• 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.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2002년도 추계학술발표논문집 (상)
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• pp.115-118
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• 2002

소켓 프로그래밍(socket programming) 인터페이스를 지원하는 C/C++, perl, python 과 같은 언어들은 폴링(polling) 기능을 갖는 select() 함수를 제공한다. 이 select()함수를 이용할 경우, 단일 쓰레드(또는 프로세스)로 다중의 클라이언트 요청을 처리할 수 있다. 최근 네트워크 프로그래밍 분야에서 주목받는 자바 언어의 경우, 최신 JDK 1.4 의 비동기 입출력 패키지에서 select()함수를 제공하고 있으나, JDK 1.3을 포함한 그 이하의 버전에서는 아직까지 이 함수를 제공하지 않고 있다. 일반적으로 다중 쓰레드를 이용하여 소켓서버 응용프로그램을 개발할 경우, 코드가 단순해지고 응답이 빠른 장점이 있는 반면에 네트워크 연결이 증가할수록 다수의 쓰레드를 관리하는 일이 CPU에 큰 부담이 된다. 반면에 소켓폴링(socket polling)을 사용할 경우, 이러한 연결 유지에 대한 부담이 줄어드는 대신, 다중 쓰레드를 이용하는 방법에 비하여 구현이 어렵다. 본 논문에서는 다양한 시뮬레이션 환경에서 세가지 소켓 프로그래밍 모델에 대하여 그 성능을 비교평가 하였다. 이 세가지 모델은 단순 다중 쓰레드 모델(typical multi-thread model), 단일 쓰레드 소켓폴링 모델(socket polling with single-thread model), 다중 쓰레드 소켓폴링 모델(socket polling with multi-threadmodel)이다. 본 논문에서는 다중 쓰레드 소켓폴링 모델을 제안하고 JDK 1.3.1을 이용하여 구현하였다. 이 모델의 경우 복잡한 구조에도 불구하고 단순 다중 쓰레드 모델와 유사하거나 더 나은 성능을 보여주었다. 또한 동일한 용량의 쓰레드 풀(thread pool)을 사용하더라도 단순 다중 쓰레드 모델보다 더 많은 수의 클라이언트를 수용할 수 있는 장점이 있다. 이러한 결과를 바탕으로 본 연구팀에서 수행중인 MoIM-Messge서버의 네트워크 모듈로 다중 쓰레드 소켓폴링 모델을 적용하였다.

• 한국구조물진단유지관리공학회 논문집
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• 제14권1호
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• pp.117-124
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• 2010

교량은 도로나 철도 네트워크를 구성하는 중요한 사회기반시설로 부재의 파손으로 인한 보수, 보강, 교체에 따른 교통통제나 갑작스런 붕괴 등이 발생할 경우 사회경제적으로 커다란 손실과 인명사상을 유발하기 때문에 일정한 안전수준 이상으로 관리되어야 한다. 사용연수의 증가에 따라 열화 손상되거나, 사고, 천재지변 등으로 인해 문제가 발생한 교량의 성능을 회복시키기 위하여 다양한 보강 공법들이 연구되고 있다. 그러나 어떤 공법을 사용하는 것이 합리적인가에 대한 판단기준 없이 의사결정을 수행하고 있는 실정이다. 따라서 본 논문에서는 개략 설계된 여러 보강대안 중 최적 보강공법을 선정하는 문제를 해결하기 위해, 의사결정인자를 도출하고 불확실성을 고려한 정량적 평가 및 의사결정방법을 제안하였으며, 이를 간략한 예제에 적용하여 개발된 모델의 합리성 및 적용성을 검토하였다. 본 연구에서 제안된 방법론은 불확실성이 존재하는 대안들 가운데 최적의 대안을 선택하는 분야에 응용하여 적용할 수 있을 것으로 기대된다.

• 한국프랜차이즈경영연구
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• 제12권4호
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• pp.25-40
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• 2021

Purpose: Marketing communication with customers is essential for companies to survive and grow in a fiercely competitive environment. Advertising is one of the most readily accepted marketing communications by consumers. Unlike a company that owns a distribution network, advertising is vital for a franchise. In general, many advertising models select celebrities. Celebrities are more likely to attract audience attention and influence consumers' purchase intentions. Customers satisfied with advertising are more likely to stay loyal and buy again when the company launches a new product. In addition, customers form a brand image through advertisements. Therefore, in this study, the effect of the characteristics of the foodservice franchise advertising model characteristics on model satisfaction, brand image, and purchase intention. Research design, data, and methodology: The survey of this study was conducted among consumers over the age of 20 who had seen a restaurant franchise advertisement and visited a store within the last 2 months. 305 copies were collected for 7 days during the survey period, from October 21 to October 27, 2021. Among the collected questionnaires, 12 insincere questionnaires were excluded, and 293 were used for analysis. SPSS 25.0 and Smart PLS 3.0 were used as data collected to test the hypothesis. Result: As a result of the study, among the advertising model characteristics of a foodservice franchise, reliability, attractiveness, expertise, and closeness all had a significant positive (+) effect on model satisfaction. In addition, reliability and closeness were found to have a significantly positive (+) effect on brand satisfaction, but attractive and expertise did not significantly affect brand image. Finally, model satisfaction was found to have a significant positive (+) effect on brand image and purchase intention. Brand image also appeared to have a significant positive effect on purchase intention. Conclusions: Research Results First, this study verified the effect of a restaurant franchise advertising model using celebrities by using the characteristics of the advertising model. Second, this study developed a conceptual structure for model characteristics - model satisfaction - brand image - purchase intention. Third, the restaurant franchise marketer needs to select a model in consideration of the privacy of the advertising model. Fourth, consumers tend to equate advertising models with advertising

• 한국수산과학회지
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• 제44권4호
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• pp.390-396
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• 2011

Southern rough shrimp Trachysalambria curvirostris is exploited mainly by small shrimp beam trawl in coastal regions of Korea. To determine the size selectivity of a shrimp beam trawl for this species, a series of comparative fishing experiments was conducted in the sea adjacent to Geoje Island off the southern cost of Korea in June and November, 2010, using codends with four different mesh sizes(14.2, 17.8, 25.5, and 35.3 mm). The extended Share Each Length's Catch Total(SELECT) analysis method, based on a multinomial distribution, was applied to the fishing data to obtain a master selection curve. The model with the estimated split parameters fit the catch data best. The master selection curve was estimated to be: s(R)=exp(15.183R-7.872)/[1+exp(15.183R-7.872)], where the relative carapace length, R, is the ratio of carapace length to mesh size. The relative carapace length for 50% retention was 0.518, and the selection range was 0.145. The results suggest that codends with a larger mesh size allow more small-sized shrimps to escape.

• 대한의용생체공학회:의공학회지
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• 제33권1호
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• pp.1-7
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• 2012

Hemorrhagic shock is a common cause of death in emergency rooms. Early diagnosis of hemorrhagic shock makes it possible for physicians to treat patients successfully. Therefore, the purpose of this study was to select an optimal survival prediction model using physiological parameters for the two analyzed periods: two and five minutes before and after the bleeding end. We obtained heart rates, mean arterial pressures, respiration rates and temperatures from 45 rats. These physiological parameters were used for the training and testing data sets of survival prediction models using an artificial neural network (ANN) and support vector machine (SVM). We applied a 5-fold cross validation method to avoid over-fitting and to select the optimal survival prediction model. In conclusion, SVM model showed slightly better accuracy than ANN model for survival prediction during the entire analysis period.

• Nuclear Engineering and Technology
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• 제52권9호
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• pp.2009-2016
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• 2020

A nuclear power plant is a large complex system with tens of thousands of components. To ensure plant safety, the early and accurate diagnosis of abnormal situations is an important factor. To prevent misdiagnosis, operating procedures provide the anticipated symptoms of abnormal situations. While the more severe emergency situations total less than ten cases and can be diagnosed by dozens of key plant parameters, abnormal situations on the other hand include hundreds of cases and a multitude of parameters that should be considered for diagnosis. The tasks required of operators to select the appropriate operating procedure by monitoring large amounts of information within a limited amount of time can burden operators. This paper aims to develop a system that can, in a short time and with high accuracy, select the appropriate operating procedure and sub-procedure in an abnormal situation. Correspondingly, the proposed model has two levels of prediction to determine the procedure level and the detailed cause of an event. Simulations were conducted to evaluate the developed model, with results demonstrating high levels of performance. The model is expected to reduce the workload of operators in abnormal situations by providing the appropriate procedure to ultimately improve plant safety.

• 한국건축시공학회지
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• 제11권3호
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• pp.238-246
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• 2011

Choosing the best-performance materials is a crucial task for the successful completion of a project in the construction field. In general, the process of material selection is performed through the use of information by a highly experienced expert and the purchasing agent, without the assistance of logical decision-making techniques. For this reason, the construction field has considered various artificial intelligence (AI) techniques to support decision systems as their own selection method. This study proposes the application of a systematic and efficient support vector machine (SVM) model to select optimal exterior materials. The dataset of the study is 120 completed construction projects in South Korea. A total of 8 input determinants were identified and verified from the literature review and interviews with experts. Using data classification and normalization, these 120 sets were divided into 3 groups, and then 5 binary classification models were constructed in a one-against-all (OAA) multi classification method. The SVM model, based on the kernel radical basis function, yielded a prediction accuracy rate of 87.5%. This study indicates that the SVM model appears to be feasible as a decision support system for selecting an optimal construction method.

• 한국공작기계학회논문집
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• 제16권4호
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• pp.87-92
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• 2007

The full automation welding has not yet been achieved partly because the mathematical model for the process parameters of a given welding task is not fully understood and quantified. Several mathematical models to control welding quality, productivity, microstructure and weld properties in arc welding processes have been studied. However, it is not an easy task to apply them to the various practical situations because the relationship between the process parameters and the bead geometry is non-linear and also they are usually dependent on the specific experimental results. Practically, it is difficult, but important to know how to establish a mathematical model that can predict the result of the actual welding process and how to select the optimum welding condition under a certain constraint. In this paper, an attempt has been made to develop an neural network model to predict the weld top-bead height as a function of key process parameters in the welding. and to compare the developed models using three different training algorithms in order to select an adequate neural network model for prediction of top-bead height.

• 산경연구논집
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• 제7권4호
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• pp.11-16
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• 2016

Purpose - There are numerous theories for retail trade area analysis which are designed to select candidate locations for new stores. In this study, comparative analysis on the characteristics from those of the theories are shown, and the explanation for the power in consumers' store-choice behaviors and their limitations are examined. Also, plans for improving commercial sphere analysis are explored. Research design, data, and methodology - This study is based on literature reviews with normative research methodology. Among many researches regarding the analysis on the location and commercial sphere for launching a new store, researches relying on statistics are excluded in this study since they belong to the marketing research area,. Results - In the Law of retail gravitation, Huff's model multinomial logit model and etc. are mutual complementary mathematical techniques for analyzing commercial spheres and each of them has its own characteristics. These theories rely on the same hypothesis in which consumers are all believed to be behaving rationally under a similar behavioral system. However, the trial in explaining or estimating behavior of choosing a store with only a select size of the population that is objectively estimated by some major properties has limits in its credibility. Conclusion - Research on consumer's spatial behaviors can be fully illustrative and explainable when it has both quantitative approaches such as 'law of retail gravitation', 'logit model' and etc., and qualitative approaches like consumer's 'cognitive structure', 'learning status', 'image formation', 'attitude' and etc.