• Journal of the Korea institute for structural maintenance and inspection
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• v.14 no.1
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• pp.117-124
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• 2010

Different to other social infrastructures, bridge elements or bridges can be damaged or collapsed and this may cause death toll and severe social and economical damage, bridges should be managed to maintain a safety level. Diverse strengthening methods is developed to improve a deteriorated bridge performance up to original design level. But rational decision-making process and methodologies to select a optimum strengthening method are absence yet in Korea. This paper therefore derived items and proposed methodologies for quantity estimate considering uncertainty to select a optimum strengthening method among conceptually designed alternatives. And also, to demonstrate the applicability and verification of the proposed approach, it was applied to select the optimum strengthening method for the deteriorated T-shape concrete girder bridge. The model and the procedure can greatly contribute to the uncertainty-oriented alternative selection.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.3
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• pp.306-310
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• 2008

Since the preference for information recommendation service can change according to the context, we should know the user context before providing information recommendation. This paper proposes recommender system that considers multi-user preference in mobile environment and attempted to apply it to restaurant recommendation. To model the preference of individual users in mobile environment, we have used Bayesian network, and restaurant recommendation mostly should consider not an individual user but several users, so this paper has used AHP of multi-criteria decision making process to obtain the preference of several users based on one of individual users. For experiments, we conducted recommendation in 10 different situations, and finally, we confirmed that the proposed system was evaluated as a good one using a usability test of SUS.

• Journal of Digital Convergence
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• v.11 no.3
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• pp.345-352
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• 2013

The demand and production for mobile music increases as the number of smart phone users increase. Thus, the standard of selection of a user's preferred music has gotten more diverse and complicated as the range of popular music has gotten wider. Research to find intelligent techniques to ingeniously recommend music on user preferences under mobile environment is actively being conducted. However, existing music recommendation systems do not consider and reflect users' preferences due to recommendations simply employing users' listening log. This paper suggests a personalized music-recommending system that well reflects users' preferences. Using AHP, it is possible to identify the musical preferences of every user. The user feedback based on the Bayesian network was applied to reflect continuous user's preference. The experiment was carried out among 12 participants (four groups with three persons for each group), resulting in a 87.5% satisfaction level.

• Journal of Internet Computing and Services
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• v.13 no.5
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• pp.21-31
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• 2012

Threat Evaluation(TE) which has air intelligence attained by identifying friend or foe evaluates the target's threat degree, so it provides information to Weapon Assignment(WA) step. Most of TE data are passed by sensor measured values, but existing techniques(fuzzy, bayesian network, and so on) have many weaknesses that erroneous linkages and missing data may fall into confusion in decision making. Therefore we need to efficient Threat Evaluation system that can refine various sensor data's linkages and calculate reliable threat values under unpredictable war situations. In this paper, we suggest new threat evaluation system based on information fusion JDL model, and it is principle that combine fuzzy which is favorable to refine ambiguous relationships with bayesian network useful to inference battled situation having insufficient evidence and to use learning algorithm. Finally, the system's performance by getting threat evaluation on an air defense scenario is presented.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.1-17
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• 2011

In order to maintain customer satisfaction and to remain productive and efficient in today's global competition, mass customization is adopted in many leading companies. Mass customization through product family and product platform enables companies to develop new products with flexibility, efficiency and quick responsiveness. Thus, product family strategy based on product platform is well suited to realize the mass customization. Product family is defined as a group of related products that share common features, components, and subsystems; and satisfy a variety of market niches. The objective is to propose a product family design strategy that provides priority weights among product components by satisfying customer requirements. The decision making process for a new product development requires a multiple criteria decision making technique with feedback. An analytical network process is adopted for the decision making modeling and procedure. For the implementation, a netbook product known as a small PC which is appropriate for the product family model is adopted. According to the proposed architecture, the priority weight of each component for each product family is derived. The relationship between the customer requirement and product component is analyzed and evaluated using QFD model.

• Journal of Digital Contents Society
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• v.17 no.5
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• pp.307-316
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• 2016

A user usually gets the same suggesting results as everyone else in most of the multimedia social services, nowadays. To address the challenging problem of personalization in the social network, we propose a method which exploits user's activities, user's moods, and user's friend relationships from the social network to build a decision-making system. Depending on a current state of the user's mood, this system infers the most appropriated video for the user. In the system, the user evaluates a set of the given recommendation methods which extract from the user's database social network and assigns a vague value to each method by a weight. Then, we find the fuzzy collection solution for the system and classify the set of methods into subsets, and order the subsets based on its local dominance to choose the best appropriate method. Finally, we conduct an experiment using the YouTube API with a lot of video types. The experiment result shows that the channel recommendation system appropriately affords the user's character, it is more satisfying than the current YouTube based on an evaluation of several users.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1173-1183
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• 2016

In this paper, we proposed an information security risk index to diagnose users' malware infection situations (such as computer virus and adware) by gathering data from KT network systems. To develop the information security risk index, we used the analytic hierarchy process methodology and estimated the risk weights of malware code types using the judgments of experts. The control chart could be used effectively to forecast the information security risk for the proposed information security risk index data.

• 한국벤처창업학회:학술대회논문집
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• 2023.11a
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• pp.85-89
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• 2023

최근 급변하는 세계 경제 환경에서 창업기업은 혁신, 고용 및 경제 활력의 핵심 동력으로 등장했다. 그러나 초기 창업 기업이 성장하는 여정에는 많은 어려움이 따르며, 이 과정에서 엔젤투자자의 역할이 필수적이다. 초기 창업 시장의 촉매제 역할을 하는 엔젤투자자는 필요한 자본을 제공할 뿐만 아니라 경영 노하우 및 네트워크를 통해 창업기업이 성공할 수 있도록 지원한다. 그러나 최근 데이터에 따르면 신생 기업 중 엔젤 투자의 혜택을 받는 기업은 1.4%에 불과한 것으로 나타나 창업기업의 잠재력과 지원 사이에는 분명한 공백이 존재한다. 이 연구는 지속가능한 경제 성장을 위해 창업 생태계의 중요한 요소인 엔젤투자자의 위험회피 성향을 이해함으로써 이들의 투자 행동, 의사결정 프로세스에 대한 통찰력을 얻을 수 있다. 위험회피가 엔젤투자에 미치는 영향을 알아보고 엔젤투자가 활성화 될 수 있는 방법을 제안하고자 한다. 본 연구를 통해 위험회피 성향이 엔젤투자에 대한 관심도와 실제 투자 활동 간의 관계를 추정해보고자 한다. 위험회피 성향이 엔젤투자자에 어떻게 영향을 미치는지 탐색하는 것에 중점을 두고, 엔젤투자자의 행동과 관심사에 영향을 미치는 다양한 요인들을 포함하여 진행한다. 연구 표본은 서울 및 경기 지역의 일반 성인과 엔젤투자자로 설문조사를 통해 필요한 데이터를 수집한다. 이 연구는 위험회피 성향이 엔젤투자 결정에 어떻게 반영되는지에 대한 깊은 이해를 제공하고, 엔젤투자 활성화를 위한 정책 및 전략을 수립하는데 중요한 통찰력을 제공할 것이다.

• Journal of Korea Port Economic Association
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• v.29 no.4
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• pp.73-95
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• 2013

This paper analyzes a competitive shipping market in East Asia in order to explore how container carriers make decisions on ship size, number of ships, service frequency, and service route. A sequential-move game based on non-cooperative game theory is applied to establish the models for the decision-makings involving the transportation volumes, freight rates, costs, and market shares of the service routes from Shanghai or Hong Kong to the ports in Busan, Gwangyang, and Incheon. According to the sub-game perfect Nash equilibrium solutions proposed by these models, carriers' decisions in such a competitive environment vary depending on sailing distance, transport demand, and freight rates. Therefore, carriers are recommended to reflect the optimal equilibrium solutions and a variety of decision factors when formulating strategies for transportation networks and operating fleets. Furthermore, ports should establish management strategies for these factors to provide optimal equilibrium solutions for carriers' transportation networks.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.5
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• pp.185-196
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• 2023

This paper investigates the effects of entrepreneurs' cognitive biases on business opportunity evaluation, given their strong entrepreneurial spirit, which is characterized by innovation, proactivity, and risk-taking. When making decisions related to business activities, entrepreneurs typically make rational judgments based on their knowledge, experience, and the advice of external experts. However, in situations of extreme stress or when quick decisions are required, they often rely on heuristics based on their cognitive biases. In particular, we often see cases where entrepreneurs fail because they make decisions based on heuristics in the process of evaluating and selecting new business opportunities that are planned to guarantee the growth and sustainability of their companies. This study was conducted in response to the need for research to clarify the effects of entrepreneurs' cognitive biases on new business opportunity evaluation, given that the cognitive biases of entrepreneurs, which are formed by repeated successful experiences, can sometimes lead to business failure. Although there have been many studies on the effects of cognitive biases on entrepreneurship and opportunity evaluation among university students and general people who aspire to start a business, there have been few studies that have clarified the relationship between cognitive biases and social networks among entrepreneurs. In contrast to previous studies, this study conducted empirical surveys of entrepreneurs only, and also conducted research on the relationship with social networks. For the study, a survey was conducted using a parallel survey method using online mobile surveys and self-report questionnaires from 150 entrepreneurs of small and medium-sized enterprises. The results of the study showed that 'overconfidence' and 'illusion of control', among the independent variables of entrepreneurs' cognitive biases, had a statistically significant positive(+) effect on business opportunity evaluation. In addition, it was confirmed that the moderating variable, social network, moderates the effect of overconfidence on business opportunity evaluation. This study showed that entrepreneurs' cognitive biases play a role in the process of evaluating and selecting new business opportunities, and that social networks play a role in moderating the structural relationship between entrepreneurs' cognitive biases and business opportunity evaluation. This study is expected to be of great help not only to entrepreneurs, but also to entrepreneur education and policy making, by showing how entrepreneurs can use cognitive biases in a positive way and the influence of social networks.