• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.5
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• pp.482-488
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• 2014

This paper aims to analyze user's emotion automatically by analyzing Twitter, a representative social network service (SNS). In order to create sentiment analysis models by using machine learning techniques, sentiment labels that represent positive/negative emotions are required. However it is very expensive to obtain sentiment labels of tweets. So, in this paper, we propose a sentiment analysis model by using self-training technique in order to utilize "data without sentiment labels" as well as "data with sentiment labels". Self-training technique is that labels of "data without sentiment labels" is determined by utilizing "data with sentiment labels", and then updates models using together with "data with sentiment labels" and newly labeled data. This technique improves the sentiment analysis performance gradually. However, it has a problem that misclassifications of unlabeled data in an early stage affect the model updating through the whole learning process because labels of unlabeled data never changes once those are determined. Thus, labels of "data without sentiment labels" needs to be carefully determined. In this paper, in order to get high performance using self-training technique, we propose 3 policies for updating "data with sentiment labels" and conduct a comparative analysis. The first policy is to select data of which confidence is higher than a given threshold among newly labeled data. The second policy is to choose the same number of the positive and negative data in the newly labeled data in order to avoid the imbalanced class learning problem. The third policy is to choose newly labeled data less than a given maximum number in order to avoid the updates of large amount of data at a time for gradual model updates. Experiments are conducted using Stanford data set and the data set is classified into positive and negative. As a result, the learned model has a high performance than the learned models by using "data with sentiment labels" only and the self-training with a regular model update policy.

• Journal of the East Asian Society of Dietary Life
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• v.25 no.2
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• pp.352-362
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• 2015

The purpose of this study was to examine portion sizes and nutritional quality of foods served to children at Community Child Centers (CCCs), July 2014, in Korea. A survey was administered to foodservice employees working at CCCs. Thirty-nine participants completed the self-administered questionnaire regarding CCCs foodservice practices. In the weight test, fifteen volunteers of demonstrated typical portion sizes for $5^{th}$ grade elementary school students. Nutrition knowledge scores were significantly different between foodservice employees with experience taking a foodservice class for one year (6.04 out of 10.0 points) and those without experience (4.58 points). Foodservice employees with experience taking a foodservice class scored significantly higher in performing meal serving practices, e.g., wearing a sanitary cap and apron when serving food, than those without experience. The amount of foods served for children did not meet standard serving sizes; portion sizes of rice, soup, main dish, side dish and kimchi served by foodservice employees were 87.3%, 63.2%, 56.5%, 37.1% and 81.3% of standard serving sizes, respectively. When energy and nutrient intakes from portion sizes were calculated, energy, vitamin A, thiamin, riboflavin and calcium intakes did not meet standards for nutrition control of school meals. However, protein, vitamin C and iron intakes met more than 100.0% of standards. These findings suggest that foodservice employees with experience taking a foodservice class apply their knowledge to foodservice practices. Although portion sizes can influence energy and nutrient intakes in children, the actual portion sizes served by CCCs foodservice employees were inadequate and did not meet standards for serving size and nutrition. Thus, all CCCs foodservice employees need to receive foodservice education and be provided guidelines regarding portion sizes for children.

• Korean Journal of Social Welfare
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• v.59 no.1
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• pp.301-327
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• 2007

The purpose of this study is to examine the timing and the risk factors associated with the adoption of legally-free foster children. The sample of the study was drawn from foster care files of Adoption and Foster Care Analysis and Reporting System(AFCARS) in 32 states between October 1998 (FY 1999) and September 2002(FY 2002). The timing post-TPR to adoption was examined by plotting the Kaplan-Meier cumulative hazard function for adoption and by plotting the KM hazard functions stratified by child's race and child's age at TPR. Cox proportional-hazards regression analysis was used to identify risk factors for adoption of legally-free foster children after TPR. The hazard of adoption was very low immediately after TPR but increased steadily starting at 3 months and then declined after 20 months. The cumulative hazard functions for White non-Hispanic children and Black non-Hispanic children crossed over at 13 months after TPR. Racial minority status, older age, and disability were negatively associated with the hazard of adoption. Physical abuse, sexual abuse had the lower hazard for adoption compared by neglect. Caretaker's inability to cope had the slightly lower hazard for adoption whereas inadequate housing showed the slightly greater hazard for adoption. Characteristics of foster care services turned into be powerful predictors of adoption. Specifically, legally-free children placed in pre-adoptive homes, those who shared the same racial/ethnic background with their foster caretakers, and those who were placed in two-parent families have a greater likelihood of adoption. The findings highlight the importance of foster care service provisions after TPR to facilitate adoption of legally-free foster children. Furthermore, a more substantial resources and targeted support for foster children who experience physical abuse and sexual abuse in need of adoption should be provided for moving the foster children into permanency.

• Journal of Korean Home Economics Education Association
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• v.31 no.1
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• pp.115-136
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• 2019

The purpose of this study is to analyze the contents of 'housing' unit in middle school Technology-Home Economics textbooks according to the 2015 revision curriculum based on the targets of SDGs. All contents of the ten textbooks of five publishers, such as texts, photographs/figures/tables, activity tasks, and supplementary materials were analyzed in terms of SDGs targets. The number of 'housing' contents among 4 small housing units of Technology-Home Economics book 1 & 2 varied from 64 to 97 by publishers. Beside SDGs4.7, which contains inclusive and general ESDGs, 24 targets of 10 SDGs were found to be related to the contents of 'housing' and were grouped into 15 target categories. The number of SDGs target categories related to housing contents of each small unit and total of all units differed by publishers. Each of 4 small 'housing' units from all the five publishers was related to 6~10 target categories. The contents of five book 1's were related to smaller number of target categories than those of five book 2's. They corresponded to 9 and 12 target categories, consecutively. Only SDGs' target11.1 (appropriate and safe housing and basic services) was related to all the four small units of 'housing' contents among all the five publishers. covering 43.8% of the housing contents. In conclusion, the contents of the 'housing' unit were related to broad range of SDGs targets. Further study could relate goals of teaching-learning plan to various global targets of SDGs according to the contents of 'housing' in order to accomplish ESDGs.

• The Journal of Korean society of community based occupational therapy
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• v.7 no.1
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• pp.59-70
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• 2017

Objective : The purpose of this study was to examine the effect of virtual reality-based remote rehabilitation on stroke patients systematically and to look for its effect and how to apply it domestically. Methods : In order to search data, EMBASE and CINAHL database were used. Relevant research used those terms of virtual reality, telerehabilitation, and stroke. A total of 10 studies satisfying the selection criteria was analyzed according to their qualitative level, general characteristics, and PICO method. Results : Based on the selected 10 studies, virtual reality-based telerehabilitation system was applied. Sensory and motor feedback was provided with inputting visual and auditory senses through a video in the home environment, and it stimulated changes in the client's nervous system. Tools to measure the results were upper extremity function, balance and gait, activities of daily living, etc. Those virtual reality-based telerehabilitation method had an effect on upper extremity function and ability of sense of balance in all studies, and on the activities of daily living partially. Telerehabilitation service to make up environmental specificity improved satisfaction of client. That meaned the effect of the intervention to maintain the function. Conclusion : The virtual reality-based telerehabilitation system was applied to upper extremity function, sense of balance, and activities of daily living largely, and it showed that it helped to improve functions through intervention, supervision, and training of therapist in the home environment as well. This study suggests the basis and possibility of clinical application on virtual-reality based telerehabilitation. Additional research is needed to diverse virtual reality intervention methods and the effect of telerehabilitation in the future.

• Journal of the Korean Institute of Landscape Architecture
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• v.41 no.4
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• pp.56-67
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• 2013

This paper asks what the Selection Attributes of urban open space are which carries out a role as an Urban Entertainment Destination. Case studies have chosen the Cheonggyecheon Waterfront, Seoul Forest Park, Seonyudo Park and Banpo Hangang Park as the representative open spaces in Seoul. The methods of study are observation investigation, a literature investigation and the survey to 233 visitors that conducted the ANOVA analysis and Regression analysis by SPSS 18.0. As a result, first, the urban open space in Seoul has had 8 elements of UED; Landscape, Multi anchoring, Contextual links, Programmability, Community, Branded identity, Security and Service. Second, they are being used not the neighborhood type but a wide area type. Third, Landscape, Security and Service are most important while Programmability and Community are less important than other factors in EUOS factors. Lastly, it was analysed that the influential factor of revisitation and satisfaction is Landscape, which is the common factor. Security in revisitation and Contextual links in satisfaction are especially additional factors. The landscape property is an important element to make an Entertainment Urban Open Space(EUOS). The virtue of landscape in the EUOS relates not only park facility or program that installed in the place but also the overall mood involving park user's activities in the place. To be a successful EUOS, a park facility, program and the overall mood involving user's activities need to be integrative approach to enhance the virtue of landscape.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.39-57
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• 2012

Recently, due to the introduction of high-tech equipment in interactive exhibits, many people's attention has been concentrated on Interactive exhibits that can double the exhibition effect through the interaction with the audience. In addition, it is also possible to measure a variety of audience reaction in the interactive exhibition. Among various audience reactions, this research uses the change of the facial features that can be collected in an interactive exhibition space. This research develops an artificial neural network-based prediction model to predict the response of the audience by measuring the change of the facial features when the audience is given stimulation from the non-excited state. To present the emotion state of the audience, this research uses a Valence-Arousal model. So, this research suggests an overall framework composed of the following six steps. The first step is a step of collecting data for modeling. The data was collected from people participated in the 2012 Seoul DMC Culture Open, and the collected data was used for the experiments. The second step extracts 64 facial features from the collected data and compensates the facial feature values. The third step generates independent and dependent variables of an artificial neural network model. The fourth step extracts the independent variable that affects the dependent variable using the statistical technique. The fifth step builds an artificial neural network model and performs a learning process using train set and test set. Finally the last sixth step is to validate the prediction performance of artificial neural network model using the validation data set. The proposed model is compared with statistical predictive model to see whether it had better performance or not. As a result, although the data set in this experiment had much noise, the proposed model showed better results when the model was compared with multiple regression analysis model. If the prediction model of audience reaction was used in the real exhibition, it will be able to provide countermeasures and services appropriate to the audience's reaction viewing the exhibits. Specifically, if the arousal of audience about Exhibits is low, Action to increase arousal of the audience will be taken. For instance, we recommend the audience another preferred contents or using a light or sound to focus on these exhibits. In other words, when planning future exhibitions, planning the exhibition to satisfy various audience preferences would be possible. And it is expected to foster a personalized environment to concentrate on the exhibits. But, the proposed model in this research still shows the low prediction accuracy. The cause is in some parts as follows : First, the data covers diverse visitors of real exhibitions, so it was difficult to control the optimized experimental environment. So, the collected data has much noise, and it would results a lower accuracy. In further research, the data collection will be conducted in a more optimized experimental environment. The further research to increase the accuracy of the predictions of the model will be conducted. Second, using changes of facial expression only is thought to be not enough to extract audience emotions. If facial expression is combined with other responses, such as the sound, audience behavior, it would result a better result.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.67-88
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• 2019

Webtoon is a Korean-style digital comics platform that distributes comics content produced using the characteristic elements of the Internet in a form that can be consumed online. With the recent rapid growth of the webtoon industry and the exponential increase in the supply of webtoon content, the need for effective webtoon content recommendation measures is growing. Webtoons are digital content products that combine pictorial, literary and digital elements. Therefore, webtoons stimulate consumer sentiment by making readers have fun and engaging and empathizing with the situations in which webtoons are produced. In this context, it can be expected that the sentiment that webtoons evoke to consumers will serve as an important criterion for consumers' choice of webtoons. However, there is a lack of research to improve webtoons' recommendation performance by utilizing consumer sentiment. This study is aimed at developing consumer sentiment pattern maps that can support effective recommendations of webtoon content, focusing on consumer sentiments that have not been fully discussed previously. Metadata and consumer sentiments data were collected for 200 works serviced on the Korean webtoon platform 'Naver Webtoon' to conduct this study. 488 sentiment terms were collected for 127 works, excluding those that did not meet the purpose of the analysis. Next, similar or duplicate terms were combined or abstracted in accordance with the bottom-up approach. As a result, we have built webtoons specialized sentiment-index, which are reduced to a total of 63 emotive adjectives. By performing exploratory factor analysis on the constructed sentiment-index, we have derived three important dimensions for classifying webtoon types. The exploratory factor analysis was performed through the Principal Component Analysis (PCA) using varimax factor rotation. The three dimensions were named 'Immersion', 'Touch' and 'Irritant' respectively. Based on this, K-Means clustering was performed and the entire webtoons were classified into four types. Each type was named 'Snack', 'Drama', 'Irritant', and 'Romance'. For each type of webtoon, we wrote webtoon-sentiment 2-Mode network graphs and looked at the characteristics of the sentiment pattern appearing for each type. In addition, through profiling analysis, we were able to derive meaningful strategic implications for each type of webtoon. First, The 'Snack' cluster is a collection of webtoons that are fast-paced and highly entertaining. Many consumers are interested in these webtoons, but they don't rate them well. Also, consumers mostly use simple expressions of sentiment when talking about these webtoons. Webtoons belonging to 'Snack' are expected to appeal to modern people who want to consume content easily and quickly during short travel time, such as commuting time. Secondly, webtoons belonging to 'Drama' are expected to evoke realistic and everyday sentiments rather than exaggerated and light comic ones. When consumers talk about webtoons belonging to a 'Drama' cluster in online, they are found to express a variety of sentiments. It is appropriate to establish an OSMU(One source multi-use) strategy to extend these webtoons to other content such as movies and TV series. Third, the sentiment pattern map of 'Irritant' shows the sentiments that discourage customer interest by stimulating discomfort. Webtoons that evoke these sentiments are hard to get public attention. Artists should pay attention to these sentiments that cause inconvenience to consumers in creating webtoons. Finally, Webtoons belonging to 'Romance' do not evoke a variety of consumer sentiments, but they are interpreted as touching consumers. They are expected to be consumed as 'healing content' targeted at consumers with high levels of stress or mental fatigue in their lives. The results of this study are meaningful in that it identifies the applicability of consumer sentiment in the areas of recommendation and classification of webtoons, and provides guidelines to help members of webtoons' ecosystem better understand consumers and formulate strategies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.9
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• pp.6089-6098
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• 2015

This study purposes to identify the effects of performance of public health services (PHS) and personal characteristics on community image to public hospitals. The subjects of this study were 33 public hospitals and 1,789 community residents. The data of '2011 Public hospital evaluation programme' were utilized in this study. The personal characteristics consisted of nine items which were gender, age, education, occupation, monthly incomes, medical security, use experience, health state, and location type. The PHS performance consisted of five items which were number of doctors, number of nurses, total number of staff, budget per 1,000 community residents, and amount of activities per 1,000 community residents. The cronbach's alpha of community image instrument was 0.916. As the results of logistic regression, the significant variables of community image, were age (OR=0.34, 95% CI=0.19-0.60), education (OR=3.03, 95% CI=1.60-5.76), use experience (OR=0.57, 95% CI=0.40-0.81), health state (OR=0.69 95% CI=0.49-0.96), location type (OR=2.10, 95% CI=1.11-3.99), and amount of activities per 1,000 community residents (OR=0.58, 95% CI=0.35-0.96). Community image is very important to public hospitals. The workforce and budget related PHS were significantly demanded to improve community image. The Central and Local government should support to public hospitals to perform PHS effectively.

• Journal of Wetlands Research
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• v.23 no.4
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• pp.352-363
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• 2021

The purpose of this study was to evaluate the load of nutrients contained in the drainage discharged from the facility horticultural complex and to use them for re-use of fluids and design for introduction of water treatment plants. Representative hydroponic cultivation crops were selected as tomato, paprika, cucumber, and strawberry, and the total number of samples analyzed for water quality was 80. As a result of the analysis, since various fertilizer components such as N, P, K⁺, Na⁺, Mg²⁺, Ca²⁺, Si₄⁺, HCO₃^-, Cl^-, S^2-, Fe, Mn, Cu, Zn, Mo and B are contained at very high concentrations in the drainage, the need for water treatment was confirmed. Through statistical analysis, it was analyzed that the drainage concentration of strawberries was lower than that of tomatoes, paprika, and cucumbers. In the case of tomatoes, these essential ion concentrations are the highest, so it was confirmed that they are subject to valuable resources in terms of reuse of fertilizers. The load of N and P of the drainage discharged from the facility horticultural complex 1m² was analyzed. For N, the daily processing capacity of 4.0 kg of tomatoes, 3.3 kg of paprika, 3.0 kg of cucumbers, and 1.5 kg of strawberries was calculated based on 1 ha. It was suggested that the P concentration needs a scale and capacity that can handle 0.5 kg of tomatoes, 0.6 kg of paprika, 0.4 kg of cucumber, and 0.2 kg of strawberries per day. Through this study, the amount of nitrogen and phosphorus contained in the drainage discharged from the greenhouse of each crop was evaluated to analyze the economy. In addition, it was expected to be used as basic data that can be used to calculate the treatment capacity to be reflected when introducing water treatment facilities in facility horticultural complexes for sustainable agriculture.