• Journal of Periodontal and Implant Science
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• 제46권3호
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• pp.207-217
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• 2016

Purpose: The aim of this study is to analyze and visualize the distribution of patients visiting the periodontology department at a dental college hospital, using a geographic information system (GIS) to utilize these data in patient care and treatment planning, which may help to assess the risk and prevent periodontal diseases. Methods: Basic patient information data were obtained from Dankook University Dental Hospital, including the unit number, gender, date of birth, and address, down to the dong (neighborhood) administrative district unit, of 306,656 patients who visited the hospital between 2007 and 2014. The data of only 26,457 patients who visited the periodontology department were included in this analysis. The patient distribution was visualized using GIS. Statistical analyses including multiple regression, logistic regression, and geographically weighted regression were performed using SAS 9.3 and ArcGIS 10.1. Five factors, namely proximity, accessibility, age, gender, and socioeconomic status, were investigated as the explanatory variables of the patient distribution. Results: The visualized patient data showed a nationwide scale of the patient distribution. The mean distance from each patient's regional center to the hospital was $30.94{\pm}29.62km$ and was inversely proportional to the number of patients from the respective regions. The distance from a regional center to the adjacent toll gate had various effects depending on the local distance from the hospital. The average age of the patients was $52.41{\pm}12.97years$. Further, a majority of regions showed a male dominance. Personal income had inconsistent results between analyses. Conclusions: The distribution of patients is significantly affected by the proximity, accessibility, age, gender and socioeconomic status of patients, and the patients visiting the periodontology department travelled farther distances than those visiting the other departments. The underlying reason for this needs to be analyzed further.

• 대한기계학회논문집A
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• 제34권6호
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• pp.781-787
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• 2010

고장의 특성을 예상하는 것은 미래의 고장을 예견하고 최적의 교체간격을 결정할 수 있도록 해주기 때문에 정비 계획에서 매우 중요하다. 본 연구에서는 신뢰도 해석에서 가장 전통적인 방법 중의 하나인 확률지에 도시하는 기법을 이용하여 J79 엔진 Transfer Gearbox의 고장 분포를 검토하였다. 고장 데이터에 대한 적절한 분포를 찾기 위해서 다양한 확률분포가 이용되었으며, 얻어진 상관계수는 고장데이터가 대수정규분포에 가장 근접함을 나타내었다. 예상되는 비계획 정비행위의 횟수와 다양한 비용 비율에 대해서 최적의 교체간격을 구하였다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.170-174
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• 2003

In this research, we consider an integrated manufacturing/distribution planning problem in supply chain (SC) which has non-integer time lags. We focus on a capacitated manufacturing planning and capacity allocation problem for the system. We develop a mixed binary integer linear programming (MBLP) model and propose an efficient heuristic procedure using an adaptive genetic algorithm, which is composed of a regeneration procedure for evaluating infeasible chromosomes and the reduced costs from the LP-relaxation of the original model. The proposed an adaptive genetic algorithm was tested in terms of the solution accuracy and algorithm speed during numerical experiments. We found that our algorithm can generate the optimal solution within a reasonable computational time.

• 한국멀티미디어학회논문지
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• 제10권12호
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• pp.1714-1725
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• 2007

This paper describes a top-down behavior planning framework in a simulation game from personality to real life action selection. The combined behavior creating system is formed by five levels of specification, which are personality definition, motivation extraction, emotion generation, decision making and action execution. Along with the data flowing process in our designed framework, NPC selects actions autonomously to adapt to the dynamic environment information resulting from active agents and human players. Furthermore, we illuminate applying Gaussian probabilistic distribution to realize character's behavior changeability like human performance. To elucidate the mechanism of the framework, we situated it in a restaurant simulation game.

• 한국정보시스템학회:학술대회논문집
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• 한국정보시스템학회 2001년도 추계학술대회 발표논문집:차세대 전상거래 시대의 비즈니스전략
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• pp.14-30
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• 2001

At present, EDI system is indispensable process in Port and e-logis industry. Using EDI system service has been variably applicable Client/Server system base on 2-Tier, Web EDI and skill oriented distribution object. Up to date, EDI System has been Closed. Moreover it raised several points on User. For settling the problem, A study make progress with Web EDI system, XML/EDl system, distribution object technology based on 3-Tier. This Study produce several EDI system and Service. With a Result of study as the central figure, All kinds of System and Service make a comparative study synthetically in port and e-logis industry. As a result of Study, this paper make an Model Construction Planning for estimating the Port EDI System.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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• pp.1453-1455
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• 1999

This paper presents an economical generation planning for operating power systems with dispersed generation. As dispersed generation introduced into an electric power distribution system, the power system will be complicated and have much variable aspects. So there is need for developing new generation scheduling. In this paper, the proposed method is tested for distribution system with two battery storage resources. Optimal generation planning of 15 thermal units in 24-hours is achieved by improved genetic algorithm. Also, to show its effectiveness, the results are compared with those of not including battery storage resources.

• 대한안전경영과학회지
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• 제8권5호
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• pp.139-150
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• 2006

The aim of this study is to establish an efficient distribution planning for a capacitated multi-stage supply chain. We assume that the demand information during planning horizon is given a deterministic form using a certain forecasting method. Under such a condition, we present a cost effective heuristic method for minimizing chain-wide supply chain inventory cost that is the sum of holding and backorder costs by using look-ahead technique. We cope with the capacity restriction constraints through look-ahead technique that considers not only the current demand information but also future demand information. To evaluate performance of the proposed heuristic method, we compared it with the extant research that utilizes echelon stock concept, under various supply chain settings.

• 유통과학연구
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• 제19권2호
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• pp.65-75
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• 2021

Purpose: During the pandemic, a large number of orders forced online retailers of fresh produce to quickly change their emergency logistics capabilities to meet the needs of ordinary consumers during the pandemic. Our research aims to help online retailers establish an emergency physical distribution framework for fresh produce during disasters to meet consumer needs. Research design and methodology: 160 effective responses were collected from the online response team in Wuhan, China, and exploratory factor analysis was used to determine the emergency logistics capability framework. Twelve experts were invited online to collect their scoring opinions and use the entropy method to determine the importance of emergency logistics capabilities. Results: Our results have identified a total of 17 emergency logistics factors for online retailers, and we found that Transportation route planning and reconstruction capabilities, Emergency plan planning ability, and Supply chain real-time information sharing capability are the most important in the overall framework. Conclusions: This research completely established the physical distribution framework of fresh agricultural products online retailer in emergency situations. It enriches academic resources in the field of emergency distribution and provides a scientific basis for corporate managers to improve their physical distribution capabilities in emergency situations.

• 가족자원경영과 정책
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• 제9권3호
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• pp.31-43
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• 2005

The purposes of this study were to (1) examine the sub-dimensions of time management behaviors and satisfaction with time management, and (2) to identify the variables that can affect satisfaction with time management. Data was collected through an Internet survey answered by 611 working men and women. The data were analyzed using descriptive statistics, factor analysis, and multiple linear regression analysis. As a result of the study, the sub-dimensions of time management behaviour were extracted into three subordinate categories, which were, planning, human relation orientation, and urgency. The sub-dimensions of the satisfaction with time management were extracted into three subordinate categories, which were, satisfaction with the management results, satisfaction with time distribution, and satisfaction of spare time. Management result satisfaction displayed a positive relationship with planning and work time. The satisfaction with time distribution displayed a positively relationship with planning, relations-intention, the level of education, and sleeping time, while displaying a negative relationship with work time. Also, Women tended to be more satisfied with time distribution than men. Finally, the satisfaction of spare time was positively related with age, while negatively related to urgency and work time.

• 한국경영과학회지
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• 제26권4호
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• pp.133-141
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• 2001

Rapid development in computer and network technology these days has created in environment in which decisions for manufacturing companies can be made in a much broader perspective. Especially, better decisions on production and distribution planning(PDP) problems can be made laking advantage of real time information from all the parties concerned. However, since the PDP problem-a core part of the supply chain management- is known to be the so-called NP-hard problem, so heuristic methods are dominantly used to find out solutions in a reasonable time. As one of those heuristic techniques, many previous studios considered genetic a1gorithms. A standard genetic a1gorithm applies rules of reproduction, gene crossover, and mutation to the pseudo-organisms so the organisms can pass along beneficial and survival-enhancing trails to a new generation. When it comes to representing a chromosome on the problem, it is hard to guarantee an evolution of solutions through classic a1gorithm operations alone, for there exists a strong epitasis among genes. To resolve this problem, we propose a hybrid genetic a1gorithm based on Silver-Meal heuristic. Using IMS-TB(Intelligent Manufacturing System Test-bed) problem sets. the good performance of the proposed a1gorithm is demonstrated.