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물류 네트워크 구축을 위한 입지 및 규모 선정을 위한 시뮬레이션 분석
정석재,이재준,김경섭,Jeong, Suk-Jae,Lee, Jae-Jun,Kim, Kyung-Sup 한국시뮬레이션학회 2005 한국시뮬레이션학회 논문지 Vol.14 No.3
Logistics network of the enterprise is defined to determine the optimal node and link considering the production, inventory and transportation based on the demand forecasting. This study consider the optimal logistics network of A painter company which maintain the existing transportation network and plan to relocate its plants and build new distribution centers. For this, we design possible alternative scenarios and install the simulation models for analysis of each scenario. The result of simulation will help the proper logistic network and determining the size of distribution center further.
특징점과 필터뱅크에 기반한 적응적 혼합형 지문정합 방법
정석재(Seok Jae Jeong),박상현(Sang Hyun Park),문성림(Sung Rim Moon),김동윤(Dong Yoon Kim) 한국정보과학회 2004 정보과학회논문지 : 소프트웨어 및 응용 Vol.31 No.7
Jain 등은 한 지문 영상에 특징점 기반 지문 정합 방법과 필터뱅크 기반 지문 정합 방법을 적용해 두 정합 방법의 성능을 혼합하는 혼합형 지문정합 방법을 제안하고, 이 방법이 두 가지 각 정합 방법에 비해 높은 성능을 보인다는 것을 실험을 통해 입증하였다[1]. 그러나 이 방법은 혼합을 수행할 때 두정합 방법을 별도로 수행한 후, 각 방법의 정합도(matching score)에 가중치를 부여해 최종 정합도를 결정하므로 두 정합 방법의 특성을 상쇄 시키는 결과를 얻게 된다. 본 논문에서는 두 가지 정합 방법을 특징값 추출 과정에서 혼합하는 방법을 제안하였다. 이 방법은 필터뱅크 기반 방법보다는 낮은 ERR(Equal eRror Rate)을 보이나 특징점 기반 방법보다 높은 ERR을 보였다. 이에 본 논문에서는 적응적인 정합도 혼합방법을 제안하여, 두 가지 방법의 특성을 살리도록 적응적으로 정합도를 선택하는 방법을 취했다. 이 방법을 이용해 Jain 등의 혼합형 방법보다 더 낮은 ERR을 얻을 수 있었다. 제안한 방법에 따라 NIST Special Database 14 지문 데이타로 실험한 결과 ERR에서 약 1%의 성능 향상을 보였다. Jain et al. proposed the hybrid matching method which was combined the minutia-based matching method and the filter-bank based matching method. And, their experimental results proved the hybrid matching method was more effective than each of them. However, this hybrid method cannot utilize each peculiar advantage of two methods. The reason is that it gets the matching score by simply summing up each weighted matching score after executing two methods individually. In this paper, we propose new hybrid matching method. It mixes two matching methods during the feature extraction process. This new hybrid method has lower ERR than the filter-bank based method and higher ERR than the minutia-based method. So, we propose the adaptive hybrid scoring method, which selects the matching score in order to preserve the characteristics of two matching methods. Using this method, we can get lower ERR than the hybrid matcher by Jain et al. Experimental results indicate that the proposed methods can improve the matching performance up to about 1% in ERR.
비즈니스 규칙 기반 폐자동차 해체 및 재활용 처리 시스템 개발 및 구현
정석재 ( Suk Jae Jeong ) 한국경영공학회 2011 한국경영공학회지 Vol.16 No.3
Recently, as increasing the interest for the recovery and recycling of end-of-life vehicle(ELV), the research on the efficient and effective recycling and dismantling of ELV have been studied extensively. Most research have focused on the necessary of development and implementation of ELV dismantling system which can support the efficient and optimal ELV process operation. So, this study establishes the rule-based decision support system for treatment of rapid recycling and dismantling process. The developed system is composed of a recovery & wearing module, an used parts inventory module, and a dismantling & decomposition module. First, the recovery & wearing module generates a rule calculating the proper ELV price using the type of ELV to distinguish whether an accident has occurred or not. Also, inventory of used parts module creates rules to manage parts inventory and rules to determine the discarded parts for preventing the lack of warehouse space caused by an excess inventory. Finally, Dismantling and decomposition module generates the rule to determine the sequence of decomposition and dismantling using information used parts value and scarcity. Rule-based system developed can monitor the whole or partial process through web based user interface and to support the efficient decision making on recycling and dismantling process. This system uses the prevailing conditions in the industrial environment in order to select dynamically and propose the most appropriate rule from a rule base of many candidate rules.