• 산업공학
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• 제17권2호
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• pp.169-179
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• 2004

In supply chain management, supplier capacity is very important to meet the customer demand quickly. This paper studies a supplier evaluation structure and then suggests a methodology using fuzzy theory for selecting an effective supplier. Several quantitative and qualitative evaluation factors should be analyzed in the evaluation structure. The qualitative factors includes not only product and service qualities but financial condition. The methodology deals with both the quantitative and qualitative factors together through fuzzy inference. A case study is also presented to show how to choose the best one among potential suppliers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제8권12호
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• pp.4269-4292
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• 2014

Currently, increasing numbers of access points (AP) are being deployed in enterprise offices, campuses and municipal downtowns for flexible Internet connectivity, but most of these access points are idle or redundant most of the time, which causes significant energy waste. Therefore, with respect to power conservation, applying energy efficient strategies in WIFI networks is strongly advocated. One feasible method is dynamically managing network resources, particularly APs, by powering devices on or off. However, when an AP is powered on, the device is initialized through a long boot time, during which period clients cannot be associated with it; therefore, the network performance would be greatly impacted. In this paper, based on a global view of an entire WLAN, we propose an AP selection technology, known as Temporary Access Selection (TAS). The criterion of TAS is a fusion metric consisting of two evaluation indexes which are based on throughput and battery life, respectively. TAS is both service and clients' preference specific through balancing the data rate, battery life and packet size. TAS also works well independently in traditional WLANs in which no energy efficient strategy is deployed. Moreover, this paper demonstrates the feasibility and performance of TAS through experiments and simulations with Network Simulator version 3 (NS3).

• 한국비블리아학회지
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• 제31권4호
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• pp.121-144
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• 2020

본 연구의 목적은 대전 지역의 U-도서관 적정입지를 제안하는 데 있다. 이를 위해 문헌연구 및 국내의 U-도서관 현황 분석을 통해 적정입지선정을 위한 평가지표를 도출하고 이를 바탕으로 공공도서관의 위치, 제안위치와의 반경, 지하철역별 수송실적, 관공서·교통시설·편의시설, 주요시설의 현황, 지역구별 거주인주수 등을 분석, 적용하였다. 최종적으로 이를 종합하여, 대전 지역의 5개 자치구인 대덕구 2개, 동구 2개, 서구 4개, 유성구 6개, 중구 2개 총 16개의 U-도서관 위치를 제안하였다.

• 한국임상약학회지
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• 제34권1호
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• pp.62-70
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• 2024

Background: Drug-related problems have the potential to threaten patient health, and pharmacists are in a position to prevent such problems through prescription reviews and patient counseling, actively engaging in pharmaceutical care activities. This study aims to categorize and analyze the intervention activities of pharmacists in community pharmacies concerning drug-related problems, following international criteria. Methods: Over a six-month period, prescription interventions completed in a community pharmacy in Seoul were selected as the research subjects. The causes of interventions were classified according to the Pharmaceutical Care Network Europe (PCNE) drug-related problems (DRPs) classification system and the types and frequencies of DRPs were identified. Results: Among a total of 49,334 prescriptions, 527 interventions were completed, constituting approximately 1.07% of the daily average filled prescriptions. Individuals over 60 years of age represented more than 50%. The primary cause of DRPs was prescribing and drug selection issues, comprising 256 cases (48.58%), with specific subcategories including 109 cases of drug selection, 79 cases of treatment duration errors, 47 cases of dose selection, and 21 cases of inappropriate dosage form selection. Patient-related issues accounted for 204 cases (38.71%). Conclusion: The study demonstrated that the pharmacists' intervention in community pharmacies contributes to the safe use of medication by patients.

• 한국사이버테러정보전학회:학술대회논문집
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• 한국사이버테러정보전학회 2004년도 제1회 춘계학술발표대회
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• pp.141-144
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• 2004

The Common Criteria (CC) philosophy is to provide assurance based upon an evaluation of the IT product or system that is to be trusted. Evaluation has been the traditional means of providing assurance. It is essential that not only the customer' srequirements for software functionality should be satisfied but also the security requirements imposed on the software development should be effectively analyzed and implemented in contributing to the security objectives of customer's requirements. Unless suitable requirements are established at the start of the software development process, the resulting end product, however well engineered, may not meet the objectives of its anticipated consumers. By the security evaluation, customer can sure about the quality of the products or systems they will buy and operate. In this paper, we propose a selection guide for If products by showing relationship between security engineering and security evaluation and make help user and customer select appropriate products or system.

• 한국경영과학회지
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• 제24권4호
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• pp.1-12
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• 1999

This paper presents a DEA-AHP hybrid model to evaluate and select R&D projects. AHP collects and processes information on the weights of evaluation criteria. The processed information is used as an input for DEA/AR model. Only desirable number of projects are selected by the hybrid model. The model is examined by an example generated from a real data set.

• 산업경영시스템학회지
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• 제17권31호
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• pp.73-80
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• 1994

Sequentiality in decision making is an inherent characteristic of the R&D Process, Conceptual changes are noted during the Course of the Project which represent a continuous improvement in the quality of the data available during the various project stages. In this paper, Eight characteristic types of project evaluation models have been developed economic index models, portfolio models, decision theory models, risk analysis models, frontier models, scoring models, profile models and checklists. Each of these will be critically reviewed and appraised.

• 경영과정보연구
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• 제4권
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• pp.67-88
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• 2000

The purpose of this study is to present models for evaluation and selection of DataBase Management Systems(DBMS) suppliers. The major concern of management is that most decision problems have multiple, usually conflicting, criteria. The fuzzified multiple-objective programming models are given to accomodate the aspiration level and satisfaction level of decision makers. The proposed models are classified into two types, that is, pre-emptive priority and interpolated non-membership function model. Numerical examples illustrating each type of model are presented and the implications of these models are discussed.

• 대한토목학회논문집
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• 제36권5호
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• pp.867-879
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• 2016

1970년대 이후 지속적인 차량의 증가로 배기가스에 의한 환경오염과 보행자 중심의 고유영역이 점차 축소되어 가고 있고, 중심상업지역, 학교 주변의 통학로, 차량이 통행하지 않은 산책로, 골목길 등 불특정 다수가 통행하는 장소에 대한 체계적 관리나 보행자 안전을 위한 최소한의 시설 구축이 미흡한 실정이다. 최근 "보행안전 및 편의 증진에 관한 법률"이 시행됨에 따라 행정자치부를 중심으로 차없는 거리에 관한 연구가 활발히 진행되고 있으나, 그에 따른 평가가중치의 산정기준은 미흡한 실정이며, 지자체를 통해 자체적으로 이루어지고 있는 차없는 거리 사업추진에 대한 평가는 이용객의 목적 및 규모, 체류시간 등을 통해 정성적인 평가만 이루어지고 있는 것이 현실이다. 본 연구에서는 차없는 거리 선정방법을 제시함으로써 앞으로 조성될 차없는 거리에 대한 선정방법 정립에 목적을 두고 설문조사를 통하여 연구를 수행하였다. 설문조사는 차없는 거리의 유형별 평가지표를 토대로 차없는 거리의 평가를 위한 가중치 제시를 목적으로 도시 통공학과 학사 이상, 교수, 공무원, 엔지니어링 회사 종사자 총 200명을 대상으로 차없는 거리의 평가가중치 제시 및 평가지표 선정을 위한 전문가 설문조사(F.G.I)를 실시하였다. 차없는 거리의 유형별 평가목표와 목표별 항목을 분류하여 가중치를 부여하고, 각 항목에 따른 세부지표별 가중치 제시를 통해 그 결과값을 점수화하였다. 본 연구에서 도출된 차없는 거리 유형별 평가가중치는 차없는 거리 조성을 위한 선정기준 수립방법의 일환으로, 향후 차없는 거리 평가방법 및 선정 기준 수립시 충분한 기여를 할 수 있을 것으로 판단된다.

• Advances in Energy Research
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• 제6권2호
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• pp.91-101
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• 2019

This paper proposes an efficient data-driven approach to build models for predicting energy consumption in buildings. Data used in this research is collected by installing humidity and temperature sensors at different locations in a building. In addition to this, weather data from nearby weather station is also included in the dataset to study the impact of weather conditions on energy consumption. One of the main emphasize of this research is to make feature selection independent of domain knowledge. Therefore, to extract useful features from data, two different approaches are tested: one is feature selection through principal component analysis and second is relative importance-based feature selection in original domain. The regression model used in this research is gradient boosting regression and its optimal parameters are chosen through a two staged coarse-fine search approach. In order to evaluate the performance of model, different performance evaluation metrics like r2-score and root mean squared error are used. Results have shown that best performance is achieved, when relative importance-based feature selection is used with gradient boosting regressor. Results of proposed technique has also outperformed the results of support vector machines and neural network-based approaches tested on the same dataset.