• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.189-196
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• 2023

As the manufacturing paradigm shifts, various collaborative robots are creating new markets. Demand for collaborative robots is increasing in all industries for the purpose of easy operation, productivity improvement, and replacement of manpower who do simple tasks compared to existing industrial robots. However, accidents frequently occur during work caused by collaborative robots in industrial sites, threatening the safety of workers. In order to construct an industrial site through robots in a human-centered environment, the safety of workers must be guaranteed, and there is a need to develop a collaborative robot guard system that provides reliable communication without the possibility of dispatch. It is necessary to double prevent accidents that occur within the working radius of cobots and reduce the risk of safety accidents through sensors and computer vision. We build a system based on OPC UA, an international protocol for communication with various industrial equipment, and propose a collaborative robot guard system through image analysis using ultrasonic sensors and CNN (Convolution Neural Network). The proposed system evaluates the possibility of robot control in an unsafe situation for a worker.

• Journal of Preventive Medicine and Public Health
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• v.28 no.4 s.51
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• pp.809-844
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• 1995

The purposes of this study are to define the scope of occupational health management and to classify occupational management by review of related journals from 1945 to 1994 in Korea. The steps of this study were as follows: (1) Search of secondary reference; (2) Collection and review of primary reference; (3) Survey; and (4) Analysis and discussion. The results were as follows ; 1. Most of the respondents majored in occupational health(71.6%), and were working in university (68.3%), males and over the age 40. Seventy percent of the respondents agreed with the idea that classification of occupational health management is necessary, and 10% disagreed. 2. After integration of the idea of respondents, we reclassified the scope of occupational health management. It was defined 3 parts, that is , occupational health system, occupational health service and others (such as assessment, epidemiology, cost-effectiveness analysis and so on). 3. The number of journals on occupational health management was 510. It was sightly increased from 1986 and abruptly increased after 1991. The kinds of journals related to occupational health management were The Korean Journal of Occupational Medicine(18.2%), Several Kinds of Medical Colloge Journal(17.0%), The Korean Journal Occupational Health(15.1%), The Korean Journal of Preventive Medicine(15.1%) and others(34.6%). As for the contents, the number of journals on occupational health management systems was 33(6.5%) and occupational health services 477(93.5%). Of the journals on occupational health management systems, the number of journals on the occupational health resource system was 15(45.5%), occupational finance system 8(24.2%), occupational health management system 6(18.2%), occupational organization 3(9.1%) and occupational health delivery system 1 (3.0%). Of the journals on occupational health services, the number of journals on disease management was 269(57.2%), health management 116(24.7%), working environmental management 85(18.1%). As for the subjects, the number of journals on general workers was 185(71.1%), followed by women worker, white coiler workers and so on. 4. Respondents made occupational health service(such as health management, working environmental management and health education) the first priority of occupational health management. Tied for the second are quality analysis(such as education, training and job contents of occupational health manager) and occupational health systems(such as the recommendation of systems of occupational and general disease and occupational health organization). 5. Thirty seven respondents suggested 48 ideas about the future research of occupational health management. The results were as follows: (1) Study of occupational health service 40.5%; (2) Study of organization system 27.1%; (3) Study of occupational health system (e.g. information network) 8.3%; (4) Study of working condition 6.2%; and (5) Study of occupational health service analysis 4.2%.

• Korean Journal of Hospice Care
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• v.1 no.1
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• pp.46-69
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• 2001

Hospice Care is the best way to care for terminally ill patients and their family members. However most of them can not receive the appropriate hospice service because the Korean health delivery system is mainly be focussed on acutly ill patients. This study was carried out to clarify the situation of hospice in Korea and to develop a hospice care delivery system model which is appropriate in the Korean context. The theoretical framework of this study that hospice care delivery system is composed of hospice resources with personnel, facilities, etc., government and non-government hospice organization, hospice finances, hospice management and hospice delivery, was taken from the Health Delivery System of WHO(1984). Data was obtained through data analysis of litreature, interview, questionairs, visiting and Delphi Technique, from October 1998 to April 1999 involving 56 hospices, 1 hospice research center, 3 non-government hospice organizations, 20 experts who have had hospice experience for more than 3 years(mean is 9 years and 5 months) and officials or members of 3 non-government hospice organizations. There are 61 hospices in Korea. Even though hospice personnel have tried to study and to provide qualified hospice serices, there is nor any formal hospice linkage or network in Korea. This is the result of this survey made to clarify the situation of Korean hospice. Results of the study by Delphi Technique were as follows: 1.Hospice Resources: Key hospice personnel were found to be hospice coordinator, doctor, nurse, clergy, social worker, volunteers. Necessary qualifications for all personnel was that they conditions were resulted as have good health, receive hospice education and have communication skills. Education for hospice personnel is divided into (i)basic training and (ii)special education, e.g. palliative medicine course for hospice specialist or palliative care course in master degree for hospice nurse specialist. Hospice facilities could be developed by adding a living room, a space for family members, a prayer room, a church, an interview room, a kitchen, a dining room, a bath facility, a hall for music, art or work therapy, volunteers' room, garden, etc. to hospital facilities. 2.Hospice Organization: Whilst there are three non-government hospice organizations active at present, in the near future an hospice officer in the Health&Welfare Ministry plus a government Hospice body are necessary. However a non-government council to further integrate hospice development is also strongly recommended. 3.Hospice Finances: A New insurance standards, I.e. the charge for hospice care services, public information and tax reduction for donations were found suggested as methods to rise the hospice budget. 4.Hospice Management: Two divisions of hospice management/care were considered to be necessary in future. The role of the hospice officer in the Health & Welfare Ministry would be quality control of hospice teams and facilities involved/associated with hospice insurance standards. New non-government integrating councils role supporting the development of hospice care, not insurance covered. 5.Hospice delivery: Linkage&networking between hospice facilities and first, second, third level medical institutions are needed in order to provide varied and continous hospice care. Hospice Acts need to be established within the limits of medical law with regards to standards for professional staff members, educational programs, etc. The results of this study could be utilizes towards the development to two hospice care delivery system models, A and B. Model A is based on the hospital, especially the hospice unit, because in this setting is more easily available the new medical insurance for hospice care. Therefore a hospice team is organized in the hospital and may operate in the hospice unit and in the home hospice care service. After Model A is set up and operating, Model B will be the next stage, in which medical insurance cover will be extended to home hospice care service. This model(B) is also based on the hospital, but the focus of the hospital hospice unit will be moved to home hospice care which is connected by local physicians, national public health centers, community parties as like churches or volunteer groups. Model B will contribute to the care of terminally ill patients and their family members and also assist hospital administrators in cost-effectiveness.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.101-116
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• 2015

Recently, due to the development of smart devices and social media, vast amounts of information with the various forms were accumulated. Particularly, considerable research efforts are being directed towards analyzing unstructured big data to resolve various social problems. Accordingly, focus of data-driven decision-making is being moved from structured data analysis to unstructured one. Also, in the field of recommendation system, which is the typical area of data-driven decision-making, the need of using unstructured data has been steadily increased to improve system performance. Approaches to improve the performance of recommendation systems can be found in two aspects- improving algorithms and acquiring useful data with high quality. Traditionally, most efforts to improve the performance of recommendation system were made by the former approach, while the latter approach has not attracted much attention relatively. In this sense, efforts to utilize unstructured data from variable sources are very timely and necessary. Particularly, as the interests of users are directly connected with their needs, identifying the interests of the user through unstructured big data analysis can be a crew for improving performance of recommendation systems. In this sense, this study proposes the methodology of improving recommendation system by measuring interests of the user. Specially, this study proposes the method to quantify interests of the user by analyzing user's internet usage patterns, and to predict user's repurchase based upon the discovered preferences. There are two important modules in this study. The first module predicts repurchase probability of each category through analyzing users' purchase history. We include the first module to our research scope for comparing the accuracy of traditional purchase-based prediction model to our new model presented in the second module. This procedure extracts purchase history of users. The core part of our methodology is in the second module. This module extracts users' interests by analyzing news articles the users have read. The second module constructs a correspondence matrix between topics and news articles by performing topic modeling on real world news articles. And then, the module analyzes users' news access patterns and then constructs a correspondence matrix between articles and users. After that, by merging the results of the previous processes in the second module, we can obtain a correspondence matrix between users and topics. This matrix describes users' interests in a structured manner. Finally, by using the matrix, the second module builds a model for predicting repurchase probability of each category. In this paper, we also provide experimental results of our performance evaluation. The outline of data used our experiments is as follows. We acquired web transaction data of 5,000 panels from a company that is specialized to analyzing ranks of internet sites. At first we extracted 15,000 URLs of news articles published from July 2012 to June 2013 from the original data and we crawled main contents of the news articles. After that we selected 2,615 users who have read at least one of the extracted news articles. Among the 2,615 users, we discovered that the number of target users who purchase at least one items from our target shopping mall 'G' is 359. In the experiments, we analyzed purchase history and news access records of the 359 internet users. From the performance evaluation, we found that our prediction model using both users' interests and purchase history outperforms a prediction model using only users' purchase history from a view point of misclassification ratio. In detail, our model outperformed the traditional one in appliance, beauty, computer, culture, digital, fashion, and sports categories when artificial neural network based models were used. Similarly, our model outperformed the traditional one in beauty, computer, digital, fashion, food, and furniture categories when decision tree based models were used although the improvement is very small.