• Journal of Life Science
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• v.33 no.6
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• pp.490-497
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• 2023

Pregnant women may need to take medications to treat preexisting diseases or diseases that develop during pregnancy. However, some drugs may be fetotoxic and lead to, for example, teratogenicity and growth retardation. Predicting the fetotoxicity of drugs is thus important for the health of the mother and fetus. The fetotoxicity of many drugs has not been established because various challenges hinder the ability of researchers to determine their fetotoxicity. The need exists for in silico-based fetotoxicity assessment models, as they can modernize the testing paradigm, improve predictability, and reduce the use of animals and the costs of fetotoxicity testing. In this study, we collected data on the fetotoxicity of drugs and constructed fetotoxicity prediction models based on various machine learning algorithms. We optimized the models for more precise predictions by tuning the hyperparameters. We then performed quantitative performance evaluations. The results indicated that the constructed machine learning-based models had high performance (AUROC >0.85, AUPR >0.9) in fetotoxicity prediction. We also analyzed the feature importance of our model's predictions, which could be leveraged to identify the specific features of drugs that are strongly associated with fetotoxicity. The proposed model can be used to prescreen drugs and drug candidates at a lower cost and in less time. It provides a predictive score for fetotoxicity risk, which may be beneficial in the design of studies on fetotoxicity in human pregnancy.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.1
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• pp.31-37
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• 2013

Background: Throughout Indonesia, thyroid cancer is one of the ten commonest malignancies, with papillary thyroid carcinoma (PTC) in our hospital accounting for about 60% of all thyroid nodules. Although fine needle aspiration biopsy (FNAB) is the most reliable diagnostic tool, some nodules are diagnosed as indeterminate and second surgery is common for PTC. The aim of this study was to establish the diagnostic value and feasibility of testing the BRAF T1799A mutation on FNA specimens for improving PTC diagnosis. Materials and Methods: This prospective study enrolled 95 patients with thyroid nodules and future surgery planned. Results of mutational status were compared with surgical pathology diagnosis. Results: Of the 70 cases included in the final analysis, 62.8% were PTC and the prevalence of BRAF mutation was 38.6%. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for BRAF mutation analysis were 36%, 100%, 100% and 48%, respectively. With other data findings, nodules with "onset less than 5 year" and "hard consistency" were proven as diagnostic determinants for BRAF mutation with a probability of 62.5%. This mutation was also a significant risk factor for extra-capsular extension. Conclusions: Molecular analysis of the BRAF T1799A mutation in FNAB specimens has high specificity and positive predictive value for PTC. It could be used in the selective patients with clinical characteristics to facilitate PTC diagnosis and for guidance regarding extent of thyroidectomy.

• Biomedical Science Letters
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• v.28 no.4
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• pp.229-236
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• 2022

To prevent cervical cancer, human papillomavirus (HPV) bivalent and quadrivalent vaccinations are common, but there is a need for a vaccination system based on the high-risk human papillomavirus (HR-HPV) genotype that differs by region. This study aimed to investigate the prevalence of HPV and the distribution of HR-HPV genotypes in 2,014 women who were not vaccinated against HPV. In this study, HPV DNA testing was performed on 2,014 women not vaccinated against HPV and who visited the Busan Obstetrics and Gynecology Department from September 2020 to July 2021. In addition, liquid-based cytology (LBC) test was performed on 493 cases of HR- HPV genotype infection confirmed by HPV DNA test. The prevalence of HPV among women in Busan was positive in 609 (30.2%) out of 2,014 cases. Among the 609 HPV-positive cases, HR-HPV infection accounted for 493 cases (81.0%), which is a high proportion. Of the total 493 HR-HPV infection cases, liquid-based cytology (LBC) was within normal limits (WNL) in 266 cases (54.0%), atypical squamous cells of undetermined significance (ASCUS) in 97 cases (19.7%), low-grade squamous intraepithelial lesion (LGSIL) in 88 cases (17.8%), and high-grade squamous intraepithelial lesion (HGSIL) in 42 cases (8.5%). Single HR-HPV 52 and 16 accounted for the highest and second highest infection rates, respectively. The high infection rate among women aged 18~39 underscores the need for continuous monitoring. In addition, when there were abnormal findings in the cervical epithelium, HPV 52 was the most common, while in the case of HGSIL, HPV 16 was the most common. The HR-HPV genotypes related to cervical cancer should be continuously collected and monitored for use in health policies, including local and national vaccinations.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.10
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• pp.701-708
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• 2022

Since the propellant tank structure of the projectile is mainly subjected to a compressive force, there is a high risk of damage due to buckling. Large and lightweight structures such as propellant tank have a complex manufacturing process. So it requires a non-destructive test method to predict buckling load to use the structure after testing. Many studies have been conducted on Vibration Correlation Technique(VCT), which predicts buckling load using the relationship between compressive load and natural frequency, but it requires a large compressive load to predict the buckling load accurately, and it tends to decrease prediction accuracy with increasing internal pressure in structure. In this paper, we analyzed the causes of the decrease in prediction accuracy when internal pressure increases and proposed a method increasing prediction accuracy under the low compressive load for being usable after testing, through VCT combined testing and FEA result. The prediction value by the proposed method was very consistent with the measured actual buckling load.

• Journal of radiological science and technology
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• v.36 no.1
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• pp.1-10
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• 2013

IEC publications have applied in many countries all over the world such as Europe or Japan and these also have been published as in dustrial standards (KS) and notifications of Korea Food and Drug Administration (KFDA) in Korea. As the general standard of IEC 60601 series for medical electric (ME) equipment was revised as $3^{rd}$ edition in 2005, additional and particular standards have been revised or established newly. Under these circumstances, it is importance for manufacturing and assembling companies or authorized testing companies to understand the trend for revisions of IEC publications. Therefore in this study, the latest version of 3 IEC standards related to medical X-ray equipment : IEC 60601-2-44 for X-ray equipment for computed tomography (CT), IEC 60601-2-45 for mammographic X-ray equipment and IEC 60601-2-54 for X-ray equipment for radiography or radioscopy were covered and analyzed for trends and features accompanied by revision based on IEC 60601-1 $3^{rd}$ Ed. As KFDA notifications in force have referred to the particular standards based on 2nd edition of IEC 60601-1, those revised version of 3 particular standards were compared to KFDA notifications in force. The features of the latest standards applying IEC 60601-1 $3^{rd}$ Ed were shown as following: 1) Requirements for mechanical hazards, especially (motorized) moving parts were emphasized. 2) Indication and recording of patient dose were required. 3) Risk management process was introduced and enabled to monitor potential risks systematically. 4) DR system (digital radiography system) as well as analogue system (film-screen system) was included in the scope. Presently, KFDA will revise the notifications applying the particular standards based on IEC 60601-1 $3^{rd}$ Ed in a few years. Therefore the features of particular standards applying IEC 60601-1 $3^{rd}$ Ed was expected to help manufacturers, assemblers or testing companies of medical electric equipment understand IEC publications or KFDA notifications slated to be published.

• Journal of Intelligence and Information Systems
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• v.26 no.1
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• pp.135-149
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• 2020

Artificial intelligences are changing world. Financial market is also not an exception. Robo-Advisor is actively being developed, making up the weakness of traditional asset allocation methods and replacing the parts that are difficult for the traditional methods. It makes automated investment decisions with artificial intelligence algorithms and is used with various asset allocation models such as mean-variance model, Black-Litterman model and risk parity model. Risk parity model is a typical risk-based asset allocation model which is focused on the volatility of assets. It avoids investment risk structurally. So it has stability in the management of large size fund and it has been widely used in financial field. XGBoost model is a parallel tree-boosting method. It is an optimized gradient boosting model designed to be highly efficient and flexible. It not only makes billions of examples in limited memory environments but is also very fast to learn compared to traditional boosting methods. It is frequently used in various fields of data analysis and has a lot of advantages. So in this study, we propose a new asset allocation model that combines risk parity model and XGBoost machine learning model. This model uses XGBoost to predict the risk of assets and applies the predictive risk to the process of covariance estimation. There are estimated errors between the estimation period and the actual investment period because the optimized asset allocation model estimates the proportion of investments based on historical data. these estimated errors adversely affect the optimized portfolio performance. This study aims to improve the stability and portfolio performance of the model by predicting the volatility of the next investment period and reducing estimated errors of optimized asset allocation model. As a result, it narrows the gap between theory and practice and proposes a more advanced asset allocation model. In this study, we used the Korean stock market price data for a total of 17 years from 2003 to 2019 for the empirical test of the suggested model. The data sets are specifically composed of energy, finance, IT, industrial, material, telecommunication, utility, consumer, health care and staple sectors. We accumulated the value of prediction using moving-window method by 1,000 in-sample and 20 out-of-sample, so we produced a total of 154 rebalancing back-testing results. We analyzed portfolio performance in terms of cumulative rate of return and got a lot of sample data because of long period results. Comparing with traditional risk parity model, this experiment recorded improvements in both cumulative yield and reduction of estimated errors. The total cumulative return is 45.748%, about 5% higher than that of risk parity model and also the estimated errors are reduced in 9 out of 10 industry sectors. The reduction of estimated errors increases stability of the model and makes it easy to apply in practical investment. The results of the experiment showed improvement of portfolio performance by reducing the estimated errors of the optimized asset allocation model. Many financial models and asset allocation models are limited in practical investment because of the most fundamental question of whether the past characteristics of assets will continue into the future in the changing financial market. However, this study not only takes advantage of traditional asset allocation models, but also supplements the limitations of traditional methods and increases stability by predicting the risks of assets with the latest algorithm. There are various studies on parametric estimation methods to reduce the estimated errors in the portfolio optimization. We also suggested a new method to reduce estimated errors in optimized asset allocation model using machine learning. So this study is meaningful in that it proposes an advanced artificial intelligence asset allocation model for the fast-developing financial markets.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.1
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• pp.268-277
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• 2019

Flight test systems should monitor various conditions in real time during flight tests and take safety measures in an emergency. The importance of ensuring test safety increases in more complicated and wider test environments. Also, due to the transition of wartime operational authority, many guided missile systems must be developed simultaneously. Early deployment and budget reduction by shortening the development and T&E periods are also necessary. Consequently, the risk of flight tests under the circumstance of inefficient test resources is increasing. To address this deficiency, a flight test system model using SysML was proposed in this study. The method of designing and verifying the test system is based on the agile shift left testing methodology of advanced T&E labs and utilizing a system reference model in the aerospace field. Through modeling and simulation analysis, early identification and correction of faults resulting from inconsistent test requirements can mitigate the risk of delays during the T&E phase of flight tests. Also, because the flight test system model was constructed using SysML, it can be applied to test various guided missile systems.

• Journal of the Korean Society of Marine Environment & Safety
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• v.24 no.2
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• pp.203-214
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• 2018

Ballast water treated by sodium dichloroisocyanurate (NaDCC) injection method in ballast water management system (BWMS) contains reactive bromine, chlorine species and disinfection by-products (DBPs). In this study, we conducted whole effluent toxicity (WET) testing and ecological risk assessment (ERA) to investigate its ecotoxicological effects on the marine environment. WET testing was carried out for eight marine and fresh water organisms, i.e. diatom, Skeletonema costatum, Navicula pelliculosa, green algae, Dunaliella tertiolecta, Pseudokirchneriella subcapitata, rotifer, Brachionus plicatilis, Brachionus calyciflorus and fish, Cyprinodon variegatus, Pimephales promelas. The WET test revealed that diatom and green algae were the only organisms that showed apparent toxicity to the effluent; it showed no observed effect concentration (NOEC), lowest observable effect concentration (LOEC) and effect concentration of 50 % (EC50) values of 25.0 %, 50.0 % and over 100.0 %, respectively, in seawater conditions. In contrast, rotifer and fish showed no toxicities to the effluent in the all salinity conditions. Meanwhile, chemical analysis revealed that the BWMS effluent contained total of 25 DBPs such as bromate, isocyanuric acid, formaldehyde, chloropicrin, trihalomethanes (THMs), halogenated acetonitriles (HANs) and halogenated acetic acids (HAAs). Based on ERA, the 25 DBPs were not considered to have persistency, bioaccumulation and toxicity (PBT) properties. The ratio of predicted environmental concentration (PEC) to predicted no effect concentration (PNEC) of the all DBPs did not exceed 1.0 for general harbour environments, but isocyanuric acid, tribromomethane, chloropicrin and monochloroacetic acid exceed 1.0 for near ship environments. However, when NOEC (25.0%) of the WET test results where actual effluent was applied, it was concluded that the NaDCC injection method did not have unacceptable ecological risks to the general harbor including near ship environments.

• Korea Trade Review
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• v.43 no.2
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• pp.159-180
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• 2018

The purpose of this study is to contribute to the efficient selection of SMEs' trade settlement system through the empirical analysis of determinants of the payment method of SMEs in Korea. In the previous study, external factors, internal factors, settlement characteristics, transaction goods, transaction amount factors and risk management factors were used. Questionnaires were excluded from analysis, and the number of validated samples collected was 155. To conduct the study, all empirical analyses were verified at the significance level p <.005. Statistical analysis was performed using the SPSSWIN 18.0 program. Analysis results found the payment method used in the company was based on the year of establishment, export items, transaction area, type of transaction, and size of company. Empirical analysis showed that factors influencing the choice of the letter of credit are external factors, internal factors, the risk management factors, and the transaction amounts, etc. Results of this study are as follows: First, the effects of external factors, internal factors, settlement characteristics, and transaction amounts were significant. Hypothesis testing of collections trading methods has not been adopted in all areas presented. In order to utilize the research results, we conducted the study and comparison of the payment method of the income.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.34 no.1
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• pp.77-84
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• 2024

Objectives: Interventions promoting physical exercise and healthy habits in workplaces have been shown to be effective in reducing risk factors for metabolic syndrome. This study was conducted to examine the effects of an individualized conditioning exercise program of IT company office workers with or at higher risk of metabolic syndrome. Methods: A total of 444 IT company office workers with or at higher risk of metabolic syndrome participated in a 3-month conditioning exercise program. Body composition data using bioelectrical impedance analysis and cardiopulmonary data using cardiopulmonary exercise testing from 53 individuals (mean age: 34.8 ± 7.1 years, sex : 21% female, height : 170.4 ± 6.8 cm, weight : 75.2±12.2 kg, body mass index : 25.8±3.3 kg/m²) who have successfully completed pre-test, intervention, and post-test were analyzed. The 12 weeks intervention encompassed: (1) health counseling (2) supervised exercise(endurance-based, aerobic exercise, or circuit training once a week for 50 minutes at heart rate reserve(HRR) of 77-95%) (3) self-directed exercise and biweekly health screening checks. Results: The results indicated a significant decrease in body weight, body fat mass and body mass index, respectively. Moreover, VO₂peak, AT VO₂ and AT Time significantly improved, respectively. Resting blood pressure(SBP/DBP) showed positive changes but were not statistically significant. We observed the correlation between characteristics of participants and rate of changes in cardiopulmonary outcomes of participants, there are no significant correlation. These results indicate positive changes in body composition and cardiorespiratory fitness parameters following individualized conditioning exercise program. Conclusions: Individualized workplace exercise program for preventing metabolic syndrome can lead to improvements in body composition and cardiorespiratory fitness.