• Journal of the Korea Convergence Society
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• v.10 no.4
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• pp.65-71
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• 2019

The purpose of this study was to investigate the relationship between cardiovascular disease and periodontal disease. The subjects were 3,149 adults over 40 years of age using the third year National Health and Nutrition Examination Survey (2015). Data were analyzed using the SPSS 22.0 program. As a result, the relationship between cardiovascular disease and periodontal disease was 1.27 times higher in obesity group compared to normal group, when adjusted for disturbance variables (age, smoking status, drinking status, income) In hypertensive patients, the hypertension group had a 1.32-fold higher risk of periodontal disease when the disturbance variables (age, smoking status, drinking status, income) were adjusted compared to those without hypertension. Therefore, cardiovascular disease is associated with periodontal disease, and it can be used as a good basis for educational and preventive measures to reduce or prevent the incidence of cardiovascular disease and periodontal disease in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.264-266
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• 2022

In order to apply the RNN model to the radio fingerprint-based indoor path generation technology, the data set must be continuous and sequential. However, Wi-Fi radio fingerprint data is not suitable as RNN data because continuity is not guaranteed as characteristic information about a specific location at the time of collection. Therefore, continuity information of sequential positions should be given. For this purpose, clustering is possible through classification of each region based on signal data. At this time, the continuity information between the clusters does not contain information on whether actual movement is possible due to the limitation of radio signals. Therefore, correlation information on whether movement between adjacent clusters is possible is required. In this paper, a deep learning network, a recurrent neural network (RNN) model, is used to predict the path of a moving object, and it reduces errors that may occur when predicting the path of an object by generating continuous location information for path generation in an indoor environment. We propose a method of giving correlation between clustering for generating an improved moving path that can avoid erroneous path prediction that cannot move on the predicted path.

• Journal of the Korean Ceramic Society
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• v.28 no.6
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• pp.443-450
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• 1991

Microstructures of tantalum oxide, anodic-oxidized in oxalic acid, are shown to be related to voltage-time characteristics during formation reaction. It is observed that a crystalline phase transformed from an amorphous phase is recrystallized in the presence of the high electric field within the film, and this recrystallized film has a very porous microstructure. From the results of the XRD, the nonlinearity observed after the first spark voltage is recognized to be due to the local crystallization.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.27-42
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• 2020

Traditional companies with offline stores were unable to secure large display space due to the problems of cost. This limitation inevitably allowed limited kinds of products to be displayed on the shelves, which resulted in consumers being deprived of the opportunity to experience various items. Taking advantage of the virtual space called the Internet, online shopping goes beyond the limits of limitations in physical space of offline shopping and is now able to display numerous products on web pages that can satisfy consumers with a variety of needs. Paradoxically, however, this can also cause consumers to experience the difficulty of comparing and evaluating too many alternatives in their purchase decision-making process. As an effort to address this side effect, various kinds of consumer's purchase decision support systems have been studied, such as keyword-based item search service and recommender systems. These systems can reduce search time for items, prevent consumer from leaving while browsing, and contribute to the seller's increased sales. Among those systems, recommender systems based on association rule mining techniques can effectively detect interrelated products from transaction data such as orders. The association between products obtained by statistical analysis provides clues to predicting how interested consumers will be in another product. However, since its algorithm is based on the number of transactions, products not sold enough so far in the early days of launch may not be included in the list of recommendations even though they are highly likely to be sold. Such missing items may not have sufficient opportunities to be exposed to consumers to record sufficient sales, and then fall into a vicious cycle of a vicious cycle of declining sales and omission in the recommendation list. This situation is an inevitable outcome in situations in which recommendations are made based on past transaction histories, rather than on determining potential future sales possibilities. This study started with the idea that reflecting the means by which this potential possibility can be identified indirectly would help to select highly recommended products. In the light of the fact that the attributes of a product affect the consumer's purchasing decisions, this study was conducted to reflect them in the recommender systems. In other words, consumers who visit a product page have shown interest in the attributes of the product and would be also interested in other products with the same attributes. On such assumption, based on these attributes, the recommender system can select recommended products that can show a higher acceptance rate. Given that a category is one of the main attributes of a product, it can be a good indicator of not only direct associations between two items but also potential associations that have yet to be revealed. Based on this idea, the study devised a recommender system that reflects not only associations between products but also categories. Through regression analysis, two kinds of associations were combined to form a model that could predict the hit rate of recommendation. To evaluate the performance of the proposed model, another regression model was also developed based only on associations between products. Comparative experiments were designed to be similar to the environment in which products are actually recommended in online shopping malls. First, the association rules for all possible combinations of antecedent and consequent items were generated from the order data. Then, hit rates for each of the associated rules were predicted from the support and confidence that are calculated by each of the models. The comparative experiments using order data collected from an online shopping mall show that the recommendation accuracy can be improved by further reflecting not only the association between products but also categories in the recommendation of related products. The proposed model showed a 2 to 3 percent improvement in hit rates compared to the existing model. From a practical point of view, it is expected to have a positive effect on improving consumers' purchasing satisfaction and increasing sellers' sales.

• Journal of Technology Innovation
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• v.22 no.3
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• pp.1-35
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• 2014

This study analyzed convergence status among input technologies used in technology development with Technology I-O analysis. It was another version of industry input-output analysis which is used in technology planning. This case is an analysis of association between technology an product. The subjects of analysis were 401 tasks that applied to '2012 Convergence Technology Development Project for Small and Medium Businesses' promoted by Korea Technology & Information Promotion Agency for Small and Medium Enterprises. The process of analysis is as followed. First step, we made a matrix table as an input of technology input-output analysis. Input was defined by technology and output was defined by the product. Input technology was defined in a 3-digit code under National Science Technology Classification and output products were defined in a 5-digit under National Standard Industry Code. Second, the Spillover ratio among technologies were calculated and was used to make a picture of technology linkage. As a result of analysis, technology spillover of embedded S/W was the highest in IT convergence, mold product in ET convergence, and functional cosmetics development technology in BT convergence. In general, IT convergence had many element technologies with high technology spillover, and ET had a small number of element technologies with high technology spillover. Therefore, investment effect of element technology is expected to be large if investment on element technologies with high technology spillover is important for vitalizing convergence.

• Journal of Engineering Education Research
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• v.12 no.3
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• pp.31-40
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• 2009

In this paper, we consider the characteristics of information technology sectors women. By surveying IT women worker, we attempted to define the attributes of them and examine the problems and what they are needed to IT education following the changes in the highly competitive information technology industry. Especially, we used data mining tools says association analysis to analyze for the Women Information Scientist Association of Korea(WINSA) provides IT worker women with education packages and what is the general culture course from the point of IT employment view. The data was analyzed by SAS enterprise tools.

• Journal of the Korean Society for information Management
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• v.39 no.3
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• pp.1-22
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• 2022

The purpose of this study is to propose a book recommendation system that can be used in school libraries. The book recommendation system applies an algorithm based on association rules using DLS lending data and is designed to provide personalized book recommendation services to school library users. For this purpose, association rules based on the Apriori algorithm and betweenness centrality analysis were applied and detailed functions such as descriptive statistics, generation of association rules, student-centered recommendation, and book-centered recommendation were materialized. Subsequently, opinions on the use of the book recommendation system were investigated through in-depth interviews with teacher librarians. As a result of the investigation, opinions on the necessity and difficulty of book recommendation, student responses, differences from existing recommendation methods, utilization methods, and improvements were confirmed and based on this, the following discussions were proposed. First, it is necessary to provide long-term lending data to understand the characteristics of each school. Second, it is necessary to discuss the data integration plan by region or school characteristics. Third, It is necessary to establish a book recommendation system provided by the Comprehensive Support System for Reading Education. Based on the contents proposed in this study, it is expected that various discussions will be made on the application of a personalization recommendation system that can be used in the school library in the future.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.132-139
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• 2005

대한민국 정통부는 IT 산업의 경쟁력 강화를 통한 국가경제발전을 유도하기 위해 8대 서비스, 3대 인프라, 및 9대 신성장동력을 연계하여 시너지효과를 극대화하는 IT 839전략을 마련하여 강력하게 추진 중에 있다. 이러한 상황 하에 향후 IT시장의 선택과 집중을 통한 정책적 육성발전방향을 제시하기 위해서는 9대 신성장동력간 가치사슬에 대한 이해가 최우선 돼야 한다. 본 연구에서는 다차원척도법을 이용하여 IT 신성장 동력 간의 연관성 분석, 시간의 변화에 따른 이동방향 분석, 및 성장동력의 속성을 반영한 PROFIT분석 등을 실시하였다. 본 연구의 결과는 전략적 중요도가 큰 산업 및 분야를 선별 할 수 있을 뿐만 아니라, 효과적인 정책적 투자를 유도하기 위한 전략을 모색할 수 있을 것으로 기대가 된다.

• Journal of Korea Game Society
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• v.20 no.1
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• pp.133-142
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• 2020

Digital educational game market is growing as it expands to smart platforms such as smart phones and tablet PCs. As games have become digital in the classroom evolving to two-ways. In this paper, it designed that enables elementary students to acquire musical knowledge related to musicians through digital board games. By collecting achievement cards of musicians associated with. Elementary students repeatedly gain relevant musical knowledge in the end. The developed game was simulated using Petri net to check the gameplay flow.

• Journal of the Korean Society for information Management
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• v.35 no.1
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• pp.13-32
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• 2018

The purpose of this study is to analyze the association among the subject areas of big data research papers. The subject group of the units of analysis was extracted by applying co-citation networks, and the rules of association were analyzed using Apriori algorithm of R program, and visualized using the arulesViz package of R program. As a result of the study, 22 subject areas were extracted and these subjects were divided into three clusters. As a result of analyzing the association type of the subject, it was classified into 'professional type', 'general type', 'expanded type' depending on the complexity of association. The professional type included library and information science and journalism. The general type included politics & diplomacy, trade, and tourism. The expanded types included other humanities, general social sciences, and general tourism. This association networks show a tendency to cite other subject areas that are relevant when citing a subject field, and the library should consider services that use the association for academic information services.