• 한국IT서비스학회지
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• 제2권2호
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• pp.39-51
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• 2003

The Internet affects all economic activities. Physical world business must either adopt new digital strategies, launch new digital business to complement their physical world models, or be forced to completely revise their strategies. The purpose of this paper is to provide a framework that organizes the managerial decision-making process to assist managers in crafting and implementing e-business strategy. We applied the methodology to the case of KNK Educational Institute to explain the process. Core competence of KNK JUNIOR is researched according to our suggested methodology and activities and roles of KNK JUNIOR have been arranged.

• 대한소아치과학회지
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• 제51권1호
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• pp.1-10
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• 2024

Deep learning algorithms are becoming more prevalent in dental research because they are utilized in everyday activities. However, dental researchers and clinicians find it challenging to interpret deep learning studies. This review aimed to provide an overview of the general concept of deep learning and current deep learning research in dental radiographic image analysis. In addition, the process of implementing deep learning research is described. Deep-learning-based algorithmic models perform well in classification, object detection, and segmentation tasks, making it possible to automatically diagnose oral lesions and anatomical structures. The deep learning model can enhance the decision-making process for researchers and clinicians. This review may be useful to dental researchers who are currently evaluating and assessing deep learning studies in the field of dentistry.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.227-227
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• 2015

The Wairarapa Valley occupies a predominantly rural area in the lower North Island of New Zealand. It supports a mix of intensive farming (dairy), dry stock farming (sheep and beef cattle) and horticulture (including wine grapes). The valley floor is traversed by the Ruamahanga River, the largest river in the Wellington region with a total catchment area of 3,430 km2. Environmental, cultural and recreational values associated with this Ruamahanga River are very high. The alluvial gravel and sand aquifers of the Wairarapa Valley, support productive groundwater aquifers at depths of up to 100 metres below ground while the Ruamahanga River and its tributaries present a further source of water for users. Water is allocated to users via resource consents by Greater Wellington Regional Council (GWRC). With intensifying land use, demand from the surface and groundwater resources of the Wairarapa Valley has increased substantially in recent times and careful management is needed to ensure values are maintained. This paper describes the approach being taken to manage water resources in the Wairarapa Valley and redefine appropriate limits of sustainable water use. There are three key parts: Quantifying the groundwater resource. A FEFLOW numerical groundwater flow model was developed by GWRC. This modelling phase provided a much improved understanding of aquifer recharge and abstraction processes. It also began to reveal the extent of hydraulic connection between aquifer and river systems and the importance of moving towards an integrated (conjunctive) approach to allocating water. Development of a conjunctive management framework. The FEFLOW model was used to quantify the stream flow depletion impacts of a range of groundwater abstraction scenarios. From this, three abstraction categories (A, B and C) that describe diminishing degrees of hydraulic connection between ground and surface water resources were mapped in 3 dimensions across the Valley. Interim allocation limits have been defined for each of 17 discrete management units within the valley based on both local scale aquifer recharge and stream flow depletion criteria but also cumulative impacts at the valley-wide scale. These allocation limits are to be further refined into agreed final limits through a community-led decision making process. Community involvement in the limit setting process. Historically in New Zealand, limits for sustainable resource use have been established primarily on the basis of 'hard science' and the decision making process has been driven by regional councils. Community involvement in limit setting processes has been through consultation rather than active participation. Recent legislation in the form of a National Policy Statement on Freshwater Management (2011) is reforming this approach. In particular, collaborative consensus-based decision making with active engagement from stakeholders is now expected. With this in mind, a committee of Wairarapa local people with a wide range of backgrounds was established in 2014. The role of this committee is to make final recommendations about resource use limits (including allocation of water) that reflect the aspirations of the communities they represent. To assist the committee in taking a holistic view it is intended that the existing numerical groundwater flow models will be coupled with with surface flow, contaminant transport, biological and economic models. This will provide the basis for assessing the likely outcomes of a range of future land use and resource limit scenarios.

• 벤처창업연구
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• 제15권4호
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• pp.83-96
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• 2020

시장경제의 메커니즘으로 해결이 어려웠던 다양한 사회적 문제는 정부 주도의 사회적 기업 등의 비영리단체가 해결해야한다는 고정관념을 벗어나, 최근 혁신적인 아이디어에 기반하여 사회적 문제를 해결하고 이러한 과정에서 사회적 가치와 경제적 가치를 함께 창출하는 소셜벤처에 대한 관심이 증대되고 있다. 소셜벤처의 의사결정 프로세스와 성과를 이해하기 위해서는 기존 경제적 가치에 집중하는 스타트업과 영리추구를 배제하는 비영리단체를 분석하는 방법과는 차별화된 접근이 필요하다. 그럼에도 불구하고 국내 안정적인 사업 궤도에 진입하는 데 성공한 소셜벤처는 상대적으로 부족하다. 특히 소셜벤처의 초기 창업 단계 및 죽음의 계곡을 극복해나가는 과정에 대한 직접적인 관찰과 조사는 현실적으로 쉽지 않다. 이에 본 연구에서는 청각장애인 택시기사들이 직접 운행할 수 있는 서비스를 개발하고 성공적으로 창업하여 성장하고 있는 '고요한택시'를 단일사례 연구방법으로 분석하였다. 창업 초기부터 현재까지 주요 전략적 의사결정 과정을 직접 관찰과 심층 인터뷰를 통해 수집된 다양한 맥락 정보를 분석한 결과, '몰입상승효과에 대한 방어기제'와 '사회적 및 경제적 가치 추구의 직교성'의 주요 의사결정 메커니즘을 파악하였다. 이러한 연구결과는 사회적 기업가들이 처한 높은 환경적 불확실성에 대응하기 위한 실무적 방안으로 활용될 수 있을 것이다. 본 연구는 탐색적 연구로서 단일사례 분석 방법을 적용한 연구결과의 일반화 범위는 제한적이나, 향후 다양한 관점에서 소셜벤처의 특성을 규명하는 학술적 논의를 마련하는데 의의를 가진다.

• 대한기계학회논문집A
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• 제35권7호
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• pp.729-736
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• 2011

TOPSIS(Technique for Order Preference by Similarity to Ideal Solution)는 상충되는 다수의 속성이 존재하는 상황에서 의사결정이 요구되는 다속성 의사결정법(Multi Attribute Decision Making) 중 하나이다. 이는 선택된 대체안이 최선의 이상적 대체안으로부터 가장 가까운 거리에 위치해야 하고, 동시에 부정적으로 이상적인 대체안으로부터는 가장 멀리 위치해야 한다는 논리에 입각한 의사결정 기법이다. TOPSIS 는 최소화와 최대화가 공존하는 다목적함수 형상 최적설계에 적용이 가능하다. 본 연구에서는 TOPSIS 와 베지어 곡선(Rational Bezier Curve)을 적용하여 CRT(Cathode Ray Tubes) 후면유리의 다중목적 형상최적설계를 수행하였다. 무게와 1 차 주응력의 두 가지 다중목적 함수를 최적화하기 위하여, 다중목적 함수의 성능지표를 TOPSIS 의 상대적 근접도로 정의하고 이를 반응표면모델로 구성하여 다중목적 형상최적설계가 가능한 방법론을 제안하였다. 이를 통해 하나의 최적해가 아닌 최적해의 군이 선정되어, 무게와 주응력 최적해의 모순관계를 확인하면서 다양한 설계요구 스펙을 만족시켜줄 수 있는 방안을 설계자가 스스로 선택하도록 하였다.

• 한국농공학회논문집
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• 제57권2호
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• pp.1-13
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• 2015

The Coupled Model Intercomparison Project Phase 5 (CMIP5), coordinated by the World Climate Research Programme in support of the Intergovernmental Panel on Climate Change (IPCC) AR5, is the most recent, provides projections of future climate change using various global climate models under four major greenhouse gas emission scenarios. There is a wide selection of climate models available to provide projections of future climate change. These provide for a wide range of possible outcomes when trying to inform managers about possible climate changes. Hence, future agrometeorological indicators estimation will be much impacted by which global climate model and climate change scenarios are used. Decision makers are increasingly expected to use climate information, but the uncertainties associated with global climate models pose substantial hurdles for agricultural resources planning. Although it is the most reasonable that quantifying of the future uncertainty using climate change scenarios, preliminary analysis using reasonable factors for selecting a subset for decision making are needed. In order to narrow the projections to a handful of models that could be used in a climate change impact study, we could provide effective information for selecting climate model and scenarios for climate change impact assessment using maximum/minimum temperature, precipitation, reference evapotranspiration, and moisture index of nine Representative Concentration Pathways (RCP) scenarios.

• 국제학술발표논문집
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• The 3th International Conference on Construction Engineering and Project Management
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• pp.700-706
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• 2009

Bridges are vital components of any road network which demand crucial and timely decision-making for Maintenance, Repair and Rehabilitation (MR&R) activities. Bridge Management Systems (BMSs) as a decision support system (DSS), have been developed since the early 1990's to assist in the management of a large bridge network. Historical condition ratings obtained from biennial bridge inspections are major resources for predicting future bridge deteriorations via BMSs. Available historical condition ratings in most bridge agencies, however, are very limited, and thus posing a major barrier for obtaining reliable future structural performances. To alleviate this problem, the verified Backward Prediction Model (BPM) technique has been developed to help generate missing historical condition ratings. This is achieved through establishing the correlation between known condition ratings and such non-bridge factors as climate and environmental conditions, traffic volumes and population growth. Such correlations can then be used to obtain the bridge condition ratings of the missing years. With the help of these generated datasets, the currently available bridge deterioration model can be utilized to more reliably forecast future bridge conditions. In this paper, the prediction accuracy based on 4 and 9 BPM-generated historical condition ratings as input data are compared, using deterministic and stochastic bridge deterioration models. The comparison outcomes indicate that the prediction error decreases as more historical condition ratings obtained. This implies that the BPM can be utilised to generate unavailable historical data, which is crucial for bridge deterioration models to achieve more accurate prediction results. Nevertheless, there are considerable limitations in the existing bridge deterioration models. Thus, further research is essential to improve the prediction accuracy of bridge deterioration models.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1597-1600
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• 1991

In this paper, we describe a notion of sensor modeling method in multisensor data fusion using fuzzy set theory. Each sensor module is characterized by its fuzzy constraints to specific features of environment. These sensor fuzzy constraints can be imposed on multisensory data to verify their degree of truth and compatibility toward the final decision making. In comparison with other sensor modeling methods, such as probabilistic models or rule-based models, the proposed method is very simple and can be easily implemented in intelligent robot systems.

• 경영과학
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• 제17권3호
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• pp.49-60
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• 2000

The proliferation of electronic commerce(EC) has led manufactureres to consider Internet based marketing as a salient candidate for strategic diversification of marketing channel. In this case, each manufacturer can build its own Web store or rent an existing special EC store. Such decision making of ‘build’ or ‘rent’ can be analyzed by a game model which derives the Nash solutions for price and profit considering degree of competition with other competitive manufacturers. In this paper, to overcome the drawbacks of the traditional linear demand function, we first propose a new linear demand function which incorporates not only the price difference between competitive products but the awareness of Web stores perceived by the consumers, then design the game models to analyze the characteristics of three typical types of marketing channel in duopoly market. Based on the Nash solutions of the game models, we analyzed the effect of the degree of competition and Web awareness in selecting the optimal marketing channel.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2001년도 추계학술대회 논문집
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• pp.97-100
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• 2001

제조 기업의 가치사슬 최적화를 위한 전략적, 운영상 의사결정 문제는 수리적 모델을 이용한 DSS의 효과적인 활용을 통하여 해결 될 수 있다. 의사결정 프로세스는 필연적으로 공급사슬의 여러 성과 목표와 관련 조직간의 Trade-off 및 연계관계(Interaction)가 고려되므로 복수의 DSS 활용이 필요하게 된다. 이와 관련하여 본 논문에서는 공급 사슬 전체의 최적화를 위한 다수의 전략적 목표 및 의사결정 프로세스, 연계된 수리적 모델들을 정의하고, 관련 조직 및 성과 지표 별 부분적 최적화(Local Optimality)를 지양하고 전체최적화 (Global Optimality)를 달성하기 위한 DSS Logic을 철강산업 프로세스를 대상으로 수리적 모델들의 분할(Decomposition) 및 통합개념을 통하여 제시하였다.