• Journal of The Korean Society of Integrative Medicine
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• v.1 no.4
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• pp.37-47
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• 2013

PURPOSE : Club dance is one of the most popular cultures worldwide and is getting popular in Korea over time. However, club still has negative awareness in the country due to the media spreading only harmful aspects of club culture. At any rate, nowadays many young aged people can easily have chances to experience clubs so we tried to find out the bad effects caused by clubs. METHOD : We conducted a survey and the number of participants who agreed to participate in this survey was 500, including both men and women. There are a total of 50 questions in the questionnaire form used by this study and the questions were divided into three categories: general(18), psychologic-related(7), social-cultural(9), and physical-related(16) questions. Data collected for this study was analyzed via frequency analysis using SPSS. RESULT : In our survey, most students who had already experienced the club culture tend to go to club once or twice a month, and they answered that they would feel bored if they were nor able to do so. In terms of social life, most respondents said that they had lower efficiency in working and studying the next day after going to clubs because of fatigue. In physical aspect, club users use then pelvis and lower back a lot while dancing. The respondents answered that they experienced muscle soreness, a loss in weight, and changes in their body as a consequence of intense dancing. They complaint pain mostly in lower limbs, so we could find out the fact that legs were primarily used for the club dance. CONCLUSION : To sum up, the club culture in undergraduate students affects on their daily living and body, and also has good effects as well as bad ones. Therefore, we need to look at the club culture positively and to improve bad effects of club culture.

• Journal of Broadcast Engineering
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• v.22 no.3
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• pp.282-294
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• 2017

In this paper, we propose a novel intelligent headlight control (IHC) system which is durable to various road lights and camera movement caused by vehicle driving. For detecting candidate light blobs, the region of interest (ROI) is decided as front ROI (FROI) and back ROI (BROI) by considering the camera geometry based on perspective range estimation model. Then, light blobs such as headlights, taillights of vehicles, reflection light as well as the surrounding road lighting are segmented using two different adaptive thresholding. From the number of segmented blobs, taillights are first detected using the redness checking and random forest classifier based on Haar-like feature. For the headlight and taillight classification, we use the random forest instead of popular support vector machine or convolutional neural networks for supporting fast learning and testing in real-life applications. Pairing is performed by using the predefined geometric rules, such as vertical coordinate similarity and association check between blobs. The proposed algorithm was successfully applied to various driving sequences in night-time, and the results show that the performance of the proposed algorithms is better than that of recent related works.

• Journal of the Korea Society of Computer and Information
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• v.17 no.3
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• pp.51-57
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• 2012

Hepatic vessel tree is the key structure for hepatic disease diagnosis and liver surgery planning. Especially, it is used to evaluate the donors' and recipients' liver for the LDLT(Living Donors Liver Transplantation) and estimate the volumes of left and right hepatic lobes for securing their life in the LDLT. In this study, we propose a method to apply canny edge detection that is not affected by noise to the liver images for automatic segmentation of hepatic vessels tree in contrast abdominal MDCT image. Using histograms and average pixel values of the various liver CT images, optimized parameters of the Canny algorithm are determined. It is more time-efficient to use the common parameters than to change parameters manually according to CT images. Candidates of hepatic vessels are extracted by threshold filtering around the detected the vessel edge. Finally, using a system which detects the true-negatives and the false-positives in horizontal and vertical direction, the true-negatives are added in candidate of hepatic vessels and the false-positives are removed. As a result of the process, the various hepatic vessel trees of patients are accurately reconstructed in 3D.

• Proceedings of the Ginseng society Conference
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• 2004.05a
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• pp.17-28
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• 2004

As Korean ginseng is hybrid, an individual variation is very severe, and it takes long times in new breeding because it is required 4 years to pick the seed. But, transformation technique makes the high-functional breeding in short time. The focus of these ginseng studies is to find and secure the useful gene. And it is urgent to accumulate the fundamental data for the molecular breeding and secure the useful genes. Therefore, transformation and soil acclimatization technique are necessary to molecular breeding in use of the introduction of functional genes. In this study, it add to secure of new regulation gene and useful gene as to accumulate the fundamental data for the place where it will contribute to raise the national competitive power. To analyze the useful genes in large scale, we constructed CDNA libraries with various tissues, species, and treated tissue. EST analysis of ginseng perform in large scale and build the EST database of ginseng. We perform the full length sequencing about the selected lots of clones that include the entire open reading frame of the amino acid residues and construct cDNA chip with the parental EST clones. Establishment of the transformation and a soil acclimatization system throuth the re-introduction of the selected ginseng gene that related with the secondary metabolism and anti-stress into the ginseng.

• Journal of Korea Society of Industrial Information Systems
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• v.12 no.4
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• pp.138-147
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• 2007

Metabolic pathway is a series of chemical reactions occuning within a cell and can be used for drug development and understanding of life phenomenon. Many biologists are trying to extract metabolic pathway information from huge literatures for their metabolic-circuit regulation study. We propose a text-mining technique based on the keyword and pattern. Proposed technique utilizes a web robot to collect huge papers and stores them into a local database. We use gene ontology to increase compound recognition rate and NCBI Tokenizer library to recognize useful information without compound destruction. Furthermore, we obtain useful sentence patterns representing metabolic pathway from papers and KEGG database. We have extracted 66 patterns in 20,000 documents for Glycosphingolipid species from KEGG, a representative metabolic database. We verify our system for nineteen compounds in Glycosphingolipid species. The result shows that the recall is 95.1%, the precision 96.3%, and the processing time 15 seconds. Proposed text mining system is expected to be used for metabolic pathway reconstruction.

• The Korean Journal of Pesticide Science
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• v.15 no.4
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• pp.434-440
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• 2011

In order to establish the guidance of management and safe use hazard substance, trend analysis of hazard substance in/on agricultural products reported by press for 5 years (2005-2009) was performed. Data for the analysis collected from the articles about hazard substances from web portals, newspapers and so on. The mostly detected harmful factors in/on agricultural products were pesticides residue and heavy metals by the reports by press for last 5 years. The number of detected pesticides was slightly increased from 14 to 34 through the passage of time but the number of cases reported by press was not increased. On the other hand, the number of accidents and reports related to heavy metals were highly increased from 3 to 13 and 42 to 112, respectively. 65 pesticides including chlorpyrifos were detected in domestic agricultural products for the 5 years. Frequently detected pesticides were chlorpyrifos, endosulfan, carbendazim, azoxystrobin, and procymidone. Pesticide residues were repeatedly detected on green vegetables such as a green perilla leaf, a lettuce, a leek, and spinach among crops.

• The Journal of the Convergence on Culture Technology
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• v.6 no.2
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• pp.561-566
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• 2020

We propose to design and to implement a recreational and end - of - play robot for symptom relief in patients with depression. The main symptom of depression is the loss of interest and interest in life. The depression diagnosis patient confirms the emotional analysis revealed by his / her robot through the robot, and performs the greeting or ending play. After analyzing the emotions in the expressions after the play, the function of the embodying robot is confirmed by receiving the report. A simple play can not completely cure a patient with a diagnosis of depression, but it can contribute to symptom relief through gradual use. The design of the play-by-play robot is using Q.bo One, an open-source robot that can interact with Thecorpora. Q.bo One's system captures a user's face, takes a picture, passes the value to the Azure server, and checks the emotional analysis before and after the play with the accumulated data.Play is implemented in Rasubian, the OS of Q.bo One, using the programming language Python and interacting with external sensors. The purpose of this paper is to help the symptom relief of depressive patients in a relatively short time with a play robot.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.11
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• pp.206-216
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• 2013

The emotion plays a critical role in human's daily life including learning, action, decision and communication. In this paper, emotion discrimination classifier is designed to reduce system complexity through reduced selection of dominant features from biosignals. The photoplethysmography(PPG), skin temperature, skin conductance, fontal and parietal electroencephalography(EEG) signals were measured during 4 types of movie watching associated with the induction of neutral, sad, fear joy emotions. The genetic algorithm with support vector machine(SVM) based fitness function was designed to determine dominant features among 24 parameters extracted from measured biosignals. It shows maximum classification accuracy of 96.4%, which is 17% higher than that of SVM alone. The minimum error features selected are the mean and NN50 of heart rate variability from PPG signal, the mean of PPG induced pulse transit time, the mean of skin resistance, and ${\delta}$ and ${\beta}$ frequency band powers of parietal EEG. The combination of parietal EEG, PPG, and skin resistance is recommendable in high accuracy instrumentation, while the combinational use of PPG and skin conductance(79% accuracy) is affordable in simplified instrumentation.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1353-1366
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• 2015

These days Shewhart control chart for evaluating stability of the process is widely used in various field. But it must follow strict assumption of distribution. In real-life problems, this assumption is often violated when many quality characteristics follow non-normal distribution. Moreover, it is more serious in multivariate quality characteristics. To overcome this problem, many researchers have studied the non-parametric control charts. Recently, SVDD (Support Vector Data Description) control chart based on RBF (Radial Basis Function) Kernel, which is called K-chart, determines description of data region on in-control process and is used in various field. But it is important to select kernel parameter or etc. in order to apply the K-chart and they must be predetermined. For this, many researchers use grid search for optimizing parameters. But it has some problems such as selecting search range, calculating cost and time, etc. In this paper, we research the efficiency of selecting parameter regions as data structure vary via simulation study and propose a new method for determining parameters so that it can be easily used and discuss a robust choice of parameters for various data structures. In addition, we apply it on the real example and evaluate its performance.

• Journal of the Korean Society of Food Science and Nutrition
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• v.38 no.3
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• pp.287-291
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• 2009

In order to use Corni fructus as functional food materials, we investigated the biological activities of ethanol extracts from Corni fructus (EECF). The hydrogen-donating activity of EECF was increased in a dose dependent manner compared with untreated control, and the activities by EECF were 64 and 74% at 300 and $500{\mu}g/mL$ concentration, respectively. The NO productions in the RAW264.7 marcrophage cells treated with EECF were increased in dose dependent manners. EECF significantly inhibited the growth of MCF-7 human breast cancer cells in dose and time dependent manners. EECF of $500{\mu}g/mL$ concentration inhibited the proliferation by over 60% in the MCF-7 cells when treated for 72 hr. Also, the proliferations were increased in the MCF-7 cells cultured in the charcoal-treated FBS (cFBS) medium with environmental hormones such as bisphenol or $17{\beta}$-estradiol of $0.1{\mu}M$ whereas the proliferations were decreased in the MCF-7 cells treated with the environmental hormones after treatment of EEFC for 72 hr. The results suggest that Corni fructus would be used as functional food materials.