• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2002.11a
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• pp.3-13
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• 2002

고석하 등(2002)은 인터넷 소매상이 상품 품목의 명목 가격과 배송료를 이용해서 고객의 일회 총 구매 비용을 조절한다는 것을 밝혔다. 고석하 등(2002)은 같은 내용의 상품 조합을 인터넷 시장에서 구매하기 위한 비용과 전통 시장에서 구매하기 위한 비용을 비교하였다. 분석 결과, 그 교호작용과 함께, 상품 종류와 일회 구매액/가격의 크기의 두 요소가 인터넷 시장의 전통 시장에 대한 총 구매비용 할인율의 변동의 약 60％내지 80％를 설명할 수 있다는 것을 보여주었다. 한편, 구매액/가격은 인터넷 시장에서의 해당 산포도(전통 시장의 그것에 대비한)에는 거의 영향을 미31지 못하며, 상품의 종류도 산포도에는 할인율에서와 같이 큰 영향을 미치지 않았다. 인터넷 시장의 가격이나 구매비용 산포도는 상품 특성이나 구매액 크기 이외의 다른 요인에 의해서 주로 영향을 받는 것으로 나타났다. 따라서, 본 논문에서는 가격 요인 이외의 경제적 경쟁요인에 관한 실증연구로서, 2002년 6월 17일부터 20일까지, 소프트웨어, PC와 주변기기, 휴대폰, 가전제품, CD, 화장품, 그리고 책의 7가지 산업 전문 쇼핑몰과 종합 쇼핑몰을 대상으로, 인터넷 시장에서 수행되고 있는 경제적인 비가격 경쟁요인에 관한 실증 조사를 실시하였다. 조사 결과, 인터넷 시장에서 수행되고 있는 경제적인 비가격 경쟁요인은 매우 다양하며, 상품별로도 다른 특성을 보이고 있는 것으로 밝혀졌다. 인터넷 소매상의 경제적인 비가격 경쟁요인은 크게 배송료 면제와 배송료 외 인센티브 제도로 구분된다. 본 논문에서는 경제적인 비가격 경쟁요인의 모든 경우의 수를 고려할 수 있도록, 코드표를 작성하여 정리하고 분석하였다.기호로 인식하였다. 실험결과, 표준패턴을 음표와 비음표의 두개의 그룹으로 나누어 인식함으로써 DP 매칭의 처리 속도를 개선시켰고, 국소적인 변형이 있는 패턴과 특징의 수가 다른 패턴의 경우에도 좋은 인식률을 얻었다.리되고 이원화된 코드체계와 데이터 형태의 이질화를 통일하는 방법으로 데이터웨어하우스 시스템을 제시하였다. 결국 병원에서 데이터웨어하우스 시스템의 구축은 임상, 연구, 교육의 유기적 순환관계를 정립하여 지식의 순환적 고리인 수집, 공유, 확산, 재창출을 지속적 유지할 수 있는 인프라를 구축해 준다. 반면 상이한 정보들간의 충돌과 이에 따른 해석의 오류로 잘못된 의사결정을 위한 정보를 제공할 수 있고 기초정보의 접근 및 추출의 유용성에 의해서 정보유출에 대한 문제가 한계점으로 나타났다.로세스 개선을 위해서 무엇을 정말로 필요로 하는지를 밝힘으로써, 한국 소프트웨어 산업의 현실적인 특수성을 고려한 소프트웨어 프로세스 평가와 개선 모델의 개발을 위한 기초적인 자료를 제공할 것으로 예상된다. 또한, 본 연구 결과는, 우리나라 소프트웨어 조직들이 실제로 무엇을 필요로 하는지를 밝힘으로써, 우리나라의 소프트웨어 산업을 육성하기 위한 실효성 있는 정책 입안을 위한 기초 자료를 제공할 것으로 예상된다.를 검증하려고 한다. 협력체계 확립, ${\circled}3$ 전문인력 확보 및 인력구성 조정, 그리고 ${\circled}4$ 방문보건사업의 강화 등이다., 대사(代謝)와 관계(關係)있음을 시사(示唆)해 주고 있다.ble nutrient (TDN) was highest in booting stage (59.7%); however no sig

• Korean Journal of Ecology and Environment
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• v.57 no.2
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• pp.83-91
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• 2024

This study utilizes association rule learning and clustering analysis to explore the co-occurrence and relationships within ecosystems, focusing on the endangered brackish-water snail Clithon retropictum, classified as Class II endangered wildlife in Korea. The goal is to analyze co-occurrence patterns between brackish-water snails and other species to better understand their roles within the ecosystem. By examining co-occurrence patterns and relationships among species in large datasets, association rule learning aids in identifying significant relationships. Meanwhile, K-means and hierarchical clustering analyses are employed to assess ecological similarities and differences among species, facilitating their classification based on ecological characteristics. The findings reveal a significant level of relationship and co-occurrence between brackish-water snails and other species. This research underscores the importance of understanding these relationships for the conservation of endangered species like C. retropictum and for developing effective ecosystem management strategies. By emphasizing the role of a data-driven approach, this study contributes to advancing our knowledge on biodiversity conservation and ecosystem health, proposing new directions for future research in ecosystem management and conservation strategies.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.40 no.4
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• pp.193-205
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• 2003

There has been so many research activities about robot soccer system in the many research fields, for example, intelligent control, communication, computer technology, sensor technology, image processing, mechatronics. Especially researchers research strategy for attacking in the field of strategy, and develop intelligent strategy. Then, soccer robots cannot defense completely and efficiently by using simple defense strategy. Therefore, intention extraction of attacker is needed for efficient defense. In this thesis, intention extractor of soccer robots is designed and developed based on FMMNN(Fuzzy Min-Max Neural networks ). First, intention for soccer robot system is defined, and intention extraction for soccer robot system is explained.. Next, FMMNN based intention extractor for soccer robot system is determined. FMMNN is one of the pattern classification method and have several advantages: on-line adaptation, short training time, soft decision. Therefore, FMMNN is suitable for soccer robot system having dynamic environment. Observer extracts attack intention of opponents by using this intention exactor, and this intention extractor is also used for analyzing strategy of opponent team. The capability of developed intention extractor is verified by simulation of 3 vs. 3 robot succor simulator. It was confirmed that the rates of intention extraction each experiment increase.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.85-107
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• 2019

Online consumers browse products belonging to a particular product line or brand for purchase, or simply leave a wide range of navigation without making purchase. The research on the behavior and purchase of online consumers has been steadily progressed, and related services and applications based on behavior data of consumers have been developed in practice. In recent years, customization strategies and recommendation systems of consumers have been utilized due to the development of big data technology, and attempts are being made to optimize users' shopping experience. However, even in such an attempt, it is very unlikely that online consumers will actually be able to visit the website and switch to the purchase stage. This is because online consumers do not just visit the website to purchase products but use and browse the websites differently according to their shopping motives and purposes. Therefore, it is important to analyze various types of visits as well as visits to purchase, which is important for understanding the behaviors of online consumers. In this study, we explored the clustering analysis of session based on click stream data of e-commerce company in order to explain diversity and complexity of search behavior of online consumers and typified search behavior. For the analysis, we converted data points of more than 8 million pages units into visit units' sessions, resulting in a total of over 500,000 website visit sessions. For each visit session, 12 characteristics such as page view, duration, search diversity, and page type concentration were extracted for clustering analysis. Considering the size of the data set, we performed the analysis using the Mini-Batch K-means algorithm, which has advantages in terms of learning speed and efficiency while maintaining the clustering performance similar to that of the clustering algorithm K-means. The most optimized number of clusters was derived from four, and the differences in session unit characteristics and purchasing rates were identified for each cluster. The online consumer visits the website several times and learns about the product and decides the purchase. In order to analyze the purchasing process over several visits of the online consumer, we constructed the visiting sequence data of the consumer based on the navigation patterns in the web site derived clustering analysis. The visit sequence data includes a series of visiting sequences until one purchase is made, and the items constituting one sequence become cluster labels derived from the foregoing. We have separately established a sequence data for consumers who have made purchases and data on visits for consumers who have only explored products without making purchases during the same period of time. And then sequential pattern mining was applied to extract frequent patterns from each sequence data. The minimum support is set to 10%, and frequent patterns consist of a sequence of cluster labels. While there are common derived patterns in both sequence data, there are also frequent patterns derived only from one side of sequence data. We found that the consumers who made purchases through the comparative analysis of the extracted frequent patterns showed the visiting pattern to decide to purchase the product repeatedly while searching for the specific product. The implication of this study is that we analyze the search type of online consumers by using large - scale click stream data and analyze the patterns of them to explain the behavior of purchasing process with data-driven point. Most studies that typology of online consumers have focused on the characteristics of the type and what factors are key in distinguishing that type. In this study, we carried out an analysis to type the behavior of online consumers, and further analyzed what order the types could be organized into one another and become a series of search patterns. In addition, online retailers will be able to try to improve their purchasing conversion through marketing strategies and recommendations for various types of visit and will be able to evaluate the effect of the strategy through changes in consumers' visit patterns.

• Korean Journal of Environment and Ecology
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• v.36 no.5
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• pp.507-524
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• 2022

In this study, we revealed the location environment and community structural characteristics after extensively investigating Korea's warm-temperate island areas and categorizing vegetation through TWINSPAN analysis. Based on it, this study aims to suggest the direction of the vegetation restoration plan for warm-temperate forests by deriving a restoration strategy for each vegetation type. The vegetation types were clearly divided into eight types, and communities I through IV were good evergreen broad-leaved forests dominated by Machilus thunbergii and Castanopsis sieboldii. On the other hand, communities V through VIII were Pinus thunbergii forest, deciduous broad-leaved forest, and artificial forest, and retrogressive succession vegetation in the warm-temperate areas. The environmental factors derived from the DCA analysis were altitude (average temperature of the coldest month) and distance from the coastline (salt tolerance). The distribution pattern of warm-temperate forests has been categorized into M. thunbergii, C. sieboldii and Cyclobalanopsis spp. forest types according to the two environmental factors. It is reasonable to apply the three vegetation types as restoration target vegetation considering the location environment of the restoration target site. In communities V through VIII, P. thunbergiiand deciduous broad-leaved formed a canopy layer, and evergreen broad-leaved species with strong seed expansion frequently appeared in the ground layer, raising the possibility of vegetation succession as evergreen broad-leaved forests. The devastated land where forests have disappeared in the island areas is narrow, but vegetation such as P. thunbergii and deciduous broad-leaved forests, which have become a retrogressive succession, forms a large area. The restoration strategy of renewing this area into evergreen, broad-leaved forests should be more effective in realizing carbon neutrality and promoting biodiversity.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.81-84
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• 2000

Rotating machine is used extensively and plays important roles in the industrial field. Therefore when rotating machine get out of order, it is necessary to know reasons then deal with the troubles immediately. So many studies far diagnosis of rotating machine are being done. However by this time most of study has an interest in gaining a high recognition But without considering error $rate^{(1)(2)(3)}$ , it is not desirable enough to apply h the actual application system. If the manager of system receives the result misjudging the condition of rotating machine and takes measures, we would lose heavily. So in order to play the creditable diagnosis, we must consider error rate. T h ~ t is. it must be able to reject the result of misjudgment. This study uses nearest neighbor classifier for diagnosis of rotating $machine^{(4)(8)}$ And the Smith's rejection $method^{(1)}$ used to recognize handwritten charter is done. Consequently creditable diagnosis of rotating machine is proposed.

• The Journal of the Convergence on Culture Technology
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• v.6 no.3
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• pp.45-55
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• 2020

Recently, as the awareness of fine dust has increased in Korea, various countermeasures have been suggested. This study examines the current status of fine dust free zones at home and abroad in order to analyze changes in guest space according to the occurrence of fine dust and to find activity patterns. I would like to predict and find implications. The purpose of this study is to forecast demand centering on domestic and foreign countermeasures for dust and domestic industry. In order to secure competitiveness for the smart city in the era of the 4th Industrial Revolution, the research is aimed at proposing a strategic plan to cope with the fine dust that is a threat to urban space. The research method is described in the following order.

• Journal of Digital Contents Society
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• v.15 no.3
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• pp.339-346
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• 2014

VOD Service, which has established a solid foothold as a profit model of digital broadcasting companies, is emerging as a key application of the N-screen technologies and services. In the circumstance, broadcasting companies are trying to promoting their VOD services by providing mobile services for improving the VOD service usability. The paper introduces a VOD mobile app (of a domestic digital cable broadcasting), which includes the functions of promoting the VOD programs and events printed on a VOD guide book, directly transmitting the information (e.g., book-marking and remote-control signals) to a set-top box, and watching the video contents stored in the mobile device on TV.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.3
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• pp.52-58
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• 2002

The purpose of condition monitoring and fault diagnosis is to detect faults occurring in machinery in order to improve the level of safety in plants and reduce operational and maintenance costs. The recognition performance is important not only to gain a high recognition rate bur a1so to minimize the diagnosis failures error rate by using off effective rejection module. We examined the problem of performance evaluation for the rejection scheme considering the accuracy of individual c1asses in order to increase the recognition performance. We use the Smith's method among the previous studies related to rejection method. Nearest neighbor classifier is used for classifying the machine conditions from the vibration signals. The experiment results for the performance evaluation of rejection show the modified optimum rejection method is superior to others.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.841-843
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• 2005

최근에 들어서 전력산업에 규제완화가 도입되면서 환경이 급변하고 있는 실정이다. 여러 가지의 환경변화가 예상되지만, 그 중에서도 공급자간에 경쟁 도입이 전력산업 참여자간에 주요 이슈로 부상하고 있다. 이와 같은 변화는 전력시스템의 기술 개발 뿐만 아니라 경영전략에도 큰 영향을 미치고 있으며, 대 수요자 서비스의 제공이 전략의 핵심이 되고 있다. 따라서 공급자는 보다 나은 서비스를 제공하기 위해서, 수요자 정보의 수집 및 분석을 해야 할 필요가 있다. 이와 같은 수요자 정보의 분석은 여러분야가 있지만 그 중에서도 수요특성을 파악하는 것이 가장 기본이 된다. 수요 특성은 원격검침시스템에서 수집되는 load profile 데이터로써 표현된다. 본 논문에서는 전력 수요자의 부하 특성을 분석하고 명가하기 위하여 수요특성별로 그룹으로 분류하는 방법을 개발하고, 분류된 그룹의 특징을 검토하였다. 이와 같은 부하분석의 정보는 가격설계, 수요 핀 에너지 예측, 송전 및 배전 계획, 에너지 효율 향상 및 부하관리의 필수 자료가 된다. 또한 향후에 개발될 전력 부가서비스의 주요 기반이 될 것으로 예상된다.