• Journal of Communication Design
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• v.68
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• pp.278-288
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• 2019

The purpose of this study is to analyze the effects of risk and convenience on purchase intention in the IOT market, and I want to analyze the moderating effect of emotional consumption value. In this study, two products were selected from three product groups. There are three major methods of research. First, theoretical considerations. Second, survey analysis. Reliability analysis and factor analysis were performed using descriptive statistics using SPSS. Third, we measured changes of EEG according to in - depth interview and indirect experience. As a result of the hypothesis of this study, it was confirmed that convenience of use of IoT product influences purchase intention. Risk was predicted to have a negative effect on purchase intentions, but not significant in this study. This implies that IoT products tend to be neglected in terms of monetary loss such as cost of purchase, cost of use, and disposal cost when purchasing. In-depth interviews and EEG analysis revealed that there is a desire to purchase and try out the IoT product due to the nature of the product, the novelty of new technology, and the vague idea that it will benefit my life. The aesthetic, symbolic, and pleasure factors, which are sub - elements of emotional consumption value, were found to have a great influence. This is consistent with previous research showing that emotional consumption value has a positive effect on purchase intention. In-depth interviews and EEG analyzes also yielded the same results. This study has revealed that emotional consumption value affects the intention to purchase IoT products. It seems that companies producing IoT products need to concentrate on marketing with more emotional consumption value.

• Therapeutic Science for Rehabilitation
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• v.13 no.1
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• pp.9-21
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• 2024

Objective : The purpose of this study was to confirm the characteristics and quality of a single-subject research that conducted interventions to improve activities of daily living (ADL) in stroke patients. Methods : 'Stroke,' 'activities of daily living,' and 'single-subject studies' were searched as keywords among papers published in the last 15 years between 2009 and 2023 among Research Information Sharing Service, DBpia, and e-articles. A total of nine papers were examined for the characteristics and quality before analysis. Results : The independent variables applied to improve ADL included constraint-induced therapy, mental practice for performing functional activities, virtual reality-based task training, subjective postural vertical training without visual feedback, bilateral upper limb movement, core stability training program, traditional occupational therapy and neurocognitive rehabilitation, smooth pursuit eye movement, neck muscle vibration, and occupation-based community rehabilitation. Assessment of Motor and Process Skills was the most common evaluation tool for measuring dependent variables, with four articles, and Modified Barthel Index and Canadian Occupational Performance Measure were two articles each. As a result of confirming the qualitative level of the analyzed papers, out of a total of nine studies, seven studies were at a high level, two at a moderate level, and none were at a low level. Conclusion : Various types of rehabilitation treatments have been actively applied as intervention methods to improve the daily life activities of stroke patients; the quality level of single-subject studies applying ADL interventions was reliable.

• Journal of agricultural medicine and community health
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• v.18 no.2
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• pp.141-151
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• 1993

This study was done about 371 tuberculosis(TB) patients composed 195 newly registered at Kyungju Gun Health Center from May 1989 to April 1990 (Group A) and 176 being treated at hospitals or private clinics from January 1988 to November 1989(Group B). When Group A patients visited and newly registered at Health Center, data was obtained by interviewing with a prepared questionnaire paper. And well trained inquirer visited Group B patients and obtained data by the same method from February 1990 to April 1990. The results are as follows ; Group A was generally lower than Group B in socioeconomic status and in family history of TB, the rate of Group A was 24.1% and higher than 11.9% in Group B(p<0.05). Knowledge about TB was improved more than past, but those who answered that TB is 'a communicable disease' were 59.5% in Group A and 51.7% in Group B(p<0.05). Those answered that TB is 'a inherited disease' were 9.2% and 11.4% each. And 1.7% of Group B answered that TB is 'a incurable disease'. Knowledge about TB treatment also was improved more than past, but in the rate of those who answered that TB is a curable disease provided by well treatment Group B(77.8%) was worse than Group A(91.3%). The rate of those who answered that TB were been able to cure by regularly anti-TB medication were 98.0% in Group A and 89.8% in Group B. Its difference was statistically significant. The rate that patients took the first diagnosis and wanted to receive treatments at the same organ were 34.9% of Group A at Health Center and 72.2% of Group B at hospitals or private clinics. And its difference was statistically significant. In the reasons that Group B knew Health Center treated pulmonary TB but they was treated at hospitals or private clinics, unreliability to Health Center was 48.1%. The reasons that Group A was treated at Health Center were 'because of trust' 63.1%, 'because of low cost' 50.3%, 'because of low cost except trust' 9.3%, 'no specific reasons' 27.7%. In the courses of knowing that TB was controlled at Health Center, 'by neighborhood, health worker and doctors' were 84.9% in Group A and 69.0% in Group B. But 'by TV or radio' were 8.2% in Group A and 14.7% in Group B, 'by school education' 2.5% in Group A and 6.2% in Group B. Conclusively, Group A patients were lower than Group B in socioeconomic status, but better than in knowledge about TB. Its reasons was suggested that Health Center had controlled TB patients better than hospitals and private clinics. But considering, that difference in the rate of the same organ for the first diagnosis and treatment, that the only 63.0% of Group A have treated due to 'reliability to Health Center', and that 48.1% of Group B knew that Health Center treated pulmonary TB but didn't visit it due to 'unreliability to Health Center', that public relations(PR) about use Health Center for pulmonary TB and health education for TB was thought to have to strengthened.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.149-169
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• 2020

"The Urban Renewal New Deal project", one of the government's major national projects, is about developing underdeveloped areas by investing 50 trillion won in 100 locations on the first year and 500 over the next four years. This project is drawing keen attention from the media and local governments. However, the project model which fails to reflect the original characteristics of the area as it divides project area into five categories: "Our Neighborhood Restoration, Housing Maintenance Support Type, General Neighborhood Type, Central Urban Type, and Economic Base Type," According to keywords for successful urban regeneration in Korea, "resident participation," "regional specialization," "ministerial cooperation" and "public-private cooperation", when local governments propose urban regeneration projects to the government, they can see that it is most important to accurately understand the characteristics of the city and push ahead with the projects in a way that suits the characteristics of the city with the help of local residents and private companies. In addition, considering the gentrification problem, which is one of the side effects of urban regeneration projects, it is important to select and implement urban regeneration types suitable for the characteristics of the area. In order to supplement the limitations of the 'Urban Regeneration New Deal Project' methodology, this study aims to propose a system that recommends urban regeneration types suitable for urban regeneration sites by utilizing various machine learning algorithms, referring to the urban regeneration types of the '2025 Seoul Metropolitan Government Urban Regeneration Strategy Plan' promoted based on regional characteristics. There are four types of urban regeneration in Seoul: "Low-use Low-Level Development, Abandonment, Deteriorated Housing, and Specialization of Historical and Cultural Resources" (Shon and Park, 2017). In order to identify regional characteristics, approximately 100,000 text data were collected for 22 regions where the project was carried out for a total of four types of urban regeneration. Using the collected data, we drew key keywords for each region according to the type of urban regeneration and conducted topic modeling to explore whether there were differences between types. As a result, it was confirmed that a number of topics related to real estate and economy appeared in old residential areas, and in the case of declining and underdeveloped areas, topics reflecting the characteristics of areas where industrial activities were active in the past appeared. In the case of the historical and cultural resource area, since it is an area that contains traces of the past, many keywords related to the government appeared. Therefore, it was possible to confirm political topics and cultural topics resulting from various events. Finally, in the case of low-use and under-developed areas, many topics on real estate and accessibility are emerging, so accessibility is good. It mainly had the characteristics of a region where development is planned or is likely to be developed. Furthermore, a model was implemented that proposes urban regeneration types tailored to regional characteristics for regions other than Seoul. Machine learning technology was used to implement the model, and training data and test data were randomly extracted at an 8:2 ratio and used. In order to compare the performance between various models, the input variables are set in two ways: Count Vector and TF-IDF Vector, and as Classifier, there are 5 types of SVM (Support Vector Machine), Decision Tree, Random Forest, Logistic Regression, and Gradient Boosting. By applying it, performance comparison for a total of 10 models was conducted. The model with the highest performance was the Gradient Boosting method using TF-IDF Vector input data, and the accuracy was 97%. Therefore, the recommendation system proposed in this study is expected to recommend urban regeneration types based on the regional characteristics of new business sites in the process of carrying out urban regeneration projects."

• Trans-
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• v.2
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• pp.1-38
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• 2017

Dance, as an art which expresses thoughts and emotions by movement human, is included in work that its copyright has to be protected, choreographers who are creators and dancers who are performing can exercise their rights included in copyright laws. However, artists who work in the dancing scene have lack of awareness about copyrights and the application level is low. The purpose of this thesis is to look into the current status and issues about dance copyright and to discuss activation plans and effectiveness plans for dance copyrights. The main point is to check into the level of awareness for dance copyrights with choreographers, dancers and students majoring in dance who are in charge of the art of dancing, to present issues about the necessity of the dance copyrights protection plans by analyzing interviews-in-depth and to prepare the dance copyrights protection plans which are concretely realistic. For the research methods, first, I looked into ideas and contents about copyrights through a document research and then, wanted to prepare theoretical background by reviewing actual cases of performing art copyrights related to dance. Next, I carried out surveys about awareness of copyrights with students majoring in dance, choreographers and dancers then carried out analysis of actual proof. Also, I chose three famous dancers who are actively performing in the current dancing scene and did interviews-in-depth about dance copyrights then carried out a recording analysis. I tried to complement the analysis by discussing deeper which I couldn't deal with in the previous surveys and to contemplate awareness activation of dance copyrights and plans. As a result of the research, the level of the awareness about dance copyrights through age, major, education and career was very low. The level of awareness was almost same compared to the previous research 10 years ago. 'Music', which can be an element of copyright issue in dance, was the highest in rate, and dance was recognized as an art which is combined with various elements as a combination work. The way of protection for works of choreography and performance only used data preservation and contracts and didn't register copyrights or record in dace notation. Majority of responders answered that they couldn't have any education about copyrights while they were recognizing the necessity of education and management for copyrights. The analysis of interviews-in-depth was also matched to the result of the previous surveys and a deeper discussion about the status of dance copyrights and issues was carried out. The plans of effectiveness for dance copyrights through the result of previous research are as followings. First, an advanced education is necessary above all to increase the awareness and application of copyrights in dancing scene. Long-term education like study curriculums and short-term education like special courses and seminars should be combined, and education about copyrights for dance groups, choreographers, dancers and students majoring in dance should keep on going. Second, revision of performing art works is necessary for the activation of dance copyrights, and establishing a dance copyright association to manage copyrights systematically and training dance copyright experts are necessary as well. Third, as the way of copyright protection for choreographers and dancers, an establishment for relation gain and loss about copyrights is necessary when creating dance works and performing, and registration of dance works should be activated. Also, the dancing scene should sign contracts for choreography and performance and this contract culture should be activated, and it should systematically preserve and manage choreography and performance records through basic ways. Hereby, it is considered to prepare a foundation to foster the awareness of dance copyrights and activate dance copyrights.

• Journal of Distribution Science
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• v.10 no.4
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• pp.47-53
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• 2012

Businesses make use of advertising strategy using models to give consumers efficient product information. Modern advertisements often make use of models for greater reminiscence to create messages and remind viewers of the product. The purpose of this study was to examine the characteristics of each type of model. The subjects were 230 college students in their twenties or older, and the material was collected from October 20, 2011 to November 5, 2011 to examine the effects of model characteristics on buying intention as well as attitude toward a brand. A questionnaire survey was used; investigators gave one copy to each interviewee. The study investigated the characteristics of each model using a questionnaire of each 40 copies with five kinds of photographs. The characteristics of models had great influence on buying intention and attitude toward the brand: First, factor 2 (being honest and virtuous and having good credit and a good press assessment) and factor 3 (being interesting and a good communicator and creating good memories) had great influence on buying intention. Factor 2 was explained by reliability, and factor 3 by the efficiency of the model in creating a feeling. Second, factors 1 (being attractive, smart, unique, friendly, loved by others, and popular), 2, and 3 influenced attitude toward brand. Factor 1 encapsulated the outgoing characteristics of a model, factor 2 was based on reliability, and factor 3 was based on the efficiency of the model in creating a feeling. The model's positive effects on buying intention and attitudes toward brand shall be examined. For their positive influence on buying intention, reliability and efficiency shall be given attention. For their positive influence on attitude toward brand, creating a good impression, having outgoing characteristics, being reliable, and efficiency shall be given attention. The findings were as follows: Model characteristics influencing buying intention were similar to those influencing attitude toward brand. The differences were as follows. First, reliability and efficiency influenced buying intention. When customers were asked to consider the influence on buying intention of an advertisement, regardless of the strength of the buying intention, they considered these two characteristics. Customers decided to buy based not only on the credibility of the product as presented in the advertisement but also the transmission of the contents of the advertisement. Second, outgoing characteristics, reliability, and efficiency influenced attitude toward a brand. The attitude toward a brand was said to be the attitude toward the business. The attitude is produced even after buying, so businesses view it as very important. The attitude might vary depending upon the model used rather than the brand. Therefore, a model with outgoing characteristics was thought to be important. Therefore, attitude toward a brand whose model influenced buying intention as well as attitude toward brand had outgoing characteristics. The result is that an image the model was related to attitude toward the brand. As such, customers would buy the goods advertised. However, an outgoing image of a model was also important to create a positive attitude toward a business brand. For instance, talent Park Gyeong-Rim's photo was used to promote cosmetics about 10 years ago. When she worked as a model of cosmetics products, she had to make compensation for losses and damages because she made a mistake on a talk show program. At that time, customers who had bought the cosmetics product asked for refunds of several billion won. As such, models who are said to be the face of the businesses they represent can play an important role. To advertise in the most attractive and effective way, the current image of a model should be investigated by examining current activities and news articles after selecting the model, and the model's efficiency and attitude toward the brand should be examined. Factors that stimulate customers' buying decisions can be used to plan advertisement that have positive influence on a brand. This study had the limitation of investigating mainly college students and there were insufficient copies of the questionnaire. The investigation was not done widely but in detail so that a concrete investigation could not be done. Further studies shall supplement these shortcomings and discuss new directions.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.109-122
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• 2014

People are nowadays creating a tremendous amount of data on Social Network Service (SNS). In particular, the incorporation of SNS into mobile devices has resulted in massive amounts of data generation, thereby greatly influencing society. This is an unmatched phenomenon in history, and now we live in the Age of Big Data. SNS Data is defined as a condition of Big Data where the amount of data (volume), data input and output speeds (velocity), and the variety of data types (variety) are satisfied. If someone intends to discover the trend of an issue in SNS Big Data, this information can be used as a new important source for the creation of new values because this information covers the whole of society. In this study, a Twitter Issue Tracking System (TITS) is designed and established to meet the needs of analyzing SNS Big Data. TITS extracts issues from Twitter texts and visualizes them on the web. The proposed system provides the following four functions: (1) Provide the topic keyword set that corresponds to daily ranking; (2) Visualize the daily time series graph of a topic for the duration of a month; (3) Provide the importance of a topic through a treemap based on the score system and frequency; (4) Visualize the daily time-series graph of keywords by searching the keyword; The present study analyzes the Big Data generated by SNS in real time. SNS Big Data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. In addition, such analysis requires the latest big data technology to process rapidly a large amount of real-time data, such as the Hadoop distributed system or NoSQL, which is an alternative to relational database. We built TITS based on Hadoop to optimize the processing of big data because Hadoop is designed to scale up from single node computing to thousands of machines. Furthermore, we use MongoDB, which is classified as a NoSQL database. In addition, MongoDB is an open source platform, document-oriented database that provides high performance, high availability, and automatic scaling. Unlike existing relational database, there are no schema or tables with MongoDB, and its most important goal is that of data accessibility and data processing performance. In the Age of Big Data, the visualization of Big Data is more attractive to the Big Data community because it helps analysts to examine such data easily and clearly. Therefore, TITS uses the d3.js library as a visualization tool. This library is designed for the purpose of creating Data Driven Documents that bind document object model (DOM) and any data; the interaction between data is easy and useful for managing real-time data stream with smooth animation. In addition, TITS uses a bootstrap made of pre-configured plug-in style sheets and JavaScript libraries to build a web system. The TITS Graphical User Interface (GUI) is designed using these libraries, and it is capable of detecting issues on Twitter in an easy and intuitive manner. The proposed work demonstrates the superiority of our issue detection techniques by matching detected issues with corresponding online news articles. The contributions of the present study are threefold. First, we suggest an alternative approach to real-time big data analysis, which has become an extremely important issue. Second, we apply a topic modeling technique that is used in various research areas, including Library and Information Science (LIS). Based on this, we can confirm the utility of storytelling and time series analysis. Third, we develop a web-based system, and make the system available for the real-time discovery of topics. The present study conducted experiments with nearly 150 million tweets in Korea during March 2013.