• Journal of the Korea Society for Simulation
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• v.15 no.2
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• pp.23-29
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• 2006

This paper studies the Internet stream server which serves multimedia stream services such as VoD and MoD. The Internet multimedia stream server is developed to provide 50 users with continuous multimedia stream contents simultaneously. This paper focuses on introducing design concepts, operation details and on evaluating system performance and doing sensitivity analysis with respect to the change of the system components. The performance evaluation is performed using simulation in order to identify the system component that mostly affects the system performance. The sensitivity analysis shows the service delay rates of the multimedia stream server depending on the user's service request pattern. Also, the analysis is made on the utilization rates of the core system components such as the PCI bus and the Ethernet card, and on the system performance change by adding more system components.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.7
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• pp.1033-1038
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• 2013

Petrochemical complex has been a lot of research for the development of a more mature product and analysis for mid-process and finished products is essential in these process. But these analyzes are still by hand work samples being manufactured in many parts. Moreover they are exposed to hazardous chemical and such as the analysis is being made in a very poor working conditions. In this paper, in order to solve such problems the multi control system has been developed for the automated analysis. In addition, the organic behavior of these systems and the development of a program for the automated applied, and throughout the experiment to verify the reliability of this device for the accuracy of the dosing pumps for the standard solution prepared with a range of error of ${\pm}0.01m{\ell}$ was able to get a very good experimental results.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.1
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• pp.45-50
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• 2019

With the gradual advancement of IT, passive work processes are automated and the overall quality of life has greatly improved. This is made possible by the formation of an organic topology between a wide variety of real-life smart devices. To serve these diverse smart devices, businesses or users are using the cloud. The services in the cloud are divided into Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS). SaaS runs on PaaS, and PaaS runs on IaaS. Since IaaS is the basis of all services, an algorithm is required to operate virtualization resources efficiently. Among them, desktop resource virtualization is used for resource high availability of unused state time of existing desktop PC. Clustering of hierarchical structures is important for high availability of these resources. In addition, it is very important to select a suitable algorithm because many clustering algorithms are mainly used depending on the distribution ratio and environment of the desktop PC. If various attempts are made to find an algorithm suitable for desktop resource virtualization in an operating environment, a great deal of power, time, and manpower will be incurred. Therefore, this paper proposes a resource clustering simulator for cluster selection of desktop virtualization. This provides a clustering simulation to properly select clustering algorithms and apply elements in different environments of desktop PCs.

• Journal of KIISE
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• v.44 no.9
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• pp.887-892
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• 2017

Brain-computer interface (BCI) is a technology that controls computer and transmits intention by measuring and analyzing electroencephalogram (EEG) signals generated in multi-channel during mental work. At this time, optimal EEG channel selection is necessary not only for convenience and speed of BCI but also for improvement in accuracy. The optimal channel is obtained by removing duplicate(redundant) channels or noisy channels. This paper propose a dual filter-based channel selection method to select the optimal EEG channel. The proposed method first removes duplicate channels using Spearman's rank correlation to eliminate redundancy between channels. Then, using F score, the relevance between channels and class labels is obtained, and only the top m channels are then selected. The proposed method can provide good classification accuracy by using features obtained from channels that are associated with class labels and have no duplicates. The proposed channel selection method greatly reduces the number of channels required while improving the average classification accuracy.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.3C
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• pp.125-132
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• 2005

This paper describes a computer vision system based on active IR illumination for real-time gaze discrimination system. Unlike most of the existing gaze discrimination techniques, which often require assuming a static head to work well and require a cumbersome calibration process for each person, our gaze discrimination system can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using generalized regression neural networks (GRNNs). With GRNNs, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. Futhermore, the mapping function can generalize to other individuals not used in the training. To further improve the gaze estimation accuracy, we employ a reclassification scheme that deals with the classes that tend to be misclassified. This leads to a 10% improvement in classification error. The angular gaze accuracy is about 5°horizontally and 8°vertically. The effectiveness of our gaze tracker is demonstrated by experiments that involve gaze-contingent interactive graphic display.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.3 no.1
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• pp.38-46
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• 2010

This paper describes a computer vision system based on active IR illumination for real-time gaze discrimination system. Unlike most of the existing gaze discrimination techniques, which often require assuming a static head to work well and require a cumbersome calibration process for each person, our gaze discrimination system can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using generalized regression neural networks (GRNNs). With GRNNs, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. Furthermore, the mapping function can generalize to other individuals not used in the training. To further improve the gaze estimation accuracy, we employ a reclassification scheme that deals with the classes that tend to be misclassified. This leads to a 10% improvement in classification error. The angular gaze accuracy is about $5^{\circ}$horizontally and $8^{\circ}$vertically. The effectiveness of our gaze tracker is demonstrated by experiments that involve gaze-contingent interactive graphic display.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.2
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• pp.322-329
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• 2005

This paper describes a computer vision system based on active IR illumination for real-time gaze discrimination system. Unlike most of the existing gaze discrimination techniques, which often require assuming a static head to work well and require a cumbersome calibration process for each person, our gaze discrimination system can perform robust and accurate gaze estimation without calibration and under rather significant head movement. This is made possible by a new gaze calibration procedure that identifies the mapping from pupil parameters to screen coordinates using generalized regression neural networks (GRNNS). With GRNNS, the mapping does not have to be an analytical function and head movement is explicitly accounted for by the gaze mapping function. furthermore, the mapping function can generalize to other individuals not used in the training. To further improve the gaze estimation accuracy, we employ a reclassification scheme that deals with the classes that tend to be misclassified. This leads to a 10$\%$ improvement in classification error. The angular gaze accuracy is about $5^{circ}$horizontally and $8^{circ}$vertically. The effectiveness of our gaze tracker is demonstrated by experiments that involve gaze-contingent interactive graphic display.

• Therapeutic Science for Rehabilitation
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• v.5 no.2
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• pp.71-80
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• 2016

Objective: To illustrate effects and application potential of Mirror Therapy (MT) for patients with post-stroke hemiplegia. Method: With reference to 9 journals (published Jan.2005-Jan.2016) on Pubmed, selected based on in/exclusion standards. Result: Simple wrist/hand movements and task-based MT were used as intervention methods to examine the effects. Tools used to assess intervention effects included upper limb functioning, Activities of Daily Living (ADL), physical condition and quality of life. Upper limb functioning turned out to have significance for ADL with higher effectiveness at the distal than the proximal region. Yet the quality of life disparity between the experiment group and the control was not found to be significant. Conclusion: We believe that research can aid clinical therapists in applying MT accordingly to individual patient characteristics. Despite prolonged difficulty in confirming efficient application due to varied protocols, development of systemized treatment protocols for maximization of MT's effectiveness remains necessary.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.521-528
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• 2021

Existing image analysis systems in use in the military field are carried out by readers analyzing and identifying images themselves, writing and disseminating related content, and in this process, repetitive tasks are frequent, resulting in workload. In this paper, to solve the previous problem, we proposed an algorithm that can operate the Seq2Seq model on a word basis, which operates on a sentence basis, and applied the Attention technique to improve accuracy. In addition, by applying the Beam Search technique, we would like to recommend various current identification sentences based on the past identification contents of a specific area. It was confirmed through experiments that the Beam Search technique recommends sentences more effectively than the existing greedy Search technique, and confirmed that the accuracy of recommendation increases when the size of Beam is large.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.5
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• pp.221-228
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• 2022

With the application of artificial intelligence technology, robots can provide efficient services in real life. Unlike industrial manipulators that do simple repetitive work, this study presented design methods of 6 degree of freedom robot arm and intelligent object search and movement methods for use alone or in collaboration with no place restrictions in the service robot field and verified performance. Using a depth camera and deep learning in the ROS environment of the embedded board included in the robot arm, the robot arm detects objects and moves to the object area through inverse kinematics analysis. In addition, when contacting an object, it was possible to accurately hold and move the object through the analysis of the force sensor value. To verify the performance of the manufactured robot arm, experiments were conducted on accurate positioning of objects through deep learning and image processing, motor control, and object separation, and finally robot arm was tested to separate various cups commonly used in cafes to check whether they actually operate.