• Journal of Life Science
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• v.17 no.2 s.82
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• pp.218-222
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• 2007

The purpose of this study is to evaluate the relationship between high sensitive C-reactive protein (hsCRP) and pulse transit time (PPT). Apparently healthy 233 subjects had been enrolled in the health promotion center of the Pusan National University Hospital from Jan. 29 to Feb. 26, 2004. They had no previous history of diabetes, hypertension and hyperlipidemia. Subjects were categorized according to tertiles of hsCRP level [Group 1: first tertile $(0.01\;{\sim}\;0.02\;mg/dl)$, Group 2: second tertile $(0.03\;{\sim}\;0.05\;mg/dl)$, Group 3: third tertile $(0.06\;{\sim}\;0.12\;mg/dl)$, and Group 4: Fourth tertile $(0.13\;{\sim}\;16.8\;mg/dl)$]. PTT body mass index (BMI), total cholesterol (T-C), LDL-cholesterol(LDL-C), blood sugar (BS), systolic blood pressure (sBP) and diastolic blood pressure (dBP) were significantly different among hsCRP groups (p<0.05). HsCRP is positively related with BMI, tryglyceride (TG), LDL, sBP and dBP (p<0.05), and negatively related with PTT and HDL-cholesterol (HDL-C) (p<0.05). PTT is significantly negatively related with hsCRP, T-C, TG, LDL-C, BS, dBP and sBP (p<0.05). The hsCRP and PTT were related before controlling BMI, T-C, LDL-C, sBP, and dBP, but not related after conkolling. The relationship between hsCRP and PTT depends on cardiovascular disease risk factors.

• Journal of Biomedical Engineering Research
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• v.25 no.1
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• pp.11-19
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• 2004

Stage 1 sleep provides important information regarding interpretation of nocturnal polysomnography, particularly sleep onset. It is a short transition period from wakeful consciousness to sleep. Lack of prominent sleep events characterizing stage 1 sleep is a major obstacle in automatic sleep stage scoring. In this study, we attempted to utilize simultaneous EEC and EOG processing and analyses to detect stage 1 sleep automatically. Relative powers of the alpha waves and the theta waves were calculated from spectral estimation. Either the relative power of alpha waves less than 50％ or the relative power of theta waves more than 23％ was regarded as stage 1 sleep. SEM (slow eye movement) was defined as the duration of both eye movement ranging from 1.5 to 4 seconds and regarded also as stage 1 sleep. If one of these three criteria was met, the epoch was regarded as stage 1 sleep. Results f ere compared to the manual rating results done by two polysomnography experts. Total of 169 epochs was analyzed. Agreement rate for stage 1 sleep between automatic detection and manual scoring was 79.3％ and Cohen's Kappa was 0.586 (p＜0.01). A significant portion (32％) of automatically detected stage 1 sleep included SEM. Generally, digitally-scored sleep s1aging shows the accuracy up to 70％. Considering potential difficulties in stage 1 sleep scoring, the accuracy of 79.3％ in this study seems to be robust enough. Simultaneous analysis of EOG provides differential value to the present study from previous oneswhich mainly depended on EEG analysis. The issue of close relationship between SEM and stage 1 sleep raised by Kinnariet at. remains to be a valid one in this study.

• Korean Journal of Food Science and Technology
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• v.37 no.4
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• pp.636-641
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• 2005

Mulberry leaves, high in dietary fiber and some nutritional materials, are thought to have hypocholesterolemic effect. Therefore, effect of mulberry leaf powder on serum lipid profiles were studied using rats with diet-induced hypercholesterolemia. Male Sprague-Dawley rats were fed AIN-93 diet (control group), and diets containing high-cholesterol and 0% mulberry leaves powder, high-cholesterol and 5% mulberry leaves powder, and high-cholesterol and 10% mulberry leaves powder for 4 weeks. Hypercholesterolemia was induced by adding 1% cholesterol and 0.5% cholic acid to all diets except in control group. Although no differences were observed in food intake and initial body weight among groups, mulberry leaf treatment resulted in significant decreases in food efficiency ratio and body weight gain. Mulberry leaf treatment decreased serum lipid profiles, atherogenic index, cardiac risk factor, low density lipoprotein cholesterol ratio, serum aspartate transaminase, and liver lipid levels. High density lipoprotein cholesterol, total cholesterol, serum HDL-cholesterol, and fecal lipid levels increased, suggesting mulberry leaves could improve hyperlipidemia and liver action, thereby proventing cardiovascular disease.

• Journal of Biomedical Engineering Research
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• v.32 no.2
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• pp.165-176
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• 2011

The femoral nerve innervates the quadriceps muscles and its dermatome supplies anteromedial thigh and medial foot. Paralysis of the quadriceps muscles due to the injury of the femoral nerve results in disability of the knee joint extension and loss of sensory of the thigh. A child could walk independently even though he had injured his femoral nerve severely due to the penetrating wound in the medial thigh. We measured and analyzed his gait performance in order to find the mechanisms that enabled him to walk independently. The child was eleven-year-old boy and he could not extend his knee voluntarily at all during a month after the injury. His gait analysis was performed five times (GA1~GA5) for sixteen months. His temporal-spatial parameters were not significantly different after the GA2 or GA3 test, and significant asymmetry was not observed except the single support time in GA1 results. The Lower limb joint angles in affected side had large differences in GA1 compared with the normal normative patterns. There were little knee joint flexion and extension motion during the stance phase in GA1 The maximum ankle plantar/dorsi flexion angles and the maximum knee extension angles were different from the normal values in the sound side. Asymmetries of the joint angles were analyzed by using the peak values. Significant asymmetries were found in GA1with seven parameters (ankle: peak planter flexion angle in stance phase, range of motion; ROM, knee: peak flexion angles during both stance and swing phase, ROM, hip: peak extension angle, ROM) while only two parameters (maximum hip extension angle and ROM of hip joint) had significant differences in GA5. The mid-stance valleys were not observed in both right and left sides of vertical ground reaction force (GRF) in the GA1, GA2. The loading response peak was far larger than the terminal stance peak of vertical ground reaction curve in the affected side of the GA3, GA4, GA5. The measured joint moment curves of the GA1, GA2, GA3 had large deviations and all of kinetic results had differences with the normal patterns. EMG signals described an absence of the rectus femoris muscle activity in the GA1 and GA2 (affected side). The EMG signals were detected in the GA3 and GA4 but their patterns were not normal yet, then their normal patterns were detected in the GA5. Through these following gait analysis of a child who had selective injuries on the knee extensor muscles, we could verify the actual functions of the knee extensor muscles during gait, and we also could observe his recovery and asymmetry with quantitative data during his rehabilitation.

• Journal of radiological science and technology
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• v.36 no.2
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• pp.123-129
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• 2013

This study investigated the rate of setup variance by the rotating unbalance of gantry in image-guided radiation therapy. The equipments used linear accelerator(Elekta Synergy TM, UK) and a three-dimensional volume imaging mode(3D Volume View) in cone beam computed tomography(CBCT) system. 2D images obtained by rotating $360^{\circ}$and $180^{\circ}$ were reconstructed to 3D image. Catpan503 phantom and homogeneous phantom were used to measure the setup errors. Ball-bearing phantom was used to check the rotation axis of the CBCT. The volume image from CBCT using Catphan503 phantom and homogeneous phantom were analyzed and compared to images from conventional CT in the six dimensional view(X, Y, Z, Roll, Pitch, and Yaw). The variance ratio of setup error were difference in X 0.6 mm, Y 0.5 mm Z 0.5 mm when the gantry rotated $360^{\circ}$ in orthogonal coordinate. whereas rotated $180^{\circ}$, the error measured 0.9 mm, 0.2 mm, 0.3 mm in X, Y, Z respectively. In the rotating coordinates, the more increased the rotating unbalance, the more raised average ratio of setup errors. The resolution of CBCT images showed 2 level of difference in the table recommended. CBCT had a good agreement compared to each recommended values which is the mechanical safety, geometry accuracy and image quality. The rotating unbalance of gentry vary hardly in orthogonal coordinate. However, in rotating coordinate of gantry exceeded the ${\pm}1^{\circ}$ of recommended value. Therefore, when we do sophisticated radiation therapy six dimensional correction is needed.

• Journal of Food Hygiene and Safety
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• v.29 no.1
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• pp.60-66
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• 2014

This test was performed to evaluate the bactericidal efficacy of a fumigation disinfectant containing 20% ortho-phenylphenol against Pseudomonas aeruginosa (P. aeruginosa) and Enterococcus hirae (E. hirae). In preliminary tests, P. aeruginosa and E. hirae working culture suspension number (N value) were $2.8{\times}10^8$ and $4.0{\times}10^8CFU/mL$, respectively. And all the colony numbers on the carriers exposed to the fumigant (n1, n2, n3) were higher than 0.5N1 (the number of bacterial test suspentions by pour plate method), 0.5N2 (the number of bacterial test suspentions by filter membrane method) and 0.5N1, respectively. In addition, the mean number of P. aeruginosa and E. hirae recovered on the control-carriers (T value) was $2.8{\times}10^8$ and $3.4{\times}10^6CFU/mL$, respectively. In the bactericidal effect of the fumigant, the reduction number of $2.8{\times}10^8$ (d value) was 6.46 and 5.19 logCFU/mL, respectively. According to the French standard for the fumigant, the d value for the effective bactericidal fumigant should be over than 5 logCFU/mL. With the results from this study, the fumigation disinfectant containing 20% ortho-phenylphenol has an effective bactericidal activity, then the fumigant can be applied to disinfect food materials and kitchen appliances contaminated with the pathogenic bacteria.

• Journal of the Korean Society of Radiology
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• v.13 no.2
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• pp.175-183
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• 2019

Cerebral nervous system intervention has been reported frequently due to radiation exposure such as blistering of the skin, hair loss, and erythema due to prolonged procedures. By applying ergonomically manufactured Bismuth (atomic number 83; Bi) shield to endovascular treatment of cerebral aneurysms, we aimed to minimize radiation exposure of scalp and lens from medical radiation exposure. The measurement site was the posterior part of the head, bilateral temporal part, bilateral quadriceps part, nose part, and the measuring part was attached to the optically stimulated Luminescence dosimeter (OSLD) Before and after the use, the entrance surface dose was compared and analyzed. The average entrance surface dose of group A (unshield) was 92.44 mGy, and group B was measured at 67.55 mGy. The average decrease in Group B was 26.92% compared to Group A. The entrance surface dose mean of the occipital region was measured at 146.08 mGy B group at 103.23 mGy and decreased by an average of 29.32% in group B compared to group A. The average entrance surface dose of the bilateral temporal part was measured in group A at 101.90 mGy group B at 72.69 mGy and decreased by an average of 28.67% in group B compared to group A. The average entrance surface dose for bilateral quadriceps part was measured at 27.51 mGy group B at 21.39 mGy and averaged 22.26% less in group B than group A. It is believed that the use of bismuth shields will be an alternative to reducing radiation disturbance due to temporary hair loss and other stochastic effects that may occur after the endovascular treatment of cerebral aneurysms procedure.

• Journal of Intelligence and Information Systems
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• v.25 no.3
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• pp.43-62
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• 2019

At one time, the anomaly detection sector dominated the method of determining whether there was an abnormality based on the statistics derived from specific data. This methodology was possible because the dimension of the data was simple in the past, so the classical statistical method could work effectively. However, as the characteristics of data have changed complexly in the era of big data, it has become more difficult to accurately analyze and predict the data that occurs throughout the industry in the conventional way. Therefore, SVM and Decision Tree based supervised learning algorithms were used. However, there is peculiarity that supervised learning based model can only accurately predict the test data, when the number of classes is equal to the number of normal classes and most of the data generated in the industry has unbalanced data class. Therefore, the predicted results are not always valid when supervised learning model is applied. In order to overcome these drawbacks, many studies now use the unsupervised learning-based model that is not influenced by class distribution, such as autoencoder or generative adversarial networks. In this paper, we propose a method to detect anomalies using generative adversarial networks. AnoGAN, introduced in the study of Thomas et al (2017), is a classification model that performs abnormal detection of medical images. It was composed of a Convolution Neural Net and was used in the field of detection. On the other hand, sequencing data abnormality detection using generative adversarial network is a lack of research papers compared to image data. Of course, in Li et al (2018), a study by Li et al (LSTM), a type of recurrent neural network, has proposed a model to classify the abnormities of numerical sequence data, but it has not been used for categorical sequence data, as well as feature matching method applied by salans et al.(2016). So it suggests that there are a number of studies to be tried on in the ideal classification of sequence data through a generative adversarial Network. In order to learn the sequence data, the structure of the generative adversarial networks is composed of LSTM, and the 2 stacked-LSTM of the generator is composed of 32-dim hidden unit layers and 64-dim hidden unit layers. The LSTM of the discriminator consists of 64-dim hidden unit layer were used. In the process of deriving abnormal scores from existing paper of Anomaly Detection for Sequence data, entropy values of probability of actual data are used in the process of deriving abnormal scores. but in this paper, as mentioned earlier, abnormal scores have been derived by using feature matching techniques. In addition, the process of optimizing latent variables was designed with LSTM to improve model performance. The modified form of generative adversarial model was more accurate in all experiments than the autoencoder in terms of precision and was approximately 7% higher in accuracy. In terms of Robustness, Generative adversarial networks also performed better than autoencoder. Because generative adversarial networks can learn data distribution from real categorical sequence data, Unaffected by a single normal data. But autoencoder is not. Result of Robustness test showed that he accuracy of the autocoder was 92%, the accuracy of the hostile neural network was 96%, and in terms of sensitivity, the autocoder was 40% and the hostile neural network was 51%. In this paper, experiments have also been conducted to show how much performance changes due to differences in the optimization structure of potential variables. As a result, the level of 1% was improved in terms of sensitivity. These results suggest that it presented a new perspective on optimizing latent variable that were relatively insignificant.

• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.89-106
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• 2022

Recently, the amount of video data collected from smartphones, CCTVs, black boxes, and high-definition cameras has increased rapidly. According to the increasing video data, the requirements for analysis and utilization are increasing. Due to the lack of skilled manpower to analyze videos in many industries, machine learning and artificial intelligence are actively used to assist manpower. In this situation, the demand for various computer vision technologies such as object detection and tracking, action detection, emotion detection, and Re-ID also increased rapidly. However, the object detection and tracking technology has many difficulties that degrade performance, such as re-appearance after the object's departure from the video recording location, and occlusion. Accordingly, action and emotion detection models based on object detection and tracking models also have difficulties in extracting data for each object. In addition, deep learning architectures consist of various models suffer from performance degradation due to bottlenects and lack of optimization. In this study, we propose an video analysis system consists of YOLOv5 based DeepSORT object tracking model, SlowFast based action recognition model, Torchreid based Re-ID model, and AWS Rekognition which is emotion recognition service. Proposed model uses single-linkage hierarchical clustering based Re-ID and some processing method which maximize hardware throughput. It has higher accuracy than the performance of the re-identification model using simple metrics, near real-time processing performance, and prevents tracking failure due to object departure and re-emergence, occlusion, etc. By continuously linking the action and facial emotion detection results of each object to the same object, it is possible to efficiently analyze videos. The re-identification model extracts a feature vector from the bounding box of object image detected by the object tracking model for each frame, and applies the single-linkage hierarchical clustering from the past frame using the extracted feature vectors to identify the same object that failed to track. Through the above process, it is possible to re-track the same object that has failed to tracking in the case of re-appearance or occlusion after leaving the video location. As a result, action and facial emotion detection results of the newly recognized object due to the tracking fails can be linked to those of the object that appeared in the past. On the other hand, as a way to improve processing performance, we introduce Bounding Box Queue by Object and Feature Queue method that can reduce RAM memory requirements while maximizing GPU memory throughput. Also we introduce the IoF(Intersection over Face) algorithm that allows facial emotion recognized through AWS Rekognition to be linked with object tracking information. The academic significance of this study is that the two-stage re-identification model can have real-time performance even in a high-cost environment that performs action and facial emotion detection according to processing techniques without reducing the accuracy by using simple metrics to achieve real-time performance. The practical implication of this study is that in various industrial fields that require action and facial emotion detection but have many difficulties due to the fails in object tracking can analyze videos effectively through proposed model. Proposed model which has high accuracy of retrace and processing performance can be used in various fields such as intelligent monitoring, observation services and behavioral or psychological analysis services where the integration of tracking information and extracted metadata creates greate industrial and business value. In the future, in order to measure the object tracking performance more precisely, there is a need to conduct an experiment using the MOT Challenge dataset, which is data used by many international conferences. We will investigate the problem that the IoF algorithm cannot solve to develop an additional complementary algorithm. In addition, we plan to conduct additional research to apply this model to various fields' dataset related to intelligent video analysis.

• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.22 no.3
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• pp.182-191
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• 2011

Objectives: The aim of this study was to investigate the sleep patterns of South Korean elementary school children and whether the differences in sleep patterns were related to behavior, emotional problems, attention and academic performance. Method: This study included a community sample of 268 boys and girls from fourth-, fifth- and sixth-grade classes in a South Korean metropolitan city from November to December 2010. The primary caregivers completed a questionnaire that included information on demographic characteristics, as well as the Child's Sleep Habit Questionnaire (CSHQ), the Korean version of Child Behavior Checklist (K-CBCL), the Korean version of the Learning Disability Evaluation Scale (K-LDES), the Korean version of ADHD Rating Scale (K-ARS) and the Disruptive Behavior Disorder Scale (DBDS). We conducted analyses on the CSHQ individual items, between the subscales, on the total scores and on the K-CBCL, the K-LEDS, the K-ARS and the DBDS. Results: Based on the findings from the CHSQ, the subjects had significantly higher scores for bedtime resistance ($9.18{\pm}2.17$), delayed sleep onset ($1.32{\pm}0.62$), the sleep duration ($4.19{\pm}1.52$) and daytime sleepiness ($14.10{\pm}3.55$) than the scores from the previous reports on children from western countries. The total CHSQ score showed positive correlations to all subscales of the K-CBCL : withdrawn (r=0.24, p<.005), somatic complaint (r=0.24, p<.005) and anxious/depressive (r=0.38, p<.005). Bedtime resistance was associated with oppositional defiant disorder (r=0.15, p<.05) and a positive correlation was demonstrated between sleep anxiety and the oppositional defiant disorder score (r=0.13, p<.05), night waking and the conduct disorder score (r=0.16, p<.05). Delayed sleep onset was related with low performance on the K-LDES with respect to thinking (r=-0.17, p<.05) and mathematical calculation (r=-0.17, p<.05). Conclusion: The results of this study reconfirm Korean children's problematic sleep patterns. Taken together the results provide that the reduced sleep duration and disruption of sleep pattern can have a significant impact on emotion, behavior, performance of learning in children. Further studies concerning more diverse psychosocial factors affecting sleep pattern will be helpful to understanding of the sleep health in Korean children.