• Exercise Science
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• v.21 no.2
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• pp.183-190
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• 2012

This study is to evaluate the availability of cardiorespiratory fitness measurement by 20 m shuttle run test based upon energy contribution rates of elite athletes in different sports type. Sixty-seven elite athletes attending K national university participated in this study. They were divided by three groups based upon sports type, composed of Anaerobic Group (sprint, jumps, weightlifting, throw; n=35), Aerobic Group (medium-long distance; n=9), and Combat Sport Group (judo; n=23). 20 m shuttle run test was conducted by Leger et al.(1982) method and calculating acceleration using measured shuttle run repetitions was conducted by Brewer et al.(1988) method. To test the usefulness of VO₂max, graded exercise treadmill test was conducted and standing long jump and 50 m run were measured as power fitness factors. Z-jump was used for measuring power, agility, and muscular endurance. Standing long jump and 50 m run of Anaerobic Group (AnG) was significantly higher than that of Aerobic Group (AeG) and Combat Sport Group (CG) (p<0.05). However, Z-jump of CG was significantly higher than that of AnG and AeG(p<.05). There was a higher correlation of 20 m shuttle run test and VO₂max in AnG(r= 0.577, p<.0001) and CG(r= 0.760, p<.0001). Otherwise, there was a low correlation of 20 m shuttle run test and VO₂max in AeG. There was no significant group difference to test the availability of 20 m shuttle run test and there was a reduced error when converting 20 m shuttle run results into VO₂max. This study examined the usefulness of 20 m shuttle run test by converting 20 m shuttle run repetition results into VO₂max calculation, which showed reduced error. Therefore, this study confirmed that it would be needed to convert 20 m shuttle run results into VO₂max for universal and practical use in the field without dividing sports type.

• Sleep Medicine and Psychophysiology
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• v.6 no.1
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• pp.68-75
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• 1999

Objectives: We intended to observe changes in sleep patterns and mood states of night-shift workers following light exposure. We also estimated the degree of tolerance of light exposure. By studying these, we investigated the possibility of applying light therapy to night-shift workers for improving their adaptation. Methods: Twelve night-shift nurses working at Yong-In Mental Hospital volunteered to participate in this study. The study consisted of 3 parts: 1) night-shift control study; 2) light exposure study; 3) day-shift control study. All the nurses accomplished 3 parts of the study, each of which continued for 3 days, except one nurse who did not participate in day-shift control study. During light exposure study, nurses were exposed to bright light for 4 hours from 1AM to 5AM. Sleep patterns were evaluated with wrist actigraphy and automatic sleep analysis program. Mood states and side effects of light exposure were assessed with self-report scales. Results: Sleep period time, total sleep time, and sleep efficiency were increased following light exposure compared with night-shift control study. Light exposure study showed no difference from day-shift control study in above-mentioned sleep parameters. Daily fluctuation of sleep efficiency was less prominent during light exposure study than during night-shift control study. During light exposure study, the subjects felt more elated and energetic in the evening after daytime sleep than during night-shift control study. None of the subjects complained of severe side effects related to light exposure on the third day of light exposure. Tolerance of side effects was noted to develop with the repetition of light exposure. Conclusion: Light exposure improved the daytime sleep of night-shift workers to the level of normal nighttime sleep, making the subjects more elated and energetic. Side effects of light exposure were found to be tolerable. Light exposure seems to be safely applicable to night-shift workers for their adaptation.

• The Journal of Korean Society for Radiation Therapy
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• v.17 no.1
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• pp.33-40
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• 2005

Purpose : We recently perform the latest radiotheraphy (3D conformal, IMRT,etc.) with the development of 3D CT planning technology. However, in case patients with breast cancer, it is difficult to acquire the CT image with the limitation of CT hole size and tilting of breast immobilization device. The Ewha Breast Device(EBD) was constructed to improve the problem in the treatment of patients with breast cancer and we are intend to introduce the procedure of the EBD construction in this study and compare the EBD with conventional breast device in the view point of usefulness. Materials and Methods : We have constructed the EBD with acryl, analyze the skull size with CT data, consider the skin folder in SCL field and evaluated the EBD usefulness from the view point of set-up reproducibility, dose distribution, skin reaction in comparison with conventional breast device. Results : In the case of patients set-up error analysis, the EBD is superior to conventional device in portal film repetition($\%$) check (80pt.), equal to that in simulation & CT image coincidence check(5pt.). There is no difference between the two systems in dose distribution and skin reaction in SCL field is better the EBD than conventional device. Conclusions : The construction of the EBD enable us to perform the latest radiotheraphy in breast treatments, relieve the pains in simulation, and reduce, the skin reaction. In the future, we expect that modification of the EBD is useful in treating for patients with breast cancer.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.69-94
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• 2017

Recently, increase of demand for big data analysis has been driving the vigorous development of related technologies and tools. In addition, development of IT and increased penetration rate of smart devices are producing a large amount of data. According to this phenomenon, data analysis technology is rapidly becoming popular. Also, attempts to acquire insights through data analysis have been continuously increasing. It means that the big data analysis will be more important in various industries for the foreseeable future. Big data analysis is generally performed by a small number of experts and delivered to each demander of analysis. However, increase of interest about big data analysis arouses activation of computer programming education and development of many programs for data analysis. Accordingly, the entry barriers of big data analysis are gradually lowering and data analysis technology being spread out. As the result, big data analysis is expected to be performed by demanders of analysis themselves. Along with this, interest about various unstructured data is continually increasing. Especially, a lot of attention is focused on using text data. Emergence of new platforms and techniques using the web bring about mass production of text data and active attempt to analyze text data. Furthermore, result of text analysis has been utilized in various fields. Text mining is a concept that embraces various theories and techniques for text analysis. Many text mining techniques are utilized in this field for various research purposes, topic modeling is one of the most widely used and studied. Topic modeling is a technique that extracts the major issues from a lot of documents, identifies the documents that correspond to each issue and provides identified documents as a cluster. It is evaluated as a very useful technique in that reflect the semantic elements of the document. Traditional topic modeling is based on the distribution of key terms across the entire document. Thus, it is essential to analyze the entire document at once to identify topic of each document. This condition causes a long time in analysis process when topic modeling is applied to a lot of documents. In addition, it has a scalability problem that is an exponential increase in the processing time with the increase of analysis objects. This problem is particularly noticeable when the documents are distributed across multiple systems or regions. To overcome these problems, divide and conquer approach can be applied to topic modeling. It means dividing a large number of documents into sub-units and deriving topics through repetition of topic modeling to each unit. This method can be used for topic modeling on a large number of documents with limited system resources, and can improve processing speed of topic modeling. It also can significantly reduce analysis time and cost through ability to analyze documents in each location or place without combining analysis object documents. However, despite many advantages, this method has two major problems. First, the relationship between local topics derived from each unit and global topics derived from entire document is unclear. It means that in each document, local topics can be identified, but global topics cannot be identified. Second, a method for measuring the accuracy of the proposed methodology should be established. That is to say, assuming that global topic is ideal answer, the difference in a local topic on a global topic needs to be measured. By those difficulties, the study in this method is not performed sufficiently, compare with other studies dealing with topic modeling. In this paper, we propose a topic modeling approach to solve the above two problems. First of all, we divide the entire document cluster(Global set) into sub-clusters(Local set), and generate the reduced entire document cluster(RGS, Reduced global set) that consist of delegated documents extracted from each local set. We try to solve the first problem by mapping RGS topics and local topics. Along with this, we verify the accuracy of the proposed methodology by detecting documents, whether to be discerned as the same topic at result of global and local set. Using 24,000 news articles, we conduct experiments to evaluate practical applicability of the proposed methodology. In addition, through additional experiment, we confirmed that the proposed methodology can provide similar results to the entire topic modeling. We also proposed a reasonable method for comparing the result of both methods.