• Clinical and Experimental Pediatrics
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• v.49 no.9
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• pp.946-951
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• 2006

Purpose : The purpose of this study was to demonstrate the effectiveness of combined exercise for 12 weeks on the adiponectin and obesity related variables in overweight and obese children. Methods : Eighteen children in 5th grade in a certain elementary school in Busan were recruited. They were all overweight or obese children(more than 85 percentile in body mass index). Nine children in the experimental group were given exercises consisting of walking and band resistant training for 12 weeks. Auxological data(including height, weight and body fat mass) and laboratory data (fasting blood sugar, insulin, adiponectin) were checked at baseline and at the 1 week, and at the 4 weeks and 12 weeks stages of their exercise program. Insulin resistance and sensitivity were evaluated indirectly using HOMA index and QUICKI index. Results : Adiponectin gradually decreased until the 4 weeks point and gradually increased thereafter to the starting level at the 12 weeks stage. Body weight, body mass index(BMI) and HOMA index significantly decreased more at the 1 week, 4 weeks, and 12 weeks stages in the experimental group than in the control group. Body fat mass significantly decreased at 12 weeks. The change of insulin was significantly correlated with changes of body weight and BMI. But there was no correlation between changes of adiponectin and changes of insulin. Conclusion : Exercise seems to effect the adiponectin concentration. And it might be assumed that exercise increases the adiponectin concentration if it is continued for long time(may be more than 12 weeks). More studies may be necessary to draw that conclusion.

• Clinics in Shoulder and Elbow
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• v.15 no.2
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• pp.79-85
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• 2012

Objective: It has been expected that patient with posttraumatic recurrent anterior shoulder dislocation might have limited daily life activity because of pain and apprehension of dislocation. But there have been only a small number of investigations regarding the rotator strength in this patient. The aim of this study is to find the characteristics about rotator strength of patient with posttraumatic recurrent anterior shoulder dislocation using an isokinetic testing. Method: We enrolled thirteen patients with posttraumatic recurrent anterior shoulder dislocation and fifteen sex, age-matched healthy nonathletic subjects in this controlled study. All participants were male and there were no significant differences between the two groups in age, height, weight, BMI. Isokinetic internal rotator and external rotator strength was evaluated with a Biodex Isokinetic Testing machine (Biodex Medical Systems, Shirley, NY, USA), tests were performed at 60 deg/sec and 180 deg/sec for both sides. Peak torque normalized to body weight, external rotator to internal rotator ratio, total work and fatigue were calculated for each angular velocity. The association between internal rotator and external rotator strength and shoulder instability was analyzed by comparisons with a control group. Results: Any notable differences could not be found between the two groups given all data from no symptomatic left shoulder. There were no significant differences between the two groups statistically in internal rotation strength of right shoulder. However, there has been a tendency that at all angular velocities, external rotator peak torque to body weight, total work and external rotator to internal rotator ratio were significantly lower in the anterior instability group than the control group at all angular velocities. There was no substantial difference between those groups with respect to the fatigue of external rotator and internal rotator in our study. Conclusion: The prominent characteristics of posttraumatic recurrent anterior shoulder dislocation are external rotator weakness and loss of balance with external rotator and internal rotator. Therefore selective training using this information rotator might be helpful in conservative treatment and rehabilitation.

• Journal of Yeungnam Medical Science
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• v.15 no.2
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• pp.341-349
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• 1998

The purpose of this study was to investigate the effects of regular treadmill running on GLUT4 protein of skeletal muscle in STZ-diabetic rats. I used 19 male Sprague-Dawley rats weighing 140 to 160 grams. Rats were randomly assigned into normal, diabetes(DM) and DE(DE) groups. The exercise was loaded with treadmill running for 5 days per week during 4 weeks. All experimental procedures were carried out following overnight fasting 48 hours after last exercise. Gain(gm) in body weight in DM rats(822.4) was lowered compared to normal rats(1092.8), and decreased by exercise. Plasma glucose concentration(mg/dl) in DM rats was 1433.1 which is higher than that of normal group of 1036.4. The concentration of DE group was lower than that of DM rats. Plasma insulin concentration(${\mu}U/ml$) of DM and DE rats was significantly lowerd compared to normal rats. There was no difference of plasma concentrations of FFA and HDL cholesterol among noraml, DM and DE groups. Plasma triglyceride concentration(mg/dl) was significantly highered in DM group compared to those of DM group, the concentration of DE group was lower. Glycogen concentration(mg/gm wet weight) of the plantaris muscle in DM and DE groups was significantly reduced compared to normal group. Glucose transporter 4(GLUT4) protein of soleus was analyzed by Western blot. In DM group, the GLUT4 protein level was markdly decreased compared to normal group, but the level was recovered to the level of normal group by 4 weeks treadmill running. In conclusion, the insulin resistance induced by STZ administration was partially improved by 4 weeks physical training in rats.

• Food Science and Preservation
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• v.14 no.6
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• pp.662-668
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• 2007

Studies have shown that onions exhibit a wide variety of health-promoting properties. The health benefits by the onion have been attributed to its ability to scavenge free radicals, to reduce blood lipids, to lower blood pressure, and to inhibit platelet aggregation. This study was performed to investigate whether onion extract supplementation would affect the blood markers of ethanol-induced fatty liver in rats. Initially, male Sprague-Dawley rats were housed singly in a room of controlled temperature and lighting and had free access to a nutritionally adequate AIN-93G and deionized water. The rats were trained for meal feeding to prevent a decline in food intake, as inevitably observed following an ethanol feeding. After the training period, rats were weight-matched and assigned to the following three groups: 1) a control group, fed the AIN-93G diet alone (control); 2) an ethanol group, fed the AIN-93G diet with ethanol at 4 g/day/kg body weight (ethanol); and 3) an onion group, fed the AIN-93G diet with ethanol plus supplemental freeze-dried onion powder at 500 mg/day/rat (ethanol + onion). All three group were meal-fed 7.0 g of their respective diets at 0900 h and 7.5 g at 1600 h for 28 days. At 0, 2, and 4 wk, blood was collected via the orbital sinus and organs were collected following overnight food deprivation. Both control and experimental groups continually gained weight throughout the study. No significant differences in the weights of the liver, kidneys, heart, spleen, and testis were observed. However, the serum level of triglycerides was significantly increased by ethanol but significantly decreased by onion extract. The activities of serum glutamate oxaloacetate transaminase (GOT), glutamate pyruvate transaminase (GPT) at 4 wk were significantly increased by ethanol feeding but were significantly decreased by onion supplementation. However, no differences among groups were observed in the serum levels of alkaline phosphatase, gamma-glutamyl transpeptidase, bilirubin, and protein. These results provide that onion extract favorably affect alcoholic fatty liver by decreasing the serum concentration of triglyceride and the activities of GOT and GPT.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.29-45
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• 2012

Bond rating is regarded as an important event for measuring financial risk of companies and for determining the investment returns of investors. As a result, it has been a popular research topic for researchers to predict companies' credit ratings by applying statistical and machine learning techniques. The statistical techniques, including multiple regression, multiple discriminant analysis (MDA), logistic models (LOGIT), and probit analysis, have been traditionally used in bond rating. However, one major drawback is that it should be based on strict assumptions. Such strict assumptions include linearity, normality, independence among predictor variables and pre-existing functional forms relating the criterion variablesand the predictor variables. Those strict assumptions of traditional statistics have limited their application to the real world. Machine learning techniques also used in bond rating prediction models include decision trees (DT), neural networks (NN), and Support Vector Machine (SVM). Especially, SVM is recognized as a new and promising classification and regression analysis method. SVM learns a separating hyperplane that can maximize the margin between two categories. SVM is simple enough to be analyzed mathematical, and leads to high performance in practical applications. SVM implements the structuralrisk minimization principle and searches to minimize an upper bound of the generalization error. In addition, the solution of SVM may be a global optimum and thus, overfitting is unlikely to occur with SVM. In addition, SVM does not require too many data sample for training since it builds prediction models by only using some representative sample near the boundaries called support vectors. A number of experimental researches have indicated that SVM has been successfully applied in a variety of pattern recognition fields. However, there are three major drawbacks that can be potential causes for degrading SVM's performance. First, SVM is originally proposed for solving binary-class classification problems. Methods for combining SVMs for multi-class classification such as One-Against-One, One-Against-All have been proposed, but they do not improve the performance in multi-class classification problem as much as SVM for binary-class classification. Second, approximation algorithms (e.g. decomposition methods, sequential minimal optimization algorithm) could be used for effective multi-class computation to reduce computation time, but it could deteriorate classification performance. Third, the difficulty in multi-class prediction problems is in data imbalance problem that can occur when the number of instances in one class greatly outnumbers the number of instances in the other class. Such data sets often cause a default classifier to be built due to skewed boundary and thus the reduction in the classification accuracy of such a classifier. SVM ensemble learning is one of machine learning methods to cope with the above drawbacks. Ensemble learning is a method for improving the performance of classification and prediction algorithms. AdaBoost is one of the widely used ensemble learning techniques. It constructs a composite classifier by sequentially training classifiers while increasing weight on the misclassified observations through iterations. The observations that are incorrectly predicted by previous classifiers are chosen more often than examples that are correctly predicted. Thus Boosting attempts to produce new classifiers that are better able to predict examples for which the current ensemble's performance is poor. In this way, it can reinforce the training of the misclassified observations of the minority class. This paper proposes a multiclass Geometric Mean-based Boosting (MGM-Boost) to resolve multiclass prediction problem. Since MGM-Boost introduces the notion of geometric mean into AdaBoost, it can perform learning process considering the geometric mean-based accuracy and errors of multiclass. This study applies MGM-Boost to the real-world bond rating case for Korean companies to examine the feasibility of MGM-Boost. 10-fold cross validations for threetimes with different random seeds are performed in order to ensure that the comparison among three different classifiers does not happen by chance. For each of 10-fold cross validation, the entire data set is first partitioned into tenequal-sized sets, and then each set is in turn used as the test set while the classifier trains on the other nine sets. That is, cross-validated folds have been tested independently of each algorithm. Through these steps, we have obtained the results for classifiers on each of the 30 experiments. In the comparison of arithmetic mean-based prediction accuracy between individual classifiers, MGM-Boost (52.95%) shows higher prediction accuracy than both AdaBoost (51.69%) and SVM (49.47%). MGM-Boost (28.12%) also shows the higher prediction accuracy than AdaBoost (24.65%) and SVM (15.42%)in terms of geometric mean-based prediction accuracy. T-test is used to examine whether the performance of each classifiers for 30 folds is significantly different. The results indicate that performance of MGM-Boost is significantly different from AdaBoost and SVM classifiers at 1% level. These results mean that MGM-Boost can provide robust and stable solutions to multi-classproblems such as bond rating.

• Journal of the Korean Applied Science and Technology
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• v.37 no.5
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• pp.1190-1199
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• 2020

The purpose of this study is to analyze the variables affecting the effective stroke in the swing performed through 12 weeks of training for golf beginners, and to provide basic data on the effective stroke factors for the golf beginners to settle on the fairway. Twenty subjects were participate in the study (age: 21.35±1.69 yrs, height: 176.75±7.99 cm, weight: 70.70±9.76 kg). All subjects were subjected to a 12-week golf training, and trackman 4 was used in the 12th week to calculate variables affecting the effective stroke during a golf swing. Trackman data was divided into club-variables and ball-variables, and a binary logistic regression analysis was performed to find out the variables affecting effective strokes. In club-variables, high dynamic loft and low face angles were found in effective stroke, and in ball-variables, fast ball speed, large smash factor, high launch angle, and many spin rates were also found in effective stroke. As a result of the binary logistic regression analysis of club-variables, the probability of an effective stroke increased as the club speed and dynamic loft increased, and the probability of an effective stroke decreased as the face angle increased. The influence of effective stroke in the club-variables was in the order of dynamic loft, face angle, and club speed. In the ball-variable, the probability of an effective stroke increased when the lunch angle increased, and the probability of an effective stroke decreased as the lunch direction increased. As a condition to increase the probability of effective stroke based on the results, it is necessary to increase the club speed through high dynamic loft and low face angle during swing through continuous practice. Through this, the probability of effective stroke through increasing the launch angle and decreasing the launch direction will increase.

• Journal of the Korean Society of Food Science and Nutrition
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• v.5 no.1
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• pp.87-92
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• 1976

Comparing the amount of Hb, the nutriture of the deaf-mutes are better than that of the amentias and the nursery school children. The former, however, shows less condition than that of the boys and girls in the junior physical education school (Hb : 12.7) and the normal family children (Hb : 10.8). In the group of six to eleven years old that is a class a elementary school, the physical condition such as stature, chest circumference, and weight of the deaf -mute is respectively almost the same degree, which is above standard in our country. On the contrary the degree of the amentias and the nursery school children has an inferiority approaching to the standard. In the group of twelve to fifteen years old that is a class of junior high school, the nursery school children have the lowest physical condition and the boys and girls of the physical training school the highest. The order of the growth of physical condition is as follows : Nursery school children

• Korean Journal of Environmental Agriculture
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• v.24 no.1
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• pp.66-70
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• 2005

The experiment was carried out to investigate the effects of gamma radiation on the early growth performance and physiological traits of BT2 clone tea, the most promising cultivar released by Bangladesh Tea Research Institute. The fresh shoot cuttings were irradiated with seven different levels of gamma radiation such as 0, 10, 20, 30, 40, 50 and 60 Gy from Cobalt 60Co source (Dept. of PlantBreeding, Bangladesh Institute of Nuclear Agriculture). Thereafter, the irradiated shoot cuttings were planted in polythene bags and kept under natural conditions. It was observed that callusing was initiated from 8th weeks after placement of tea shoot cuttings in the polythene bags and completed by 12th weeks. The morphological growth of tea shoot cuttings were recorded under varying levels of gamma radiation and growth stages. It was observed that the number of leaves, number of primary branches, base diameter, root length and total leaf area per plant significantly increased with the progress of time and increasing levels of gamma radiation, however, the plant height showed decreasing trend with the increasing levels of gamma radiation, which could be due to the change in chromosomal structure and genetic makeup. After 56 weeks of planting, the plant height, the number of leaves and primary branches per plant, base diameter, root length and total leaf area per plant recorded were 65.70 cm, 30.67, 7.33, 1.48 cm, 23.50 cm, and 1250.67 cm2 per plant respectively under the radiation level 60 Gy, whereas the corresponding figures of the above parameters at the control treatment were 76.21 cm, 18.33, 3.67, 0.92 cm, 17.75 cm and 778.33 cm2 per plant, respectively. A significant relationship was observed among the physiological growth parameters with the increasing levels of gamma radiation. The total dry matter gain, leaf area index, absolute growth rate and relative growth rate were significantly influenced with the rising levels of gamma radiation (up to 60 Gy), whereas the net assimilation rate of individual tea plant non-significantly responded as compared to those of control treatment. Finally after 56 weeks of planting, the maximum total dry weight gain, leaf area index, absolute growth rate, relative growth rate and net assimilation rate recorded under 60 Gay radiation level were 40.25 g/plant/week, 4.25, 1.18 g/week, 0.0621g/g/week and 17.07 g/m2/week respectively.

• The Transactions of the Korea Information Processing Society
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• v.1 no.2
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• pp.225-236
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• 1994

Many research result conducted by neural network researchers claimed that the degree of generalization of the neural network system is higher or at least equal to that of statistical methods. However, those successful results could be brought only if the neural network was trained by appropriately sound data, having a little of noisy data and being large enough to control noisy data. Real data used in a lot of fields, especially business fields, were not so sound that the network have frequently failed to obtain satisfactory prediction accuracy, the degree of generalization. Enhancing the degree of generalization with noisy data is discussed in this study. The suggestion, which was obtained through a series of experiments, to enhance the degree of generalization is to remove inconsistent data by checking overlapping and inconsistencies. Furthermore, the previous conclusion by other reports is also confirmed that the learning mechanism of neural network takes average value of two inconsistent data included in training set［2］. The interim results of on-going research project are reported in this paper These are ann architecture of the neural network adopted in this project and the whole idea of developing on-line credit evaluation system,being intergration of the expert(resoning)system and the neural network(learning system.Another definite result is corroborated through this study that quickprop,being agopted as a learing algorithm, also has more speedy learning process than does back propagation even in very noisy environment.

• Journal of the Korean Society of Marine Environment & Safety
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• v.19 no.4
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• pp.375-381
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• 2013

To assess the risk of marine traffic environments, with high confidential level, the risk factors comprising it should be identified and the risk acceptance criteria should be also provided. Furthermore, the relative importance of each risk factor(the weight of each risk factor on total risk) should be analyzed because the risk is expressed as the sum of risk factors comprising it. The twenty kinds of risk factors and its assessment criteria were suggested for the domestic marine traffic environments by an examination of the existing risk assessment models on the previous studies. The relative importance of each risk factor was also analyzed through the questionnaire using analytic hierarchy process by the marine traffic experts on the same studies. Based on these previous studies, the risk was evaluated at the port of Mokpo and its approaches on this study. The port of Mokpo and its approaches were divided into four sectors for the comparative evaluation, the result of the comparative evaluation on four sectors showed that the risk of the Jeongdeung-hae passage is the highest due to higher risk level of some risk factors(water movements, complexities, tug boats, pilotage, VTS) than the other sectors. The result of this evaluation is in accord with the analysis results of the other studies using various qualitative or quantitative risk analysis methods at the same sea areas.