• Ocean and Polar Research
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• 제45권2호
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• pp.43-55
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• 2023

This study was conducted to understand the seasonal patterns and variation of the copepod community in the Anma Islands of Yeonggwang, Yellow Sea, with a focus on seasonal surveys to assess the factors affecting their occurrence. Throughout the survey period, Acartia hongi, Paracalanus parvus s. l., and Ditrichocorycaeus affinis were dominant species, while Acartia ohtsukai, Acartia pacifica, Bestiolina coreana, Centropages abdominalis, Labidocera rotunda, Paracalanus sp., Tortanus derjugini, Tortanus forcipatus occurred differently by season and station. As a results of cluster analysis, the copepod communities were distinguished into three distinct groups: spring-winter, summer, and autumn. The results of this study showed that the occurrence patterns of copepod species can vary depending on environmental conditions (topographic, distance from the inshore, etc.), and their spatial occurrence patterns between seasons were controlled by water temperature and prey conditions. One of the physical mechanisms that can affect the distribution of zooplankton in the Yellow Sea is the behavior of the Yellow Sea Bottom Cold Water (YSBCW), which shows remarkable seasonal fluctuations. More detailed further studies are needed for clear grounds for mainly why to many Calanus sinicus in the central region of the Yellow Sea are seasonally moving to the inshore, what strategies to seasonally maintain the population, and support the possibilities of complex factors.

• 한국분무공학회지
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• 제28권1호
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• pp.1-9
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• 2023

In the cylinder of gasoline direct injection engines, the spray targeting from injectors is of great significance for fuel consumption and pollutant emissions. The automotive industry is putting a lot of effort into improving injector targeting accuracy. To improve the targeting accuracy of injectors, it is necessary to develop models that can predict the spray targeting positions. When developing spray targeting models, the most used technique is computational fluid dynamics (CFD). Recently, due to the superiority of machine learning in prediction accuracy, the application of machine learning in this field is also receiving constant attention. The purpose of this study is to build a machine learning model that can accurately predict spray targeting based on the design parameters of injectors. To achieve this goal, this study firstly used laser sheet beam visualization equipment to obtain many spray cross-sectional images of injectors with different parameters at different injection pressures and measurement planes. The spray images were processed by MATLAB code to get the targeting coordinates of sprays. A total of four models were used for the prediction of spray targeting coordinates, namely ANN, LSTM, Conv1D and Conv1D & LSTM. Features fed into the machine learning model include injector design parameters, injection conditions, and measurement planes. Labels to be output from the model are spray targeting coordinates. In addition, the spray data of 7 injectors were used for model training, and the spray data of the remaining one injector were used for model performance verification. Finally, the prediction performance of the model was evaluated by R² and RMSE. It is found that the Conv1D&LSTM model has the highest accuracy in predicting the spray targeting coordinates, which can reach 98%. In addition, the prediction bias of the model becomes larger as the distance from the injector tip increases.

• 대한통합의학회지
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• 제11권2호
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• pp.207-219
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• 2023

Purpose : This study was conducted to investigate the changes in trunk movement and ground reaction during sit to stand motion using visual feedback. Methods : Fifteen adults (average age: 23.53±1.77 years) participated in this study. An infrared reflective marker was attached to the body each participant for motion analysis, and the participants performed sit to stand motion while wearing a hat attached with a laser pointer, which provided visual feedback. First, the sit to stand action was repeated thrice without obtaining any visual feedback, followed by a three minute break. Next, the laser pointers attached to hats were irradiated on a whiteboard, located at a distance of 5 m in front of the chairs, on which the participants sat; a baseline was set, and the participants performed stand up movements three times under this condition. A visual feedback was provided to the participants to prevent the laser pointers from crossing the set baseline. During each stand-up movement, the position of the reflective marker attached to the subject's body was recorded in real time using an infrared camera for motion analysis. The trunk movement and ground reaction force were extracted through recorded data and analyzed according to the presence or absence of visual feedback. Results : The results indicated that in the presence of a visual feedback during the sit-to-stand movements, the range of motion of the trunk and hip joints decreased, whereas that of the knee and ankle joints increased in the sagittal plane. The rotation angle of the trunk in the horizontal plane decreased. The left and right movement speed of the center of pressure increased, the pressing force decreased, and the forward and backward movement speed of the trunk decreased. Conclusion : The results suggest that the efficiency and stability of the stand up movement of a body increase when a visual feedback is provided.

• 대한통합의학회지
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• 제11권2호
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• pp.159-168
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• 2023

Purpose : This study aimed to investigate how neuromuscular electrical stimulation (NMES) affects the balance ability of patients who have undergone total knee arthroplasty owing to osteoarthritis. Methods : Thirty patients who had undergone total knee arthroplasty were randomized to an experimental group (n=15) and a control group (n=15). The experimental group received conventional physical therapy for 50 minutes and NMES treatment for 30 minutes, whereas the control group received conventional physical therapy for 50 minutes and active range of motion (AROM) exercises for 30 minutes. Within-group and between-group changes in static and dynamic balance ability before and after the 4-week intervention were analyzed. Results : In the within-group comparison, sway velocity in the center of gravity and total distance were significantly improved in both the experimental and control groups (p<.05), with no significant differences between the groups (p>.05). In the within-group comparison, both the experimental and control groups showed significant improvement in the functional reach test and movement velosity (p<.05). In the between-group comparison, the experimental group showed a significantly better improvement than the control group in the functional reach test (p<.05), but there was no significant difference in the movement velosity test (p>.05). Conclusion : In this study, NMES improved the static and dynamic balance in patients who had undergone total knee arthroplasty. Compared with AROM exercises, there was a greater effect on dynamic balance partially; however, the overall effect was similar. Therefore, NMES may be one option among various interventions to improve the balance ability in patients who have undergone total knee arthroplasty. In particular, this method may be effective when it is difficult to apply balance training for patients with total knee arthroplasty in a clinical setting.

• 대한중풍순환신경학회지
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• 제14권1호
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• pp.102-106
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• 2013

■ Objectives The purpose of the this study was to investigate organization change(pennation angle) of lower extremity muscle in elderly with knee osteoarthritis through ultrasonic image. Also, we examined organizational change of muscle was by influenced after total knee replacement(TKR). ■ Methods Rectus femoris image was taken at 50% of the distance between the anterior superior iliac spine and the superior border of the patella. Vastus medialis image was taken at the most distal insertion level of vastus medialis on the medial border of the patella. measurements included the most distal insertion level of the vastus medialis on the medial border of the patella. ■ Results Change of pennation angle in rectus femoris showed decrease from 5.11° in preoperation to 4.29° in 1 week after operation. Change of pennation angle in vastus medialis showed decrease from 6.94° in preoperation to 5.76° in 1 week after operation. ■ Conclusion We consider decrease of pennation angle after total knee replacement in this study was casued by organizational change of muscle and this pennation angle was influenced force created by muscle. Therefore, we thinks that this pennation angle through ultrasonic image will be available to plane individual muscle exercise program and to confirm muscle mass by muscle strength training.

• 문화기술의 융합
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• 제9권4호
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• pp.577-585
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• 2023

이 연구는 LPG 충전소의 가스누출로 발생이 예상되는 화재 및 폭발에 따른 피해예측에 ALOHA 프로그램을 적용 영향범위와 거리를 도식화함으로 피해방지 방안을 제시하였다. LPG 충전소에서 프로판 가스가 누출될 경우 LPG 충전소 주변지역 주민들에게 호흡곤란 등의 인명피해 및 건물파괴 등 재산피해를 입히는 것으로 나타났다. 이의 감소방안으로 첫째 LPG 충전소의 위험물안전관리자는 수시로 계측기와 안전밸브가 제대로 작동하는지 점검하여 누출을 사전에 방지할 필요가 있다. 둘째 LPG 충전소에서 저장탱크에 충전하는 작업은 위험물안전관리법 규정에 따라 "위험물안전관리자 교육"을 받고, 소방관서에서 "위험물안전관리자"로 선임된 사람의 책임하에 해야 한다는 것이다. 셋째 LPG차량의 과충전 방지장치 등 각종 안전장치의 기능을 평상시 정기적으로 점검할 필요가 있다. 마지막으로 LPG 충전소에 가스가 누출될 때 정전기에 의해 화재가 발생할 수 있으므로 정전기를 방지할 수 있는 작업복·작업화를 착용하는 등의 조치로 정전기발생을 억제하는 것이 바람직하다.

• Geomechanics and Engineering
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• 제34권3호
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• pp.267-284
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• 2023

Landslides are one of the most dangerous phenomena and natural disasters. Landslides cause many human and financial losses in most parts of the world, especially in mountainous areas. Due to the climatic conditions and topography, people in the northern and western regions of Iran live with the risk of landslides. One of the measures that can effectively reduce the possible risks of landslides and their crisis management is to identify potential areas prone to landslides through multi-criteria modeling approach. This research aims to model landslide potential area in the Oshvand watershed using a support vector machine algorithm. For this purpose, evidence maps of seven effective factors in the occurrence of landslides namely slope, slope direction, height, distance from the fault, the density of waterways, rainfall, and geology, were prepared. The maps were generated and weighted using the continuous fuzzification method and logistic functions, resulting values in zero and one range as weights. The weighted maps were then combined using the support vector machine algorithm. For the training and testing of the machine, 81 slippery ground points and 81 non-sliding points were used. Modeling procedure was done using four linear, polynomial, Gaussian, and sigmoid kernels. The efficiency of each model was compared using the area under the receiver operating characteristic curve; the root means square error, and the correlation coefficient . Finally, the landslide potential model that was obtained using Gaussian's kernel was selected as the best one for susceptibility of landslides in the Oshvand watershed.

• 한국컴퓨터정보학회논문지
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• 제28권10호
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• pp.103-111
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• 2023

산악지대, 특히 오픈스페이스에서의 보행은 산악지형을 기반으로 이루어지는 특수 활동영역에서 중요하다. 그러나 최근의 보행 경로 연구는 보행자와 환경 요소를 포괄적으로 네트워크 분석에 포함시키지만, 주로 한정된 공간을 대상으로 하며 산악지형 등, 데이터가 부족한 지형은 분석 대상에서 제외된다. 본 논문에서는 산악지형의 오픈스페이스에서 그물망 기반의 가상 보행 네트워크를 만들며, 경사도를 반영한 산악 보행 경로 생성 방법을 제안한다. 이 방법은 거리측정에 경사도를 고려하여 실제 지형을 더 잘 반영하며, 기존 경로 분석 서비스에서 제공하지 않는 오픈스페이스를 이용한 산악 보행 경로를 제시하고, 시험을 통해 이를 입증하였다. 본 논문의 설계 방법은 조난, 산악구조, 전술 훈련 등에서 산악지형의 오픈스페이스를 포함한 경로 생성 방법으로 활용될 수 있을 것으로 기대한다.

• 한국컴퓨터정보학회논문지
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• 제28권12호
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• pp.191-199
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• 2023

본 논문에서는 자율협력주행을 위한 인프라로써 제작된 5가지 센서 전용 시설물들에 대해 라이다로 취득한 포인트 클라우드 데이터로부터 시설물들의 특징을 추출하는 방법을 제안한다. 자율주행차량에 장착된 영상 취득 센서의 경우에는 기후 환경 및 카메라의 특성 등으로 인해 취득 데이터의 일관성이 낮기 때문에 이를 보완하기 위해서 라이다 센서를 적용했다. 또한, 라이다로 기존의 다른 시설물들과의 구별을 용이하게 하기 위해서 고휘도 반사지를 시설물의 용도별로 디자인하여 부착했다. 이렇게 개발된 5가지 센서 전용 시설물들과 데이터 취득 시스템으로 취득한 포인트 클라우드 데이터로부터 측정 거리별 시설물의 특징을 추출하는 방법으로 해당 시설물에 부착된 고휘도 반사지의 평균 반사강도을 기준으로 특징 포인트들을 추출하여 DBSCAN 방법으로 군집화한 후 해당 포인트들을 투영법으로 2차원 좌표로 변경했다. 거리별 해당 시설물의 특징은 3차원 포인트 좌표, 2차원 투영 좌표, 그리고 반사강도로 구성되며, 추후 개발될 시설물 인식을 위한 모형의 학습데이터로 활용될 예정이다.

• 응용통계연구
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• 제37권2호
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• pp.239-253
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• 2024

본 연구는 learning-to-rank (LTR) 기법 중 point-wise와 pair-wise learning을 적용하여 서울 경마경기 순위 예측을 수행하였다. Point-wise learning으로는 선형 회귀와 랜덤 포레스트를 pair-wise learning으로는 RankNet, LambdaMART (XGBoost Ranker, LightGBM Ranker, CatBoost Ranker)을 활용하였다. 또한 데이터 불균형 문제를 해결하기 위해 전처리 과정에서 경주기록을 경주거리에 따라 표준화하는 방식을 채택하였으며, 모형의 예측 능력 향상을 위해 경기 정보, 기수 정보, 마필 정보, 조교사 정보 등의 다양한 데이터를 사용하였다. 그 결과 아이템 간의 순위관계를 학습할 수 있는 pair-wise learning이 point-wise learning보다 전반적으로 더 뛰어난 예측력을 보이는 것을 확인하였다. 특히 CatBoost Ranker는 제시된 모형들 중 가장 뛰어난 예측 성능을 보였다. 마지막으로 섀플리 값을 통해 CatBoost Ranker에서 경주마의 성적, 직전 경주기록, 경주마의 출발훈련 횟수, 누적 출발훈련 횟수, 질병 진단횟수 등이 상위 10개 중요 변수에 포함된 것을 확인하였다.