• The Journal of Korean Physical Therapy
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• v.22 no.6
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• pp.77-83
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• 2010

Purpose: The aim of this study was to do numerical analysis of the wavelength dependence in low level laser therapy (LLLT) using a finite element method (FEM). Methods: Numerical analysis of heat transfer based on a Pennes' bioheat equation was performed to assess the wavelength dependence of effects of LLLT in a single layer and in multilayered tissue that consists of skin, fat and muscle. The three different wavelengths selected, 660 nm, 830 nm and 980 nm, were ones that are frequently used in clinic settings for the therapy of musculoskeletal disorders. Laser parameters were set to the power density of 35.7 W/$cm^2$, a spot diameter of 0.06 cm, and a laser exposure time of 50 seconds for all wavelengths. Results: Temperature changes in tissue based on a heat transfer equation using a finite element method were simulated and were dominantly dependent upon the absorption coefficient of each tissue layer. In the analysis of a single tissue layer, heat generation by fixed laser exposure at each wavelength had a similar pattern for increasing temperature in both skin and fat (980 nm > 660 nm > 830 nm), but in the muscle layer 660nm generated the most heat (660 nm ${\gg}$ 980 nm > 830 nm). The heat generation in multilayered tissue versus penetration depth was shown that the temperature of 660 nm wavelength was higher than those of 830 nm and 980 nm Conclusion: Numerical analysis of heat transfer versus penetration depth using a finite element method showed that the greatest amount of heat generation is seen in multilayered tissue at = 660 nm. Numerical analysis of heat transfer may help lend insight into thermal events occurring inside tissue layers during low level laser therapy.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.2
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• pp.835-838
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• 2016

Background: Lung cancer remains one of the most common cancers in the world, both in terms of new cases (about 13% of total per year) and deaths (nearly one cancer death in five), because of the high case fatality. Errors in lung cancer type or malignant growth determination lead to degraded treatment efficacy, because anticancer strategy depends on tumor morphology. Materials and Methods: We have made an attempt to evaluate effectiveness of machine learning algorithms in the task of lung cancer classification based on gene expression levels. We processed four publicly available data sets. The Dana-Farber Cancer Institute data set contains 203 samples and the task was to classify four cancer types and sound tissue samples. With the University of Michigan data set of 96 samples, the task was to execute a binary classification of adenocarcinoma and non-neoplastic tissues. The University of Toronto data set contains 39 samples and the task was to detect recurrence, while with the Brigham and Women's Hospital data set of 181 samples it was to make a binary classification of malignant pleural mesothelioma and adenocarcinoma. We used the k-nearest neighbor algorithm (k=1, k=5, k=10), naive Bayes classifier with assumption of both a normal distribution of attributes and a distribution through histograms, support vector machine and C4.5 decision tree. Effectiveness of machine learning algorithms was evaluated with the Matthews correlation coefficient. Results: The support vector machine method showed best results among data sets from the Dana-Farber Cancer Institute and Brigham and Women's Hospital. All algorithms with the exception of the C4.5 decision tree showed maximum potential effectiveness in the University of Michigan data set. However, the C4.5 decision tree showed best results for the University of Toronto data set. Conclusions: Machine learning algorithms can be used for lung cancer morphology classification and similar tasks based on gene expression level evaluation.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.8
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• pp.3430-3438
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• 2011

The purpose of this study is to set the Korean mandarine quality standards based on consumer preference survey. Until now the Korean mandarine's quality standards has been based on the fruit size. The Korean mandarine's quality in agricultural cooperative, citrus agricultural cooperative federation, and some agricultural corporation has been selected in accordance with its own brand of quality grade using a non-destruction sorting machine. But, setting the Korean mandarine's quality standards has been based on the convenient and routine method rather than the scientific and objective method, consumer's preference. According to the grade contents, the highest grade brand was required more than sugar $12^{\circ}Bx$ and less than acid 1.0% and the following grade brand was required more than sugar $11^{\circ}Bx$ and less than acid 1.0% uniformally. Thus, in this study, based on the consumers' preference of Korean mandarine, 4-level grades of sugar and 4-level grades of acidity were divided into the total 16-level grades. Based on them, 5-level grades were set.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.7
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• pp.2996-3005
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• 2011

The purpose of this study is to set the Hallabong tangor's quality standards based on consumer preference survey. Until now the Hallabong tangor's quality standards has been based on the fruit size. Hallabong tangor's quality in agricultural cooperative, citrus agricultural cooperative, and some agricultural corporation has been selected in accordance with its own brand of quality grade using a non-destruction sorting machine. But, setting the Hallabong tangor's quality standards has been based on the convenient and routine method rather than the scientific and objective method, consumer's preference. According to the grade contents, more than sugar $13^{\circ}Bx$ and less than acid 1.10% has been used uniformly. Thus, in this study, based on the consumers' preference of Hallabong tangor, 5-level grades of sugar and 7-level grades of acidity were divided into the total 35-level grades. Based on this, 5-level grades were set and were divided into selling product grades(1~3) and non-selling product grades(4~5).

• Journal of the Korean Society of Safety
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• v.35 no.2
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• pp.28-33
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• 2020

Recently, the overseas construction market has been actively promoted for about 10 years, and overseas dam construction has been continuously performed. For the economic and safe construction of the dam, it is important to prepare the main dam construction plan considering the design frequency of the diversion tunnel and the cofferdam. In this respect, the prediction of river level during the rainy season is significant. Since most of the overseas dam construction sites are located in areas with poor infrastructure, the most efficient and economic method to predict the water level in dam construction is to use the upstream water level. In this study, a linear regression model, which is one of the simplest statistical methods, was proposed and examined to predict the downstream level from the upstream level. The Pyeongchang River basin, which has the characteristics of the upper stream (mountain stream), was selected as the target site and the observed water level in Pyeongchang and Panwoon gaging station were used. A regression equation was developed using the water level data set from August 22th to 27th, 2017, and its applicability was tested using the water level data set from August 28th to September 1st, 2018. The dependent variable was selected as the "level difference between two stations," and the independent variable was selected as "the level of water level in Pyeongchang station two hours ago" and the "water level change rate in Pyeongchang station (m/hr)". In addition, the accuracy of the developed equation was checked by using the regression statistics of Root Mean Square Error (RMSE), Adjusted Coefficient of Determination (ACD), and Nach Sutcliffe efficiency Coefficient (NSEC). As a result, the statistical value of the linear regression model was very high, so the downstream water level prediction using the upstream water level was examined in a highly reliable way. In addition, the results of the application of the water level change rate (m/hr) to the regression equation show that although the increase of the statistical value is not large, it is effective to reduce the water level error in the rapid level rise section. Accordingly, this is a significant advantage in estimating the evacuation water level during main dam construction to secure safety in construction site.

• The Korean Journal of Nuclear Medicine Technology
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• v.27 no.1
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• pp.42-46
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• 2023

Purpose The reference range described in Adrenocorticotropic Hormone reagent used in our laboratory is 10-60 pg/mL at 8 a.m. to 10 a.m., and 6-30 pg/mL at 8 p.m. to 10 p.m. However, in the case of outpatients, blood is mainly collected between 10 a.m. and 6 p.m., accounting for 57.8% of the total. Therefore, This study is intended to help make a more accurate diagnosis by reevaluating the reference range provided by the manufacturer of the Adrenocorticotropic Hormone reagent and setting split-timed reference range. Materials and Methods The patients collected blood before 10 a.m. were group A (68 people), and the patients collected blood after 10 a.m. were set to group B (80 people). A T-test was performed between groups to test their significance. And it was confirmed whether it was necessary to set the gender classification as a subgroup. The method of setting the reference range was calculated by the Bayesian's method and the Hoffmann's method. Results The reference range of Group A was 8.6 to 60.6 pg/mL by the Bayesian's method, and the Hoffmann's method was 3.6 to 61.3 pg/mL. The reference range of Group B was 6.9 to 50.5 pg/mL when applying the Bayesian's method, and the Hoffmann method's was 2.3 to 48.9 pg/mL. Conclusion This study was concluded that it was necessary to set the split-timed reference range. Through this study, the later the blood collection time, the lower the level of Adrenocorticotropic Hormone, indicating that blood collection time is important for patients with clinical significance. If a large number of subjects are selected and supplemented in the future, it is believed that systematic and accurate reference range can be set.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.81-87
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• 2012

The current defacing method for keeping an anonymity of brain images damages the integrity of a precise brain analysis due to over removal, although it maintains the patients' privacy. A novel method has been developed to create an anonymous face model while keeping the voxel values of an image exactly the same as that of the original one. The method contains two steps: construction of a mockup brain template from ten normalized brain images and a substitution of the mockup brain to the brain image. A level set segmentation algorithm is applied to segment a scalp-skull apart from the whole brain volume. The segmented mockup brain is coregistered and normalized to the subject brain image to create an anonymous face model. The validity of this modification is tested through comparing the intensity of voxels inside a brain area from the mockup brain with the original brain image. The result shows that the intensity of voxels inside from the mockup brain is same as ones from an original brain image, while its anonymity is guaranteed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.109-117
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• 2022

Most of real-world decision-making processes are used to optimize problems with many objectives of conflicting. Since the betterment of some objectives requires the sacrifice of other objectives, different objectives may not be optimized simultaneously. Consequently, Pareto solution can be considered as candidates of a solution with respect to a multi-objective optimization (MOP). Such problem involves two main procedures: finding Pareto solutions and choosing one solution among them. So-called multi-objective genetic algorithms have been proved to be effective for finding many Pareto solutions. In this study, we suggest a fitness evaluation method based on the achievement level up to the target value to improve the solution search performance by the multi-objective genetic algorithm. Using numerical examples and benchmark problems, we compare the proposed method, which considers the achievement level, with conventional Pareto ranking methods. Based on the comparison, it is verified that the proposed method can generate a highly convergent and diverse solution set. Most of the existing multi-objective genetic algorithms mainly focus on finding solutions, however the ultimate aim of MOP is not to find the entire set of Pareto solutions, but to choose one solution among many obtained solutions. We further propose an interactive decision-making process based on a visualized trade-off analysis that incorporates the satisfaction of the decision maker. The findings of the study will serve as a reference to build a multi-objective decision-making support system.

• Earthquakes and Structures
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• v.24 no.6
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• pp.429-437
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• 2023

This paper studied the prediction of structural damage indices to buildings after earthquake occurrence using Multiple Linear Regression (MLR) and Fuzzy Linear Regression (FLR) methods. Particularly, the structural damage degree, represented by the Maximum Inter Story Drift Ratio (MISDR), is an essential factor that ensures the safety of the building. Thus, the seismic response of a steel building was evaluated, utilizing 65 seismic accelerograms as input signals. Among the several response quantities, the focus is on the MISDR, which expresses the postseismic damage status. Using MLR and FLR methods and comparing the outputs with the corresponding evaluated by nonlinear dynamic analyses, it was concluded that the FLR method had the most accurate prediction results in contrast to the MLR method. A blind prediction applying a set of another 10 artificial accelerograms also examined the model's effectiveness. The results revealed that the use of the FLR method had the smallest average percentage error level for every set of applied accelerograms, and thus it is a suitable modeling tool in earthquake engineering.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.275-281
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• 2007

This paper presents a motion planning strategy for legged robots using locomotion primitives in the complex 3D environments. First, we define configuration, motion primitives and locomotion primitives for legged robots. A hierarchical motion planning method based on a combination of 2.5 dimensional maps of the 3D workspace is proposed. A global navigation map is obtained using 2.5 dimensional maps such as an obstacle height map, a passage map, and a gradient map of obstacles to distinguish obstacles. A high-level path planner finds a global path from a 2D navigation map. A mid-level planner creates sub-goals that help the legged robot efficiently cope with various obstacles using only a small set of locomotion primitives that are useful for stable navigation of the robot. A local obstacle map that describes the edge or border of the obstacles is used to find the sub-goals along the global path. A low-level planner searches for a feasible sequence of locomotion primitives between sub-goals. We use heuristic algorithm in local motion planner. The proposed planning method is verified by both locomotion and soccer experiments on a small biped robot in a cluttered environment. Experiment results show an improvement in motion stability.