• The Korean Journal of Nuclear Medicine Technology
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• v.13 no.1
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• pp.112-115
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• 2009

Purpose: The test had been applied for outpatient by end of 2006, however, it has been included in the medical examination since January 2007, as demand and interests have been gradually increasing in the thyroid gland disease and cancer. thus, we would necessarily evaluate usefulness of the test by comparing the number of patients who are diagnosed as "benignancy" by the medical test with the number of outpatient who attend and are diagnosed as autoimmune thyroid disease among the benign patient, in samsung medical center for a certain period. Materials and Methods: Based on the result for Anti-TPO Antibody test by RIA for the 12,937 patients in samsung medical center from October 2007 to March 2008, for six months, benignancy rate classified by sex and age is measured statistically and number of the patients who are diagnosed as autoimmune thyroid disease are kept tracked on. Results: According to the analysis of the Anti-TPO antibody test 1,135 of 12,937, which is 8.77% are benign and 218 treated patient of them, which is 19.2%, were diagnosed as autoimmune thyroid disease. Conclusions: Based on the statistics, usefulness of the test seem to have co relationship with derivation of autoimmune thyroid disease. this is 19.2% of probability relatively high. this figure, however, does not have strong relationship with specialty of the disease. Thus screening test seems to have somewhat effectiveness, considering other experiments and their margin.

• Korean Journal of Occupational Health Nursing
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• v.6 no.1
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• pp.23-43
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• 1997

The work-related diseases due to continuous overwork are mainly cerebro- and cardio-vascular ones, which is commonly called 'Karoshi', death from overwork. Many factors are capable for Karoshi : occupational stress in relation to technological renovation and industrial rationalization, competitive social structure, and accumulated fatigue accured to long time or irregular working. And its occurence is on the rise. The World Labor Report 1993 released by ILO, pointed out the diseases related to overwork and stress as one of the most important occupational health problem. In Korea, social awareness of Karoshi is at an infant stage, and reliable statistics for its occurence are not compiled in a convenient manner. Despite the rising Karoshi, there are no reliable clauses in workmen's compensation enough to settle down the disputes. Therefore, it is not uncommon that the Labour Ministry and Civil Court find difficulties in reaching an agreement. This study was intended to provide proper compensation and prevention program for workers by suggesting reasonable compensation clauses for the death from overwork. This study consists of two comparative reviews on the compensaton clauses for the death from overwork. One is to review legal standards of Karoshi among three countries, such as Korea, Japan and Taiwan. The other is to investigate the cases of Karoshi in Korea, 121 cases identified at the Labor Welfare Corperation and the Labour Ministrial process of examination and reexamination, and 73 leading cases at the High Court of Justice. The main findings of the study are as follows : 1. Comparisons of comperative review on compensation clauses for the death from overwork among three countries. 1) All of three countries have the same kinds of disease for compensation, which were cerebro-and cardiao-vascular diseases, while for cardiac disease group, Korea has the smaller number of diseases for compensation than Japan. 2) As for the definition of overwork, the three countries share equally that overload for one week prior to collapse is considered as an important factor, but accumulated chronic fatigue is disregarded. 3) As the basis of overwork, in Japan, there is a tendency to move from the conditions of an ordinary healthy adult to those of the individual concerned in Japan, whereas there is no such concern yet in Korea. 4) All the three countries use a common standard of medical judgement in demonstrating causal relationship between a job and a disease. However, Korea is progressive in the sense that in the case of CVA at worksite, the worker himself has no obligation to prove the cause. 2. The results of a comparative review on excutive decisions by Labor Ministry and judicial decisions by the Court in Korea : A judicial decision is based on the legalistic probability, but a excutive decision is not. Therefore, excutive decisions have such restrictions that : 1) TIA (transitory ischemic cerebral attack) and myocarditis are excluded from compensation, and there is little consistency of decision in the case of cause-unknown death. 2) There is a tendency not to compensate for the death from overwork since the work terms such as repeated long-time working, shift work or night-shift work are not considered as overloading. 3) There is a tendency to regard the conditions of a ordinary healthy adult rather than those of the individual concerned(age, existing diseases, health state, etc.) as the comparative basis of overload. 4) There remains a tendency not to compensate for the death from overwork in the case of collapse occuring out of workplace, on the ground of 'on the course of working' and 'in the cause of accident'. Through the study, the fact manifests itself that Korea's compensation clauses for work-related diseases due to overwork are very restrictive. So, it is necessary to extend the Labor Ministry's clauses of compensation for the death from overwork following to the recent changes of other countries and internal judicial decisions. This is very important in the perspective of occupational health that aims at health promotion of workers including prevention of the Karoshi.

• Journal of the Korean Applied Science and Technology
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• v.37 no.3
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• pp.594-603
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• 2020

The aim of this study was to investigate the issue in obese children with a high probability of leading to precocious puberty for they have more advanced skeletal maturation compared to normal children in order to contribute to the health of obese children by identifying the relationship between physique and physical fitness according to their skeletal maturation. A total of 243 obese children between the ages of 10-13 were enrolled as subjects, and the skeletal maturation, which symbolize indicators of biological maturation, were evaluated by using the TW3 method after hand-wrist radiographs, thus classified the skeletal maturation level into retarded group(n=70), normal group(n=128), and advanced group(n=45). A stadiometer and InBody 270 (Biospace, Korea) were used to measure 3 components in physique. A total of 7 components in physical fitness, which included muscular strength, muscular endurance, flexibility, power, cardiovascular endurance, balance, agility, were measured as well. Descriptive statistics and one-way variable analysis (ANOVA) were conducted for data processing using SPSS 25.0, and Duncan's multiple-range method was used for post hoc analysis; and it was considered significant at the level of P< .05. Analysis results of this study may be summarized as follow. First, height and weight in physique factors according to the skeletal maturation between the retarded, normal, and advanced groups in males and females were highly significant. Second, physical fitness comparison according to the skeletal maturation in males were statistically significant in muscular strength, power, and agility whereas muscular strength and balance were statistically significant in females.

• Journal of Intelligence and Information Systems
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• v.25 no.4
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• pp.53-65
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• 2019

Object tracking is one of important steps to achieve video-based surveillance systems. Object tracking is considered as an essential task similar to object detection and recognition. In order to perform object tracking, various machine learning methods (e.g., least-squares, perceptron and support vector machine) can be applied for different designs of tracking systems. In general, generative methods (e.g., principal component analysis) were utilized due to its simplicity and effectiveness. However, the generative methods were only focused on modeling the target object. Due to this limitation, discriminative methods (e.g., binary classification) were adopted to distinguish the target object and the background. Among the machine learning methods for binary classification, total error rate minimization can be used as one of successful machine learning methods for binary classification. The total error rate minimization can achieve a global minimum due to a quadratic approximation to a step function while other methods (e.g., support vector machine) seek local minima using nonlinear functions (e.g., hinge loss function). Due to this quadratic approximation, the total error rate minimization could obtain appropriate properties in solving optimization problems for binary classification. However, this total error rate minimization was based on a batch mode setting. The batch mode setting can be limited to several applications under offline learning. Due to limited computing resources, offline learning could not handle large scale data sets. Compared to offline learning, online learning can update its solution without storing all training samples in learning process. Due to increment of large scale data sets, online learning becomes one of essential properties for various applications. Since object tracking needs to handle data samples in real time, online learning based total error rate minimization methods are necessary to efficiently address object tracking problems. Due to the need of the online learning, an online learning based total error rate minimization method was developed. However, an approximately reweighted technique was developed. Although the approximation technique is utilized, this online version of the total error rate minimization could achieve good performances in biometric applications. However, this method is assumed that the total error rate minimization can be asymptotically achieved when only the number of training samples is infinite. Although there is the assumption to achieve the total error rate minimization, the approximation issue can continuously accumulate learning errors according to increment of training samples. Due to this reason, the approximated online learning solution can then lead a wrong solution. The wrong solution can make significant errors when it is applied to surveillance systems. In this paper, we propose an exactly reweighted technique to recursively update the solution of the total error rate minimization in online learning manner. Compared to the approximately reweighted online total error rate minimization, an exactly reweighted online total error rate minimization is achieved. The proposed exact online learning method based on the total error rate minimization is then applied to object tracking problems. In our object tracking system, particle filtering is adopted. In particle filtering, our observation model is consisted of both generative and discriminative methods to leverage the advantages between generative and discriminative properties. In our experiments, our proposed object tracking system achieves promising performances on 8 public video sequences over competing object tracking systems. The paired t-test is also reported to evaluate its quality of the results. Our proposed online learning method can be extended under the deep learning architecture which can cover the shallow and deep networks. Moreover, online learning methods, that need the exact reweighting process, can use our proposed reweighting technique. In addition to object tracking, the proposed online learning method can be easily applied to object detection and recognition. Therefore, our proposed methods can contribute to online learning community and object tracking, detection and recognition communities.

• 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 Nutrition and Health
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• v.52 no.5
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• pp.449-464
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• 2019

Purpose: North Koreans could be at higher risk for their bone health because of previous periods of severe famine and the continuing low availability of food. This study determined the bone mineral density (BMD) status and its relationship with dietary behaviors and nutrient intake of North Korean refugees (NKR) in South Korea (SK). Methods: This cross-sectional study analyzed 110 female NKR from a NORNS cohort of a non-probability sample of adult NKR in Seoul. BMD examined by DEXA was used to divide participants into the normal group (NG) and the non-normal group (NNG) according to the WHO guideline. A self-administered questionnaire included questions on age, the socioeconomic situation in North Korea (NK) and SK, the food security in NK and SK, and the health behaviors, dietary behaviors, and food frequency questionnaire administered in SK. A one-day 24-hr recall was conducted and the results were analyzed by using CanPro. SPSS was used to analyze whether BMD and related dietary behaviors and nutrient intakes differed according to the groups. Results: NG (62.7%) was significantly younger and had a lower abdominal obesity score than NNG (p < 0.001). While 14.5% of NG reported experiencing menopause, all of NNG reported experiencing menopause. The NG more frequently consumed the dairy group of foods (9.6 times a week) than did the NNG (4.8 times a week) after the statistics were adjusted for age (p < 0.007). The NG consumed significantly more animal protein and animal calcium than did the NNG (p = 0.01, p = 0.009, respectively). Calcium intake was low with 49.3% of NG, and 78.0% of the NNG reported consuming calcium lower than the estimated average requirement. Only calcium showed an index of nutrient quality lower than one in both groups. Conclusion: These results showed that NKR women and possibly all North Korean women are at high risk for bone health and they consumed low levels of bone-related nutrients, and this should be considered for the nutrition policy for NKR and North Korea.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.5
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• pp.53-73
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• 2023

Although it is mandatory to wear a seat belt that can minimize human injury when traffic accident occurs, the number of traffic accident casualties not wearing seat belts still accounts for a significant proportion.The seat belt wearing detection system for all seats is a system that identifies whether all seat passengers wear a seat belt and encourages their usage, also it can be a useful technical countermeasure. Firstly, this study established the viability of system implementation by assessing the factors influencing the severity of injuries in traffic accidents through the development of an ordered probit model. Analysis results showed that the use of seat belts has statistically significant effects on the severity of traffic accidents, reducing the probability of death or serious injury by 0.054 times in the event of a traffic accident. Secondly, a meta-analysis was conducted based on prior research related to seat belts and injuries in traffic accidents to estimate the expected reduction in accident severity upon the implementation of the system.The analysis of the effect of accident severity reduction revealed that wearing seat belts would lead to a 63.3% decrease in fatal accidents, with the front seats showing a reduction of 75.7% and the rear seats showing a reduction of 58.1% in fatal accidents. Lastly, Using the results of the meta-analysis and traffic accident statistics, the expected decrease in the number of traffic accident casualties with the implementation of the system was derived to analyze the traffic safety effects of the proposed detection system. The analysis demonstrated that with an increase in the adoption rate of the system, the number of casualties in accidents where seat belts were not worn decreased. Specifically, at a system adoption rate of 60%, it is anticipated that the number of fatalities would decrease by more than three times compared to the current scenario. Based on the analysis results, operational strategies for the system were proposed to increase seat belt usage rates and reduce accident severity.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.16 no.4
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• pp.223-237
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• 2011

The intermittent freshwater discharge has an critical influence upon the biophysical environments and the ecosystems of the Yeongsan Estuary where the estuary dam altered the continuous mixing of saltwater and freshwater. Though freshwater discharge is controlled by human, the extreme events are mainly driven by the heavy rainfall in the river basin, and provide various impacts, depending on its magnitude and frequency. This research aims to evaluate the magnitude and frequency of extreme freshwater discharges, and to establish the magnitude-frequency relationships between basin-wide rainfall and freshwater inflow. Daily discharge and daily basin-averaged rainfall from Jan 1, 1997 to Aug 31, 2010 were used to determine the relations between discharge and rainfall. Consecutive daily discharges were grouped into independent events using well-defined event-separation algorithm. Partial duration series were extracted to obtain the proper probability distribution function for extreme discharges and corresponding rainfall events. Extreme discharge events over the threshold 133,656,000 $m^3$ count up to 46 for 13.7y years, following the Weibull distribution with k=1.4. The 3-day accumulated rain-falls which occurred one day before peak discharges (1day-before-3day -sum rainfall), are determined as a control variable for discharge, because their magnitude is best correlated with that of the extreme discharge events. The minimum value of the corresponding 1day-before-3day-sum rainfall, 50.98mm is initially set to a threshold for the selection of discharge-inducing rainfall cases. The number of 1day-before-3day-sum rainfall groups after selection, however, exceeds that of the extreme discharge events. The canonical discriminant analysis indicates that water level over target level (-1.35 m EL.) can be useful to divide the 1day-before-3day-sum rainfall groups into discharge-induced and non-discharge ones. It also shows that the newly-set threshold, 104mm, can just separate these two cases without errors. The magnitude-frequency relationships between rainfall and discharge are established with the newly-selected lday-before-3day-sum rainfalls: $D=1.111{\times}10^8+1.677{\times}10^6{\overline{r_{3day}}$, (${\overline{r_{3day}}{\geqq}104$, $R^2=0.459$), $T_d=1.326T^{0.683}_{r3}$, $T_d=0.117{\exp}[0.0155{\overline{r_{3day}}]$, where D is the quantity of discharge, ${\overline{r_{3day}}$ the 1day-before-3day-sum rainfall, $T_{r3}$ and $T_d$, are respectively return periods of 1day-before-3day-sum rainfall and freshwater discharge. These relations provide the framework to evaluate the effect of freshwater discharge on estuarine flow structure, water quality, responses of ecosystems from the perspective of magnitude and frequency.

• Communications of Mathematical Education
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• v.24 no.1
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• pp.235-257
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• 2010

Contemporary belief is that the creative talented can create new knowledge and lead national development, so lots of countries in the world have interest in Gifted Education. As we well know, U.S.A., England, Russia, Germany, Australia, Israel, and Singapore enforce related laws in Gifted Education to offer Gifted Classes, and our government has also created an Improvement Act in January, 2000 and Enforcement Ordinance for Gifted Improvement Act was also announced in April, 2002. Through this initiation Gifted Education can be possible. Enforcement Ordinance was revised in October, 2008. The main purpose of this revision was to expand the opportunity of Gifted Education to students with special education needs. One of these programs is, the opportunity of Gifted Education to be offered to lots of the Gifted by establishing Special Classes at each school. Also, it is important that the quality of Gifted Education should be combined with the expansion of opportunity for the Gifted. Social opinion is that it will be reckless only to expand the opportunity for the Gifted Education, therefore, assessment on the Teaching and Learning Program for the Gifted is indispensible. In this study, 3 middle schools were selected for the Teaching and Learning Programs in mathematics. Each 1st Grade was reviewed and analyzed through comparative tables between Regular and Gifted Education Programs. Also reviewed was the content of what should be taught, and programs were evaluated on assessment standards which were revised and modified from the present teaching and learning programs in mathematics. Below, research issues were set up to assess the formation of content areas and appropriateness for Teaching and Learning Programs for the Gifted in mathematics. A. Is the formation of special class content areas complying with the 7th national curriculum? 1. Which content areas of regular curriculum is applied in this program? 2. Among Enrichment and Selection in Curriculum for the Gifted, which one is applied in this programs? 3. Are the content areas organized and performed properly? B. Are the Programs for the Gifted appropriate? 1. Are the Educational goals of the Programs aligned with that of Gifted Education in mathematics? 2. Does the content of each program reflect characteristics of mathematical Gifted students and express their mathematical talents? 3. Are Teaching and Learning models and methods diverse enough to express their talents? 4. Can the assessment on each program reflect the Learning goals and content, and enhance Gifted students' thinking ability? The conclusions are as follows: First, the best contents to be taught to the mathematical Gifted were found to be the Numeration, Arithmetic, Geometry, Measurement, Probability, Statistics, Letter and Expression. Also, Enrichment area and Selection area within the curriculum for the Gifted were offered in many ways so that their Giftedness could be fully enhanced. Second, the educational goals of Teaching and Learning Programs for the mathematical Gifted students were in accordance with the directions of mathematical education and philosophy. Also, it reflected that their research ability was successful in reaching the educational goals of improving creativity, thinking ability, problem-solving ability, all of which are required in the set curriculum. In order to accomplish the goals, visualization, symbolization, phasing and exploring strategies were used effectively. Many different of lecturing types, cooperative learning, discovery learning were applied to accomplish the Teaching and Learning model goals. For Teaching and Learning activities, various strategies and models were used to express the students' talents. These activities included experiments, exploration, application, estimation, guess, discussion (conjecture and refutation) reconsideration and so on. There were no mention to the students about evaluation and paper exams. While the program activities were being performed, educational goals and assessment methods were reflected, that is, products, performance assessment, and portfolio were mainly used rather than just paper assessment.