• International Journal of Highway Engineering
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• v.17 no.6
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• pp.117-126
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• 2015

PURPOSES : This study prioritizes potential technology for establishing a safe work zone environment on roadways. We consider almost all conceivable technologies that enable mitigation of unexpected accidents for both road workers and drivers. METHODS : This study suggests a methodology to set the priority of potential technology for establishing a safe work zone environment by using the analytical hierarchy process (AHP). For this purpose, the AHP structure was first developed. Thereafter, a web-based survey was conducted to collect experts' opinions. Based on the survey results, weights associated with the relevant criteria of the developed structure were estimated. With the consistency index (CI) and consistency ratio (CR), we verified the estimated weights. In addition, a sensitivity analysis was performed to confirm whether the estimated weights were reliable. We finally proposed the priority for potential technology for establishing a safe work zone environment on roadways. RESULTS : In the first level, safety technology has the highest priority, and real-time information delivery for work zone, hazard warning for drivers, and temporal automated operation for traffic facilities were selected in the second level of hierarchy. CONCLUSIONS : The results imply that establishing the priority will be useful to establish a future road map for improving the work environment for road workers and drivers by employing appropriate protection facilities and developing safety systems.

• Journal of Korean Academy of Nursing
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• v.36 no.2
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• pp.330-340
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• 2006

Purpose: This study was performed to investigate the factors influencing health behavior. Method: Data used in this study was drawn from a 2001 National Health survey done by Korea Institute for Health and Social Affairs. Number of samples were 5,085 people between age 20 years and 69 years in whole country. In this study, we modified Green and Kreuter's Precede-Proceed model to analyse influence of factors in health behavior, Hierarchical regression were used in the analysis. Result: 1) Factors that had statistically significant positive relation with overall health behavior were age, educational level, income level, disease in the family, medical examination, subjective weight, and concern about health, 2) Factors that had statistically significant negative relation with overall health behavior were sex, subjective health, stress, and degree of physical activity. Conclusion: 1) It would be necessary to set the target group for the health promotion in advance. 2) It was very important to adopt easy and efficient methods to change the health behavior of target group, for example, ability to control stress.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.1
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• pp.293-297
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• 2013

Background: : Chemotherapy-induced thrombocytopenia (CIT) is an important cause of morbitity in patients with cancer. Aim: To investigate the effect of the baseline plasma D-dimer level, an important marker for thrombotic activity, on chemotherapy-induced thrombocytopenia in patients with stage III colon cancer. Materials and Methods: A total of 43 (28 men) eligible patients were divided into two groups according to whether they exhibited chemotherapy-induced thrombocytopenia: Group 1 (n=21) and Group 2 (n=22). Comparison was made using demographic, histopathologic, and laboratory variables. Additionally, baseline plasma D-dimer levels underwent receiver operation characteristics curve analysis, and areas under the curve were calculated. Sensitivity, specificity, and positive and negative likelihood rates were then determined. Results: The incidence of chemotherapy-induced thrombocytopenia had a significant correlation with baseline platelet count (r=0.568, P=0.031) and baseline plasma D-dimer levels (r=0.617, P=0.036). When the cut-off point for the latter was set as 498 ng/mL, the area under the curve was 0.89 (95%CI: 0.74-0.93), the sensitivity was 91.4%, the specificity was 89.7%, the positive likelihood rate was 3.64 and the negative likelihood rate was 0.24 for chemotherapy-induced thrombocytopenia diagnosis. Conclusions: The baseline level of plasma D-dimer could help to differentiate high-risk patients for chemotherapy-induced thrombocytopenia.

• Korean Journal of Adult Nursing
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• v.19 no.1
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• pp.78-88
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• 2007

Purpose: The purpose of this study was to find out the degree of cognitive function among the elderly and to confirm its correlated factors. Methods: The subjects consisted of 392 elderly people over the age 65 who were living in Busan. Data were collected by the interview method, using a structured questionnaire and the K-MMSE scale. Results: The average points of the elderly's cognitive functions measured by K-MMSE were 23.76(${\pm}4.02$). With the cut-off point for cognitive impairment set as 24 points below using K-MMSE scale, 38.8% of the subjects have cognitive impairments. Among the variables related to cognitive functions, literacy showed the highest correlation with cognitive function(${\beta}=.330$, t=7.249, p<.001), followed in order by educational level, age, depression level, attendance of elderly's college, and religious activity. The total explanatory power of these variables is 36%. Conclusion: In order to prevent cognitive impairment among the elderly, elderly people have to maintain social relationships continuously, and expand the social network by participating in the related programs. Some efforts to prevent the occurrence of depression and to stimulate patients' brain activity need to be recommended.

• Korean Management Science Review
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• v.32 no.2
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• pp.111-124
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• 2015

In the management literature, it has been widely accepted among both researchers and practitioners that the level of team creativity is significantly related to the organizational performance. Besides, researchers posited with confidence that team diversity and task difficulty would affect team creativity through team members' activities of exploration and exploitation. However, empirical approaches to proving this belief suffered from lack of real data and proper methods as well. To tackle the research void like this, we propose a multi-agent simulation (MAS) mechanism. By adopting a set of parameters which validity were proven in the related literature, we conducted a series of experiments in the environment of the MAS platform named NetLogo. There sults suggest that managers can differentiate team diversity strategies according to task difficulty. In the case of a difficult task, managers need to increase team diversity so that their teams can maximize team creativity through rigorous exploration and exploitation. It is desirable to maintain an average level of team diversity when performing an easy task.

• Journal of Veterinary Clinics
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• v.29 no.1
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• pp.68-77
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• 2012

Whenever planning a study design or preparing a research proposal it is highly recommended that investigators decide the optimum sample size that is required to yield an outcome of interest with a predetermined level of precision. This is because that, all else being equal, if a study with less than the optimum sample size would not detect the significance of differences in reality, and similarly, if a study with more than the optimum sample size will be costly. For these reasons, the majority of peer reviewed biomedical journals assess the adequacy of sample size requirements. The calculated sample size is used as a target number of samples to be collected to provide an estimate of the parameter with the desired and predetermined level of accuracy, and the sample size is a major determinant of the probability of detecting diseased animals from the population. There is no single method of calculating sample size for any given study design. In this context, the purpose of this article is to provide a collection of formulas and examples for some typical situations likely to be encountered in veterinary clinical practice and to highlight the importance of performing prospective sample size calculations when planning a research. Specifically, this paper is concerned with the basic principle of sample size calculation, and considerations for methodological applications were illustrated for a given data set. Also included in this paper is factors influencing sample size calculations using a statistically valid techniques. Appropriate methods to consider these factors are presented.

• Journal of Korean Society on Water Environment
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• v.20 no.6
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• pp.652-656
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• 2004

Both surface wash and backwash are considered as one of the most important methods that can improve the filtration efficiency in the existing water treatment plant. This study has mainly focused on the improvement of filtering efficiency by controlling surface wash and backwash time, and water level before backwash (when drained up to the trough, when drained up to 10 cm above filter bed, and when drained below 10 cm filter bed). Filtration efficiency was shown a little bit of differences depending on the operating conditions like surface wash injection pressure, the distance control between filter bed and the facility, and the types of surface wash. When the water level before backwash was reached up to 10 cm below filter bed after draining, however, the filtration velocity and the turbidity removal efficiency in the filter bed was improved. When the surface wash followed by backwash is longer, it showed a similar result. Because the proper adjustment of surface washing time makes filtration efficiency higher, therefore, it is necessary to set up the backwash time moderately.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.3
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• pp.115-120
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• 2009

Point-based methods with experienced human operators are processed well in traditional photogrammetric activities but not the autonomous environment of digital photogrammetry. To develop more robust and accurate techniques, higher level objects of straight linear features accommodating element other than points are adopted instead of points in aerial triangulation. Even though recent advanced algorithms provide accurate and reliable linear feature extraction, extracting linear features is more difficult than extracting a discrete set of points which can consist of any form of curves. Control points which are the initial input data and break points which are end points of piecewise curves are easily obtained with manual digitizing, edge operators or interest operators. Employing high level features increase the feasibility of geometric information and provide the analytical and suitable solution for the advanced computer technology.

• Journal of Biomedical Engineering Research
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• v.22 no.4
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• pp.369-375
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• 2001

The statistical regression model is one of the most frequently used clinical analysis methods. It has basic assumption of linearity, additivity and normal distribution of data. However, most of biological data in medical field are nonlinear and unevenly distributed. To overcome the discrepancy between the basic assumption of statistical model and actual biological data, we propose a new analytical method based on artificial neural network. The newly developed multilayer perceptron(MLP) is trained with 120 data set (60 normal, 60 patient). On applying test data, it shows the discrimination power of 0.76. The diabetic risk factors were also identified from the MLP neural network model and the logistic regression model. The signigicant risk factors identified by MLP model were post prandial glucose level(PP2), sex(male), fasting blood sugar(FBS) level, age, SBP, AC and WHR. Those from the regression model are sex(male), PP2, age and FBS. The combined risk factors can be identified using the MLP model. Those are total cholesterol and body weight, which is consistent with the result of other clinical studies. From this experiment we have learned that MLP can be applied to the combined risk factor analysis of biological data which can not be provided by the conventional statistical method.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.3
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• pp.61-67
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• 2020

The fourth industrial revolution encourages manufacturing industry to pursue a new paradigm shift to meet customers' diverse demands by managing the production process efficiently. However, it is not easy to manage efficiently a variety of tasks of all the processes including materials management, production management, process control, sales management, and inventory management. Especially, to set up an efficient production schedule and maintain appropriate inventory is crucial for tailored response to customers' needs. This paper deals with the optimized inventory policy in a steel company that produces granule products under supply contracts of three targeted on-time delivery rates. For efficient inventory management, products are classified into three groups A, B and C, and three differentiated production cycles and safety factors are assumed for the targeted on-time delivery rates of the groups. To derive the optimized inventory policy, we experimented eight cases of combined safety stock and data analysis methods in terms of key performance metrics such as mean inventory level and sold-out rate. Through simulation experiments based on real data we find that the proposed optimized inventory policy reduces inventory level by about 9%, and increases surplus production capacity rate, which is usually used for the production of products in Group C, from 43.4% to 46.3%, compared with the existing inventory policy.