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- 저자 : SangWon Ha (검색결과 34 건)
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Ha, Kyungho,Chung, Sangwon,Joung, Hyojee,Song, YoonJu The Korean Nutrition Society 2016 Nutrition Research and Practice Vol.10 No.5
BACKGROUND/OBJECTIVES: Dietary sugar intake, particularly added sugar and sugar-sweetened beverages, has received worldwide attention recently. Investigation of dietary behaviors may facilitate understanding of dietary sugar intakes of children and adolescents. However, the relationship between dietary sugar intake and dietary behaviors in the Korean population has not been investigated. Thus, this study aimed to estimate dietary sugar intake and food sources according to sex as well as examine the relationship of dietary sugar intake with frequent snacking and dietary patterns among Korean children and adolescents. SUBJECTS/METHODS: We pooled data from five studies involving Korean children and adolescents conducted from 2002 to 2011. A total of 2,599 subjects aged 9-14 years were included in this study. Each subject completed more than 3 days of dietary records. RESULTS: Mean daily total sugar intake was 46.6 g for boys and 54.3 g for girls. Compared with boys, girls showed higher sugar intakes from fruits (7.5 g for boys and 8.8 g for girls; P = 0.0081) and processed foods (27.9 g for boys and 34.9 g for girls; P < 0.0001). On average, 95.4% of boys and 98.8% of girls consumed snacks during the study period, and total sugar intake showed a significantly increasing trend with increasing energy intake from snacks (P < 0.0001 for both sexes). Two dietary patterns were identified by cluster analysis: Traditional and Westernized patterns. Total sugar intake was higher in the Westernized pattern (56.2 g for boys and 57.2 g for girls) than in the Traditional pattern (46.5 g for boys and 46.3 g for girls). CONCLUSIONS: These results suggest that multilateral and practical development of a nutrition education and intervention program that considers dietary behaviors as well as absolute sugar intake is required to prevent excessive sugar intake in Korean children and adolescents.
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환경정의 관점에서 본 폭염 취약 지역과 사회⋅취약계층 간의 공간적 패턴 분석
오상원(Sangwon Oh),하동오(Dongoh Ha),정주철(Juchul Jung) 한국방재학회 2023 한국방재학회논문집 Vol.23 No.4
오늘날 전 세계는 기후변화로 인한 일 최고기온 증가, 폭염일수의 증대 등으로 인해 인명피해 및 피해액이 지속적으로 상승하는추세이다. 이에 따라 폭염으로 인한 취약계층에 대한 고려가 필수적이며, 실질적으로 큰 피해가 예상되는 취약계층에 대한기준이 필요하다. 그러므로 본 연구는 시간 및 공간적 범위로는 2010년부터 2018년까지의 전국 시군구들을 대상으로 폭염취약성 지수에 따른 폭염 취약지역을 선정하고, moran’s I 공간자기상관 분석 및 LISA군집지도 분석을 통한 공간적 분석을 진행하였다. 본 연구는 사회적 취약계층 거주 및 활동 지역과 폭염 위험지역과의 공간적 상관관계를 확인하고 이에 무더위쉼터정책의 적용에 대하여 환경 부정의 지역을 도출하였다. Currently, the number of human casualties and damages is continuously increasing owing to increases in the daily maximum temperature and number of heat wave days caused by climate change. Therefore, considering the class vulnerable to heat waves and setting standards for the vulnerable class expected to suffer substantial damage are essential. Therefore, in terms of time and space, this study selected heatwave-vulnerable areas according to the heatwave vulnerability index, targeting cities, counties, and districts nationwide from 2010 to 2018, and performed spatial analysis using Moran's I spatial autocorrelation analysis and LISA cluster map analysis. proceeded. The spatial correlation between socially vulnerable living and activity areas and the heat wave risk area was confirmed, and the area of environmental negativity for applying an extreme heat shelter policy was derived.
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Longitudimal Automatic Landing in Adaptive PID Control Law Under Wind Shear Turbulence
Cheolkeun Ha,Sangwon Ahn 한국항공우주학회 2004 International Journal of Aeronautical and Space Sc Vol.5 No.1
??This paper deals with a problem of automatic landing guidance and control of the longitudinal airplane motion under the wind shear turbulence. Adaptive gain scheduled PID control law is proposed in this paper. Fuzzy logic is the main part of the adaptive PID controller as gain scheduler. To illustrate the successful application of the proposed control law to the automatic landing control problem, numerical simulation is carried out based on the longitudinal nonlinear airplane model excited by the wind shear turbulence. The simulation results show that the automatic landing maneuver is successfully achieved with the satisfactory performance and the gain adaptation of the control law is made adequately within the limited gains.
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Lee, Sangwon,Ha, Taehyun,Lee, Daeho,Kim, Jang Hyun Elsevier 2018 Information processing & management Vol.54 No.6
<P><B>Abstract</B></P> <P>Majority opinions are often observed in the process of social interaction in online communities, but few studies have addressed this issue with empirical data. To identify an appropriate theoretical lens for explaining majority opinions in online environments, this study investigates the skewness statistic, which indicates how many “Likes” are skewed to major comments on a Facebook post; 3489 posts are gathered from the New York Times Facebook page for 100 days. Results show that time is not an influential factor for skewness increase, but the number of comments has a logarithmic relation to skewness increase. Regression models and Chow tests show that this relationship differs depending on topic contents, but majority opinions are significant in overall. These results suggest that the bandwagon effect due to social affordance can be a suitable mechanism for explaining majority opinion formation in an online environment and that majority opinions in online communities can be misperceived due to overestimation.</P> <P><B>Highlights</B></P> <P> <UL> <LI> This study investigates how major opinions are constructed in online environments. </LI> <LI> Skewness statistic is adopted to describe distributional property of the Likes of comments on a Facebook post. </LI> <LI> The skewness statistic is logarithmically changed by the number of comments on a post. </LI> <LI> The results show that bandwagon effect is more suitable mechanism to explain the major opinion construction in online environments. </LI> <LI> This study discusses how the bandwagon effect can be afforded from the social affordance perspective. </LI> </UL> </P>
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A Serendipity-Oriented Music Recommendation System Using Artificial Neural Networks
( Taehyun Ha ),( Sangwon Lee ) 한국감성과학회 2014 춘계학술대회 Vol.2014 No.-
Recently the interests with culture technologies have been heightened and accordingly many studies for recommendation systems considering individuals`preferences have been done. As a part of this trend, music recommendation systems have been developed in content-based and collaborative filtering methods. Previous studies have emphasized on technical aspects such as the extraction of music items` features and the development of comparison algorithms for them. However, there are few studies to develop a music recommendation system based on individual users` cognitive characteristics. To contribute to this issue, the present study proposes a music recommendation method considering serendipity based on individual users` play records. Serendipity occurs when users meet familiar music items unexpectedly. The serendipity is determined by the comparison between users`listening records in the past and the recent days. This is to find music items which users have often listen to in the past but do not anymore, and to recommend new music items similar to them. To apply the serendipity in the recommendation process, we utilize artificial neural network models. The artificial neural network models consist of long-term and short-term models, each of which is used to analyze user`s listening behaviors. Music items in a user`s playlist are used to train the models based on the last played times. The models use music items`features as input values and play counts (the numbers of play times) as output values.
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A serendipity-oriented music recommendation system using artificial neural networks
Taehyun Ha,Sangwon Lee 대한인간공학회 2014 대한인간공학회 학술대회논문집 Vol.2014 No.5
Recently the interests with culture technologies have been heightened and accordingly many studies for recommendation systems considering individuals’ preferences have been done. As a part of this trend, music recommendation systems have been developed in content-based and collaborative filtering methods. Previous studies have emphasized on technical aspects such as the extraction of music items’ features and the development of comparison algorithms for them. However, there are few studies to develop a music recommendation system based on individual users’ cognitive characteristics. To contribute to this issue, the present study proposes a music recommendation method considering serendipity based on individual users’ play records. Serendipity occurs when users meet familiar music items unexpectedly. The serendipity is determined by the comparison between users’ listening records in the past and the recent days. This is to find music items which users have often listen to in the past but do not anymore, and to recommend new music items similar to them. To apply the serendipity in the recommendation process, we utilize artificial neural network models. The artificial neural network models consist of long-term and short-term models, each of which is used to analyze user’s listening behaviors. Music items in a user’s playlist are used to train the models based on the last played times. The models use music items’ features as input values and play counts (the numbers of play times) as output values. Music items’ features are expressed by MFCC(Mel-frequency cepstral coefficients). After the artificial neural network models are trained, each model allocates the predicted play counts for music items in database. The music items’ serendipity degrees are calculated by difference between the predicted play counts in long-term model and short-term model. A high serendipity degree of item means users would satisfy the item with high probability. Finally, the music items in database are appeared in the recommendation list according to the serendipity degrees. The music recommendation method suggested in this study is a new approach based on individual users’ listening habits and preferences. It is expected that this method can improve users’ satisfaction with recommended items.
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