• 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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• 2014.05a
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• pp.234-237
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• 2014

The increasing of Cloud Computing technology among several companies has been a key strategy for IT services to provide desirable IT solutions to consumers of cloud services. More attention is concentrated to these core technologies that enable cloud services and more particularly to the virtualization aspect. The accessibility to a larger number of users is possible because of the usage of the data-intensive, data management and data integrity. Unfortunately, those useful services are vulnerable to kind of attacks by hackers, thus the security of personal information is in critical situation. To solve this to leakage vulnerability, and with the proliferation of cloud services, the cloud service providers adopt a security system with firewall, antivirus software and a large number of virtualized servers and Host. In this paper, a variety of virtualization technologies, threats and vulnerabilities are described with a complement of different security solutions as countermeasures.

• Journal of the Korean Society of Systems Engineering
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• v.14 no.2
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• pp.73-82
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• 2018

In this work, a hardware based cryptographic module for the cyber security of nuclear power plant is developed using a system engineering approach. Nuclear power plants are isolated from the Internet, but as shown in the case of Iran, Man-in-the-middle attacks (MITM) could be a threat to the safety of the nuclear facilities. This FPGA-based module does not have an operating system and it provides protection as a firewall and mitigates the cyber threats. The encryption equipment consists of an encryption module, a decryption module, and interfaces for communication between modules and systems. The Advanced Encryption Standard (AES)-128, which is formally approved as top level by U.S. National Security Agency for cryptographic algorithms, is adopted. The development of the cyber security module is implemented in two main phases: reverse engineering and re-engineering. In the reverse engineering phase, the cyber security plan and system requirements are analyzed, and the AES algorithm is decomposed into functional units. In the re-engineering phase, we model the logical architecture using Vitech CORE9 software and simulate it with the Enhanced Functional Flow Block Diagram (EFFBD), which confirms the performance improvements of the hardware-based cryptographic module as compared to software based cryptography. Following this, the Hardware description language (HDL) code is developed and tested to verify the integrity of the code. Then, the developed code is implemented on the FPGA and connected to the personal computer through Recommended Standard (RS)-232 communication to perform validation of the developed component. For the future work, the developed FPGA based encryption equipment will be verified and validated in its expected operating environment by connecting it to the Advanced power reactor (APR)-1400 simulator.

• Journal of The Korean Society of Integrative Medicine
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• v.9 no.4
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• pp.49-58
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• 2021

Purpose : This study investigates the effects of the application of traditional occupational therapy and the korean computerized cognition training system on the cognitive function and performance of daily activities of stroke patients with cognitive impairment. Methods : From inpatients referred for rehabilitation treatment at L Rehabilitation Hospital located in Busan, 20 patients diagnosed with stroke from April 05. 2021 to May 02. 2021 (study period) were selected, They were divided into two, an experimental group consisting of 10 subjects who underwent a computerized cognitive rehabilitation program and traditional occupational therapy in combination and a control group of 10 subjects who underwent traditional occupational therapy alone. In order to measure the cognitive function of the subjects before the intervention, two assessment tests were conducted: a Neurobehavioral Cognitive Status Examination (NCSE), which evaluates stroke-related cognitive ability, and a Functional Independence Measure (FIM) test, which evaluates life activities. Then, both groups received a total of 20 training sessions at 30 minutes per session, five times a week for four weeks. Results : A statistically significant difference was found in cognitive function between before and after the cognitive training for both the experimental group and the control group. For the FIM scores, statistically significant differences were observed after intervention in the categories of handling personal matters and social cognition, and in the total score. The average scores of the remaining items also improved. Conclusion : The results of this study showed that both the computerized cognition rehabilitation program and the traditional occupational therapy had a positive effect on the improvement of cognitive function in stroke patients.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.172-178
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• 2020

In order to recommend contents, the company generally uses collaborative filtering that takes into account both user preferences and video (item) similarities. Such services are primarily intended to facilitate user convenience by leveraging personal preferences such as user search keywords and viewing time. It will also be ranked around the keywords specified in the video. However, there is a limit to analyzing video similarities using limited keywords. In such cases, the problem becomes serious if the specified keyword does not properly reflect the item. In this paper, I would like to propose a system that identifies the characteristics of a video as it is by the system without human intervention, and analyzes and recommends similarities between videos. The proposed system analyzes similarities by taking into account all words (keywords) that have different meanings from training videos, and in such cases, the methods handled by big data clusters are applied because of the large scale of data and operations.

• The korean journal of orthodontics
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• v.51 no.2
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• pp.77-85
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• 2021

Objective: To evaluate the accuracy of a multi-stage convolutional neural network (CNN) model-based automated identification system for posteroanterior (PA) cephalometric landmarks. Methods: The multi-stage CNN model was implemented with a personal computer. A total of 430 PA-cephalograms synthesized from cone-beam computed tomography scans (CBCT-PA) were selected as samples. Twenty-three landmarks used for Tweemac analysis were manually identified on all CBCT-PA images by a single examiner. Intra-examiner reproducibility was confirmed by repeating the identification on 85 randomly selected images, which were subsequently set as test data, with a two-week interval before training. For initial learning stage of the multi-stage CNN model, the data from 345 of 430 CBCT-PA images were used, after which the multi-stage CNN model was tested with previous 85 images. The first manual identification on these 85 images was set as a truth ground. The mean radial error (MRE) and successful detection rate (SDR) were calculated to evaluate the errors in manual identification and artificial intelligence (AI) prediction. Results: The AI showed an average MRE of 2.23 ± 2.02 mm with an SDR of 60.88% for errors of 2 mm or lower. However, in a comparison of the repetitive task, the AI predicted landmarks at the same position, while the MRE for the repeated manual identification was 1.31 ± 0.94 mm. Conclusions: Automated identification for CBCT-synthesized PA cephalometric landmarks did not sufficiently achieve the clinically favorable error range of less than 2 mm. However, AI landmark identification on PA cephalograms showed better consistency than manual identification.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.6
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• pp.2086-2097
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• 2021

The current cultural assets are being restored depending on the opinions of experts (craftsmen). We intend to introduce digitalized artificial intelligence techniques, excluding the personal opinions of experts on reconstruction of such cultural properties. The first step toward restoring digitized cultural properties is separation. The restoration of cultural properties should be reorganized based on recorded documents, period historical backgrounds and regional characteristics. The cultural properties in the form of photographs or images should be collected by separating the background. In addition, when restoring cultural properties most of them depend a lot on the tendency of the restoring person workers. As a result, it often occurs when there is a problem in the accuracy and reliability of restoration of cultural properties. In this study, we propose a search method for learning stored digital cultural assets using AI technology. Pagoda was selected for restoration of Cultural Properties. Pagoda data collection was collected through the Internet and various historical records. The pagoda data was classified by period and region, and grouped into similar buildings. The collected data was learned by applying the well-known CNN algorithm for artificial intelligence learning. The pagoda search used Yolo Marker to mark the tower shape. The tower was used a total of about 100-10,000 pagoda data. In conclusion, it was confirmed that the probability of searching for a tower differs according to the number of pagoda pictures and the number of learning iterations. Finally, it was confirmed that the number of 500 towers and the epochs in training of 8000 times were good. If the test result exceeds 8,000 times, it becomes overfitting. All so, I found a phenomenon that the recognition rate drops when the enemy repeatedly learns more than 8,000 times. As a result of this study, it is believed that it will be helpful in data gathering to increase the accuracy of tower restoration.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.581-587
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• 2021

Real-time video streaming scheme for multimedia content delivery and remote conference services is one of technologies that are significantly sensitive to data transmission delay. Recently, because of COVID-19, real-time video streaming contents for the services are significantly increased such as personal broadcasting and remote school class. In order to support the services, there is a growing emphasis on low transmission delay and secure content delivery, respectively. Therefore, our research proposed a packet aggregation algorithm to reduce the transmission delay of selectively encrypted video transmission for real-time video streaming services. Through the application of the proposed algorithm, the selectively encrypted video framework can control the amount of MPEG-2 TS packets for low latency transmission with a consideration of packet priorities. Evaluation results on testbed show that the application of the proposed algorithm to the video framework can reduce approximately 11% of the transmission delay for high and low resolution video.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.11 no.5
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• pp.53-62
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• 2001

Fast diffusion of personal computer and network, and developed security technology are augmenting specific gravity of convenient and safe electronic voting system supplementing much problems of existent off-line vote form. But in spite of enlargement of these weight, much limitations are extravagant. Specially, problem that secure voter\`s anonymousness and accuracy of poll can be important urea that judge if electronic voting system can be applied actually. Also, problems such as buying and selling of vote remain to subject that must solve yet. In this paper, we introduce items that is considered to design the safe electronic voting system, and present limitation of electronic polling system announced in [1]. And we propose improvement way. Improved protocol keeping advantages that is presented in [1], designed to keep away voter\`s anonymousness defamation by conspiracy of Election Administration Committee and Totaling Committee, and block unlawful election intervention as original.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.4
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• pp.797-808
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• 2012

In smart work environment, a company provides employees a flexible work environment for tele-working using mobile phone or portable devices. On the other hand, such environment are exposed to the risks which the attacker can intrude into computer systems or leak personal information of smart-workers' and gain a company's sensitive information. To reduce these risks, the security administrator needs to analyze the usage patterns of employees and detect abnormal behaviors by monitoring VPN(Virtual Private Network) access log. This paper proposes a decision support system that can notify the status by using visualization and similarity measure through clustering analysis. On average, 88.7% of abnormal event can be detected by this proposed method. With this proposed system, the security administrator can detect abnormal behaviors of the employees and prevent account theft.