• 한국직업건강간호학회지
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• 제30권4호
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• pp.206-215
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• 2021

Purpose: This study aimed to investigate the factors affecting cardiovascular disease in middle-aged male workers. Methods: The participants were 137 male office workers over 40 years old and under 60 years old working in small- and medium-sized workplaces from three southern provinces of Korea. Data were collected through self-reported questionnaires and health screening reports from the 2014 National Health Examination. The influencing factors included general characteristics of participants, anger expression style, and occupational stress. Data were analyzed using t-test, ANOVA, and regression analysis with SPSS 22.0. Results: The mean score of risk of cardiovascular disease was 6.73±4.69 and there were significant differences in exercise (t=2.13, p=.035) working time (t=-2.15, p=.034). Logistic regression analysis showed that, when adjusted for exercise and working time, the probability of becoming under a cardiovascular disease risk was 21% higher for those who anger-in (OR=1.21, 95% CI=1.02~1.44, p=.027) and 12% higher for those perceived occupational stress (OR=1.12, 95% CI=1.01~1.24, p=.030). Conclusion: The results suggest developing the strategies for middle-aged male workers to encourage exercise and to decrease occupational stress, as well as an appropriate anger expression style to improve holistic aspect of health considering their demographic characteristics.

• 한국산업정보학회논문지
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• 제27권2호
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• pp.11-24
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• 2022

LMS 기반의 온라인 평가를 위해 출제되는 문제들은 교수자가 직접 출제하거나 또는 카테고리별로 나뉘어진 문제은행에서 난이도에 따른 자동 출제 방식을 주로 이용한다. 이중에서 난이도에 따른 자동출제 방식은 평가자들에게 출제되는 문제가 서로 다를수 있기 때문에 무엇보다 객관적이고 효율적인 방법으로 문제의 난이도를 관리하는 것이 중요하다. 본 논문에서는 문제의 정답률뿐만 아니라 해당 문제를 해결하는데 사용된 소요시간을 같이 고려한 난이도 재조정 알고리즘을 제시한다. 이를 위해 머신러닝의 로지스틱 회귀 분류 알고리즘을 이용하였으며, 학습모델의 예측 확률값을 기반으로 기준 임계값을 설정하여 각 문항별 난이도 재조정에 활용하였다. 그 결과 정답률에만 의존한 문항별 난이도에 많은 변화가 일어남을 확인할 수 있었다. 또한 조정된 난이도의 문제를 이용하여 그룹별 평가를 수행한 결과, 정답률 기반의 난이도 문제에 비해서 대부분의 그룹에서 평균 점수가 향상됨을 확인할 수 있었다.

• 응용통계연구
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• 제35권4호
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• pp.485-499
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• 2022

표본오차와 비표본오차를 포함하는 총오차(total survey error)를 관리하는 것은 표본설계에서 매우 중요하다. 무응답으로 인해 발생한 비표본오차는 총오차에서 차지하는 비중이 매우 크며 이를 해결하는 방법인 무응답 대체에 관한 다수의 연구가 수행되었다. 최근 전통적 통계학 관련 기법에 추가하여 기계학습 관련 기법을 이용한 무응답 대체법이 다수 연구되고 실질적으로 사용되고 있다. 기존에 발표된 다수의 방법은 MCAR(missing completely at random) 또는 MAR(missing at random) 가정을 사용하고 있다. 그러나 관심변수에 영향을 받는 MNAR(missing not at random) 또는 무시할 수 없는 무응답(non-ignorable non-response; NN)은 편향을 발생시켜 대체 결과의 정확성을 크게 떨어뜨리지만 이에 관한 연구는 상대적으로 미미하다. 본 연구에서는 무시할 수 없는 무응답이 발생한 경우에 적용 가능한 무응답 대체법을 제안하였다. 특히 편향을 추정한 후 이를 제거하는 방법을 이용하여 무응답 대체 결과의 정확성을 향상하는 방법을 제안하였다. 또한, 모의실험을 이용하여 제안된 방법의 타당성을 확인하였다.

• 한국융합학회논문지
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• 제13권2호
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• pp.249-255
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• 2022

본 연구는 최근 가공 불량 예측 방법으로 주목받고 있는 머신러닝 기반의 모델을 이용하여 CNC 가공 불량 발생의 실시간 예측을 위한 분석 프레임워크를 제안하고, 해당 프레임워크에 기반하여 XGBoost, CatBoost, LightGBM, 랜덤 포레스트, Extra Trees, SVM, k-최근접 이웃, 로지스틱 회귀 모델을 CNC 설비에 기본 내장된 센서들로부터 추출된 데이터에 적용 및 분석하였다. 분석 결과 XGBoost, CatBoost, LightGBM 모델이 동일하게 가장 우수한 정확도, 정밀도, 재현율, F1 점수, AUC 값을 보였으며, 이 중 LightGBM 모델이 소요 실행 시간이 가장 짧은 것으로 나타났다. 이러한 짧은 소요 실행 시간은 실 시스템 구축 비용 절감, 빠른 불량 예측에 따른 CNC 장비 파손 확률 감소, 전체적인 CNC 활용률 증가 등의 실무적 장점을 가지므로 LightGBM 모델이 기본 센서들만 설치된 CNC 설비에 적용 시 가공 불량 예측에 가장 효과적으로 판단된다. 또한 소요 실행 시간 및 컴퓨팅 파워의 제약이 없는 상황에서는 LightGBM, Extra Trees, k-최근접 이웃, 로지스틱 회귀 모형으로 구성된 앙상블 모델을 적용할 경우 분류 성능이 최대화됨을 확인하였다.

• 여성건강간호학회지
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• 제28권2호
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• pp.112-122
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• 2022

Purpose: The prevalence of osteoporosis in postmenopausal women is increasing, and diabetes patients have decreased bone density. Their health-related quality of life (HRQoL) is diminished by the resultant physical dysfunction and depression. The purpose of this study was to identify factors influencing HRQoL in postmenopausal women with diabetes and osteoporosis. Methods: This was a secondary data analysis of the Seventh Korea Health and Nutrition Examination Survey (2016-2018), which utilized a complex, multistage probability sample design. The participants in the study were 237 women with diabetes and osteoporosis. To evaluate the factors that influenced HRQoL, a complex-samples general linear model was constructed, and the Bonferroni correction was performed. Results: In this sample of women aged 45 to 80 years (mean±standard deviation, 71.12±7.21 years), the average HRQoL score was 0.83±0.18 out of 1.0. Factors influencing HRQoL were age (70s: t=-3.74, p<.001; 80s: t=-3.42, p=.001), walking for exercise more than 5 days a week (t=-2.83, p=.005), cerebrovascular disease (t=-8.33, p<.001), osteoarthritis (t=-2.04, p=.014), hypertension (t=2.03, p=.044), higher perceived stress (t=-2.17, p=.032), poor glycemic control (t=3.40, p=.001), waist circumference (t=-2.76, p=.007), sitting time per day (t=-2.10, p=.038), and a longer postmenopausal period (t=3.09, p=.002). Conclusion: In order to improve the HRQoL of postmenopausal women with osteoporosis and diabetes, it is necessary to implement intervention strategies that enable the effective management of chronic diseases, while preventing the complications of diabetes and minimizing stress through physical activity.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권6호
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• pp.1706-1727
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• 2023

Under Water Sensor Networks (UWSN) has gained attraction among various communities for its potential applications like acoustic monitoring, 3D mapping, tsunami detection, oil spill monitoring, and target tracking. Unlike terrestrial sensor networks, it performs an acoustic mode of communication to carry out collaborative tasks. Typically, surface sink nodes are deployed for aggregating acoustic phenomena collected from the underwater sensors through the multi-hop path. In this context, UWSN is constrained by factors such as lower bandwidth, high propagation delay, and limited battery power. Also, the vulnerabilities to compromise the aquatic environment are in growing numbers. The paper proposes an Energy-Efficient standalone Intrusion Detection System (EEIDS) to entail the acoustic environment against malicious attacks and improve the network lifetime. In EEIDS, attributes such as node ID, residual energy, and depth value are verified for forwarding the data packets in a secured path and stabilizing the nodes' energy levels. Initially, for each node, three agents are modeled to perform the assigned responsibilities. For instance, ID agent verifies the node's authentication of the node, EN agent checks for the residual energy of the node, and D agent substantiates the depth value of each node. Next, the classification of normal and malevolent nodes is performed by determining the score for each node. Furthermore, the proposed system utilizes the sheep-flock heredity algorithm to validate the input attributes using the optimized probability values stored in the training dataset. This assists in finding out the best-fit motes in the UWSN. Significantly, the proposed system detects and isolates the malicious nodes with tampered credentials and nodes with lower residual energy in minimal time. The parameters such as the time taken for malicious node detection, network lifetime, energy consumption, and delivery ratio are investigated using simulation tools. Comparison results show that the proposed EEIDS outperforms the existing acoustic security systems.

• 한국임상수의학회지
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• 제40권3호
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• pp.238-241
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• 2023

This study determined the effect of ovarian status at the beginning of the modified Double-Ovsynch program on reproductive performance in dairy cows. In the study, 1,302 cows were treated with a modified Double-Ovsynch program at 56 days after calving. This program comprises administering gonadotropin-releasing hormones (GnRH), prostaglandin F_2α (PGF_2α) 10 days later, GnRH 3 days later, GnRH 7 days later, and GnRH 56 h later, followed by timed artificial insemination (TAI) 16 h later. At the beginning of the program, cows were categorized according to the size of the largest follicle and the presence of a corpus luteum (CL) in the ovaries as follows: 1) small follicle (<5 mm, SF group, n = 100), 2) medium follicle (8-20 mm, MF group, n = 538), and 3) large follicle (≥25 mm, LF group, n = 354) without a CL, or 4) the presence of a CL (CL group, n = 310). The pregnancies per AI after the first TAI were analyzed by logistic regression using the LOGISTIC procedure, and the logistic model included the fixed effects of the herd size, parity, body condition score (BCS) at the first TAI, TAI period, and ovarian status. A larger herd size, higher BCS at the first TAI, and TAI period with no heat stress increased (p < 0.05) the probability of pregnancy per AI after the first TAI. However, ovarian status at the beginning of the program did not affect (p > 0.05) the pregnancies per AI (ranges of 37.9% to 42.9%). These results show that the modified Double-Ovsynch program can be used effectively while maintaining good fertility regardless of the ovarian status in dairy herds.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.304-311
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• 2022

Construction inspection is a crucial stage that ensures that all contractual requirements of a construction project are verified. The construction inspection capabilities among state highway agencies have been greatly affected due to budget reduction. As a result, efficient inspection practices such as risk-based inspection are required to optimize the use of limited resources without compromising inspection quality. Automated prioritization of textual requirements according to their criticality would be extremely helpful since contractual requirements are typically presented in an unstructured natural language in voluminous text documents. The current study introduces a novel model for predicting the risk level of requirements using machine learning (ML) algorithms. The ML algorithms tested in this study included naïve Bayes, support vector machines, logistic regression, and random forest. The training data includes sequences of requirement texts which were labeled with risk levels (such as very low, low, medium, high, very high) using the fuzzy logic systems. The fuzzy model treats the three risk factors (severity, probability, detectability) as fuzzy input variables, and implements the fuzzy inference rules to determine the labels of requirements. The performance of the model was examined on labeled dataset created by fuzzy inference rules and three different membership functions. The developed requirement risk prediction model yielded a precision, recall, and f-score of 78.18%, 77.75%, and 75.82%, respectively. The proposed model is expected to provide construction inspectors with a means for the automated prioritization of voluminous requirements by their importance, thus help to maximize the effectiveness of inspection activities under resource constraints.

• Korean Journal of Radiology
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• 제21권6호
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• pp.684-694
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• 2020

Objective: The purpose was to review the diagnostic performance of the length of tumor capsular contact (LCC) on magnetic resonance imaging (MRI) for detecting prostate cancer extraprostatic extension (EPE). Materials and Methods: PubMed and EMBASE databases were searched up to March 24, 2019. We included diagnostic accuracy studies that evaluated LCC on MRI for EPE detection using radical prostatectomy specimen histopathology as the reference standard. Quality of studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies-2 tool. Sensitivity and specificity were pooled and graphically presented using hierarchical summary receiver operating characteristic (HSROC) plots. Meta-regression and subgroup analyses were conducted to explore heterogeneity. Results: Thirteen articles with 2136 patients were included. Study quality was generally good. Summary sensitivity and specificity were 0.79 (95% confidence interval [CI] 0.73-0.83) and 0.67 (95% CI 0.60-0.74), respectively. Area under the HSROC was 0.81 (95% CI 0.77-0.84). Substantial heterogeneity was present among the included studies according to Cochran's Q-test (p < 0.01) and Higgins I² (62% and 86% for sensitivity and specificity, respectively). In terms of heterogeneity, measurement method (curvilinear vs. linear), prevalence of Gleason score ≥ 7, MRI readers' experience, and endorectal coils were significant factors (p ≤ 0.01), whereas method to determine the LCC threshold, cutoff value, magnet strength, and publication year were not (p = 0.14-0.93). Diagnostic test accuracy estimates were comparable across all assessed MRI sequences. Conclusion: Greater LCC on MRI is associated with a higher probability of prostate cancer EPE. Due to heterogeneity among the studies, further investigation is needed to establish the optimal cutoff value for each clinical setting.

• 한국산학기술학회논문지
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• 제17권5호
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• pp.530-537
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• 2016

본 연구는 정면충돌사고를 분석하여 충돌방향과 관련된 운전저의 행동변화를 분석하고, 인체손상정도를 파악해보고자 한다. 연구기간은 2013년 8월~2014년 1월까지로 응급의학 팀에 의해 차량의 손상정도와 인체상해 데이터를 수집하였다. 자료수집에서 사고차량, 사고방향 등은 KIDAS(Korea In-depth Accident Study; 한국형 교통사고 심층조사)와 인체손상정보에 기반을 둔 ISS(Injury Severity Score; 인체손상점수) 내용을 수집하였다. 자료분석은 Minitab 17과 SPSS 22.0을 이용하여 빈도분석과 ANOVA분석을 시행하였다. 분석결과 정면충돌은 12시 방향에서 55.8%로 가장 높게 나타났다. 연령에 따른 정면충돌 방향을 분석해 본 결과 11시방향이 평균 $46.46{\pm}13.47$세, 12시방향이 $44.43{\pm}13.40$세, 1시 방향에서 $52.46{\pm}12.04$세로 통계적으로 유의하게 연령이 높을수록 1시 방향에서 높게 나타났다(p<0.05). 남자의 연령에 따른 정면충돌 방향에서도 11시방향이 $47.10{\pm}13.88$세, 12시방향이 $45.24{\pm}13.78$세, 1시 방향에서 $55.73{\pm}13.38$세로 연령이 증가함에 따라 1시방향의 충돌이 높게 나타났다(p<0.05). 그러나 여자의 경우 연령에 따른 정면충돌 방향에서는 통계적으로 유의하지 않았다(p>0.05). 남녀의 연령에 따른 충돌방향에서의 ISS점수를 비교해봤을 때 남자의 경우 $ISS{\geq}9$에서 12시방향 충돌은 감소하고 ISS<9에서 1시방향 충돌이 증가하였다(p<0.05). 결과적으로 정면충돌방향은 12시 방향에서 가장 높은 빈도로 일어나고, 연령이 증가할수록 정면충돌 방향이 1시 방향으로 높아져 ISS점수가 낮아진다. 따라서 남성에서 12시방향 충돌을 인지하고 핸들을 왼쪽으로 틀어 1시 방향 충돌로 바꾸어 신체손상을 줄이려는 행동을 한다.