• Journal of the Korea Safety Management & Science
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• v.13 no.3
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• pp.115-121
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• 2011

Incheon Port has many advantages for import of log and timber for furniture. More than 50% of lumber which was imported is through Incheon Port. However, most companies move and set up their business by taking lease of workshop. Because of expensive cost of transportation, it is suggested to construct a lumber Industrial district in the North Port in Incheon. By researching the national plans about the North Port and Incheon Ports, an adequate acquaintance of lumber industry in Incheon has been realized. ills study conducted the economic effect analysis for lumber industry clustering and the necessity of cluster composition is derived. Then effectiveness analysis for lumber industry cluster composition is sequentially operated.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.2
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• pp.321-330
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• 2019

Prevention of corporate confidentiality leakage by insiders in enterprises is an essential task for the survival of enterprises. In order to prevent information leakage by insiders, companies have adopted security solutions, but there is a limit to effectively detect abnormal behavior of insiders with access privileges. In this study, we use the Unsupervised Learning algorithm of the machine learning technique to effectively and efficiently cluster the normal and abnormal access logs of the worker's work screen in the manufacturing information system, which includes the company's product manufacturing history and quality information. We propose an optimal feature selection model for anomaly detection by studying clustering methods.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1097-1104
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• 2021

Online game-bots are already known for a lot of persons by various ways. It leads to problems such as declining game player's interest, in-game financial crisis, etc. Detecting and restricting of game-bot is now essential. Because both publishers and players get disadvantages from their long term abnormal working. But it is not easy to restrict, because of false restriction risks. Game publishers need to distinguish game-bot from server-side game logs. At last, it should can make reasons for game-bot restriction. In this paper, we classified game-bot users by using daily separated game logs for testing data. For daily-driven detection, we separated total dataset into one day logs. Preliminary detects game-bots with one day logs, and determines total results by using these data. Daily driven detection advantages on detection which contains combined game playing style. Which shows like normal user and game-bot. These methodology shows better F1-score, which one of indicator which demonstrate classification accuracy. It increases from 0.898 to 0.945 by using Random Forest classifier.

• Journal of the Korean Geotechnical Society
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• v.24 no.10
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• pp.57-70
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• 2008

The advantage of piezocone penetration test is a guarantee of continuous data, which is a source of reliable interpretation of target soil layer. Many researches have been carried out f3r several decades and several classification charts have been developed to classify in-situ soil from the cone penetration test result. Since most present classification charts or methods were developed based on the data which were compiled over the world except Korea, they should be verified to be feasible for Korean soil. Furthermore, sometimes their charts provide different soil classification results according to the different input parameters. However, unfortunately, revision of those charts is quite difficult or almost impossible. In this research a new soil classification model is proposed by using fuzzy C-mean clustering and neuro-fuzzy theory based on the 5371 CPT results and soil logging results compiled from 17 local sites around Korea. Proposed neuro-fuzzy soil classification model was verified by comparing the classification results f3r new data, which were not used during learning process of neuro-fuzzy model, with real soil log. Efficiency of proposed neuro-fuzzy model was compared with other soft computing classification models and Robertson method for new data.

• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.3
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• pp.645-661
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• 2009

The water extract of Dohongsamul-Tang(DHSMT) has been traditionally used to stroke and brain injuries in Oriental Medicine. The present study was designed to investigate the effects of DHSMT on the gene expression profile of cerebral infarction by cDNA microarray in photothrombotic ischemia mouse model. Photothrombotic ischemia was induced in stereotactically held male BALB/c mice using rose bengal and cold light. MRI was performed 24 hours after inducing photothrombosis using 1.5 T MRI and 47 mm surface coil to obtain T2-weighted, and contrast-enhanced images. After MRI test, animal was sacrificed and the brain sections were stained for hematoxylin and eosin and immunohistochemistry. MRI and histological analysis revealed that lesion of thrombotic ischemia was well induced in the cortex with the evidence of biological courses of infarction. The target area of thrombotic infarction was 1 mm anterior to bregma and 3 mm lateral to midline with 2 mm in diameter, which were decreased by administration of DHSMT. To assess gene expression pattern of cerebral infarction, mRNA was isolated and reacted with microarray chip(Agilant's DNA Microarray 44K). Scatter and MA plot analysis were performed to clustering of each functional genes. M value [M=log2(R/G), A={log2(R ${\times}$ G)}/2] was between -0.5 and +0.5 with 40% difference. After pretreatment with DHSMT, the expression levels of mRNA of many genes involved in various signaling pathway such as apoptosis, cell cycle, cell proliferation, response to oxidative stress, immune response, angiogenesis, and inflammatory cytokine were markedly inhibited in photothrombotic ischemia lesion compared to the control group. These results suggest that DHSMT prevent ischemic death of brain on photothrombotic ischemia model of mice through modulation of gene expression at the transcriptional level.

• Journal of KIISE:Software and Applications
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• v.31 no.5
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• pp.586-594
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• 2004

Because web documents become creation and disappearance rapidly, users require the recommend system that offers users to browse the web document conveniently and correctly. One largely untapped source of knowledge about large data collections is contained in the cumulative experiences of individuals finding useful information in the collection. Recommendation systems attempt to extract such useful information by capturing and mining one or more measures of the usefulness of the data. The existing Information Filtering system has the shortcoming that it must have user's profile. And Collaborative Filtering system has the shortcoming that users have to rate each web document first and in high-quantity, low-quality environments, users may cover only a tiny percentage of documents available. And dynamic recommendation system using the user browsing pattern also provides users with unrelated web documents. This paper classifies these web documents using the similarity between the web documents under the web document type and extracts the user browsing sequential pattern DB using the users' session information based on the web server log file. When user approaches the web document, the proposed Dynamic recommendation system recommends Top N-associated web documents set that has high similarity between current web document and other web documents and recommends set that has sequential specificity using the extracted informations and users' session information.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.117-140
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• 2019

As the aging phenomenon accelerates and various social problems related to the elderly of the vulnerable are raised, the need for effective elderly care solutions to protect the health and safety of the elderly generation is growing. Recently, more and more people are using Smart Toys equipped with ICT technology for care for elderly. In particular, log data collected through smart toys is highly valuable to be used as a quantitative and objective indicator in areas such as policy-making and service planning. However, research related to smart toys is limited, such as the development of smart toys and the validation of smart toy effectiveness. In other words, there is a dearth of research to derive insights based on log data collected through smart toys and to use them for decision making. This study will analyze log data collected from smart toy and derive effective insights to improve the quality of life for elderly users. Specifically, the user profiling-based analysis and elicitation of a change in quality of life mechanism based on behavior were performed. First, in the user profiling analysis, two important dimensions of classifying the type of elderly group from five factors of elderly user's living management were derived: 'Routine Activities' and 'Work-out Activities'. Based on the dimensions derived, a hierarchical cluster analysis and K-Means clustering were performed to classify the entire elderly user into three groups. Through a profiling analysis, the demographic characteristics of each group of elderlies and the behavior of using smart toy were identified. Second, stepwise regression was performed in eliciting the mechanism of change in quality of life. The effects of interaction, content usage, and indoor activity have been identified on the improvement of depression and lifestyle for the elderly. In addition, it identified the role of user performance evaluation and satisfaction with smart toy as a parameter that mediated the relationship between usage behavior and quality of life change. Specific mechanisms are as follows. First, the interaction between smart toy and elderly was found to have an effect of improving the depression by mediating attitudes to smart toy. The 'Satisfaction toward Smart Toy,' a variable that affects the improvement of the elderly's depression, changes how users evaluate smart toy performance. At this time, it has been identified that it is the interaction with smart toy that has a positive effect on smart toy These results can be interpreted as an elderly with a desire to meet emotional stability interact actively with smart toy, and a positive assessment of smart toy, greatly appreciating the effectiveness of smart toy. Second, the content usage has been confirmed to have a direct effect on improving lifestyle without going through other variables. Elderly who use a lot of the content provided by smart toy have improved their lifestyle. However, this effect has occurred regardless of the attitude the user has toward smart toy. Third, log data show that a high degree of indoor activity improves both the lifestyle and depression of the elderly. The more indoor activity, the better the lifestyle of the elderly, and these effects occur regardless of the user's attitude toward smart toy. In addition, elderly with a high degree of indoor activity are satisfied with smart toys, which cause improvement in the elderly's depression. However, it can be interpreted that elderly who prefer outdoor activities than indoor activities, or those who are less active due to health problems, are hard to satisfied with smart toys, and are not able to get the effects of improving depression. In summary, based on the activities of the elderly, three groups of elderly were identified and the important characteristics of each type were identified. In addition, this study sought to identify the mechanism by which the behavior of the elderly on smart toy affects the lives of the actual elderly, and to derive user needs and insights.

• Journal of Intelligence and Information Systems
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• v.13 no.3
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• pp.83-99
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• 2007

Nowadays, the advancement of digital information technology resulting in the increased interest of the management and the use of information has given stimulus to the research on the use and management of information. In this paper, we propose an integrated data mining model that can provide the necessary information and interface to users of scientific information portal service according to their respective classification groups. The integrated model classifies users from log files automatically collected by the web server based on users' behavioral patterns. By classifying the existing users of the web site, which provides information service, and analyzing their patterns, we proposed a web site utilization methodology that provides dynamic interface and user oriented site operating policy. In addition, we believe that our research can provide continuous web site user support, as well as provide information service according to user classification groups.

• Journal of Microbiology and Biotechnology
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• v.28 no.5
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• pp.796-808
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• 2018

The intracellular bacterium Wolbachia pipientis is widespread in arthropods. Recently, possibilities of novel Wolbachia-mediated hosts, their distribution, and natural rate have been anticipated, and the coconut leaf beetle Brontispa longissima (Gestro) (Coleoptera: Chrysomelidae), which has garnered attention as a serious pest of palms, was subjected to this interrogation. By adopting Wolbachia surface protein (wsp) and multilocus sequence type (MLST) genotypic systems, we determined the Wolbachia infection density within host developmental stages, body parts, and tissues, and the results revealed that all the tested samples of B. longissima were infected with the same Wolbachia strain (wLog), suggesting complete vertical transmission. The MLST profile elucidated two new alleles (ftsZ-234 and coxA-266) that define a new sequence type (ST-483), which indicates the particular genotypic association of B. longissima and Wolbachia. The quantitative real-time PCR analysis revealed a higher infection density in the eggs and adult stage, followed by the abdomen and reproductive tissues, respectively. However, no significant differences were observed in the infection density between sexes. Moreover, the wsp and concatenated MLST alignment analysis of this study with other known Wolbachia-mediated arthropods revealed similar clustering with distinct monophyletic supergroup B. This is the first comprehensive report on the prevalence, infection dynamics, and phylogeny of the Wolbachia endosymbiont in B. longissima, which demonstrated that Wolbachia is ubiquitous across all developmental stages and distributed in the entire body of B. longissima. Understanding the Wolbachia infection dynamics would provide useful insight to build a framework for future investigations, understand its impacts on host physiology, and exploit it as a potential biocontrol agent.

• Journal of Advanced Navigation Technology
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• v.8 no.1
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• pp.73-80
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• 2004

In the case of Non-Line-of-Sight (NLOS), common telecommunication systems typically have Rayleigh distributed amplitude characteristics. However measurement result of Ultra Wideband (UWB) Multi-Band Orthogonal Frequency Division Multiplexing (MB-OFDM) system which is proposed as one of candidate standard in IEEE 802. 15. 3a for Wireless Personal Area Network (WPAN) shows that it has independent log normal fading in each cluster as well as in each ray within the cluster. Based on this clustering phenomenon observed, MB-OFDM channel model derived from Saleh-Valenzuela model with a couple of slight modifications. In this paper, channel remodeling for RF frequency hopping in MB-OFDM system is achieved, and performances of MB-OFDM system for each channel mode and data rate are verified using modified channel model.