• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.424-424
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• 2009

• Proceedings of the Korea Society of Design Studies Conference
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• 1998.04a
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• pp.2-3
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• 1998

• Proceedings of the Korea Society of Design Studies Conference
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• 1995.04a
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• pp.88-89
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• 1995

• Bulletin of the Korean Chemical Society
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• v.10 no.2
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• pp.216-218
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• 1989

• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.131-140
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• 2014

TMost of the medical images that are being used today are to confirm the existence of lesions. These kind of medical images can not only be used to confirm lesions but if we could use it for academic studies or for analysis and reference materials for surgical operations, it could offer great help in medical studies. Furthermore, we could reduce the number of errors in treatment through simulations in the surgical operations and treatments. In this paper, the necessary parts regarding the medical image visuals were extracted through the point cloud and by using the information obtained through it, it manufactures the necessary information for academic studies, diagnoses or operations. By designing and realizing the system which makes simulation possible with the manufactured information, the paper attempts to provide a more effective way to approach academic studies or giving appropriate diagnoses in the treatment of patients.

• The Journal of Korean Association of Computer Education
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• v.5 no.2
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• pp.1-10
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• 2002

Recent studies have shown that Korea has achieved similar or better environments for computer education in hardware perspective. However, in software perspective, many problems have been reported. We tried to suggest more effective ways of computer education based on the results from comparative study on computer education in Korea with respect to technology standards of USA.

• Journal of the Korea Computer Industry Society
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• v.4 no.12
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• pp.1021-1032
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• 2003

Former studies on computer games have not suggested practical influence on the analysis results of their impacts on learning of teenagers focusing on the social, spiritual and psychological aspects. To look over the impacts, 560 teenagers are surveyed from the age of 14 to 19 for making use of their computer games int this study and their going through lower grades or learning interference from those uses. It is proposed that the analyzing methods about the impacts on learning and effective how to use computer games in this thesis.

• Bulletin of the Korean Chemical Society
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• v.27 no.2
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• pp.273-276
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• 2006

Three dimensional quantitative structure-activity relationship studies for a series of isatin derivatives as a nonpeptidyl caspase-3 enzyme inhibitor were investigated using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The first approach of non-peptidyl small molecules by 3D QSAR may be useful in guiding further development of potent caspase-3 inhibitors.

• Journal of the Korea Society of Computer and Information
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• v.20 no.9
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• pp.67-72
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• 2015

Recently, studies that interact with human and things through motion recognition are increasing due to the expansion of IoT(Internet of Things). This paper proposed the system that recognizes the user's logical activity in home environment by attaching some sensors to various objects. We employ Arduino sensors and appreciate the logical activity by using the physical activitymodel that we processed in the previous researches. In this System, we can cognize the activities such as watching TV, listening music, talking, eating, cooking, sleeping and using computer. After we produce experimental data through setting virtual scenario, then the average result of recognition rate was 95% but depending on experiment sensor situation and physical activity errors the consequence could be changed. To provide the recognized results to user, we visualized diverse graphs.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.172-180
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• 2022

Crypto-mining malware (known as crypto-jacking) is a novel cyber-attack that exploits the victim's computing resources such as CPU and GPU to generate illegal cryptocurrency. The attacker get benefit from crypto-jacking by using someone else's mining hardware and their electricity power. This research focused on the possibility of detecting the potential crypto-mining malware in an environment by analyzing both static and dynamic approaches of deep learning. The Program Executable (PE) files were utilized with deep learning methods which are Long Short-Term Memory (LSTM). The finding revealed that LTSM outperformed both SVM and RF in static and dynamic approaches with percentage of 98% and 96%, respectively. Future studies will focus on detecting the malware using larger dataset to have more accurate and realistic results.