• Journal of Preventive Medicine and Public Health
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• v.28 no.1 s.49
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• pp.103-121
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• 1995

An investigation on psychophysiological health and social well-being of shift workers been carried out on workers of a automobile manufacturing plant in Ulsan, for 1 month from April, 1993. This cross-sectional survey compared shift workers(n=544) with day workers(n=115). Each subject completed a questionnaire about his personal habit, background, shift schedule, sleep and eating patterns, subjective digestive symptom and psychological well-being and distress using the General Well-Being Schedule(GWB) by self administrated questionnaire that was developed for the U.S. Health and Nutrition Examination Surveys (HANES I). Chi-square analysis was used for discontinuous data and the t-test was used for continous data to determine whether differences noted between the two groups. In terms of sleep quality, a greater percentage of shift workers frequently had trouble getting back to sleep once awakend(p<0.01), and a greater percentage of shift workers awakend tired or sleepy frequently more often than day workers(p<0.05). In rating the quality of their sleep, more shift workers rated their sleep fair to poor than day workers, and greater percentage of shift workers felt tired or sleepy at work two or more times per week(p<0.01) and a much higher percentage of shift workers felt tired or sleepy after work every days(p<0.01). In terms of sleep patterns, a much higher percentage of day workers reported uninterrupted sleep per 24hours than shift workers. The shift workers reported different eating patterns from day workers but there were no statistically significant and rate of their appetite. Thirteen percent of day workers reported the best appetite but only 6.6% of shift workers had the best appetite. The gastric complaints is more frequent in shift workers than day workers(p<0.01). Among subscores in General Well-Being Schedule, anxiety, depression, positive well-being and vitality subscale of shift workers were lower than those of day workers(p<0.05) and general health and self control subscale of shift workers were lower than .those of day workers but there were no statistical significant difference. Based on these study result, it could be concluded that the shift work has significant effects on some psychophysiological conditions of the workers.

• Journal of the Economic Geographical Society of Korea
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• v.7 no.1
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• pp.65-81
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• 2004

Foreign direct investment (FDI) by firms has various motives in terms of the strategy for firms' long-term growth. This research uses the case study of Hyundai Motor Manufacturing Alabama to analyze the motives of the Korean auto industry's FDI in the U.S. and the locational factors that determined the selection of the site. This paper starts from the question of why Hyundai made the decision to invest in the U.S., which is not favorable in terms of production cost, especially considering that its exports to the U.S. have been on the increase. The results indicate that the strongest motive for the decision to invest in the U.S. was to ameliorate the trade friction between Korea and the U.S. Given that Hyundai depends on the U.S. market to a large extent for its exports, the foremost motive was to use local production in order to reduce the serious trade imbalance in the automobile sector between Korea and the U.S. in order that trade friction with the U.S. may be avoided and causes for trade disputes may be reduced. Other motives such as improving the access to local consumers were of secondary importance. After the selection of the country in which to invest, however, various factors were considered in the decision regarding the location of the plant, and incentives by local governments ultimately played a key role in this decision. The results imply that the Korean manufacturing industry's investment in the U.S. cannot be explained by traditional FDI theories and instead was greatly driven by a strategic defensive motive. In addition, the results confirm that the design of an appropriate incentive structure by host governments is important for attracting FDI.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.639-647
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• 2011

In this paper, we introduce a design methodology of data-centroid Radial Basis Function neural networks with extended polynomial function. The two underlying design mechanisms of such networks involve K-means clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on K-means clustering method for efficient processing of data and the optimization of model was carried out using PSO. In this paper, as the connection weight of RBF neural networks, we are able to use four types of polynomials such as simplified, linear, quadratic, and modified quadratic. Using K-means clustering, the center values of Gaussian function as activation function are selected. And the PSO-based RBF neural networks results in a structurally optimized structure and comes with a higher level of flexibility than the one encountered in the conventional RBF neural networks. The PSO-based design procedure being applied at each node of RBF neural networks leads to the selection of preferred parameters with specific local characteristics (such as the number of input variables, a specific set of input variables, and the distribution constant value in activation function) available within the RBF neural networks. To evaluate the performance of the proposed data-centroid RBF neural network with extended polynomial function, the model is experimented with using the nonlinear process data(2-Dimensional synthetic data and Mackey-Glass time series process data) and the Machine Learning dataset(NOx emission process data in gas turbine plant, Automobile Miles per Gallon(MPG) data, and Boston housing data). For the characteristic analysis of the given entire dataset with non-linearity as well as the efficient construction and evaluation of the dynamic network model, the partition of the given entire dataset distinguishes between two cases of Division I(training dataset and testing dataset) and Division II(training dataset, validation dataset, and testing dataset). A comparative analysis shows that the proposed RBF neural networks produces model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• Korean Chemical Engineering Research
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• v.43 no.4
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• pp.487-494
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• 2005

Nowadays a large amount of wastewater containing metal working fluids and cleaning agents is generated during the cleaning process of parts working in various industries of automobile, machine and metal, and electronics etc. In this study, aqueous or semi-aqueous cleaning wastewater contaminated with soluble or nonsoluble oils was treated using ultrafiltration system. And the membrane permeability flux and performance of oil-water separation (or COD removal efficiency) of the ultrafiltration system employing PAN as its membrane material were measured at various operating conditions with change of membrane pore sizes and soil concentrations of wastewater and examined their suitability for wastewater treatment contaminated with soluble or insoluble oil. As a result, in case of wastewater contaminated with soluble oil and aqueous or semi-aqueous cleaning agent, the membrane permeability increased rapidly even though COD removal efficiency was almost constant as 90 or 95％ as the membrane pore size increased from 10 kDa to 100 kDa. However, in case of the wastewater contaminated with nonsoluble oil and aqueous or semi-aqueous cleaning agent, as the membrane pore size increased from 10 kDa to 100 kDa and the soil concentration of wastewater increased, the membrane permeability was reduced rapidly while COD removal efficiency was almost constant. These phenomena explain that since the membrane material is hydrophilic PAN material, it blocks nonsoluble oil and reduces membrane permeability. Thus, it can be concluded that the aqueous or semi-aqueous cleaning solution contaminated with soluble oil can be treated by ultrafiltration system with the membrane of PAN material and its pore size of 100 kDa. Based on these basic experimental results, a pilot plant facility of ultrafiltration system with PAN material and 100 kDa pore size was designed, installed and operated in order to treat and recycle alkaline cleaning solution contaminated with deep drawing oil. As a result of its field application, the ultrafiltration system was able to separate aqueous cleaning solution and soluble oil effectively, and recycle them. Further more, it can increase life span of aqueous cleaning solution 12 times compared with the previous process.

• Computational Structural Engineering
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• v.7 no.3
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• pp.95-103
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• 1994

The safety related components in the nuclear power plant should be designed to withstand the seismic load. Among these components the integrity of reactor internals under earthquake load is important in stand points of safety and economics, because these are classified to Seismic Class I components. So far the modelling methods of reactor internals have been investigated by many authors. In this paper, the dynamic behaviour of reactor internals of Yong Gwang 1&2 nuclear power plants under SSE(Safe Shutdown Earthquake) load is analyzed by using of the simpled Global Beam Model. For this, as a first step, the characteristic analysis of reactor internal components are performed by using of the finite element code ANSYS. And the Global Beam Model for reactor internals which includes beam elements, nonlinear impact springs which have gaps in upper and lower positions, and hydrodynamical couplings which simulate the fluid-filled cylinders of reactor vessel and core barrel structures is established. And for the exciting external force the response spectrum which is applied to reactor support is converted to the time history input. With this excitation and the model the dynamic behaviour of reactor internals is obtained. As the results, the structural integrity of reactor internal components under seismic excitation is verified and the input for the detailed duel assembly series model could be obtained. And the simplicity and effectiveness of Global Beam Model and the economics of the explicit Runge-Kutta-Gills algorithm in impact problem of high frequency interface components are confirmed.

• Korean Journal of Culture and Social Issue
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• v.9 no.spc
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• pp.107-122
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• 2003

The object of this study is to evaluate the prevailing physical and psychosocial conditions regarding occupational low back injury. This study consists of two parts. In the first part of the study, analytic biomechanical model and NIOSH guidelines are applied to evaluate risk levels of low back injury for automobile assembly jobs. Total of 246 workers are analysed. There are 20 jobs having greater back compressive forces than 300kg at L5/S1. Also, there are 44 jobs over Action Limit with respect to 1981 NIOSH guidelines. The relationship between psychosocial factors and low back injury was examined in the second part of the study. A battery of questionnaires concerning the psychosocial stress based on PWI (Psychosocial Well-being Index) and musculoskeletal pain symptoms at low back was completed by 246 workers at the same plant. Results showed that 207 out 246 workers experienced the symptoms and 27 workers were diagnosed as patients. Two groups(low stressed, high stressed) based on PWI score had no significant relationships with both symptoms and results of diagnosis. The relationships between physical work load and psychosocial stress were also analysed. Specifically, some postural factors(vertical deviation angle of forearm, horizontal deviation angle of upperarm, vertical deviation angle of thigh, etc) were highly correlated with psychosocial stress. The results illustrated that PWI scores were associated with some physical workloads. However, psychosocial stress levels couldn't be well related with the pain symptom as well as the actual incidence of low back injury since pain or discomfort regarding low back injury were more complex than that of other musculoskeletal disorders.