• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3141-3143
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• 1999

Fuel cell systems offer high energy efficiencies for transportation application. In addition, they can use alcohols and alternative fuels as the fuel, while producing little or no noxious emissions. Fuel cell-powered energy source should be competitive in performance characteristics and in capital and maintenance costs with internal combustion engine systems. From computer simulation program, battery and fuel cell energy output and total power profile, motor power, battery energy output, fuel cell energy output. It simulates the performance of fuelcell/battery powered energy source operation over any user inputted transit route cycle, and provides performance criteria through user specifications for preliminary design consideration.

• Journal of Astronomy and Space Sciences
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• v.11 no.2
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• pp.296-307
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• 1994

Using X-Window system (Motif Graphic User Interface), the AKM (Apogee Kick Motor) firing software for Koreasat which will be launched in 1995 has been developed to transfer the spacecraft from its transfer orbit, provided by the DeltaII launch vehicle, into a nearly geostationary drift orbit. The AKM firing software runs in one of two modes. In mission analysis mode, using a fixed magnitude impulsive velocity change, it provides the necessary data for planning the burn parameters. In insert mode, it uses the orbit propagator function to integrate the spacecraft state through the AKM burn. In this case, an AKM thrust profile and specific impulse are applied to the necessary data for planning the burn parameters to obtain the best possible drift orbit. The apogee burn planning simulation for orbital transfer of Koreasat has been performed using the AKM firing software. And the result of this simulation has been analyzed.

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.43-56
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• 2020

Recommender systems help users make the best choice among various options. Especially, recommender systems play important roles in internet sites as digital information is generated innumerable every second. Many studies on recommender systems have focused on an accurate recommendation. However, there are some problems to overcome in order for the recommendation system to be commercially successful. First, there is a lack of transparency in the recommender system. That is, users cannot know why products are recommended. Second, the recommender system cannot immediately reflect changes in user preferences. That is, although the preference of the user's product changes over time, the recommender system must rebuild the model to reflect the user's preference. Therefore, in this study, we proposed a recommendation methodology using topic modeling and sequential association rule mining to solve these problems from review data. Product reviews provide useful information for recommendations because product reviews include not only rating of the product but also various contents such as user experiences and emotional state. So, reviews imply user preference for the product. So, topic modeling is useful for explaining why items are recommended to users. In addition, sequential association rule mining is useful for identifying changes in user preferences. The proposed methodology is largely divided into two phases. The first phase is to create user profile based on topic modeling. After extracting topics from user reviews on products, user profile on topics is created. The second phase is to recommend products using sequential rules that appear in buying behaviors of users as time passes. The buying behaviors are derived from a change in the topic of each user. A collaborative filtering-based recommendation system was developed as a benchmark system, and we compared the performance of the proposed methodology with that of the collaborative filtering-based recommendation system using Amazon's review dataset. As evaluation metrics, accuracy, recall, precision, and F1 were used. For topic modeling, collapsed Gibbs sampling was conducted. And we extracted 15 topics. Looking at the main topics, topic 1, top 3, topic 4, topic 7, topic 9, topic 13, topic 14 are related to "comedy shows", "high-teen drama series", "crime investigation drama", "horror theme", "British drama", "medical drama", "science fiction drama", respectively. As a result of comparative analysis, the proposed methodology outperformed the collaborative filtering-based recommendation system. From the results, we found that the time just prior to the recommendation was very important for inferring changes in user preference. Therefore, the proposed methodology not only can secure the transparency of the recommender system but also can reflect the user's preferences that change over time. However, the proposed methodology has some limitations. The proposed methodology cannot recommend product elaborately if the number of products included in the topic is large. In addition, the number of sequential patterns is small because the number of topics is too small. Therefore, future research needs to consider these limitations.

• Journal of Internet Computing and Services
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• v.12 no.2
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• pp.9-17
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• 2011

This paper proposes an algorithm that predicts the state of user's next actions, exploiting the HMM (Hidden Markov Model) on user profile data stored in the ubiquitous home network. The HMM, recognizes patterns of sequential data, adequately represents the temporal property implicated in the data, and is a typical model that can infer information from the sequential data. The proposed algorithm uses the number of the user's action performed, the location and duration of the actions saved by "Activity Recognition System" as training data. An objective formulation for the user's interest in his action is proposed by giving weight on his action, and change on the state of his next action is predicted by obtaining the change on the weight according to the flow of time using the HMM. The proposed algorithm, helps constructing realistic ubiquitous home networks.

• The KIPS Transactions:PartD
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• v.11D no.5
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• pp.1049-1062
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• 2004

With the popularization of a World Wide Web (WWW), the quantity of web information has been increased. Therefore, an efficient searching system is needed to offer the exact result of diverse Information to user. Due to this reason, it is important to extract and analysis of user requirements in the distributed information environment. The conventional searching method used the only keyword for the web searching. However, the searching method proposed in this paper adds the context information of keyword for the effective searching. In addition, this searching method extracts keywords by the new keyword extraction method proposed in this paper and it executes the web searching based on a keyword mining profile generated by the extracted keywords. Unlike the conventional searching method which searched for information by a representative word, this searching method proposed in this paper is much more efficient and exact. This is because this searching method proposed in this paper is searched by the example based query included content information as well as a representative word. Moreover, this searching method makes a domain keyword list in order to perform search quietly. The domain keyword is a representative word of a special domain. The performance of the proposed algorithm is analyzed by a series of experiments to identify its various characteristic.

• Journal of the Korea Safety Management & Science
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• v.16 no.3
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• pp.219-229
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• 2014

Employees used computer significantly(IT employee) is increased by technological development in workplace. This study tried to find the magnitude of IT employees and the profile of their working conditions and ill health experiences in South Korea. Korean Working Conditions Survey was used with descriptive and mean difference test in order to find the difference working conditions and ill health status among the groups classified by the degree of using computer during work. Some of working conditions was positively correlated with the density of computer use such as work autonomy, the exposure of repetitive movement of hand and arms. The pain of upper extreme was also more frequently found in the highest user group of computer than lower user groups. Based on the result of hierarchical regression analysis, the effect of computer using on the experience of work-related symptoms after controlling other factors was shown as U shape. This study as heuristic one suggest that some of depth analysis with hypothesis will be done to identify the causes and pathway of impact of computer use.

• Journal of Information Technology Applications and Management
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• v.14 no.4
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• pp.221-233
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• 2007

Which factors should influence consumer consideration to subscribe to Voice over Internet Protocol (VoIP)? Policy issues, managerial concerns, and demographic variables are possible factors. This paper discusses policy and managerial issues regarding VoIP adoption. A model that explains VoIP adoption is proposed and tested. This study analyzes a survey of 750 prospective VoIP users in Korea. The testing is accompanied by logistic regression and discriminant analysis. The results show that trust in VoIP, relative comparison of Quality to fixed service, numbering plan, satisfactions of call Quality and customer services on both fixed and mobile services have impacts on the adoption of VoIP. Implications for VoIP providers and policy makers are presented.

• The Journal of Korean Society for School & Community Health Education
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• v.9 no.2
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• pp.65-80
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• 2008

Objectives: To identify the relationship between the internet addition of elementary school students, and their health behavior and VDT syndrome, and thereby to detect the impact of internet addiction on the health behavior of elementary school students, to get the basic information necessary to develop a prevention program for internet addiction and to plan for VDT syndrome prevention program. Methods: We conducted this study during the period from jun 27, 2007 through July 8, 2007. The subjects of this study were 416 children whose grades were in 4th through 6th grades of elementary schools located in the city A in Kyung Pook Providence. Data were obtained from self-rating questionnaires. The questionnaires were composed of Korean Internet Addiction Self-examination on Internet Use Patterns (K-scale), Health Behavior Profile, VDT Syndrome, and general characteristics. We used t-test, AVOVA with Ducan method for Post-hoc comparison in means comparison between groups, $X^2$-test for frequency analysis and Pearson's correlation coefficient. We used SPSS/PC(12.0 ver) program and the LISREL 8.53 Win program for covariance structural analysis. Results: Major results were as follows. 1. The internet addiction propensity distribution based on the distribution of scores were investigated according to the self diagnosis scale on internet addiction. 6.5% of them were high risk user group, 14.4% were potential risk users and 79.1% of them were common user groups. 2. Internet addictions by sex, internet use duration, frequency (days/week), time(hours/day), purpose, position, brightness of internet, attitude of parents and frequency of conversation of family members were statistically significant(p<0.01). 3. There was a statistically significant difference in VDT syndrome according to internet addiction groups(p<0.001) besides ocular symptoms, dry mouth and GI troubles. 4. The health behavior score was the lowest in high risk user group(p<0.001). There were significant differences between internet addiction groups in personal hygiene and habits of daily living(p<.002), the prevention of accidents(p<.002), the practice concerned with the prevention of infectious disease(p=.002), and mental health(p<.001). 5. There was also a significant negative correlation between internal addiction and health profile(r=-0.365, p<0.01) and a significant positive correlation between internal addiction and VDT syndrome(r=0.331, p<0.01). 6. As the result of structural model analysis, internet use time(/day), days of internet use(/1week), conversation frequency among family members, degree of brightness of internet use had significant direct effects on internet addiction. Conclusions: The results will help the development of an effective intervention program for the prevention and treatment of internal addiction by clarifying the effect of the internal addiction upon elementary school students' VDT syndrome and health behavior.

• 한국HCI학회:학술대회논문집
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• 2009.02a
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• pp.11-14
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• 2009

In this paper, we propose the method configuring social networks among users based on users' context and profile. Recently, many researchers are concerned about social networks related with collaborative systems. In case of the existing researches, however, it is difficult to configure social networks dynamically because they are based on static data types, such as log and profile of users. The proposed method uses not only user profiles but also context reflecting users' behavior dynamically. It computes the similarity among users' behavior contexts using hierarchical structure of context domain knowledge model. And it calculates relationships between contexts by given weight factors of category of context model. In order to verify usefulness of the method, we conduct an experiment on configuring social network according to change of user context. We expect that it makes dynamic analysis of relationship of users possible.

• Journal of Korea Multimedia Society
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• v.6 no.1
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• pp.97-104
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• 2003

The appearance of various portal web sites that have individual customers, customizing information operate importantly upon a content. But most current portal sites that has a goal for international electronic commerce use information for customer to a simply individual profile and don't create more and new information that customizing. In this paper, we propose a system that generates a new customizing information with classification and analysis in detail and provides automatically to individual customers. The goal of our research is the development of personalizing auto generation agent that composed form of e-mail from preference of each individual user using open rate and mouse event Information for e-mail.