• Clinical and Experimental Pediatrics
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• v.65 no.2
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• pp.85-89
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• 2022

Background: There is evidence of a relationship between prenatal excess androgen exposure and central nervous developmental problems and attention-deficit/hyperactivity disorder (ADHD) in the offspring of mothers with polycystic ovary syndrome (PCOS). Purpose: Here we aimed to use a meta-analysis to investigate whether the offspring of mothers with PCOS are at an increased chance of developing ADHD. Methods: Three main English databases were searched for articles published through December 2020. The Newcastle-Ottawa Scale was used to assess study quality. Study heterogeneity was determined using I² statistics and publication bias was assessed using Begg and Egger tests. The results are presented as odds ratio (OR) and relative ratio (RR) estimates with 95% confidence intervals (CIs) using a random-effects model. Results: Six articles (3 cohort and 3 case-control studies; 401,413 total ADHD cases) met the study criteria. Maternal PCOS was associated with an increased risk of ADHD in the offspring based on OR and RR (OR, 1.42; 95% CI, 1.27-1.57) and (RR, 1.43; 95% CI, 1.35-1.51), respectively. There was no heterogeneity among the included articles based on OR (I²=0.0%, P=0.588) and RR (I²=0.0%, P=0.878). Conclusion: Our study showed that maternal PCOS is a risk factor for ADHD. Therefore, screening their offspring for ADHD should be considered part of the comprehensive clinical care of women with PCOS.

• Journal of Advanced Navigation Technology
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• v.27 no.4
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• pp.365-373
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• 2023

Unmanned aerial vehicles are widely used in various fields, and real-time path replanning is a critical factor in enhancing the safety and efficiency of these devices. In this paper, we propose a real-time path replanning technique based on RRT* and LOSPO. The proposed technique first generates an initial path using the RRT* algorithm and then optimizes the path using LOSPO. Additionally, the optimized path can be converted into a trajectory that considers actual time and the dynamic limits of the aircraft. In this process, environmental changes and collision risks are detected in real-time, and the path is replanned as needed to maintain safe operation. This method has been verified through simulation-based experiments. The results of this paper make a significant contribution to the research on real-time path replanning for UAVs, and by applying this technique to various situations, the safety and efficiency of UAVs can be improved.

• Journal of Korean Neurosurgical Society
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• v.66 no.5
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• pp.525-535
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• 2023

Objective : We performed an expanded multi-ethnic meta-analysis to identify associations between inflammation-related loci with intracranial aneurysm (IA) susceptibility. This meta-analysis possesses increased statistical power as it is based on the most data ever evaluated. Methods : We searched and reviewed relevant literature through electronic search engines up to August 2022. Overall estimates were calculated under the fixed- or random-effect models using pooled odds ratio (OR) and 95% confidence intervals (CIs). Subgroup analyses were performed according to ethnicity. Results : Our meta-analysis enrolled 15 studies and involved 3070 patients and 5528 controls including European, Asian, Hispanic, and mixed ethnic populations. Of 17 inflammation-related variants, the rs1800796 locus (interleukin [IL]-6) showed the most significant genome-wide association with IA in East-Asian populations, including 1276 IA patients and 1322 controls (OR, 0.65; 95% CI, 0.56-0.75; p=3.24#x00D7;10^-9) under a fixed-effect model. However, this association was not observed in the European population (OR, 1.09; 95% CI, 0.80-1.47; p=0.5929). Three other variants, rs16944 (IL-1β), rs2195940 (IL-12B), and rs1800629 (tumor necrosis factor-α) showed a statistically nominal association with IA in both the overall, as well as East-Asian populations (0.01<p<0.05). Conclusion : Our updated meta-analysis with increased statistical power highlights that rs1800796 which maps on the IL-6 gene is associated with IA, and in particular confers a protective effect against occurrence of IA in the East-Asian population.

• The korean journal of orthodontics
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• v.53 no.5
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• pp.328-335
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• 2023

Objective: The aim of this study was to determine whether an association between study quality, other study characteristics, and Altmetric Attention Scores (AASs) existed in orthodontic studies. Methods: The Scopus database was searched to identify orthodontic studies published between January 1, 2017, and December 31, 2019. Articles that satisfied the eligibility criteria were included in this study. Study characteristics, including study quality were extracted and entered into a pre-pilot data collection sheet. Descriptive statistics were calculated. On an exploratory basis, random forest and gradient boosting machine learning algorithms were used to examine the influence of article characteristics on AAS. Results: In total, 586 studies with an AAS were analyzed. Overall, the mean AAS of the samples was 5. Twitter was the most popular social media platform for publicizing studies, accounting for 53.7%. In terms of study quality, only 19.1% of the studies were rated as having a high level of quality, with 41.8% of the studies deemed moderate quality. The type of social media platform, number of citations, impact factor, and study type were among the most influential characteristics of AAS in both models. In contrast, study quality was one of the least influential characteristics on the AAS. Conclusions: Social media platforms contributed the most to the AAS for orthodontic studies, whereas study quality had little impact on the AAS.

• Journal of the Korea Society of Computer and Information
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• v.14 no.7
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• pp.73-80
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• 2009

Internet accidents have skyrocketed every year. It always has been threatened by the methods such as hacking and Spyware. The majority of security accident is formed of the loss of authentication information, and the internal user who is not authorized. The importance of security is also emphasized when someone tries to do something accessing to the main information system. Accordingly, Biometrics has been used in many ways. OTP, however, must have a few devices accessing to several systems, and Biometrics involve some risk of mis-recognition rate and mis-denial rate. It also has the risk possible to access to the main information system when losing OTP. This research reduced risks about the loss as separating RFID leader for mobile, Tag and the accessor's cellular phone, and is about pseudo random validation key generated from the administration system through contact with RFID leader for mobile and Tag. As sending the key to user's cell phone which is already registered, security is strengthened more than existing connection methods through the ID and password. RFID for mobile not generalized to the present has been studied as a tool accessing to the main information system.

• Journal of Korean Society on Water Environment
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• v.38 no.6
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• pp.292-305
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• 2022

The Yeongsan River, one of the four largest rivers in South Korea, has been facing difficulties with water quality management with respect to algal bloom. The algal bloom menace has become bigger, especially after the construction of two weirs in the mainstream of the Yeongsan River. Therefore, the prediction and factor analysis of Chlorophyll-a (Chl-a) concentration is needed for effective water quality management. In this study, Chl-a prediction model was developed, and the performance evaluated using machine and deep learning methods, such as Deep Neural Network (DNN), Random Forest (RF), and eXtreme Gradient Boosting (XGBoost). Moreover, the correlation analysis and the feature importance results were compared to identify the major factors affecting the concentration of Chl-a. All models showed high prediction performance with an R² value of 0.9 or higher. In particular, XGBoost showed the highest prediction accuracy of 0.95 in the test data.The results of feature importance suggested that Ammonia (NH₃-N) and Phosphate (PO₄-P) were common major factors for the three models to manage Chl-a concentration. From the results, it was confirmed that three machine learning methods, DNN, RF, and XGBoost are powerful methods for predicting water quality parameters. Also, the comparison between feature importance and correlation analysis would present a more accurate assessment of the important major factors.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.450-450
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• 2021

기후변화 보고서에 따르면 집중 호우의 강도 및 빈도 증가가 향후 몇 년동안 지속될 것이라 제시하였다. 이러한 집중호우가 빈번히 발생하게 된다면 강우 침식성이 증가하여 표토 침식에 더 취약하게 발생된다. Universal Soil Loss Equation (USLE) 입력 매개 변수 중 하나인 강우침식능인자는 토양 유실을 예측할때 강우 강도의 미치는 영향을 제시하는 인자이다. 선행 연구에서 USLE 방법을 사용하여 강우침식능인자를 산정하였지만, 60분 단위 강우자료를 이용하였기 때문에 정확한 30분 최대 강우강도 산정을 고려하지 못하는 한계점이 있다. 본 연구의 목적은 강우침식능인자를 이전의 진행된 방법보다 더 빠르고 정확하게 예측하는 머신러닝 모델을 개발하며, 총 월별 강우량, 최대 일 강우량 및 최대 시간별 강우량 데이터만 있어도 산정이 가능하도록 하였다. 이를 위해 본 연구에서는 강우침식능인자의 산정 값의 정확도를 높이기 위해 1분 간격 강우 데이터를 사용하며, 최근 강우 패턴을 반영하기 위해서 2013-2019년 자료로 이용했다. 우선, 월별 특성을 파악하기 위해 USLE 계산 방법을 사용하여 월별 강우침식능인자를 산정하였고, 국내 50개 지점을 대상으로 계산된 월별 강우침식능인자를 실측 값으로 정하여, 머신러닝 모델을 통하여 강우침식능인자 예측하도록 학습시켜 분석하였다. 이 연구에 사용된 머신러닝 모델들은 Decision Tree, Random Forest, K-Nearest Neighbors, Gradient Boosting, eXtreme Gradient Boost 및 Deep Neural Network을 이용하였다. 또한, 교차 검증을 통해서 모델 중 Deep Neural Network이 강우침식능인자 예측 정확도가 가장 높게 산정하였다. Deep Neural Network은 Nash-Sutcliffe Efficiency (NSE) 와 Coefficient of determination (R²)의 결과값이 0.87로서 모델의 예측성을 입증하였으며, 검증 모델을 테스트 하기 위해 국내 6개 지점을 무작위로 선별하여 강우침식능인자를 분석하였다. 본 연구 결과에서 나온 Deep Neural Network을 이용하면, 훨씬 적은 노력과 시간으로 원하는 지점에서 월별 강우침식능인자를 예측할 수 있으며, 한국 강우 패턴을 효율적으로 분석 할 수 있을 것이라 판단된다. 이를 통해 향후 토양 침식 위험을 지표화하는 것뿐만 아니라 토양 보전 계획을 수립할 수 있으며, 위험 지역을 우선적으로 선별하고 제시하는데 유용하게 사용 될 것이라 사료된다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3A
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• pp.539-546
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• 2006

The reliability analysis of simply-supported composite plate girder and box girder bridges under positive flexure is performed. The bridges are designed based on the AASHTO-LRFD specification. A performance function for flexural failure is expressed as a function of such random variables as flexural resistance of composite section and design moments due to permanent load and live load. For the flexural resistance, the statistical parameters obtained by analyzing over 16,000 samples of domestic structural steel products are used. Several different values of statistical parameters with the bias factor in the range of 0.95-1.05 and the coefficient of variation in the range of 0.15-0.25 are used for the live-load moment. Due to the lack of available domestic measured data on the dead load moment, the same values of statistical properties used in the calibration of AASHTO-LRFD are applied. The reliability indices for the composite plate girder and box girder bridges with various span lengths are calculated by applying the Rackwitz-Fiessler technique.

• Korea Trade Review
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• v.48 no.3
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• pp.199-216
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• 2023

Rapidly growing cross-border e-commerce exhibits different characteristics from traditional trade. This paper empirically investigates influencing factors of CBEC trade between Korea and foreign countries including product characteristics, such as product type and unit price. We construct panel data based on Korea's e-commerce export data by country and product and analyze it by the OLS, fixed effect, and random effect estimation. Our main findings can be summarized as follows: geographical distance still remained as an obstacle to the CBEC trade, product unit price, and durable consumer goods dummy variables positively affect e-commerce export of Korea, and capital goods dummy variables negatively affect e-commerce export. This research can help us understand the characteristics of cross-border e-commerce and can be used as a basis for future research using product-specific data.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.223-232
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• 2023

The purpose of this study is to determine the impact of social network sports community consciousness on loyalty and sports attitude. In order to achieve this research purpose, the population of the study was selected as adult men and women over the age of 20 who are active in the social network sports community in 2022. The sampling method used cluster random sampling to select a total of 300 people, 150 men and 150 women, as research subjects. The survey tool used was the questionnaire method, and the questionnaire whose reliability and validity had been verified in previous studies at home and abroad was used by requoting, modifying, or supplementing it to suit the purpose of this study. It was also structured on a 5-point scale. Frequency analysis, factor analysis, reliability analysis, simple regression analysis, and multiple regression analysis were performed on the collected data using the statistical program SPSS Windows 20.0 Version. The results obtained through this process are as follows. First, social network sports community consciousness was found to have a partial effect on loyalty. Second, social network sports community consciousness was found to have a partial effect on sports attitudes. Third, social network sports community loyalty was found to have a partial effect on sports attitudes. Considering these results, various activities such as decision-making process, relationship formation, and opinion expression of modern people are carried out by the O-line community. In addition, while in the past it was a format that led from offline activities to online activities, currently, there are more and more formats that lead from online activities to offline activities. Therefore, modern people's SNS sports community activities provide many experiences, which creates a sense of community and sports attitudes are formed based on this. This can be said to lead to loyal activities.