개미 시스템을 이용한 무선 센서 네트워크 라우팅 알고리즘 개발

옥창수(Chang-Soo Ok) 한국경영과학회 2010 한국경영과학회지 Vol.35 No.2

This paper proposes an ant-based routing algorithm, Ant System-Routing in wireless Senor Networks(AS-RSN), for wireless sensor networks. Using a transition rule in Ant System, sensors can spread data traffic over the whole network to achieve energy balance, and consequently, maximize the lifetime of sensor networks. The transition rule advances one of the original Ant System by re-defining link cost which is a metric devised to consider energy-sufficiency as well as energy-efficiency. This metric gives rise to the design of the AS-RSN algorithm devised to balance the data traffic of sensor networks in a decentralized manner and consequently prolong the lifetime of the networks. Therfore, AS-RSN is scalable in the number of sensors and also robust to the variations in the dynamics of event generation. We demonstrate the effectiveness of the proposed algorithm by comparing three existing routing algorithms: Direct Communication Approach, Minimum Transmission Energy, and Self-Organized Routing and find that energy balance should be considered to extend lifetime of sensor network and increase robustness of sensor network for diverse event generation patterns.

장치산업의 라인별 평가를 위한 DEA-Super-Efficiency 모형에서의 정성적 평가자료의 활용

옥창수 ( Chang Soo Ok ),이영관 ( Young Kwan Lee ),하정훈 ( Chung Hun Ha ) (주)엘지씨엔에스(구 LGCNS 엔트루정보기술연구소) 2012 Entrue Journal of Information Technology Vol.11 No.2

본 연구는 화학 장치산업에서 생산라인 또는 의사결정단위를 평가하는 방안으로 개선된 DEA-Super-Efficiency 모델을 제안한다. 먼저, 화학산업 생산라인의 성과측정 또는 효율성을 평가하는데 고려되어야 하는 사항을 제시하고 이를 반영하기 위한 성과지표의 선정에 대하여 토의한다. 다품종 생산으로 인한 생산 효율 저하나 제조 난이도를 고려하기 위한 평가지표를 제안한다. 특히, 생산라인별 향후 수익 가능성이나 관련 산업의 시황에 따른 평가의 왜곡을 방지하기 위하여 경영층을 대상으로 설문조사를 실시하고 이 정성 데이터를 생산라인 평가에 활용한다. 이와 같이 생산라인의 공정한 평가를 위하여 정량적 데이터를 바탕으로한 여러 성과지표를 고려함과 동시에 각 생산라인의 가능성이나 예측 정보에 대한 정성 데이터를 활용하는 새로운 Super-Efficiency 모델을 제안하고 이에 대한 적용방법에 대하여 논의한다. This study proposes a new DEA-super-efficiency model utilizing qualitative data to evaluate production lines or DMUs (Decision Making Units) in chemical industry. We pointed out characteristics of chemical industry to be considered in evalua-tion of production lines. In consideration of these features a DEA-Super-Efficiency is devised to assess DMUs with several key performance indices(KPIs). The proposed model is capable of utilizing various KPIs simultaneously and discriminating efficient DMUs in the appraisal of production lines. In addition, it gives a way to utilize some qualitative information such as market impact and potential profit in assessment of DMUs. We demonstrate the effectiveness of our approach with a case study.

수요 예측 평가를 위한 가중절대누적오차지표의 개발

최대일(Dea-Il Choi)옥창수(Chang-Soo Ok) 한국산업경영시스템학회 2015 한국산업경영시스템학회지 Vol.38 No.3

Aggregate Production Planning determines levels of production, human resources, inventory to maximize company’s profits and fulfill customer's demands based on demand forecasts. Since performance of aggregate production planning heavily depends on accuracy of given forecasting demands, choosing an accurate forecasting method should be antecedent for achieving a good aggregate production planning. Generally, typical forecasting error metrics such as MSE (Mean Squared Error), MAD (Mean Absolute Deviation), MAPE (Mean Absolute Percentage Error), and CFE (Cumulated Forecast Error) are utilized to choose a proper forecasting method for an aggregate production planning. However, these metrics are designed only to measure a difference between real and forecast demands and they are not able to consider any results such as increasing cost or decreasing profit caused by forecasting error. Consequently, the traditional metrics fail to give enough explanation to select a good forecasting method in aggregate production planning. To overcome this limitation of typical metrics for forecasting method this study suggests a new metric, WACFE (Weighted Absolute and Cumulative Forecast Error), to evaluate forecasting methods. Basically, the WACFE is designed to consider not only forecasting errors but also costs which the errors might cause in for Aggregate Production Planning. The WACFE is a product sum of cumulative forecasting error and weight factors for backorder and inventory costs. We demonstrate the effectiveness of the proposed metric by conducting intensive experiments with demand data sets from M3-competition. Finally, we showed that the WACFE provides a higher correlation with the total cost than other metrics and, consequently, is a better performance in selection of forecasting methods for aggregate production planning.

아이템 연관성을 고려한 협력적 필터링 기반 추천시스템 개발

강호윤 ( Ho Yun Kang ),옥창수 ( Chang Soo Ok ) (주)엘지씨엔에스(구 LGCNS 엔트루정보기술연구소) 2015 Entrue Journal of Information Technology Vol.14 No.1

정보기술과 인터넷 기술의 발달로 전자상거래가 활성화되면서 추천시스템의 중요성이 증가하였다. 전자상거래에서 추천시스템은 사용자 개인 정보와 구매 이력을 통해 필요로 할 것이라 예상되는 상품을 사용자에게 추천해 준다. 추천시스템은 협력적 필터링과 군집모델, 그리고 검색 기반 방법 등 많은 연구가 수행되었다. 그러나 이러한 연구들은 상품 간의 연관성은 고려하지 않고 사용자 정보만을 가지고 상품을 추천해 주기 때문에 추천 상품의 정확도가 떨어진다. 본 연구에서는 이러한 문제점을 보안하기 위해 기존의 협력적 필터링 기법과 아마존에서 사용자고 있는 아이템 간 협력적 필터링 기법을 활용하여 혼합 추천시스템을 제안하고 이 추천시스템을 중소 제조기업을 위한 제조용 앱스토어에 적용한다. 본 연구에서 제안하는 추천시스템은 기존 연구에서 사용된 Recall과 Precision 두 척도의 조화평균 값으로 평가하였다. 평가 결과 제안한 추천시스템이 기존 협력적 필터링 보다 좀더 높은 정확도를 제공하는 것으로 나타났다. As glowing e-commerce markets, many websites for online shopping mall and B-to-B trading has emerged and, consequently, the websites need to differentiate themselves with their competitors. To obtain the goal e-commerce companies have considered recom-mender system as a business tool and the important of recommender system has increased. In e-commerce, recommender system help users find products which might be useful for user based on their personal and purchasing history information to acquire increase of sales and business superiority. Recommender system, collaborative filtering, cluster models, search-based methods, and many studies have been conducted. These studies, however, the quality of recommendation is relatively low, since those approaches consider user`s information only, without considering the correlation among products. In this study, in order to make up for these problems, a hybrid recommender system uti-lizing traditional collaborative filtering and item-to-item collaborative filtering is proposed. To demonstrate the effectiveness of the proposed algorithm is applied the manufacturing appstore (www.mfg-app.co.kr) and a user survey have conducted. The result of the analysis shows that our recommendation system is effective and provides more helpful recommendations to website users.

증례 : 호흡기 ; GM-CSF 흡입치료로 호전된 폐포단백증 1예

장복순 ( Bok Soon Chang ),노정원 ( Jung Won Noh ),옥창수 ( Chang Soo Ok ),이가연 ( Ga Yeon Lee ),손서영 ( Seo Young Sohn ),방선하 ( Sun Ha Bahng ),정만표 ( Man Pyo Chung ) 대한내과학회 2011 대한내과학회지 Vol.80 No.5

표준치료법인 전 폐하세척술에서 효과를 보지 못했던 폐포단백증 환자에서 GM-CSF 흡입법을 이용하여 임상적으로 증상, 폐기능, 흉부단층촬영에서 호전을 보인 증례를 보고하고자 한다. Pulmonary alveolar proteinosis (PAP) is a rare condition that is treated using whole lung lavage. A recent study suggested that granulocyte-macrophage colony stimulating factor (GM-CSF) plays roles in both the pathogenesis and treatment of PAP. We present a 69-year-old man with PAP who deteriorated despite bilateral whole lung lavage; that said, his symptoms, chest X-ray findings, and pulmonary function test improved after GM-CSF inhalation therapy over 12 months. GM-CSF therapy is an effective treatment modality for PAP.

공용환경 설계를 위한 선호도 기반 클러스터링

손기혁(Kihyuk Son),옥창수(Chang-Soo Ok) 한국산업경영시스템학회 2013 한국산업경영시스템학회지 Vol.36 No.1

In ubiquitous computing, shared environments adjust themselves so that all users in the environments are satisfied as possible. Inevitably, some of users sacrifice their satisfactions while the shared environments maximize the sum of all users ' satisfa ctions. In our previous work, we have proposed social welfare functions to avoid a situation which some users in the system face the worst setting of environments. In this work, we consider a more direct approach which is a preference based clustering to handle this issue. In this approach, first, we categorize all users into several subgroups in which users have similar tastes to environmental parameters based on their preference information. Second, we assign the subgroups into different time or space of the shared environments. Finally, each shared environments can be adjusted to maximize satisfactions of each subgroup and consequently the optimal of overall system can be achieved. We demonstrate the effectiveness of our approach with a numerical analysis.

시간대별 차등 전기요금을 고려한 최소비용 장비운용계획

김인호(In ho Kim),옥창수(Chang soo Ok) 한국산업경영시스템학회 2014 한국산업경영시스템학회지 Vol.37 No.4

As power consumption increases, more power utilities are required to satisfy the demand and consequently results in tremendous cost to build the utilities. Another issue in construction of power utilities to meet the peak demand is an inefficiency caused by surplus power during non-peak time. Therefore, most power company considers power demand management with time-based electricity rate policy which applies different rate over time. This paper considers an optimal machine operation problem under the time-based electricity rates. In TOC (Theory of Constraints), the production capacities of all machines are limited to one of the bottleneck machine to minimize the WIP (work in process). In the situation, other machines except the bottleneck are able to stop their operations without any throughput loss of the whole manufacturing line for saving power utility cost. To consider this problem three integer programming models are introduced. The three models include (1) line shutdown, (2) block shutdown, and (3) individual machine shutdown. We demonstrate the effectiveness of the proposed IP models through diverse experiments, by comparing with a TOC-based machine operation planning considered as a current model.

현대 실내공간에서의 비물질적 특성에 관한 연구

신홍경(Shin, Hong-Kyung),옥창수(Ok, Chang-Soo) 한국실내디자인학회 2004 한국실내디자인학회논문집 Vol.13 No.3

동적 스케줄링을 위한 분산 도착시간 제어 (Distributed Arrival Time Control) 알고리즘의 개량

고재호(Jea-Ho Ko),옥창수(Chang-Soo Ok) 대한산업공학회 2012 대한산업공학회지 Vol.38 No.1

PLS를 활용한 고차요인구조 추정방법의 비교

손기혁(Ki-Hyuk Son),전영호(Young-Ho Chun),옥창수(Chang-Soo Ok) 한국산업경영시스템학회 2013 한국산업경영시스템학회지 Vol.36 No.4

Estimation approaches for casual relation model with high-order factors have strict restrictions or limits. In the case of ML (Maximum Likelihood), a strong assumption which data must show a normal distribution is required and factors of exponentiation is impossible due to the uncertainty of factors. To overcome this limitation many PLS (Partial Least Squares) approaches are introduced to estimate the structural equation model including high-order factors. However, it is possible to yield biased estimates if there are some differences in the number of measurement variables connected to each latent variable. In addition, any approach does not exist to deal with general cases not having any measurement variable of high-order factors. This study compare several approaches including the repeated measures approach which are used to estimate the casual relation model including high-order factors by using PLS (Partial Least Squares), and suggest the best estimation approach. In other words, the study proposes the best approach through the research on the existing studies related to the casual relation model including high-order factors by using PLS and approach comparison using a virtual model.