• 대한상한금궤의학회지
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• 제5권1호
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• pp.19-29
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• 2013

Objective : The purpose of this study is to analyze the naming of 'A diagnostic system based on Shanghanlun six meridian patterns and provisions' and to suggest an alternative naming. Methods : 1. The meaning of 'Six meridian(六經)' was reviewed on existing theories and Shanghanlun provisions. 2. Comparing the name of diangostic system with the term in 'Korean Standard Classification of Diseases-6(KCD-6)' and term in 'WHO international standard terminologies on traditional medicine in the western pacific region' was done. Results : 'Six meridian' is customary used in the Shagnhanlun study but its meaning is not match with original Shanghanlun system and could possibly make misunderstanding. So 'Disease pattern identification' is suitable than 'Six meridian' for this diagnostic system. Conclusions : This study suggests that using 'A disease pattern identification diagnostic system based on Shanghanlun provisions.'is more appropriate instead of using the name of the six meridian diagnostic system.

• Journal of Korea Multimedia Society
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• 제7권1호
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• pp.113-125
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• 2004

Active networks aim to provide a software framework that enables active network applications to customize the processing their communications. Active security component architecture focuses on the support of reuse system by active security component. The architecture is standard layer to acquire, understand, and assemble component, and it has to support a guideline for component identification, search and customization. In this paper we present the active security architecture as a standard model of discrete active network solution, and we propose the method for component classification and specification.

• Journal of the Korean housing association
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• 제12권3호
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• pp.149-156
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• 2001

Recently, with the increase of income level, many people desire to have agreeable and quiet surrounding. However, construction noise has caused much annoyance for a number of dwellers and workers in nearby construction field. It has become a very serious issue in our living environment. For the accurate evaluation of construction noise with various frequency spectrums and fluctuation characteristics, the evaluation system should reflect not only physical quantities but also the psychological respects of individual persons. With preceding study of psycho-acoustical experiments, this study attempts to survey the classification of adjectives and sound using the method of selected description and intends to get the basic data for establishment of a standard about construction noise.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2004년도 ICCAS
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• pp.1319-1323
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• 2004

In this paper, a problem of Thai sign language recognition using a neural network is considered. The paper addresses the problem in classifying certain signs conveying quantitative meaning, e.g., large or small. By treating those signs corresponding to different quantities as derived from different classes, the recognition error rate of the standard multi-layer Perceptron increases if the precision in recognizing different quantities is increased. This is due the fact that, to increase the quantitative recognition precision of those signs, the number of (increasingly similar) classes must also be increased. This leads to an increase in false classification. The problem is due to misinterpreting the amount of quantity the quantitative signs convey. In this paper, instead of treating those signs conveying quantitative attribute of the same quantity type (such as 'size' or 'amount') as derived from different classes, here they are considered instances of the same class. Those signs of the same quantity type are then further divided into different subclasses according to the level of quantity each sign is associated with. By using this two-level classification, false classification among main gesture classes is made independent to the level of precision needed in recognizing different quantitative levels. Moreover, precision of quantitative level classification can be made higher during the recognition phase, as compared to that used in the training phase. A standard multi-layer Perceptron with a back propagation learning algorithm was adapted in the study to implement this two-level classification of quantitative gesture signs. Experimental results obtained using an electronic glove measurement of hand postures are included.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제25권12호
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• pp.1809-1816
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• 2021

In order to identify the latest research trends using data related to national R&D projects and to produce and utilize meaningful information, the application of automatic classification technology was also required in the national R&D information service, so we conducted research to automatically classify and recommend research field. About 450,000 cases of national R&D project data from 2013 to 2020 were collected and used for learning and evaluation. A model was selected after data pre-processing, analysis, and performance analysis for valid data among collected data. The performance of Word2vec, GloVe, and fastText was compared for the purpose of deriving the optimal model combination. As a result of the experiment, the accuracy of only the subcategories used as essential items of task information is 90.11%. This model is expected to be applicable to the automatic classification study of other classification systems with a hierarchical structure similar to that of the national science and technology standard classification research field.

• Journal of Korean Academy of Nursing
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• 제26권2호
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• pp.399-412
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• 1996

Even though Korean medical law stipulates that number of patients attended by a nurse is 2.5 for hospitalization and 30 for ambulatory care, the number of patients cared by a nurse per day is much greater than the standard prescribed by the medical law. Current nursing productivity of nurses is not desirable unless the quality of care considered. Moreover. nursing manpower staffing based on neither current nurses' productivity nor standard of medical law cannot respond properly to dynamic situation of the medical services. As for the nurse scheduling, the critical problem of it in the hospital is determining the day-to-day shift assignments for each nurse for the specified period in a way that satisfies the given requirements of the hospital. Nurse scheduling, however, involves many factors and requirements, manual scheduling requires much time and effort to produce an adequate schedule. Under these backgrounds, the necessity of more efficient management of nursing manpower occupying 1/3 of total hospital workers has been recognized by many nursing administrators. This study was performed to develop a system computerizing nurse staffing and scheduling based on the patient classification. As a preliminary step for the system development, nursing workload in a secondary hospital was measured from Sep. to Oct. 1994. On the grounds of this result, computerization of nurse staffing and scheduling was proceeded with three options. First one is based on the current medical law. Second one is based on the assigned number of nursing staff. And the last is based on the request by patient classification. Computer languages used in this study were MS Visual Basic 3.0 for the staffing and Access 2.0 for the scheduling, respectively. Prospective users may operate this system easily because icons and mouse are used for easier graphic user interface and reducing the need for typing efforts. This system can help nurse administrators manage nursing manpower efficiently and nurses develop quick and easy schedule generation and allow more time for the patient care.

• Journal of KIBIM
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• 제8권4호
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• pp.49-59
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• 2018

Recently, the application of BIM for port & harbour facilities has been increasing, as it is widely applied to the infrastructure field both at domestic and abroad. However, the port and harbour projects still have very poor facilities information management system and the application level of BIM is very low compared to other facilities. Even if BIM is applied for those project, it is very difficult to determine in advance what information is needed without an accurate understanding of the business process. The purpose of this study is to develop a BIM framework for port & harbour facilities and to examine its applicability. To do this, we structured the classification of the port & harbour facilities and constructed object-based classification system based on ISO12006-3 standard. We also derived the BIM framework requirements from the viewpoint of process, standard, interface, and information, and confirmed the linkage of the BIM object classification system in the framework item. The applicability of the BIM framework for inspection process cases of port & harbour was examined. Accordingly, this study can solve requirement setting method, which is the non - procedural and non - systematic project information, in the BIM application process of the port & harbour project with the BIM framework. In addition, the framework is expected to be integrated into the system to play a key role in the selection of project objectives, and the ability to clearly identify the information requirements required by the BIM manager to perform the project.

• Journal of the Korean Society of Safety
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• 제34권5호
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• pp.119-131
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• 2019

Among the themes for CSR(Corporate Social Responsibility), consumer issues include protecting the health and safety of consumers who purchase and use the products. In particular, ensuring product safety is a major theme of consumer issues for corporate social responsibility. Currently, the government implements the Electrical Appliances and Consumer Products Safety Control Act for product safety management and selects products that may harmful to consumers as safety control items, and manages the products by designating them as 4 types of safety certification, safety confirmation, supplier conformity verification, and safety standard compliance. In this paper, we propose management plans for the establishment of a more reasonable classification type of safety management target for 48 items of consumer products to be controlled by the act, and confirm the validity of the plan. First, we perform cluster analysis using data for CISS (Consumer Injury Surveillance System) to derive a new classification type of the safety management target. Next, we compare the results of the cluster analysis with the classification type of the act and the existing scenario classification method RAS (Risk Assessment by Scenario) and the causal network method RAMP (Risk Assessment Method based on Probability). Based on these results, we propose two new plans of safety management target classification and verify its validity.

• Journal of the Korean Society of Safety
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• 제15권2호
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• pp.1-7
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• 2000

This paper presents the approach involving fault detection and diagnosis of gears using pattern recognition and Wavelet transform. It describes result of the comparison between KDI (Kullback Discrimination Information) with the nearest neighbor classification rule as one of pattern recognition methods and Wavelet transform to know a way to detect and diagnosis of gear damages experimentally. To model the damages 1) Normal (no defect), 2) one tooth is worn out, 3) All teeth faces are worn out 4) One tooth is broken. The vibration sensor was attached on the bearing housing. This produced the total time history data that is 20 pieces of each condition. We chose the standard data and measure distance between standard and tested data. In Wavelet transform analysis method, the time series data of magnitude in specified frequency (rotary and mesh frequency) were earned. As a result, the monitoring system using Wavelet transform method and KDI with nearest neighbor classification rule successfully detected and classified the damages from the experimental data.

• The Journal of the Korea Contents Association
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• 제5권4호
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• pp.169-179
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• 2005

Standard industry and occupation code are usually assigned manually in Korean census. The manual coding is very labor intensive and expensive task. Furthermore, inconsistent coding is resulted from the ability of human experts and their working environments. This paper proposes an automatic code classification system which converts natural language responses on survey questionnaires into corresponding numeric codes by using manually constructed rule base and example-based machine learning. The system was trained with 400,000 records of which standard codes was assigned. It was evaluated with 10-fold cross validation and was tested with three code sets: population occupation set, industry set, and industry survey set. The proposed system showed 76.63%, 82.24 and 99.68% accuracy for each code set.