• Journal of the Korea Computer Graphics Society
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• v.25 no.3
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• pp.55-63
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• 2019

Recently, the GPU computing method has been utilized to improve the performance of the physics simulation field. In particular, in the case of a deformed object simulation requiring a large amount of computation, a GPU-based parallel processing algorithm is required to guarantee real-time performance. We have studied the parallel structure design method to improve the performance of the mass spring simulation method which is one of the methods of implementing the deformation object simulation. We used OpenGL's GLSL, a graphics library that allows direct access to the GPU, and implemented the GPGPU environment using an independent pipeline, the compute shader. In order to verify the effectiveness of the parallel structure design method, the mass - spring system was implemented based on CPU and GPU. Experimental results show that the proposed method improves computation speed by about 6,000% compared to the CPU Environment. It is expected that the lightweight simulation technology can be effectively applied to the augmented reality and the virtual reality field by using the design method proposed later in this research.

• Journal of Industrial Convergence
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• v.17 no.2
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• pp.45-52
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• 2019

A systematic review was conducted to identify components and convergent effects of simulation program using schizophrenia scenario in nursing education. Using 4 different databases, 226 articles were identified and 11 studies met the inclusion criteria. There were 5 qualitative studies, 5 quantitative studies and 1 study used mixed method design. The simulation incorporated various methods including standardized patients, role playing, simulator and virtual reality that majority studies(63.6%) used standardized patients. For the evaluation, studies examined diverse variables including knowledge, learning self competency, learning satisfaction and self directed learning. Considering complexity and difficulty of nursing for schizophrenia, future studies with well designed simulation program are required to prove its effectiveness.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.675-678
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• 2014

One time, Home video game console's penetration was as comparable to the personal computer's penetration, growth has slowed since the advent of smartphones, tablets and moblie devices. But game console actively introducing new IT technologies not available in the pc games and mobile games, still keeping a firm position in the relevent market. In this paper Home video game console's history, contemporary trends, and learn about trends in the company, New IT technologies applied to gaming was analyzed. Home video console market become the arena of New IT technologies according to the introduction of New IT technologies such as gesture recognition technology, speech recognition technology, media facade technology, virtual reality technology.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.915-918
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• 2016

Virtual testing devices are required due to rapid changes in the health care industry and the increase of the medical or nursing workforce. The importance of devices such as the simulator, blood vessels, and lab equipment for modeling blood flow to the heart is increasing too. In this study, we made heart pump by using a step motor and developed device which simulates arterial, venous blood pressure, and blood flow. We finally evaluated the function of proposed device. The proposed system is composed of the pump for simulating, the valve device to describe the resistance of the artery and vein, and a reducing device showing the characteristics of the venous system. We used BOXER pump for heart simulator and silicon tube for arterial and venous vessels, and designed a reducing device. We also used the pressure sensor to measure arterial blood pressure. For the evaluation of the proposed system, we selected a range of 50~100mmHg of the blood circuit 60 per minute and then compared the blood pressure of a person and the measured blood pressure.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.822-823
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• 2014

The usual method of generating an image for a multiview display system requires acquiring a color image and depth information of a reference camera. Then, intermediate images, generated using DIBR method, will be captured at a number of different viewpoints and composed to construct an multiview image. When such intermediate views are generated, several holes would be shown because some hidden parts are shown when the screenshot is taken at different angle. Previous research tried to solve this problem by creating a new hole-filling algorithm or enhancing the depth information. This paper describes a new method of enhancing the intermediate view images by applying the Ball Pivoting algorithm, which constructs meshes from a point cloud. When the new method is applied to the Microsoft's "Ballet" and "Break Dancer" data sets, PSNR comparison shows that about 0.18~1.19 increasement. This paper will explaing the new algorithm and the experiment method and results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.525-531
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• 2019

Efforts to utilize human gestures to effectively implement a more natural and interactive interface between humans and computers have been ongoing in recent years. In this paper, we propose a new algorithm that accepts consecutive three-dimensional (3D) depth images, defines a hand model, and robustly extracts the human hand region based on six palm joints and 15 finger joints. Then, the 3D depth images are adaptively binarized to exclude non-interest areas, such as the background, and accurately extracts only the hand of the person, which is the area of interest. Experimental results show that the presented algorithm detects only the human hand region 2.4% more accurately than the existing method. The hand region extraction algorithm proposed in this paper is expected to be useful in various practical applications related to computer vision and image processing, such as gesture recognition, virtual reality implementation, 3D motion games, and sign recognition.

• The Korean Journal of Applied Statistics
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• v.32 no.2
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• pp.199-211
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• 2019

This paper is concerned with issues in the finite mixture of regression modeling as well as the simultaneous selection of the number of mixing components and relevant predictors. We propose a penalized likelihood method for both mixture components and regression coefficients that enable the simultaneous identification of significant variables and the determination of important mixture components in mixture of regression models. To avoid over-fitting and bias problems, we applied smoothly clipped absolute deviation (SCAD) penalties on the logarithm of component probabilities suggested by Huang et al. (Statistical Sinica, 27, 147-169, 2013) as well as several well-known penalty functions for coefficients in regression models. Simulation studies reveal that our method is satisfactory with well-known penalties such as SCAD, MCP, and adaptive lasso.

• Convergence Security Journal
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• v.19 no.1
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• pp.121-126
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• 2019

The big data utilization category in the sports field was mainly focused on the big data analysis to improve the competence of the athlete and the performance. Since then, 'big data technology' which collect and analyze more detailed and diverse data through the application of ICT technology such as IoT and AI has been applied. The use of big data of sports contents in future has value and possibility in the smart environment, but it is necessary to overcome the shortage and limitation of platform to manage and share sports contents. In order to solve such problems, it is important to change the perception of the companies or providers that provide sports contents and cultivate and secure professional personnel capable of providing sports contents. Also, it is necessary to implement policies to systematically manage and utilize big data poured from sports contents.

• Journal of IKEEE
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• v.23 no.3
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• pp.852-857
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• 2019

In order to manage the demand resources of project participants and to provide appropriate strategies in the virtual power plant's power trading platform for consumers or operators who want to participate in the distributed resource collective trading market, it is very important to forecast the next day's demand of individual participants and the overall system's electricity demand. This paper developed a power demand forecasting model for the next day. For the model, we used LSTM algorithm of deep learning technique in consideration of time series characteristics of power demand forecasting data, and new scheme is applied by applying one-hot encoding method to input/output values such as power demand. In the performance evaluation for comparing the general DNN with our LSTM forecasting model, both model showed 4.50 and 1.89 of root mean square error, respectively, and our LSTM model showed high prediction accuracy.

• Convergence Security Journal
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• v.18 no.4
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• pp.81-87
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• 2018

Military training is being carried out to win the combats through the quick and accurate response exercise for changeable engagement situations on battle fields. However, practically, it is really difficult to do actual fight training. Even though ROK Army is doing effort for practical training in KCTC(Korea army advanced Combat Training Center) supplying such as MILES equipments but a single platoon is able to use KCTC facilities or MILES equipments only 10 days a year. In order to find solution on this problem many researches suggesting AR or VR technology are still on the way. Nevertheless these are not fully covered the training done in the real field. In this regard, this paper proposes how the AR technology algorithm to apply on small units during field training exercise.