• Journal of Navigation and Port Research
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• v.32 no.8
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• pp.637-643
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• 2008

When planning outfall system, the first target cif design is to maximize initial dilution of discharge effluent. To achieve the target effectively, the characteristics of mixing phenomenon between ambient and discharged water should be analyzed. Especially the analysis at the Near-Field-Region(NFR) as initial dilution zone should be preceded. Usually, the initial behavior of effluent through outfall system is rising toward the surface due to mixing with ambient water for heat discharge and sinking toward the bottom due to the difference of density for brine discharge. After mixed with eddies accompanied by the ambient water, the plumes are showing the same density and internal current pattern by advection and diffusion. Until recently, lots of studies are being carried out for the optimum design of outfall system. but it is difficult to find any studies of heat and brine discharge at the same time. Therefore, this study is hoped to provide some basic data for optimum design of outfall system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.317-324
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• 2021

This study deals with keywords from social media on domestic portal sites related to COVID-19, which is spreading widely. The data were collected between January 20 and August 15, 2020, and were divided into three stages. The precursor period is before COVID-19 started spreading widely between January 20 and February 17, the serious period denotes the spread in Daegu between February 18 and April 20, and the stable period is the decrease in numbers of confirmed infections up to August 15. The top 50 words were extracted and clustered based on TF-IDF. As a result of the analysis, the precursor period keywords corresponded to congestion of the Situation. The frequent keywords in the serious period were Nation and Infection Route, along with instability surrounding the Treatment of COVID-19. The most common keywords in all periods were infection, mask, person, occurrence, confirmation, and information. People's emotions are becoming more positive as time goes by. Cafes and blogs share text containing writers' thoughts and subjectivity via the internet, so they are the main information-sharing spaces in the non-face-to-face era caused by COVID-19. However, since selectivity and randomness in information delivery exists, a critical view of the information produced on social media is necessary.

• Information Systems Review
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• v.17 no.1
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• pp.49-64
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• 2015

Customer reviews which include subjective opinions for the product or service in online store have been generated rapidly and their influence on customers has become immense due to the widespread usage of SNS. In addition, a number of studies have focused on opinion mining to analyze the positive and negative opinions and get a better solution for customer support and sales. It is very important to select the key terms which reflected the customers' sentiment on the reviews for opinion mining. We proposed a document-level terms-based sentiment classification model by select in the optimal terms with part of speech tag. SVMs (Support vector machines) are utilized to build a predictor for opinion mining and we used the combination of POS tag and four terms extraction methods for the feature selection of SVM. To validate the proposed opinion mining model, we applied it to the customer reviews on Amazon. We eliminated the unmeaning terms known as the stopwords and extracted the useful terms by using part of speech tagging approach after crawling 80,000 reviews. The extracted terms gained from document frequency, TF-IDF, information gain, chi-squared statistic were ranked and 20 ranked terms were used to the feature of SVM model. Our experimental results show that the performance of SVM model with four POS tags is superior to the benchmarked model, which are built by extracting only adjective terms. In addition, the SVM model based on Chi-squared statistic for opinion mining shows the most superior performance among SVM models with 4 different kinds of terms extraction method. Our proposed opinion mining model is expected to improve customer service and gain competitive advantage in online store.

• 한국벤처창업학회:학술대회논문집
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• 2007.11a
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• pp.111-140
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• 2007

This paper was analyzed to improve internal corporate venture system in public companies. The problems of internal corporate venture systems in a public company were as follows: First, lack of the CEO's willingness in venture business was shown. The culture of venture business also was not mature; Second, the employees were behind the effort to develop their business ability; Third, the objective views are needed to screening venture items and evaluation; Fourth, to measure performance of internal corporate venture, a clear basis and measure system were needed. Fifth, the reward was restricted; Finally, the mother-company did not invest any money for the spin-outed ventures The results of the paper were as follows: First, the CEO's support and effusion of venture culture were needed for successful internal corporate venture system; Second, a public company has to provide education program for venture and information--sharing system; Third, outside consultant may be utilized in finding venture items and feasibility evaluation. Fourth, each venture team may be provided a clear object and specific evaluation system based on characteristic of each team; Fifth, performance-base reward system is needed to enhance motivation; Finally, the public company has to provide find for the spin-off venture by utilizing government system and forming venture capital funds.

• Journal of Korea Technology Innovation Society
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• v.1 no.1
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• pp.125-146
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• 1998

본 연구의 목적은 우리나라의 대형국가연구개발프로그램인 Biotech2000프로그램에 대한 체계적인 평가를 시도하는데 있다. 대형연구개발프로그램과 그 평가에 관련된 연구가 아직 구조화되지 못한 상황이기 때문에 공공정책학분야에서 발전되어온 정책평가이론을 바탕으로 대형연구개발프로그램의 평가를 하기 위한 탐색적인 개념틀을 적립하고, 이를 바탕으로 총14년(1994-2007)의 장기대형프로그램으로 1단계를 마친 Biotech 2000프로그램을 대상으로 프로그램평가의 구성요소 및 이들간의 관계를 체계적으로 평가하여 정책적 시사점을 얻고자 하였다. 평가는 참여자와의 인터뷰조사와 생명공학관련 산·학·연 연구자에 대한 설문조사 및 그 밖의 2차 자료를 통하여 이루어졌으며, 평가의 구성요소로는 프로그램의 원칙 및 전략평가, 추진체계 및 집행평가 그리고 목표달성평가(성과 및 영향평가)를 대상으로 하였다. 본 프로그램은 범부처적인 프로그램으로 프로그램의 형성 및 집행에 있어 성공적으로 이루어지고 있는 것으로 나타났으며, 특히 프로그램의 초기단계이긴 하지만 생명공학기술의 중요성에 대한 인식의 확산에 결정적인 기여를 한 것으로 보인다. 그러나 부처간의 조정이나 연구과제의 비일관성, 산업화에 대한 전략 등의 부재가 문제인 것으로 나타났다.

• Journal of Korea Technology Innovation Society
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• v.14 no.2
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• pp.260-278
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• 2011

Along with the launch of National R&D Program in 1982, National R&D licensing policy began to operate in order to expand and promote the outputs of R&D. Even though various studies attempted to draw plans to improve the National R&D licensing policy, most of their focus was limited to the collection and allocation structure of royalty. Thus, with the aim of approaching National R&D licensing policy in a whole cyclic perspective [from collection allocation to execution' post control], this study incorporates interviews with specialists and officials in charge of technology licensing fee, Industry-University-Institute surveys as well as literature review. Through this endeavor, suggestions are made in the aspects of (1) National R&D licensing policy reformation, (2) Technology licensing fee collection and allocation structure refinement, (3)Post control system establishment.

• Management & Information Systems Review
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• v.30 no.2
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• pp.161-184
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• 2011

It has been widely spread that the acquisition and retention of the core personnel is very important for improving firms' competitiveness. Many companies have made a lot of efforts to keep these core personnel, job embeddedness and work satisfaction are important factors which make effects on workers turnover. Prior research applying for many different industries do not show the consistent research results. There is no empirical research applying for construction IT industry which information technology has been playing more important role because of u-city etc. Therefore, in this research job embeddedness and work satisfaction are to be measured and the relationship with turnover intentions are to be investigated focusing on small and medium construction IT workers. The sub-constructs of job embeddedness are fit, links and sacrifice, and the sub-constructs of work satisfaction are career satisfaction and job satisfaction. It is empirically tested how these factors can have effects on the turnover intentions. Field surveys targeted to construction IT workers were done and finally 177 survey questionnaires were used to analyze. Research results show that if the sacrifice, career satisfaction and job satisfaction of small and medium construction IT workers are higher, turnover intentions will be lower. On the other hand, 2 hypotheses are rejected that if the fit and links of these workers are higher, turnover intentions will be lower. These research results clarified the factors affecting the turnover intentions of small and medium construction IT workers and can be utilized how turnover intentions can be decreased practically.

• Journal of Korea Technology Innovation Society
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• v.21 no.2
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• pp.587-614
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• 2018

The Korean government is aiming to strengthen industrial and national competitiveness through the promotion of cooperation between universities, public research institutes and industry and vitalization of technology transfer. In 2013 and 2014, the Ministry of Trade, Industry and Energy and Ministry of Science, ICT and Future Planning have announced policies to support SMEs by public research organizations. In addition, in 2015, the 'Korean Fraunhofer support system', which pay government subsidies according to the amounts of private R&D funds was adopted. However, there are some concern about the government's policies. There is yet disclosed how these policies affect technology transfer because industrial R&D funding has not been activated in Korea unlike German. Therefore this paper analyzes effects of relationship between universities, public research institutes and external organizations on performance of technology transfer based on the Triple Helix Model. Empirical results show that the relationship with the government has a significant impact on the resource security and the relationship with the industry has a significant effect on the diffusion of the performance. In addition, a public research institute was selected and case analysis was conducted to suggest policy implications for improving the technology transfer performance of universities and public research institutes.

• Journal of Convergence for Information Technology
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• v.7 no.6
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• pp.259-265
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• 2017

This study reviewed the existing studies in order to set up a strategy that can achieve the trust and business performance of the franchisers, who are actually operating franchised business, breaking from the research trend centered around franchise headquarters and added the factors of the franchise headquarters' strategy for expanding franchises, including word-of-mouth communication and advertising & publicity and added the exercise of recruitment agency outsourcing, flagship store, recently utilized often as preceding variables to verify the causal relation between the trust of the franchiser and the business performance of the franchise. The implications of this study, it can be concluded that the government authority for the attraction of healthy franchises can continuously attract franchises and enter the market can continuously attract franchises by increasing the trust of the franchises, and powerfully investing and managing them for the effort through word-of-mouth marketing. It is expected that this study will be helpful in the establishment of a business strategy for forming a continuous relationship as well as the franchise head office's strategy for the recruitment of new franchises.

• Information Systems Review
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• v.24 no.1
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• pp.1-19
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• 2022

Social media-based communication has become crucial part of our personal and official lives. Therefore, it is no surprise that social media sentiment analysis has emerged an important way of detecting potential customers' sentiment trends for all kinds of companies. However, social media sentiment analysis suffers from huge number of sentiment features obtained in the process of conducting the sentiment analysis. In this sense, this study proposes a novel method by using Bayesian Network. In this model MBFS (Markov Blanket-based Feature Selection) is used to reduce the number of sentiment features. To show the validity of our proposed model, we utilized online review data from Yelp, a famous social media about restaurant, bars, beauty salons evaluation and recommendation. We used a number of benchmarking feature selection methods like correlation-based feature selection, information gain, and gain ratio. A number of machine learning classifiers were also used for our validation tasks, like TAN, NBN, Sons & Spouses BN (Bayesian Network), Augmented Markov Blanket. Furthermore, we conducted Bayesian Network-based what-if analysis to see how the knowledge map between target node and related explanatory nodes could yield meaningful glimpse into what is going on in sentiments underlying the target dataset.