• International journal of advanced smart convergence
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• 제8권4호
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• pp.130-137
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• 2019

We conducted this study to identify the composition factors for consumers' selection attributes of accommodation applications and to identify the differences in the selection attributes perception of accommodation applications based on demographic characteristics and use status. According to the study, 6 factors were derived as the components of the selectivity of accommodation application and were named convenience, interactivity, economic efficiency, transaction reliability, product reliability and informativeness. And the respondents differed in their selection attributes perception of the accommodation application they used. In particular, it was found that the highest perception of informativeness and interactivity, and the lowest perception of product reliability. Finally, there were differences in the selection attributes perception of the accommodation application they used by demographic characteristics and use status. Based on the results of this study, we should strive to derive the effective marketing strategy needed for travel industry-related companies.

• 한국콘텐츠학회논문지
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• 제17권1호
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• pp.69-79
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• 2017

본 연구의 목적은 제주지역 양돈농가에 지원하는 농업보조금에 관한 정보제공 및 투명성 등과 같은 사업 선정절차, 구비서류 및 구비조건 등과 같은 사업신청조건이 보조금 지원정책의 만족도와 향후 재신청의도에 미치는 영향을 파악하고자 하였다. 분석결과를 정리하면 다음과 같다. 첫째, 보조금 지원사업의 만족도 향상을 위해서는 사업신청조건 완화보다는 사업선정절차에 대한 만족도 향상을 위한 노력이 필요하다. 둘째, 보조금 지원사업에 의한 소득증대 등의 효과를 통한 보조금 재신청 확대를 위해서는 사업신청조건 완화보다는 사업선정절차에 대한 만족도 향상을 위한 노력이 필요하다. 왜냐하면 보조금 지원사업 선정절차에 대한 만족도 향상 노력은 보조금 지원사업의 만족도 향상뿐만 아니라 재신청 효과를 동시에 향상시킬 수 있는 것으로 나타났다. 따라서 다른 어떤 요인보다도 보조금 사업에 대한 정보제공, 의견반영 등 사업선정절차 만족도 향상에 초점을 맞추어야 할 것이다.

• 대한산업공학회지
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• 제33권4호
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• pp.402-409
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• 2007

Markov Chains has proven to be effective in predicting human behaviors in the areas of web site assess, multimedia educational system, and driving environment. In order to extend an application area of predicting human behaviors using Markov Chains, this study was conducted to investigate whether Markov Chains could be used to predict human behavior in selecting mobile phone menu item. Compared to the aforementioned application areas, this study has different aspects in using Markov Chains : m-order 1-step Markov Model and the concept of Power Law of Learning. The results showed that human behaviors in predicting mobile phone menu selection were well fitted into with m-order 1-step Markov Model and Power Law of Learning in allocating history path vector weights. In other words, prediction of mobile phone menu selection with Markov Chains was capable of user's actual menu selection.

• International Journal of Advanced Culture Technology
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• 제8권4호
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• pp.212-219
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• 2020

We conducted this study to identify the accommodation applications users' lifestyle types and the composition factors for consumers' accommodation applications selection attributes and to identify the difference in the selection attributes perception of accommodation applications between groups classified by user's lifestyle types. According to the study, 6 factors were derived as the accommodation applications users' lifestyle types and were named social/leisure-oriented type, fashion-seeking type, culture-seeking type, self-examining type, self-centered type, family-oriented type. Also 6 factors were derived as the accommodation applications selection attributes and were named convenience, interactivity, economic efficiency, transaction reliability, product reliability and informativeness. Valid clusters were divided into four groups and were named culture/tourism group, self-examining group, passive and cautious group and Social and practicality-seeking group. Most of the selection attributes perception of accommodation applications between groups had statistically significant differences(p<.05), except for some items of transaction reliability. Based on the results of this study, we should strive to establish effective marketing strategies that reflect differences in the selection attributes perception of the accommodation application between groups classified by users' lifestyle types.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2005년도 추계학술대회 논문집
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• pp.488-493
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• 2005

Railload line design of the railroad construction project should be planed considering the variety of quantitative and qualitative factors, and needs to be selected the optimum altinative weighing from VE/LCC analysis of the planned design. The purpose of this research is for showing selecting plan of the optimum railload line and railway bridge applying VE/LCC analysis in selecting the optimum altinative of railroad construction based on quantitative and qualitative factors, such as initial construction cost, maintenance cost, owner and user's requirements. In this research showed the application plan by each stage using data analysis, function analysis, and alternative evaluation of VE/LCC analysis with AHP and LCC analysis program for the selection. This research is proved the rationality and application of the course of selecting the optimum alternative through case application

• 시스템엔지니어링학술지
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• 제18권1호
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• pp.84-89
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• 2022

For system maintenance optimization, it is necessary to establish a state information system by CBM+ including CBM and RCM, and sensor selection for CBM+ application requires system process for function model analysis at the early design stage. The study investigated the contents of CBM and CBM+, analyzed the function analysis tasks and procedures of the system, and thus presented a D-FMEA based sensor selection inference methodology at the early stage of design for CBM+ application, and established it as a D-FMEA based sensor selection inference process. The D-FMEA-based sensor inference methodology and procedure in the early design stage were presented for diesel engine sub assembly.

• 한국전자통신학회논문지
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• 제2권3호
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• pp.174-179
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• 2007

본 논문에서는 유전자 알고리듬을 이용하여 전력, 면적, 속도를 고려한 저전력 모듈 선택을 제안한다. 제안한 알고리듬은 최적의 모듈 선택을 통해서 전력 소모를 최소화 할 수 있다. 비교 실험에서는 최적 모듈 선택을 고려한 알고리듬은 최대 전력 감소량은 26.9 %를 얻을 수 있었고, 반면에 최소 전력 감소량은 9.0% 얻었다. 모든 벤치마크 평균 전력 감소량은 15.525%가 되었다.

• 한국정밀공학회지
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• 제9권3호
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• pp.53-60
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• 1992

This paper deals with developing an Expert system for tool selection using knowledge base system approach, and its application. For the sake of building of knowledge base, the information from process through sensor, tool handbook and interview with expert are referrenced and managed. The system developed shows good application flexibility in providing the actual cutting process with the selection of tool(insert, holder) and cutting conditions(feed, speed, rake type, and so on), is found as a useful system for real-time machining process. The Expert system for tool selection is written in TURBO PROLOG ver. 2.0 for inference engine capability, and can be run in interactive mode for user friendliness. In order to apply the system developed in actual cutting process, more parameters should be considered and scrutinized, and the system should be further extended in modular basis.

• International journal of advanced smart convergence
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• 제11권2호
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• pp.38-43
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• 2022

In this study, there are many difficulties in defining and judging creative people because there is no systematic analysis method using accurate standards or numerical values. Analyze and judge whether In the previous study, A study on the application of rule success cases through machine learning algorithm extraction, a case study was conducted to help verify or confirm the psychological personality test and aptitude test. We proposed a solution to a research problem in psychology using machine learning algorithms, Data Mining's Cross Industry Standard Process for Data Mining, and CRISP-DM, which were used in previous studies. After that, this study proposes a solution that helps to judge creative people by applying the feature selection algorithm. In this study, the accuracy was found by using seven feature selection algorithms, and by selecting the feature group classified by the feature selection algorithms, and the result of deriving the classification result with the highest feature obtained through the support vector machine algorithm was obtained.

• 상하수도학회지
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• 제30권4호
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• pp.427-440
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• 2016

Various kinds of processes are used in the Public Sewage Treatment Works(PSTWs) in order to achieve water quality criteria and TMDL in the watershed. The performance of the existing processes at PSTWs depends on influent characteristics, effluent quality target, amount of sludge production, power cost and other factors. In present, the Selection Guideline for the Available Treatment Process of PSTWs is used for a process decision in the country. But there are some problems regarding redundancy of assessment factors and complexity of assessment procedure in the guideline. In this study, we did a test application of AHP for process selection of PSTWs, which propose is to simplify assessment factors such as pollutant removal amount, sludge generation, electricity consumption, stability of operation, convenience of maintenance, easiness of existing process application, installation cost, and operating cost concerning of environmental factors, technical factors and economical factors. According to the study, the PSTWs selection procedure guideline can be improved using application of AHP method.