• Science of Emotion and Sensibility
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• v.8 no.1
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• pp.17-28
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• 2005

With the advent of computer technology, the fundamental nature of products has shaped from physical forms towards product interactivity, The focus is now on usability of the product with ease and efficiency rather than conversing with just the looks of the product. However, most definitions of usability and contemporary usability-related researches, have focused on the performance-oriented functional aspects of usability (i.e., how well users perform tasks using a product). Today, user expectations are higher; products that bring not only functional benefits but also emotional satisfaction. So far, there have been many studies on human emotions and the emotional side of products in the field of emotional engineering. Contemporary emotion-related researches have focused mainly on the relationship between product aesthetics and the emotional responses elicited by the products, but little is known about emotions elicited from using the products. The main objective of our research is analyzing user's emotional changes while using a product, to reveal the influence of usability on human emotions. In this research, we suggested conceptual framework for the study on the relationship between usability of products, and human emotions with emphasis on mobile phones. We also extracted emotional words for measuring user's emotions expressed not from looking at the product's appearance, but from using the product. First, we assembled a set of emotions that is sufficiently extensive to represent a general overview of the full repertoire of Korean emotions from the literature study. Secondly, we found emotional words in the after note by the users on the websites. Finally, verbal protocols in which the user says out loud what he/she ks feeling while he/she ks carrying out a task were collected. And then, the appropriateness of extracted emotional words was verified by the members of the consumer panel of a company through web survey. It is expected that emotional words extracted in this research will be used to measure user's emotional changes while using a product. Based on the conceptual framework suggested in this research, basic guidelines on interface design methods that reflect user's emotions will be illustrated.

• Korean journal of health promotion
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• v.18 no.4
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• pp.177-183
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• 2018

Background: Many studies have reported that adolescents living with single parent have a high risk of obesity. However, those studies did not explore the implication of the gender of single parent living with adolescents. This study investigated the differences in obesity rates according to status of co-residence with their parents in Korean adolescents. The family living with single parent was classified into the family living with single father and the family living with single mother. Methods: This cross-sectional study involved 59,602 adolescents who participated in the 2017 Korea Youth Risk Behavior Web-based Survey. The data on height, weight, status of co-residence with parents, and the other variables were obtained through online questionnaires. Results: In male adolescents, the family living with single mother was related to a high proportion of obesity (odds ratio [OR] 1.24, 95% confidence interval [CI] 1.09-1.40) and overweight (OR 1.17, 95% CI 1.03-1.34). However, in female adolescents, the family living with single father was related to a high proportion of obesity (OR 1.49, 95% CI 1.23-1.82). In addition, female adolescents living with neither parent were more likely to be obese (OR 1.47, 95% CI 1.13-1.91) and overweight (OR 1.31, 95% CI 1.00-1.70). Conclusions: This study showed a risk of obesity in adolescents living with single parent differs according to the gender of single parent living with adolescents. Not adolescents living with a same-gender parent, but those living with an opposite-gender parent have a high risk of obesity.

• Radiation Oncology Journal
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• v.22 no.3
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• pp.192-199
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• 2004

Purpose: To determine the patterns on evaluation and treatment in the patient with early breast cancer treated with conservative surgery and radiotherapy and to improve the radiotherapy techiniques, nationwide survey was peformed. Materials and Methods: A web-based database system for korean Patterns of Care Study (PCS) for 6 common cancers was developed. Two hundreds sixty-one randomly selected records of eligible patients treated between 1998$\~$1999 from 15 hospitals were reviewed. Results: The patients ages ranged from 24 to 85 years(median 45 years). Infiltrating ductal carcinoma was most common histologic type (88.9$\%$) followed by medullary carcinoma (4.2$\%$) and infiltrating lobular carcinoma (1.5$\%$). Pathologic T stage by AJCC was T1 in 59.7$\%$ of the casses, T2 in 29.5$\%$ of the cases, Tis in 8.8$\%$ of the cases. Axillary lymph node dissection was peformed I\in 91.2$\%$ of the cases and 69.7$\%$ were node negative. AJCC stage was 0 in 8.8$\%$ of the cases, stage I in 44.9$\%$ of the cases, stage IIa in 33.3$\%$ of the cases, and stage IIb in 8.4$\%$ of the cases. Estrogen and progesteron receptors were evaluated in 71.6$\%$, and 70.9$\%$ of the patients, respectively. Surgical methods of breast-conserving surgery was excision/lumpectomy in 37.2$\%$, wide excision in 11.5$\%$, quadrantectomy in 23$\%$ and partial mastectomy in 27.5$\%$ of the cases. A pathologically confirmed negative margin was obtained in 90.8$\%$ of the cases. Pathological margin was involved with tumor in 10 patients and margin was close (less than 2 mm) in 10 patients. All the patients except one recieved more than 90$\%$ of the planned radiotherapy dose. Radiotherapy volume was breast only In 88$\%$ of the cases, breast+supraclavicular fossa (SCL) in 5$\%$ of the cases, and breast+ SCL+ posterior axillary boost in 4.2%$\%$of the cases. Only one patient received isolated internal mammary lymph node irradiation. Used radiation beam was Co-60 in 8 cases, 4 MV X-ray in 115 cases, 6 MV X-ray in 125 cases, and 10 MV X-ray in 11 cases. The radiation dose to the whole breast was 45$\~$59.4 Gy (median 50.4) and boost dose was 8$\~$20 Gy (median 10 Gy). The total radiation dose delivered was 50.4$\~$70.4 Gy (median 60.4 Gy). Conclusion: There was no major deviation from current standard in the patterns of evaluation and treatment for the patients with early breast cancer treated with breast conservation method. Some varieties were identified in boost irradiation dose. Separate analysis for the datails of radiotherapy planning will be followed and the outcome of treatment is needed to evaluate the process.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.1-23
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• 2013

To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.