• Journal of Intelligence and Information Systems
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• v.16 no.1
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• pp.71-92
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• 2010

As the use of trading systems increases recently, many researchers are interested in developing intelligent trading systems using artificial intelligence techniques. However, most prior studies on trading systems have common limitations. First, they just adopted several technical indicators based on stock indices as independent variables although there are a variety of variables that can be used as independent variables for predicting the market. In addition, most of them focus on developing a model that predicts the direction of the stock market indices rather than one that can generate trading signals for maximizing returns. Thus, in this study, we propose a novel intelligent trading system that mitigates these limitations. It is designed to use both the technical indicators and the other non-price variables on the market. Also, it adopts 'two-threshold mechanism' so that it can transform the outcome of the stock market prediction model based on support vector machines to the trading decision signals like buy, sell or hold. To validate the usefulness of the proposed system, we applied it to the real world data-the KOSPI200 index from May 2004 to December 2009. As a result, we found that the proposed system outperformed other comparative models from the perspective of 'rate of return'.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.451-463
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• 2003

Recently, there have been various research efforts to develop strategies for accelerating OLAP operations on huge amounts of spatio-temporal data. Most of the work is based on multi-tree structures which consist of a single R-tree variant for spatial dimension and numerous B-trees for temporal dimension. The multi~tree based frameworks, however, are hardly applicable to spatio-temporal OLAP in practice, due mainly to high management cost and low query efficiency. To overcome the limitations of such multi-tree based frameworks, we propose a new approach called Hilbert Cube(H-Cube), which employs fractals in order to impose a total-order on cells. In addition, the H-Cube takes advantage of the traditional Prefix-sum approach to improve Query efficiency significantly. The H-Cube partitions an embedding space into a set of cells which are clustered on disk by Hilbert ordering, and then composes a cube by arranging the grid cells in a chronological order. The H-Cube refines cells adaptively to handle regional data skew, which may change its locations over time. The H-Cube is an adaptive, total-ordered and prefix-summed cube for spatio-temporal data warehouses. Our approach focuses on indexing dynamic point objects in static spatial dimensions. Through the extensive performance studies, we observed that The H-Cube consumed at most 20% of the space required by multi-tree based frameworks, and achieved higher query performance compared with multi-tree structures.

• Journal of Information Management
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• v.43 no.4
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• pp.191-210
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• 2012

Scholarly science citation data is typically of large volume and consists of a variety of data. Moreover, the volume of data is increasing more and more. Therefore, there are some requirements to store and manage the data efficiently and Korea Institute of Science and Technology Information (KISTI) develops Korea Science Citation Database (KSCD) which manage and serve very large-volume of korea science technique information including citation data. However, current services based on KSCD are not enough for various users. Thus, it is important issue to offer a variety of services using KSCD. For example, if a user searches articles described by a specific author, then a user may want to find not only the articles cited by a certain author but also those articles that study similar topics. However, it is not always easy to provide these services with citation data. Therefore, this paper surveys studies about services using citation data in order to find approaches for better utilizing KSCD. Especially, this paper considers data mining techniques, because data mining is one of the main techniques to extracting semantic information from big data. Therefore, this paper discusses methods for utilizing large volume of KSCD based on data mining technique.

• Korean Journal of Community Nutrition
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• v.22 no.5
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• pp.441-455
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• 2017

Objectives: The purpose of this study is to describe beverage patterns among healthy Korean adults and investigate their association with prevalence and components of metabolic syndrome. Methods: Subjects consisted of 6,927 Korean adults, aged 19-64 years in the $6^{th}$ Korea National Health and Nutrition Examination Survey (KNHANES, 2013-2015). Beverages were regrouped into twelve groups based on food codes and beverage intake (g/day) was assessed by 24-hour recall. Factor analysis was used to obtain beverage patterns. Waist circumference and body mass index (BMI) were used as anthropometric data; fasting blood glucose, triglyceride, high density lipoprotein (HDL), and blood pressure were used as biochemical indicators. The odds ratio (OR) for prevalence of metabolic syndrome and components of metabolic syndrome was assessed using logistic regression analysis. Results: Three beverage patterns were identified using factor analysis: 1) carbonated soft drinks 2) coffee (without added sugar or powdered creamer), and 3) alcoholic beverages. Subjects with high scores for the carbonated soft drink and coffee without added sugar or powdered creamer patterns were younger and subjects with high scores for the alcoholic beverage pattern were older. There were significant differences in gender distribution in all three beverage patterns, with men more likely to have high scores for carbonated soft drink and alcoholic beverage patterns. On the other hand, women were more likely to have higher scores for coffee without added sugar or powdered creamer pattern. Within each pattern, there were significant differences in sociodemographic and lifestyle characteristics such as education, household income, frequency of eating out, and smoking status according to the quartile of pattern scores. Alcoholic beverages and carbonated soft drinks patterns were associated with an increased levels of metabolic syndrome components, but coffee without added sugar or powdered creamer was not associated with any of metabolic syndrome components in healthy Korean adults after adjusting for age, sex, education, BMI, weight management, household income, smoking status, frequency of eating out, and energy intake. Conclusions: Alcoholic beverages and carbonated soft drinks patterns are associated with increased levels of metabolic syndrome components while coffee without added sugar or powdered creamer pattern is not associated with any of metabolic syndrome components in healthy Korean adults.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.42 no.2
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• pp.166-172
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• 1997

This experiment was carried out to clarify the effect of the deep water irrigation on dry-seeded rice cultivation at the three different water managements-deep continuous flooding(DCF), water saving irrigation(WSI), ordinary irrigation(OI). The highest tillering numbers per $m^2$ of rice were 551, 466 and 455 in OI, WSI and DCF, respectively. The tillering number of rice plants were significantly reduced in DCF. Heading date was delayed and the total chlorophyll content in leaf after heading was higher in DCF than those in other irrigation methods. For the characteristics associated with lodging, the culm length in DCF was slightly elongated and the diameter of culm in DCF was thicker than that in WSI and OI. The breaking weight and bending moment in DCF also were higher than those in others. As the result, although the culm length in DCF was long, the lodging index was comparatively low. The panicle length in DCF was longer than in OI and WSI. The spikelet number per $m^2$ and 1,000-grain weight were the most in WSI, while panicle number, ripened grain ratio and grain weight were not significantly different. Longer panicle length and more spikelet number resulted in higher yielding capacity in DCF.

• Archives of design research
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• v.17 no.3
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• pp.111-122
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• 2004

The purpose of this study are two the first is to identify the positioning of product design and analyze its functional relationship with product development, manufacturing, marketing and sales in the comprehensive competitiveness evaluation model ; and the second is to estimate the determinants of QCI(quality competitiveness index), analyze the impact of product design on QCI, and compare the aforementioned results for the seven industrial sectors and the five product patterns. For this empirical analysis, this study surveyed 400 Korean manufacturing firms during August-October 2003. The major empirical findings are summarized as follows : First, the hypothesis on the positive effect of product design on QCI is accepted at a highly significant level (p < 0.001) for all : the manufacturing sector, seven industrial sectors, and five product categories. Second, the correlation analysis and factor analysis lead to the result that the effect of product design on QCI is estimated to be relatively very low, in comparison to those of product functionality and basic performance on QCI. These findings imply that Korean manufacturing sector has been still in the prematured stage at which product design has not played an important role yet. This study concludes that product design in line with other functions (product development, manufacturing, marketing, and sales) should make a good contribution to the improvement of QCI in the future.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.06a
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• pp.233-239
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• 2001

최근 대부분의 회사들은 업무를 수행하는데 필요한 지식과 노하우를 공유하고 재사용하기 위하여 지적 자산 관리의 중요성을 인식하고 있다. 특히 고도로 지식 집약적인 업종이라 할 수 있는 IT컨설팅 회사에서는 지적 자산의 관리가 다른 어떤 회사에서보다 큰 중요성을 가지게 된다. 컨설팅 회사에 있어서 검증이 완료된 지적 자산의 공유 및 지능적이면서도 신속한 검색은 컨설팅 서비스의 품질과 고객 만족에 직결되는 중요한 요소이다. 따라서 대부분의 컨설팅 회사들은 자사의 지식 자산을 관리하기 위하여 많은 노력을 기울이고 있다. 본 논문의 목적은 IT 컨설팅 회사예서 관리되는 다양한 형태의 지적 자산들을 중앙 관리하여 설친 고객 사이트에 흩어져 프로젝트를 수행하는 컨설턴트들이 공유할 수 있도록 함으로써 컨설팅 서비스의 생산성과 품질들 높이고자 하는데 있다 이를 위하여 건설팅 회사에서 관리되는 모든 지적 자산의 재고를 조사하여 모델링하고 이를 쉽게 저장하고 검색할 수 있는 시스템 아키텍처를 제안한다. 제안된 아키텍처를 NT 기반에서 Index server를 이용하여 시스템으로 구현하였다 (KMSCR: A Knowledge Management System for managing Consulting Resources). KMSCR에서는 컨설턴트가 찾고자 하는 검색어를 입력하면 다양한 포맷의 (.doc, .ppt, xls, .rtf, .txt, .html 등과 같은) 결과물을 관련성이 높은 순서대로 출력해 줌으로써 컨설팅 리소스를 효과적으로 재사용할 수 있도록 도와 준다. 또한 검색 시에는 미리 등록된 키워드 뿐 아니라 본문 내의 텍스트 검색까지 가능하게 함으로써 컨설팅 리소스에 대한 보다 효과적이고 효율적인 검색을 가능하게 한다.간을 성능 평가 인자로 하여 수행하였다. 논문에서 제한된 방법을 적용한 개선된 RICH-DP을 모의 실험을 통하여 분석한 결과 기존의 제한된 RICH-DP는 실시간 서비스에 대한 처리율이 낮아지며 서비스 시간이 보장되지 못했다. 따라서 실시간 서비스에 대한 새로운 제안된 기법을 제안하고 성능 평가한 결과 기존의 RICH-DP보다 성능이 향상됨을 확인 할 수 있었다.(actual world)에서 가상 관성 세계(possible inertia would)로 변화시켜서, 완수동사의 종결점(ending point)을 현실세계에서 가상의 미래 세계로 움직이는 역할을 한다. 결과적으로, IMP는 완수동사의 닫힌 완료 관점을 현실세계에서는 열린 미완료 관점으로 변환시키되, 가상 관성 세계에서는 그대로 닫힌 관점으로 유지 시키는 효과를 가진다. 한국어와 영어의 관점 변환 구문의 차이는 각 언어의 지속부사구의 어휘 목록의 전제(presupposition)의 차이로 설명된다. 본 논문은 영어의 지속부사구는 논항의 하위간격This paper will describe the application based on this approach developed by the authors in the FLEX EXPRIT IV n$^{\circ}$EP29158 in the Work-package "Knowledge Extraction & Data mining"where the information captured from digital newspapers is extracted and reused in tourist information context.terpolation performance of CNN was relatively

• Journal of Information Management
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• v.40 no.3
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• pp.79-97
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• 2009

Thanks to current development of many search engines and web technologies, a new semantic searching technology appears, featuring giving a relevant meaning to the keyword beyond the previous keyword search service. On the wave of advance of various search engines, the enhancement of OASIS offered by KIOM is needed as well. To do this, KIOM examined demographic and sociological analysis on their position, status, and career, the convenience of OASIS, and the value of papers offered in OASIS from members who have ever used it. Furthermore, the importance of each area involved in oriental medicine is also examined in terms of a new direction for OASIS improvement. Based on the result of the user survey, it turned out that not only an automatic search system that can find meaning of chinese character-centered key words but also a Authority-system which can distinguish homonym beyond simple keyword search system should be introduced quickly. Also, we reached the conclusion that it is necessary to interconnect a citation index information on references with laboratory information of the agencies concerned and interconnect major web sites around the world by using Open API. OASIS is the only domestic web site for offering papers that cover oriental medicine. Therefore, if requirements about the site in oriental medical circles are analyzed sufficiently and the problems of its information search system are improved, OASIS is expected to play a critical role in the development of oriental medicine.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2000.11a
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• pp.247-256
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• 2000

오늘날의 기업은 상품을 판매하는 것 뿐만 아니라 기업의 신용과 이미지를 위해 그 상품에 대한 사후처리(After Service) 업무에 많은 투자를 하고 있다. 이러한 양질의 사후서비스를 고객에게 공급하기 위해서는 많은 인력을 합리적으로 관리해야 하고 요청되는 고장수리 서비스 업무를 빠르게 해결하기 위해서는 업무를 인력들에게 합리적으로 배정을 하고 회사의 비용을 최소화하면서 정해진 시간에 요청된 작업을 처리하기 위해서는 인력들에게 작업을 배정하고 스케줄링하는 문제가 발생된다. 본 논문에서는 이러한 문제를 해결하기 위해 화학계기의 A/S 작업을 인력에게 합리적으로 배정하는 스케줄링 시스템에 관한 연구이다. 먼저 스케줄링 모델을 HP 사의 화학분석 및 시스템을 판매, 유지보수 해 주는 "영진과학(주)"회사의 작업 스케줄을 분석하여 필요한 도메인과 고객서비스전략과 인력관리전략에서 제약조건을 추출하였고 여기에 스케줄링 문제를 해결하기 위한 방법으로 제약만족문제(CSP) 해결기법인 도메인 여과기법을 적용하였다. 도메인 여과기법은 제약조건에 의해 변수가 갖는 도메인의 불필요한 부분을 여과하는 것으로 제약조건과 관련되어 있는 변수의 도메인이 축소되는 것이다. 또한, 스케줄링을 하는데에 있어서 비용적인 측면에서의 스케줄링방법과 고객 만족도에서의 스케줄링 방법을 비교하여 가장 이상적인 해를 찾는데 트래이드오프(Trade-off)를 이용하여 최적의 해를 구했으며 실험을 통해 인력에게 더욱 효율적으로 작업들을 배정 할 수 있었고 또한, 정해진 시간에 많은 작업을 처리 할 수 있었으며 작업을 처리하는데 있어 소요되는 비용을 감소하는 결과를 얻을 수 있었다. 검증하였다.를, 지지도(support), 신뢰도(confidence), 리프트(lift), 컨빅션(conviction)등의 관계를 통해 다양한 방법으로 모색해본다. 이 연구에서 제안하는 이러한 개념계층상의 흥미로운 부분의 탐색은, 전자 상거래에서의 CRM(Customer Relationship Management)나 틈새시장(niche market) 마케팅 등에 적용가능하리라 여겨진다.선의 효과가 나타났다. 표본기업들을 훈련과 시험용으로 구분하여 분석한 결과는 전체적으로 재무/비재무적 지표를 고려한 인공신경망기법의 예측적중률이 높은 것으로 나타났다. 즉, 로지스틱회귀 분석의 재무적 지표모형은 훈련, 시험용이 84.45%, 85.10%인 반면, 재무/비재무적 지표모형은 84.45%, 85.08%로서 거의 동일한 예측적중률을 가졌으나 인공신경망기법 분석에서는 재무적 지표모형이 92.23%, 85.10%인 반면, 재무/비재무적 지표모형에서는 91.12%, 88.06%로서 향상된 예측적중률을 나타내었다.ting LMS according to increasing the step-size parameter $\mu$ in the experimentally computed. learning curve. Also we find that convergence speed of proposed algorithm is increased by (B+1) time proportional to B which B is the number of recycled data buffer without complexity

• Journal of Korea Water Resources Association
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• v.50 no.11
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• pp.769-779
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• 2017

As the occurrence of drought is recently on the rise, the reliable drought forecasting is required for developing the drought mitigation and proactive management of water resources. This study developed a probabilistic hydrological drought forecasting method using the Bayesian Networks and drought propagation relationship to estimate future drought with the forecast uncertainty, named as the Propagated Bayesian Networks Drought Forecasting (PBNDF) model. The proposed PBNDF model was composed with 4 nodes of past, current, multi-model ensemble (MME) forecasted information and the drought propagation relationship. Using Palmer Hydrological Drought Index (PHDI), the PBNDF model was applied to forecast the hydrological drought condition at 10 gauging stations in Nakdong River basin. The receiver operating characteristics (ROC) curve analysis was applied to measure the forecast skill of the forecast mean values. The root mean squared error (RMSE) and skill score (SS) were employed to compare the forecast performance with previously developed forecast models (persistence forecast, Bayesian network drought forecast). We found that the forecast skill of PBNDF model showed better performance with low RMSE and high SS of 0.1~0.15. The overall results mean the PBNDF model had good potential in probabilistic drought forecasting.