• Korea Journal of Hospital Management
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• 제19권3호
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• pp.11-28
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• 2014

This study, targeting Korean tertiary hospitals and general hospitals, aims to analyze how value chain model in health and medical institution suggested by Duncan and else influences on hospital management. A survey was conducted to verify the actual proof analysis of this study model. 880 questionnaires were distributed to entire 88 hospitals and 739 copies were returned from 76 hospitals. This study mainly consists of three steps to analyze the effect value chain activity has on management performance of general hospitals. For the first step, we analyzed the effects service delivery activity has on management performance. For the second step, we analyzed the effects service support activity has on management performance and for the third, we analyzed the effects interaction between service delivery activity and service support activity has on management performance. The main results of this study are as follows. First, in terms of the management performance of scale, the factors which influenced on daily charge of outpatient were service activity before treatment, at the moment of treatment and value chain activity, while more important factors in daily charge of inpatient were organizational culture, organizational structure and value chain activity. In terms of management performance of quality, the factors which influenced on the first medical examination rate of outpatient were service activity before, at the moment of and after treatment, while activity at the moment of treatment, organizational structure, and value chain activity which is interaction were more important factors in average length of stay. In terms of non-financial performance, the management performance factors which influenced on job satisfaction were service activity at the moment of, after the treatment and value chain activity, while organizational culture, strategy resources and value chain activity which is interaction were more important factors in job commitment. Secondly, all the service support activity, service delivery activity and value chain activity had statistically significant effect on management performance. Among the three factors, service support activity had relatively high effect than others.

• Journal of Agricultural Extension & Community Development
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• 제22권4호
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• pp.455-464
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• 2015

The purposes of this study are to explain and identify the frame of structural relations of learning orientation, self-efficacy, learning transfer and job performance of farmers who participated in the strong and small farms education. This is an experimental research with the data collected from 495 farmers who have taken the farm education. Based on the collected data, the study conducted a structural equation modeling(SEM) to confirm the validity and analyze the structural relations of the suggested model. Using measured and latent variables drew from the analyses, the study set a structural equation model and tested the model by analysis of the structural equation modeling with AMOS 18.0. The results found from the empirical analysis can be summarized as follows. 1) Learning orientation and self-efficacy positively influenced job performance through learning transfer. 2) The hypothesis that learning orientation would have direct impact on job performance was not supported. 3) The strong and small farms education is useful to expand learning transfer and to enhance job performance. So, government policy support has to reinforce learning support on farmers in order to achieve high performance of learning and job management through farm educations.

• Management & Information Systems Review
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• 제38권2호
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• pp.225-240
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• 2019

It has been known that health industry clusters promote economy of a nation in a macro view and make growth and development of individual firm. As a result, Korean health industry has been grown to play a role of making a high value added in Kwangkyo, Daedeok, Wonju, and Songdo. Using 156 firms locating in health industry clusters such as Kwangkyo, Daedeok, Wonju, and Songdo in increasing value added, this study investigated the structural relationships among R&D resources, R&D collaboration, policy support, and operational performance. All hypotheses, except a hypothesis for the effect R&D resources on operational performance, are reported to be statistically significant. In other words, the positive effect of R&D resources on policy support is reported. And policy support and R&D collaboration positively affect operational performance, and also the positive effect of policy support on R&D collaboration is reported. From the empirical results, we can know that policy support and R&D collaboration are the crucial factors to promote operational performance of the firms locating in Korean health industry clusters. It is important that this study has been investigated with the firms of health industry developing economy of a nation.

• Proceedings of the Korea Concrete Institute Conference
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• 한국콘크리트학회 2002년도 가을 학술발표회 논문집
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• pp.695-702
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• 2002

Shotcrete (or Sprayed concrete) has been used as an important support material in New Austrian Tunnelling Method (NATM). Since the mid of 1990, permanent shotcrete tunnel linings such as Single-shell, NMT (Norwegian Method of Tunnelling) has been constructed in many countries for reducing the construction time and lowing construction costs instead of conventional in-situ concrete linings. Among essential technologies for successful application of permanent shotcrcte linings, high performance shotcrete providing high strength, high durability, better pumpability has to be developed in advance as an integral component. This paper presents the Ideas and first experimental attempts to increase early strength and bond strength of wet-mixed Steel Fiber Reinforced Shotcrete(SFRS) in sump water condition. In order to increase early strength, a new approach using high-early strength cement with liquid alkali-free accelerator has been investigated From the results, wet-mix SFRS with high-early strength cement and alkali-free accelerator exhibited excellent early strength improvement compared to the ordinary portland content and good bond strength even under sump water condition.

• International Journal of Internet, Broadcasting and Communication
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• 제13권2호
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• pp.231-243
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• 2021

In Recent years the way we analyze the breast cancer has changed dramatically. Breast cancer is the most common and complex disease diagnosed among women. There are several subtypes of breast cancer and many options are there for the treatment. The most important is to educate the patients. As the research continues to expand, the understanding of the disease and its current treatments types, the researchers are constantly being updated with new researching techniques. Breast cancer survival rates have been increased with the use of new advanced treatments, largely due to the factors such as earlier detection, a new personalized approach to treatment and a better understanding of the disease. Many machine learning classification models have been adopted and modified to diagnose the breast cancer disease. In order to enhance the performance of classification model, our research proposes a model using A Hybrid Modified K-Means Clustering with Modified SVM (Support Vector Machine) Machine learning algorithm to create a new method which can highly improve the performance and prediction. The proposed Machine Learning model is to improve the performance of machine learning classifier. The Proposed Model rectifies the irregularity in the dataset and they can create a new high quality dataset with high accuracy performance and prediction. The recognized datasets Wisconsin Diagnostic Breast Cancer (WDBC) Dataset have been used to perform our research. Using the Wisconsin Diagnostic Breast Cancer (WDBC) Dataset, We have created our Model that can help to diagnose the patients and predict the probability of the breast cancer. A few machine learning classifiers will be explored in this research and compared with our Proposed Model "A Hybrid Modified K-Means with Modified SVM Machine Learning Algorithm to Enhance the Cancer Prediction" to implement and evaluated. Our research results show that our Proposed Model has a significant performance compared to other previous research and with high accuracy level of 99% which will enhance the Cancer Prediction.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 한국해양공학회 2006년 창립20주년기념 정기학술대회 및 국제워크샵
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• pp.277-280
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• 2006

Most real world design evaluation and risk-based decision support combine quantitative and qualitative (linguistic) variables. Decision-making based on conventional mathematics that combines qualitative and quantitative concepts always exhibit difficulty in modelling actual problems. The successful selection process for choosing a design/procurement proposal is based on a high degree of technical integrity, safety levels and low costs in construction, corrective measures, maintenance, operation, inspection and preventive measures. However, the objectives of maximising the degree of technical performance, maximising the safety levels and minimising the costs incurred are usually in conflict, and the evaluation of the technical performance, safety and costs is always associated with uncertainties, especially for a novel system at the initial concept design stage. In this paper, a design-decision support framework using a composite structure methodology grounded in approximate reasoning approach and evidential reasoning method is suggested for design evaluation of machinery space of a ship engine room at the initial stages. It is a Multiple Attribute Decision-Making (MADM) or Multiple Criteria Decision Making (MCDM) framework, which provides a juxtaposition of cost, safety and technical performance of a system during evaluation to assist decision makers in selecting the winning design/procurement proposal that best satisfies the requirement in hand. An illustrative example is used to demonstrate the application of the proposed framework.

• Journal of the Korean Data and Information Science Society
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• 제14권2호
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• pp.337-343
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• 2003

In this paper we present the prediction interval estimation method using bootstrap method for least squares support vector machine(LS-SVM) regression, which allows us to perform even nonlinear regression by constructing a linear regression function in a high dimensional feature space. The bootstrap method is applied to generate the bootstrap sample for estimation of the covariance of the regression parameters consisting of the optimal bias and Lagrange multipliers. Experimental results are then presented which indicate the performance of this algorithm.

• Proceedings of the IEEK Conference
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.2164-2167
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• 2003

In this paper we propose effective speech recognizer through recognition experiments for three feature parameters(PCA, ICA and MFCC) using SVM(Support Vector Machine) classifier In general, SVM is classification method which classify two class set by finding voluntary nonlinear boundary in vector space and possesses high classification performance under few training data number. In this paper we compare recognition result for each feature parameter and propose ICA feature as the most effective parameter

• Journal of Korean Academy of Nursing Administration
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• 제5권1호
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• pp.39-61
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• 1999

This thesis is attempted to ananlyze the relationship between the empowerment in the nursing work environment, the job-related personal charateristics and the nursing job performance according to the individual variables of hospital, age, experience, education, position, practice area, number of nurses in the practice area, number of beds. 'Opportunity', 'support', 'informantion', ,resource' are used as structural factors of empowerment suggested by Kanter's theory of structural power in organization, and 'self-efficacy', 'burnout', 'motivation', 'organizational commitment' are defined as four job-related personal charateristics. The ultimate goal of this study is to find out the work effectiveness of the structural factors of empowerment and the job-related personal charateristics. The basic data consists of two sets of questionaires. One is the self-reporting quetionaires for the staff nurses and the other one is questionaires answered by nursing managers. The latter is designed to objectively measure the job performance. A total of 523 items of data are collected randomly from nursing population of 7 different university teaching hospitals in Seoul metropolitan area. The data were analyzed mainly using descriptive statistics, correlation analysis. ANOVA, and Duncan test according to the various purposes of the analysis. The main results of this study are as follows : 1. The mean score of four structural empowerment factors are ranked by support, opportunity, resource, and information. And among the four job-related personal charateristics self-efficacy factor shows especially high score. 2. The results of the correlation analysis between the empowerment factors and the job-related personal charateristics are as follow: 1) The 'opportunity' factor is correlated with organizational commitment' (r=.37), 'motivation' (r=.36), 'burnout' (r=-.17), and (r=.09). 2) The 'information' factor is correlated with 'organizational commitment' (r=.44), 'motivation' (r=.39), 'burnout' (r=-.24), and 'self-efficacy' (r=.17), 3) The 'support' factor is correlated with 'organizational commitment' (r=.47). 'motivation' (r=.42), 'burnout' (r=-.24), and 'self-efficacy (r=.20), 4) The 'resource' factor is correlated with 'burnout' (r=-.28), 'organizational commitment' (r=.26), and 'motivation' (r=.26), 3. The job performance are correlated with 'motivation' (r=.24) , 'self-efficacy' (r=.16), 'burnout' (r=-.16) and 'organizational commitment' (r=.12), 4. The job performance are correlated with' support' (r=.17), 'information' (r=.12) 'opportunity' (r=.10), 5. The result of ANOVA for analysing the relationship between the structural factors of empowerment and individual variables shows that the level of empowerment are significantly different by the variables such as 'hospital' and 'the number of beds in the practice area'. In summary, there were several findings in this study, First, the structural factors of empowerment defined as opportunity, support, information are significantly correalted with the job-related personal charateristics that are supposed to relate to the level of job performance. These results support the basic hypothesis suggested by Kanter's theory and implies that for improving the job performance of nurses, hospital has to have more concern about the structural factors of nursing environment.

• Journal of Korean Academy of Nursing
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• 제35권6호
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• pp.1081-1090
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• 2005

Purpose: The purpose of this study was to evaluate a Self-efficacy-based Basic Life Support (SEBLS) program for high-risk patients' family caregivers on cardiac arrest. The SEBLS program was constructed on the basis of Bandura's self-efficacy resources as well as the International Liaison Committee on Resuscitation's '2000 Guidelines for CPR and ECC'. Method: The effect of the SEBLS program on emergency response self-efficacy and emergency response behavior such as BLS(Basic Life Support) knowledge and BLS skill performance was measured by a simulated control group pretest-posttest design. Study subjects were38 high-risk patients' family caregivers(20 experimental subjects and 18 control subjects) whose family patients were admitted to a general hospital in Incheon, Korea. Result: 1. Emergency response self-efficacy was significantly higher in the experimental subjects who participated in the SEBLS program than in the control subjects. (t=8.3102, p=0.0001). 2. For emergency response behavior, BLS knowledge (t=5.6941, p=0.0001) and BLS skill performance (t=27.8281, p=0.0001) was significantly higher in experimental subjects than in control subjects. Conclusion: A SEBLS program can increase emergency response self-efficacy and emergency response behavior, and could be an effective intervention for high-risk patient's family caregivers. Long-term additional studies are needed to determine the lasting effects of the program.