• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.1
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• pp.203-215
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• 2017

Recently, interest in Pedestrian Navigation Service (PNS) is being increased due to the diffusion of smart phone and the improvement of location determination technology and it is efficient to use landmarks in route guidance for pedestrians due to the characteristics of pedestrians' movement and success rate of path finding. Accordingly, researches on extracting landmarks have been progressed. However, preceding researches have a limit that they only considered the difference between buildings and did not consider visual attention of maps in display of PNS. This study improves this problem by defining building attributes as local variable and global variable. Local variables reflect the saliency of buildings by representing the difference between buildings and global variables reflects the visual attention by representing the inherent characteristics of buildings. Also, this study considers the connectivity of network and solves the overlapping problem of landmark candidate groups by network voronoi diagram. To extract landmarks, we defined building attribute data based on preceding researches. Next, we selected a choice point for pedestrians in pedestrian network data, and determined landmark candidate groups at each choice point. Building attribute data were calculated in the extracted landmark candidate groups and finally landmarks were extracted by principal component analysis. We applied the proposed method to a part of Gwanak-gu, Seoul and this study evaluated the extracted landmarks by making a comparison with labels and landmarks used by portal sites such as the NAVER and the DAUM. In conclusion, 132 landmarks (60.3%) among 219 landmarks of the NAVER and the DAUM were extracted by the proposed method and we confirmed that 228 landmarks which there are not labels or landmarks in the NAVER and the DAUM were helpful to determine a change of direction in path finding of local level.

• Management & Information Systems Review
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• v.36 no.5
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• pp.121-149
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• 2017

This study looks into individual entrepreneurship engaged in an enterprise; the effect of creative efficacy and internal and external networks on organizational commitment based on the previous studies. The hypothesis, the internal and external networks constructed in social context by individuals in the relationship between individual entrepreneurship and organizational commitment; and mediating effect through creative efficacy obtained by the previous experience can be in existence, is to be confirmed through an empirical study. The analysis data is collected from 244 of currently working employees via a survey. The determination of employee-oriented study is summarized as follows: first, the promotion of employee's individual entrepreneurship is significant as well as of the leader for the result of organizational commitment, because there are positive effects between the individual entrepreneurship and organizational commitment. Second, the internal and external networks owned by individuals affect one's own outcome as the internal and external networks of enterprise mediate the relationship between individual entrepreneurship and organizational commitment. Third, it is confirmed that the confidence in individual creativity is an essential factor as creative efficacy exhibits a mediating effect in relationship between individual entrepreneurship and organizational commitment. Particularly, it is verified that an enterprise is in need to expand education or programs not only for networks leading to an outcome but also for creativity improvement of affiliated individuals from the fact that creative efficacy, a hybridized concept of creativity and self-efficacy studied in the previous research, mediates the relationship between individual entrepreneurship and an outcome. In the conclusion, additional implications are offered; the thresholds and frameworks for the study are discussed.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.1-20
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• 2013

Nowadays, social network is a huge communication platform for providing people to connect with one another and to bring users together to share common interests, experiences, and their daily activities. Users spend hours per day in maintaining personal information and interacting with other people via posting, commenting, messaging, games, social events, and applications. Due to the growth of user's distributed information in social network, there is a great potential to utilize the social data to enhance the quality of recommender system. There are some researches focusing on social network analysis that investigate how social network can be used in recommendation domain. Among these researches, we are interested in taking advantages of the interaction between a user and others in social network that can be determined and known as social relationship. Furthermore, mostly user's decisions before purchasing some products depend on suggestion of people who have either the same preferences or closer relationship. For this reason, we believe that user's relationship in social network can provide an effective way to increase the quality in prediction user's interests of recommender system. Therefore, social relationship between users encountered from social network is a common factor to improve the way of predicting user's preferences in the conventional approach. Recommender system is dramatically increasing in popularity and currently being used by many e-commerce sites such as Amazon.com, Last.fm, eBay.com, etc. Collaborative filtering (CF) method is one of the essential and powerful techniques in recommender system for suggesting the appropriate items to user by learning user's preferences. CF method focuses on user data and generates automatic prediction about user's interests by gathering information from users who share similar background and preferences. Specifically, the intension of CF method is to find users who have similar preferences and to suggest target user items that were mostly preferred by those nearest neighbor users. There are two basic units that need to be considered by CF method, the user and the item. Each user needs to provide his rating value on items i.e. movies, products, books, etc to indicate their interests on those items. In addition, CF uses the user-rating matrix to find a group of users who have similar rating with target user. Then, it predicts unknown rating value for items that target user has not rated. Currently, CF has been successfully implemented in both information filtering and e-commerce applications. However, it remains some important challenges such as cold start, data sparsity, and scalability reflected on quality and accuracy of prediction. In order to overcome these challenges, many researchers have proposed various kinds of CF method such as hybrid CF, trust-based CF, social network-based CF, etc. In the purpose of improving the recommendation performance and prediction accuracy of standard CF, in this paper we propose a method which integrates traditional CF technique with social relationship between users discovered from user's behavior in social network i.e. Facebook. We identify user's relationship from behavior of user such as posts and comments interacted with friends in Facebook. We believe that social relationship implicitly inferred from user's behavior can be likely applied to compensate the limitation of conventional approach. Therefore, we extract posts and comments of each user by using Facebook Graph API and calculate feature score among each term to obtain feature vector for computing similarity of user. Then, we combine the result with similarity value computed using traditional CF technique. Finally, our system provides a list of recommended items according to neighbor users who have the biggest total similarity value to the target user. In order to verify and evaluate our proposed method we have performed an experiment on data collected from our Movies Rating System. Prediction accuracy evaluation is conducted to demonstrate how much our algorithm gives the correctness of recommendation to user in terms of MAE. Then, the evaluation of performance is made to show the effectiveness of our method in terms of precision, recall, and F1-measure. Evaluation on coverage is also included in our experiment to see the ability of generating recommendation. The experimental results show that our proposed method outperform and more accurate in suggesting items to users with better performance. The effectiveness of user's behavior in social network particularly shows the significant improvement by up to 6% on recommendation accuracy. Moreover, experiment of recommendation performance shows that incorporating social relationship observed from user's behavior into CF is beneficial and useful to generate recommendation with 7% improvement of performance compared with benchmark methods. Finally, we confirm that interaction between users in social network is able to enhance the accuracy and give better recommendation in conventional approach.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.1
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• pp.74-82
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• 2002

The present study is aimed to investigate the effect of the safety hat on the balance of body temperature by observation of the physiological response under hot working environment. The experiment was carried out in a climate chamber of 3$0^{\circ}C$, 50%RH for 70 minutes. To compare the two kinds of safety hat, 5 healthy male subjects worn safety hat without hole (called 'without hole') or safety hat with hole (called 'with hole') according to a randomized cross-over design. The main results of this study are as fellows: Rectal temperature and heart rate were significantly lower level in 'with hole'than in 'without hole'. The mean skin temperature was significantly higher in 'without hole'than in 'with hole'. Blood pressure were significantly low in 'with hole'. Sweat rate which was measured by weight loss before and after experiment was higher in 'without hole'. In subjective ratings, subjects replied more hot, more uncomfortable and more wet, they felt more fatigue in condition of 'without hole'. Work ability which was measured by a grip strength dynamometer was higher in 'with hole'. Safety hat which can be used for safety of the brain in work place is meaningful device of behavioral thermoregulatory response under the hot working environment. The safety hat which is designed for proper ventilation and hygiene can maintain the homeostasis of body temperature by releasing body temperature efficiently.

• Journal of Life Science
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• v.25 no.5
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• pp.523-532
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• 2015

A variety of previous pharmacological studies have suggested Liriope platyphylla (L. platyphylla) may exert beneficial biological effects on inflammation, diabetes, neurodegenerative disorder, obesity, constipation, and atopic dermatitis. In addition, hydrocolloid membranes (HCMs) have attracted attention in dermatological care, including in the treatment of scleroderma skin ulcers, cutaneous ulcers, permanent tympanic membrane perforations, pressure sores, and decubitus ulcers in the elderly. To investigate the therapeutic effects of HCM containing an aqueous extract of L. platyphylla (HCM-LP) on second-degree burn wounds, their physico-chemical properties were analyzed and the therapeutic effects were observed in SD rats after treatment with HCM-LP for 14 days. Significant declines in tensile strength (38.4%) and absorptiveness (46.3%), as well as an increase in surface roughness (38.1%) were detected in HCM-LP compared with that of HCM. In SD rats with burned skin, the wound diameter was shorter in the HCM-LP treated group than in the GZ group on post-surgical day 14, while the significant improvements in scar tissue reduction, epithelium regeneration, angiogenesis, and extracellular matrix deposition were observed in the HCM-LP-treated group during all experimental periods. Overall, these results suggest HCM-LP may accelerate the process of healing the burn injury skin of SD rats through the regulation of angiogenesis and connective tissue formation.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.5
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• pp.79-96
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• 2021

Green infrastructure planning represents landscape planning measures to reduce particulate matter. This study aimed to derive factors that may be used in planning green infrastructure for particulate matter reduction using text mining techniques. A range of analyses were carried out by focusing on keywords such as 'particulate matter reduction plan' and 'green infrastructure planning elements'. The analyses included Term Frequency-Inverse Document Frequency (TF-IDF) analysis, centrality analysis, related word analysis, and topic modeling analysis. These analyses were carried out via text mining by collecting information on previous related research, policy reports, and laws. Initially, TF-IDF analysis results were used to classify major keywords relating to particulate matter and green infrastructure into three groups: (1) environmental issues (e.g., particulate matter, environment, carbon, and atmosphere), target spaces (e.g., urban, park, and local green space), and application methods (e.g., analysis, planning, evaluation, development, ecological aspect, policy management, technology, and resilience). Second, the centrality analysis results were found to be similar to those of TF-IDF; it was confirmed that the central connectors to the major keywords were 'Green New Deal' and 'Vacant land'. The results from the analysis of related words verified that planning green infrastructure for particulate matter reduction required planning forests and ventilation corridors. Additionally, moisture must be considered for microclimate control. It was also confirmed that utilizing vacant space, establishing mixed forests, introducing particulate matter reduction technology, and understanding the system may be important for the effective planning of green infrastructure. Topic analysis was used to classify the planning elements of green infrastructure based on ecological, technological, and social functions. The planning elements of ecological function were classified into morphological (e.g., urban forest, green space, wall greening) and functional aspects (e.g., climate control, carbon storage and absorption, provision of habitats, and biodiversity for wildlife). The planning elements of technical function were classified into various themes, including the disaster prevention functions of green infrastructure, buffer effects, stormwater management, water purification, and energy reduction. The planning elements of the social function were classified into themes such as community function, improving the health of users, and scenery improvement. These results suggest that green infrastructure planning for particulate matter reduction requires approaches related to key concepts, such as resilience and sustainability. In particular, there is a need to apply green infrastructure planning elements in order to reduce exposure to particulate matter.

• Journal of the Korean Society of Food Science and Nutrition
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• v.44 no.9
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• pp.1388-1398
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• 2015

Quality Function Deployment (QFD) is the most complete and comprehensive method for translating what customers need from a product. This study utilized QFD to develop sauces made from Gochujang and to determine how to fulfill international customers' requirements. A customer survey and expert opinion survey were conducted from May 13 to August 22, 2014 and targeted 220 consumers and 20 experts in the U.S. and China. Finally, a total of 208 (190 consumers and 18 experts) useable data were selected. The top three customer requirements for Gochujang sauces were identified as fresh flavor (4.40), making better flavor (3.99), and cooking availability (3.90). Thirty-three engineering characteristics were developed. The results from the calculation of relative importance of engineering characteristics identified that 'cooking availability', 'free sample and food testing', 'unique concept', and 'development of brand' were the highest. The relative importance of engineering characteristics, correlation, and technical difficulties are ranked, and this result could contribute to the development Korean sauces based on customer needs and engineering characteristics.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.3
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• pp.21-29
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• 2023

In this study, the stress characteristics of temporary fixed steel rods were analyzed in the "temporary fixing system using internal prestressing tension", which is mainly applied to the construction of superstructures by FCM. It was difficult to confirm the changes in initial tensile force in this system because the steel rod was internally connected to the pier and the PSC BOX. Therefore, measurement was performed before and after the completion of each segment using an FBG sensor to measure the change in the micro length of the steel rod. The results of the analysis showed that 75% to 90% of the maximum vertical contraction of the steel rod that occurred until the completion of the cantilever segment occurred in the fixing ~ 1segment, and the maximum loss of initial prestressing force was 39%. Such excessive loss of tension force to 1 segment means that tension is needed to improve the precision of construction during the fixation, and re-tension is needed to secure stability for conduction of cantilever segments after the completion of 1segment. In the 2 ~ last segment, the stress of the steel rod decreased gradually, and in the summer, the decrease in stress tended to partially recover due to the increase in the length of the steel rod corresponding to the increase in the vertical volume of PSC BOX. The dominant factor in the stress change in 2~ last segment in this phenomenon is judged to be the change in the length of the steel rod according to the temperature. Unlike the change in length, the relaxation was 1.2-2.7%, which was mostly offset by the opposite stress corresponding to the temperature stress. Therefore, a plan was proposed to improve the internal stress, such as adjusting the fixation time.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.1
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• pp.72-85
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• 2018

This study focused on cases that led sustainable urban development through the construction and utilization of organic greenery systems linking green spaces of urban peripheries with metropolitan areas. To that end, Berlin - Brandenburg's regional parks in Germany and Milan's Raggi Verdi, a radial green axis project, in Italy were selected for analysis as case studies. As frameworks for this analysis, this study has established existing infrastructure accessibility and linkage, recycling and cooperative management. The results of the case study analysis are as follows: First, the specialized spatial strategy based on the individuality of the green space outside the city rather than a uniform landscape was used as the foundation of the sustainable development plan. Second, physical linkage from the center of the city to the periphery contributed to the sustainable development of the overall metropolis by improving the economic value of the surrounding area as well as ecological and environmental values. Third, the central management system was established to reduce the administrative inconvenience caused by multiple administrative districts in the green space of urban periphery. The implications of applying the above results to Seoul, Korea are as follows. First, it is necessary to establish a differentiation strategy by re-establishing the identity of a green landscape in the urban periphery, because the green spaces of Seoul's periphery are dispersed and mostly have a repetitious mountain landscape. Also, it is necessary to actively link peripheral mountains and urban green areas to create ecological value and economic value, and ultimately to help the sustainable development of the city. Finally, building an integrated management system is required to solve fragmented green space management departments in most of the urban periphery's green spaces. In conclusion, this study shows the significant possibility that the sustainable development of a metropolis can be derived from the utilization, linkage, and management of the green space in the urban peripheries, which is extraordinary compared to normal centralized urban development.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.4 no.3 s.8
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• pp.33-43
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• 2005

Traffic condition monitoring system serves as the foundation for all intelligent transportation system operation. Loop detectors and Video Image Processing are the most widely common technology approach to condition monitoring in korea Highways. Lane Usage is defined as the proportion of total link volume served by each lane. In this research, the lane Usage(LU) of two lane link for one day. Interval is 56% : 44%. The LU of three lane link is 39% : 37% : 24%. The LU of four lane link is 25% : 29% : 26% : 21%. These analysis reveal that each lane distributions of link are not same. This research investigates the general concept of lane usage by using collected loop detector data and the investigated that lane distribution is different by traffic lane and lane usage is consistent by time of day.