• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.4
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• pp.587-594
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• 2018

The purpose of this study is to propose a power demand volatility evaluation system based on LSTM and not to verify the accuracy of the demand module which is a core module, but to recognize the sudden change of power pattern by using deeplearning in the actual power demand monitoring system. Then we confirm the availability of the module. Also, we tried to provide a visualized report so that the manager can determine the fluctuation of the power usage patten by applying it as a module to the web based system. It is confirmed that the power consumption data shows a certain pattern in the case of government offices and hospitals as a result of implementation of the volatility evaluation system. On the other hand, in areas with relatively low power consumption, such as residential facilities, it was not appropriate to evaluate the volatility.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.10
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• pp.1751-1758
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• 2008

Digital holography interference pattern generated by a computer calculation (CGH) is one of the most expensive contents and its usage is being expanded. Thus, it is highly necessary to protect the ownership of digital hologram. In this paper a hologram-domain and a frequency-domain electronic watermarking schemes were proposed. The hologram-domain scheme was only to compare the results to the ones from frequency-domain scheme and the frequence-domain scheme used 2-dimensional against the attaks. Especially the MDWT-domain scheme was very high robustness such that th error ratio at the worst case was only 3%. Thus, we expect that it is used as a good watermarking scheme of digital hologram with high performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.762-777
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• 2014

With the increasing usage of cloud applications such as MapReduce and social networking, the amount of data traffic in data center networks continues to grow. Moreover, these appli-cations follow the incast traffic pattern, where a large burst of traffic sent by a number of senders, accumulates simultaneously at the shallow-buffered data center switches. This causes severe packet losses. The currently deployed TCP is custom-tailored for the wide-area Internet. This causes cloud applications to suffer long completion times towing to the packet losses, and hence, results in a poor quality of service. An Explicit Congestion Notification (ECN)-based approach is an attractive solution that conservatively adjusts to the network congestion in advance. This legacy approach, however, lacks scalability in terms of the number of flows. In this paper, we reveal the primary cause of the scalability issue through analysis, and propose a new congestion-control algorithm called FaST. FaST employs a novel, virtual congestion window to conduct fine-grained congestion control that results in improved scalability. Fur-thermore, FaST is easy to deploy since it requires only a few software modifications at the server-side. Through ns-3 simulations, we show that FaST improves the scalability of data center networks compared with the existing approaches.

• 한국정보통신설비학회:학술대회논문집
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• 2004.08a
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• pp.273-277
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• 2004

서울대학교와 KT는 연구 환경 조성과 U-Campus 시범 구축을 위해서 산학협력 협약을 하고, 서울대학교에 NESPOT 시설을 구축하였다. 본 논문은 서울대학교 내의 NESPOT 이용자들의 NESPOT 서비스 이용 패턴 및 무선랜의 트래픽 특성을 분석하기 위한 시스템의 설계와 구현에 대한 내용을 다룬다. NESPOT 트래픽 특성을 분석하기 위한 시스템은 TCPDUMP를 이용하여 백본 라우터로부터 네트워크 전체에 대한 정보를 획득하고, SNMP (Simple Network management Protocol)을 통해 AP로부터 무선랜 관련 정보를 얻는다. 그리고, NESPOT 사용자의 단말에 관련된 보다 구체적인 정보를 얻기 위해서 TIS (Terminal Information System)을 개발하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.5
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• pp.978-985
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• 2003

The implementation of abnormal behavior detection IDS is more difficult than the implementation of misuse behavior detection IDS because usage patterns are various. Therefore, most of commercial IDS is misuse behavior detection IDS. However, misuse behavior detection IDS cannot detect system intrusion in case of modified intrusion patterns occurs. In this paper, we apply data mining so as to detect intrusion with only audit data related in intrusion among many audit data. The agent in the distributed IDS can collect log data as well as monitoring target system. False positive should be minimized in order to make detection accuracy high, that is, core of intrusion detection system. So We apply data mining algorithm for prediction of modified intrusion pattern in the level of audit data learning.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.6
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• pp.459-464
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• 2013

In this paper, we introduce a modulation code design problem where best selection of two-dimensional codewords are determined to reduce two-dimensional (2D) intersymbol interference (ISI) and interpage interference (IPI). Codeword selection problem is formulated as a quadratic integer programming model that minimizes intra- and inter-symbol differences subject to uniform symbol usage and minimal Hamming distance violations. Second integer programming model detects the occurrence of isolated pixel pattern in the selected codewords. The proposed models are applied to 4-level and 2-level 6/8 codes.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.3
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• pp.35-45
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• 2011

Due to people's internet use growth and proliferation of ubiquitous technology, the internet addiction is becoming a social issue. However, the current adults' self-diagnosis measure about internet addiction, the K-scale, is a normal diagnostic method, which it does not consider user characteristics. In this research, we will propose a new internet addiction diagnostic method based on users' non-duty internet activities by using some questionnaire items to collect users' basic internet patterns used on duty related or non-duty related web sites. Since we simply ask for the basic internet usage pattern to each user who does not like to check frankly questionnaire items in the K-scale, the proposed method can find some hidden internet addicts compared to the K-scale with the SPSS statistical analysis tool.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.1185-1190
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• 2009

Korea is an industrial country that overspends energy and has a policy that is more focused on a supply side. When an urban developmental program is to set up, surveys are carried out only with the respect to electricity, telecommunication, gas, and heating sources. Based on the existing survey results, the problems related to the supply side are being dealt with more importantly and the quantities of those supplies are estimated only by each energy source. The aim of this study is to provide basic information on energy consumption patterns of a diverse comsumer groups including industry, transportation, commerce, public and household to plan diverse energy policies. Through this basic information, it may be possible to analyze the energy consumption pattern by each consumer group and provide data for setting up efficient energy policies by the government. The energy consumption map that are analyzed and developed by the data obtained from Busan municipal area will be deposited and used as a part of the national energy statistics.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.12A
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• pp.959-965
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• 2011

As the usage of mobile stations increases thanks to various services, power saving mechanisms of mobile station operated by battery power have been gained much attention. This paper presents a power saving mechanism(PSM) of IEEE 802.16m, called Mobile WiMAX, for 4G mobile technology. This paper first presents different points of the PSM of IEEE 802.16m from IEEE 802.16e, which is a basis of IEEE 802.16m. This paper proposes a dynamic sleep cycle adjustment algorithm for improving the performance of IEEE 802.16m PSM by considering the arrival pattern of incoming packets from base station. Performance of the algorithm is analyzed in terms of energy consumption as well as waiting time of packets.

• Microbiology and Biotechnology Letters
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• v.48 no.2
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• pp.138-147
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• 2020

Various microorganisms play important roles in food fermentation, food spoilage, and agriculture. In this study, the biotype of 54 yeast and bacterial strains having high potential for utilization in food and agriculture, including Candida spp., Lactobacillus spp., and Acetobacter spp., were characterized by matrix-assisted laser desorption/ionization time-of flight mass spectrometry (MALDI-TOF MS). This characterization using a fast and robust method provides much-needed information on the selected microorganisms and will facilitate effective usage of these strains in various applications. Importantly, the unique protein profile of each microbial species obtained from this study was used to create a database of fingerprints from these species. The database was validated using microbial strains of the same species by comparing the mass spectra with the created database through pattern matching. The created reference database provides crucial information and is useful for further utilization of a large number of valuable microorganisms relevant to food and agriculture.