to a wide range of practical situation for a long time, including sonar detection, air traffic control and so on. In general, in this theory, sensitivity parametric index d' and bias parametric index $\beta$ are used to evaluated the performance of vigilance. These indices use observer's response "hit" and "false alarm" to explain and evaluate vigilance, but not considering reaction time. However, the reaction time of detecting should be considered in measuring vigilance in some supervisory tasks such as unlimited monitoring tasks (e.g., supervisors in nuclear plant). There are some researchers have used the segments of reaction time to generate a pair of probabilities of hit and false alarm probabilities and plot the receiver operating characteristic curve. The purpose of this study was to develop a quantitative vigilance-measuring model by fuzzy sets, which combined the concepts of hit, false alarm and reaction time. The model extends two-values logic to multi-values logic by membership functions of fuzzy sets. A simulated experiment of monitoring task in nuclear plant was carried out. Results indicated that the new vigilance-measuring model is more efficient than traditional indices; the characteristics of vigilance would be realized more clearly in unlimited monitoring task.

• Communications for Statistical Applications and Methods
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• v.8 no.1
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• pp.193-207
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• 2001

When designing a test set, we need to consider constraints on items that are deemed important by item developers or test specialists. The constraints are essentially on the components of the test domain or abilities relevant to a given test set. And so if the test domain could be represented in a more refined form, test construction would be made in a more efficient way. We assume that relationships among task abilities are representable by a causal model and that the item response theory (IRT) is not fully available for them. In such a case we can not apply traditional item selection methods that are based on the IRT. In this paper, we use entropy as an uncertainty measure for making inferences on task abilities and developed an optimal item selection algorithm which reduces most the entropy of task abilities when items are selected from an item pool.

• Journal of Korea Multimedia Society
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• v.14 no.1
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• pp.76-84
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• 2011

Embedded Systems need to ensure real-time of the task response time depending on the applied fields of it. And task could be faulty due to various reasons in real time systems. Therefore in this paper, we design a task scheduler that guarantees deadlines of periodic tasks and considers a fault tolerance of defective task in embedded system with a single processor. In order to provide real-time, we classify tasks with periodic/aperiodic tasks and applies RMS(Rate Monotonic Scheduling) method to schedule periodic tasks and can guarantees execution of aperiodic tasks by managing surplus times obtained after analyzing the execution time of periodic tasks. In order to provide fault tolerance, we manage backup times and reexecute a fault task to restore it's conditions.

• Journal of Korea Multimedia Society
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• v.24 no.1
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• pp.51-57
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• 2021

In this paper, we propose a task distribution scheme in fog computing environment considering opportunistic fog computing nodes. As latency is one of the important performance metric for IoT(Internet of Things) applications, there have been lots of researches on the fog computing system. However, since the load can be concentrated to the specific fog computing nodes due to the spatial and temporal IoT characteristics, the load distribution should be considered to prevent the performance degradation. Therefore, this paper proposes a task distribution scheme which considers the static as well as opportunistic fog computing nodes according to their mobility feature. Especially, based on the task requirements, the proposed scheme supports the delay sensitive task processing at the static fog node and delay in-sensitive tasks by means of the opportunistic fog nodes for the task distribution. Based on the performance evaluation, the proposed scheme shows low service response time compared to the conventional schemes.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.4
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• pp.337-342
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• 2012

This paper presents performance evaluation of real-time mechanisms for real-time embedded linux. First, we presents process for implementing open-source real-time embedded linux namely RTAI and Xenomai. These are real-time extensions to linux kernel and we implemented real-time embedded linux over the latest linux kernel. Measurements of executions of real-time mechanisms for each distribution are performed to give a quantitative comparison. Performance evaluations are conducted in kernel space about repeatability of periodic task, response time of Semaphore, FIFO, Mailbox and Message queue in terms of inter-task communication for each distribution. These rules can be helpful for deciding which real-time linux extension should be used with respect to the requirements of the real-time applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.117-135
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• 2016

Performance enhancement is one of the most important issues in high performance distributed computing systems. In such computing systems, online users submit their jobs anytime and anywhere to a set of dynamic resources. Jobs arrival and processes execution times are stochastic. The performance of a distributed computing system can be improved by using an effective load balancing strategy to redistribute the user tasks among computing resources for efficient utilization. This paper presents a multi-class load balancing strategy that balances different classes of user tasks on multiple heterogeneous computing nodes to minimize the per-class mean response time. For a wide range of system parameters, the performance of the proposed multi-class load balancing strategy is compared with that of the random distribution load balancing, and uniform distribution load balancing strategies using simulation. The results show that, the proposed strategy outperforms the other two studied strategies in terms of average task response time, and average computing nodes utilization.