• PNF and Movement
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• v.11 no.1
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• pp.27-33
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• 2013

Purpose : The purpose of this research was to research on Needs for the Construction of the CSFT(Cluster with a Strongpoint for Field Training) on students and professors of health-related majors. Methods : We investigated 164 students and professors using a self-reporting method with experience of Field Training. A statistical analysis was performed using SPSS 17.0 for window version. Results : It showed that educational satisfaction had scored 4.05 in curriculum, 4.00 in environment, 3.52 in schedule, 3.71 in evaluation and 3.71 in teaching and 3.84 in industrial-college systems for Field Training. Needs for the Construction of the CSFT had scored 4.17 in $mean{\pm}standard$ deviation. Conclusion : Characterization of Nursing, Department of Health and local health care environment and conditions, if you think the quality of education for the Department of Health Nursing, gradually, the acquisition and improvement of the base hospital is necessary. Therefore, it is considered to be institutionalized by installing the strongpoint hospital at least one in each region, so that they can contribute to the improvement of people's health.

• Journal of the Korea Society of Computer and Information
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• v.19 no.12
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• pp.309-317
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• 2014

Recently, crime prediction and prevention are the most important social issues, and global and local governments have tried to prevent crime using various methodologies. One of the methodologies, data mining can be applied at various crime fields such as crime pattern analysis, crime prediction, etc. However, there is few researches to find the relationships between the results of data mining and crime components in terms of criminology. In this study, we introduced environmental criminology, and identified relationships between environment factors related with crime and variables using at data mining. Then, using real burglary data occurred in South Korea, we applied clustering to show relations of results of data mining and crime environment factors. As a result, there were differences in the crime environment caused by each cluster. Finally, we showed the meaning of data mining use at crime prediction and prevention area in terms of criminology.

• IE interfaces
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• v.25 no.3
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• pp.309-318
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• 2012

Forecasting probability or likelihood of technology development success has been a crucial factor for critical decisions in technology management such as R&D project selection and go or no-go decision of new product development (NPD) projects. This paper proposes an analytic network process (ANP) approach to forecasting of technology development success. Reviewing literature on factors affecting technology development success has constructed the ANP model composed of four criteria clusters : R&D characteristics, R&D competency, technological characteristics, and technological environment. An alternative cluster comprised of two elements, success and failure is also included in the model. The working of the proposed approach is provided with the help of a case study example of MRAM (magnetic random access memory) technology.

• International Commerce and Information Review
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• v.7 no.4
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• pp.245-268
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• 2005

The purpose of this paper is to acquire competitiveness faced with a global business so that Korea and China make them put ICT into practice through industrial policy of regional innovation clustering. In the Chapter 2, overall review of industrial spaces theory and the environment in Global-business is conducted. In the Chapter 3, current main economic issue and West Great Development of China are viewed. Chapter 4 proposes models and strategies for the target of regional innovation clustering and phasing in development. The results of this study is that both country should do more long-term cooperation and collecting intensive knowledge for the property of region and preparatory research of regional innovation clustering than do reckless investment.

• Journal of Korean Academy of Nursing
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• v.35 no.8
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• pp.1500-1507
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• 2005

Purpose. The purpose of this study was to identify subgroups of the physical and behavioral risk profiles for cardiovascular disease among industrial workers, and to examine predicting factors for the subgroups. Sample and Method. Health records of 2,616 male and female workers aged 19-56 years who were employed in an airplane manufacturing industry were analyzed. Data were analyzed using the Latent class cluster analysis. Results. Four different clusters (two high-risk groups, one low-risk group, and one normal group) were found and these clusters were significantly different by age, gender, and work type (p < .05 ). The two high-risk groups had higher chances of drinking alcohol, elevated BMI, FBS, total cholesterol, having hypertension, and were significantly older, and had relatively high chances of being day workers rather than other groups. The low-risk group had higher chances of drinking alcohol, higher BMI and total cholesterols compared to normal group, and highest portions of current smokers and shift workers in the four clusters and their mean BP was within prehypertension criteria. Conclusion. Industrial nurses should guide the lifestyle behaviors and risk factors of the high risk groups for CVD and need to intervene early for behavioral change for the low-risk group who are young and shift workers. Age, and work environment should be considered in planning for targeted preventive interventions for industrial workers.

• Journal of Ecology and Environment
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• v.32 no.2
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• pp.115-121
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• 2009

In order to elucidate the mechanisms affecting plant distributions in the reclaimed dredging area in the Gwangyang steelworks, in the Gwangyang Bay, Korea, we examined soil characteristics and plant distributions in four study sites and a control site in the study area. Desalination occurring along a gradient with increasing elevation, resulting in decrease of soil pH, EC, P, K, Cl, Ca, Mg, and salt and an increase in soil T-N, silt, clay contents. From site 1 (the lowest-elevation site) to site 5 (the highest-elevation site), halophytes decreased in abundance and nonhalophytes increased. The dominant species in each site were: Phragmites communis, Limonium tetragonum, and 12 additional species at site 1, Carex pumila, Suaeda japonica, and 15 additional species at site 2, Spergularia marina, Scirpus planiculmis, and 22 additional species at site 3, Miscantus sinensis, Lespedeza bicolor, and 26 additional species at site 4 and Pinus thunberii, Rhododendron mucronulatum, and 39 additional species at site 5, which resembled a naturally-occurring P. thinbergii community. Cluster analysis of the vegetation data matrix grouped the 35 plots into 5 major groups, and cluster analysis using the soil environment data matrix revealed 4 major groups. CCA of the floristic and environmental data matrix showed a positive relationship of SAR, EC, Na, Cl, and Ca, which are related to salt, in the $1^{st}$ axis and $2^{nd}$ axis, but negative relationships for altitude, organic contents, silt, and clay contents. Notably, plant species in the reclaimed dredging area that were separated along the $1^{st}$ axis showed strong relationships with factors that related to salt. Long-term exposure to natural rainfall in the reclaimed dredging area changed the soil characteristics, such as salinity. This change in soil characteristics might alter the SAR, which affects plant survival strategies in a given habitat. These results strongly indicated that factors related to salt and elevation play important roles in determining the overall plant distribution in the reclaimed dredging area.

• Journal of Korean Society on Water Environment
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• v.25 no.5
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• pp.735-741
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• 2009

In order to support the basic information for planning and performing the environment management such as Total Maximum Daily Loads (TMDLs), it is highly recommended to understand the spatial distribution of water quality and runoff data in the unit watersheds. Therefore, in the present study, we applied Self-Organizing Map (SOM) to detect the characteristics of spatial distribution of Biological Oxygen Demand (BOD) concentration and runoff data which have been measured in the Yeongsan, Seomjin, and Tamjin River basins. For the purpose, the input dataset for SOM was constructed with the mean, standard deviation, skewness, and kurtosis values of the respective data measured from the stations of 22-subbasins in the rivers. The results showed that the $4{\times}4$ array structure of SOM was selected by the trial and error method and the best performance was revealed when it classified the stations into three clusters according to the basic statistics. The cluster-1 and 2 were classified primarily by the skewness and kurtosis of runoff data and the cluster-3 including the basic statistics of YB_B, YB_C, and YB_D stations was clearly decomposed by the mean value of BOD concentration showing the worst condition of water quality among the three clusters. Consequently, the methodology based on the SOM proposed in the present study can be considered that it is highly applicable to detect the spatial distribution of BOD concentration and runoff data and it can be used effectively for the further utilization using different water quality items as a data analysis tool.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.2
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• pp.562-574
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• 2012

Simulation validation techniques which have been employed in most studies are statistical analysis, which validate a model with mean or variance of throughput and resource utilization as an evaluation object. However, these methods have not been able to ensure the reliability of individual elements of the model well. To overcome the problem, the weighted F-measure method was proposed, but this technique also had some limitations. First, it is difficult to apply the technique to complex system environment with numerous values of interarrival time because it assigns a class to an individual value of interarrival time. In addition, due to unbounded weights, the value of weighted F-measure has no lower bound, so it is difficult to determine its threshold. Therefore, this paper propose weighted F-measure technique with cluster analysis to solve these problems. The classes for the technique are defined by each cluster, which reduces considerable number of classes and enables to apply the technique to various systems. Moreover, we improved the validation technique in the way of assigning minimum bounded weights without any lack of objectivity.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.23 no.3
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• pp.229-242
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• 2013

Objectives: This study was designed to investigate the current status of the association of job-related information such as employment status, workplace environment, and hazard material exposures with health examination outcomes. Methods: The study used data from KNHANES 2007-2009 representing the three years of 2007-2009, which was conducted annually using a rolling sampling design that involved a complex, stratified, multistage, probability-cluster survey of a representative sample of the non-institutionalized civilian population in Korea. The final analytical sample consisted of 17,240 participants. Information on age, education, smoking history and alcohol intake was collected during the health interview. Job related information consisted of employment status, workplace environment, and hazardous material exposure. The selected indices of health examination were blood pressure, fasting glucose, blood cholesterol, HDL, SGOT, SGPT, and BUN. Results: In multiple logistic regression analysis using hypertension and pre-hypertension as dependent variables and job related categories as independent variables after covariate adjustments, the odds of hypertension and pre-hypertension were significantly lower in those with responsibility and power in their job activities. Interestingly, low odds for hypertension were observed among those who reported that their jobs were fast-paced. Conclusions: This study confirmed that some job-related categories in employment status, workplace environment, and hazardous material exposure had an association with health outcome status. It is worthwhile to comment that high responsibility and power in job activities were revealed as one of the important favorable factors to improve health condition of workers.

• Journal of Marine Bioscience and Biotechnology
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• v.14 no.2
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• pp.124-132
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• 2022

By-products from fisheries produced in Korea are of the same industrial material as imported raw materials and are valuable resources for marine bioindustries. Securing raw materials for the mass production of functional materials is one of the main objectives for marine bioindustrial development. The use of fishery by-products as raw materials is anticipated to increase rapidly as the biomarket is growing into a promising industry. In this study, data were acquired from an open-source environment to perform exploratory data analysis, and various visualization methods were used to compare fishery production to the production of marine processed products in the year 2020. This study suggested that the amount of seafood processing, types of processing items, and areas where fishery processing residue is generated, should be able to secure hygienic raw material supply in large quantities. Thus far, it has been found that the Gyeonggi-do and Busan province, where HACCP-certified processing facilities are concentrated, and the local government Seafood Cluster and the Smart Aquaculture Cluster are at the forefront of stable, mass production of raw materials.