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Development of Tunnel-Environment Monitoring System and Its Installation III -Measurement in Solan Tunnel- (터널 환경 측정 시스템 개발 및 측정 III -솔안터널 측정결과 분석-)

  • Park, Won-Hee;Cho, Youngmin;Kwon, Tae-Soon
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.17 no.5
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    • pp.637-644
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    • 2016
  • This paper is a follow-up to previous papers entitled, "Development of Tunnel-Environment Monitoring System and Its Installation" I [1] and II [2]. The target tunnel of these studies is the Solan Tunnel, which is a loop-type, single-track, 16.7-km-long tunnel located in mountainous terrain and passing through the Baekdudaegan mountain range. It is an ordinary railway tunnel designed for both freight and passenger trains. We analyzed the environmental conditions of the tunnel using temperature and humidity data recorded over approximately one year. The data were recorded using the Tunnel Rough Environment Measuring System (TREMS), which measures environmental data in subway and high-speed train tunnels and is installed in three locations inside the tunnel. Previous studies analyzed environmental conditions inside tunnels located in or near a city, whereas the tunnel in this study is located in a mountainous area. The tunnel conditions were compared with those measured outside the tunnel for each month. Hourly changes during summer and winter periods were also analyzed, and the environmental conditions at different locations inside the tunnel were compared. The results are widely applicable in studies on the thermal environment and air quality of tunnels, as well as for computer analysis of tunnel airflow such as tunnel ventilation and fire simulations.

Smoke Control Experiment of a Very Deep Underground Station Where Platform Screens Doors are Installed - Analysis on Smoke Control Performance by Fans equipped in Tunnel (스크린도어가 설치된 대심도 지하역사의 제연 실험 - 터널 송풍기에 의한 제연의 효과 분석)

  • Park, Won-Hee;Kim, Chang-Yong;Cho, Youngmin
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.9 no.9
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    • pp.721-736
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    • 2019
  • In this paper, the behavior of the fire smoke due to the operation of the ventilation systems when the fire occurred in the underground station (6 basement floors) and the tunnel at the great depth was measured. Fire smoke was generated by using a smoke generator which realized heat buoyancy effect by using hot air blower. The two locations of the fire were selected on the platform and on the platform of the tunnel located outside the screen door. A ventilation mode is generally used in which smoke is exhausted through a vent hole provided in a platform when a platform fire occurs. The tests were performed by operating the exhaust through the ventilation holes of the tunnel part located at both ends of the platform. The smoke density and the wind speed/velocity were measured at various positions, and the videos were taken to analyze the movement and smoke of the smoke. In both cases for fire inside the platform and in the railway tunnel, due to the ventilation mode operation of the fan for the platform and the exhaust of the fans in the tunnel smoke were well exhausted and the smoke propagation to the area near the smoke zone was suppressed. The smoke-control mode, which is applied to both fans for the platform and fans for in the tunnel at both ends of the platform, can provide a safer evacuation environment to the passengers from the fire smoke when the platform fire or fire train stops.

Detection and Identification of Moving Objects at Busy Traffic Road based on YOLO v4 (YOLO v4 기반 혼잡도로에서의 움직이는 물체 검출 및 식별)

  • Li, Qiutan;Ding, Xilong;Wang, Xufei;Chen, Le;Son, Jinku;Song, Jeong-Young
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.21 no.1
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    • pp.141-148
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    • 2021
  • In some intersections or busy traffic roads, there are more pedestrians in a specific period of time, and there are many traffic accidents caused by road congestion. Especially at the intersection where there are schools nearby, it is particularly important to protect the traffic safety of students in busy hours. In the past, when designing traffic lights, the safety of pedestrians was seldom taken into account, and the identification of motor vehicles and traffic optimization were mostly studied. How to keep the road smooth as far as possible under the premise of ensuring the safety of pedestrians, especially students, will be the key research direction of this paper. This paper will focus on person, motorcycle, bicycle, car and bus recognition research. Through investigation and comparison, this paper proposes to use YOLO v4 network to identify the location and quantity of objects. YOLO v4 has the characteristics of strong ability of small target recognition, high precision and fast processing speed, and sets the data acquisition object to train and test the image set. Using the statistics of the accuracy rate, error rate and omission rate of the target in the video, the network trained in this paper can accurately and effectively identify persons, motorcycles, bicycles, cars and buses in the moving images.

Influence of Self-driving Data Set Partition on Detection Performance Using YOLOv4 Network (YOLOv4 네트워크를 이용한 자동운전 데이터 분할이 검출성능에 미치는 영향)

  • Wang, Xufei;Chen, Le;Li, Qiutan;Son, Jinku;Ding, Xilong;Song, Jeongyoung
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.20 no.6
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    • pp.157-165
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    • 2020
  • Aiming at the development of neural network and self-driving data set, it is also an idea to improve the performance of network model to detect moving objects by dividing the data set. In Darknet network framework, the YOLOv4 (You Only Look Once v4) network model was used to train and test Udacity data set. According to 7 proportions of the Udacity data set, it was divided into three subsets including training set, validation set and test set. K-means++ algorithm was used to conduct dimensional clustering of object boxes in 7 groups. By adjusting the super parameters of YOLOv4 network for training, Optimal model parameters for 7 groups were obtained respectively. These model parameters were used to detect and compare 7 test sets respectively. The experimental results showed that YOLOv4 can effectively detect the large, medium and small moving objects represented by Truck, Car and Pedestrian in the Udacity data set. When the ratio of training set, validation set and test set is 7:1.5:1.5, the optimal model parameters of the YOLOv4 have highest detection performance. The values show mAP50 reaching 80.89%, mAP75 reaching 47.08%, and the detection speed reaching 10.56 FPS.

On The Voice Training of Stage Speech in Acting Education - Yuri Vasiliev's Stage Speech Training Method - (연기 교육에서 무대 언어의 발성 훈련에 관하여 - 유리 바실리예프의 무대 언어 훈련방법 -)

  • Xu, Cheng-Kang
    • Journal of Korea Entertainment Industry Association
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    • v.15 no.3
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    • pp.203-210
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    • 2021
  • Yuri Vasilyev - actor, director and drama teacher. Russian meritorious artist, winner of the stage "Medal of Friendship" awarded by Russian President Vladimir Putin; academician of the Petrovsky Academy of Sciences and Arts in Russia, professor of the Russian National Academy of Performing Arts, and professor of the Bavarian Academy of Drama in Munich, Germany. The physiological sense stimulation method based on the improvement of voice, language and motor function of drama actors. On the basis of a systematic understanding of performing arts, Yuri Vasiliev created a unique training method of speech expression and skills. From the complicated art training, we find out the most critical skills for focused training, which we call basic skills training. Throughout the whole training process, Professor Yuri made a clear request for the actor's lines: "action! This is the basis of actors' creation. So action is the key! Action and voice are closely linked. Actor's voice is human voice, human life, human feeling, human experience and disaster. It is also the foundation of creation that actors acquire their own voice. What we are engaged in is pronunciation, breathing, tone and intonation, speed and rhythm, expressiveness, sincerity, stage voice and movement, gesture, all of which are used to train the voice of actors according to the standard of drama. In short, Professor Yuri's training course is not only the training of stage performance and skills, but also contains a rich view of drama and performance. I think, in addition to learning from the means and methods of training, it is more important for us to understand the starting point and training objectives of Professor Yuri's use of these exercises.

Examining Access Mode Choice Behavior of Local Metropolitan High-Speed Rail Station - A Case Study of Dong-Daegu Station - (고속철도 지방대도시 정차역의 연계교통수단 선택모형 구축에 관한 연구 - 동대구역을 사례로 -)

  • Kim, Sang Hwang;Kim, Kap Soo
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.4D
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    • pp.565-571
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    • 2006
  • This study aimed to analyze access mode choice behavior for KTX Passengers. To fulfill the aims of this study, Dong-Daegu Station was selected as a station for a case study. This study takes place in two stages. These are (i) descriptive statistical analysis of transportation status before and after introduction of the KTX, (ii) empirical model estimation for analyzing access mode choice behavior. This study makes use of the data from travel survey from Daegu metropolitan area. The main part of the survey was carried out in the KTX Dong-Daegu station. The data was collected from a sample of 1,800 individuals. The survey data includes the information on travel from Dong-Daegu station to Seoul. From descriptive statistical analysis of transportation status before and after introduction of the KTX, it is found that revealed demand of the KTX is lower than that expected. Moreover, it is found that the low demand of the KTX stems from high cost for the KTX itself and inconvenience( including travel time and cost) of access mode. In order to analyze mode choice behavior for accessing Dong-Daegu station, multinomial logit model structure is used. For the model specification, a variety of behavioral assumptions about the factors which affect the access mode choice, were considered. From the empirical model estimation, it si found that access travel time and access travel cost are significant in choosing access mode. Given the empirical evidence, we see that improvement of access transportation system for Dong-Daegu station is very important for enhancing the use of KTX.

A Study on Determination of the Minimum Vertical Spring Stiffness of Track Pads Considering Running Safety (열차주행안전을 고려한 궤도패드의 최소 수직 스프링계수 결정에 관한 연구)

  • Kim, Jeong-il;Yang, Sin-Chu;Kim, Yun-Tae
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.26 no.2D
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    • pp.299-309
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    • 2006
  • Railway noise and vibration has been recognized as major problems with the speed-up of rolling stock. As a kind of solution to these problems, the decrease of stiffness of track pad have been tried. However, in this case, overturning of rail due to lateral force should be considered because it can have effect on the safety of running train. Therefore, above two things - decrease of stiffness of track pad and overturning of rail due to lateral force - should be considered simultaneously for the appropriate determination of spring coefficient of track pad. With this viewpoint, minimum spring coefficient of track pad is estimated through the comparison between the theoretical relationship about the overturning of rail and 3-dimensional FE analysis result. Two kinds of Lateral force and wheel load are used as input loads. Extracted values from the conventional estimation formula and the Shinkansen design loads are used. It is found that the overturning of rail changes corresponding to the change of the stiffness of track pad and the ratio of lateral force to wheel load. Moreover, it is found that the analysis model can have influence on the results. Through these procedure, minimum spring coefficient of track pad is estimated.

Flexible Planar Heater Comprising Ag Thin Film on Polyurethane Substrate (폴리우레탄 유연 기판을 이용한 Ag 박막형 유연 면상발열체 연구)

  • Seongyeol Lee;Dooho Choi
    • Journal of the Microelectronics and Packaging Society
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    • v.31 no.1
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    • pp.29-34
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    • 2024
  • The heating element utilizing the Joule heating generated when current flows through a conductor is widely researched and developed for various industrial applications such as moisture removal in automotive windshield, high-speed train windows, and solar panels. Recently, research utilizing heating elements with various nanostructures has been actively conducted to develop flexible heating elements capable of maintaining stable heating even under mechanical deformation conditions. In this study, flexible polyurethane possessing excellent flexibility was selected as the substrate, and silver (Ag) thin films with low electrical resistivity (1.6 μΩ-cm) were fabricated as the heating layer using magnetron sputtering. The 2D heating structure of the Ag thin films demonstrated excellent heating reproducibility, reaching 95% of the target temperature within 20 seconds. Furthermore, excellent heating characteristics were maintained even under mechanically deforming environments, exhibiting outstanding flexibility with less than a 3% increase in electrical resistance observed in repetitive bending tests (10,000 cycles, based on a curvature radius of 5 mm). This demonstrates that polyurethane/Ag planar heating structure bears promising potential as a flexible/wearable heating element for curved-shaped appliances and objects subjected to diverse stresses such as human body parts.

Islamist Strategic Changes against U.S. International Security Initiative (미국(美國)의 대외안보전략(對外安保戰略)에 대응한 이슬람Terrorism의 전술적(戰術的) 진화(進化))

  • Choi, Kee-Nam
    • Korean Security Journal
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    • no.14
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    • pp.517-534
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    • 2007
  • Since the beginning of human society, there have always been struggles and competitions for survival and prosperity, terrorism is not a recent phenomenon, however in modern times it has progressed to reflect the advances in civilization and power structures. At the time of the 9.11 terrorist attacks in the U.S. A., a new world order was in the process of being established after the breakdown of the Cold War era. The attacks drove both the Western and the Islamic worlds into heightened fear of terrorism and war, which threatened the quality of life of the whole mankind. Through two war campaigns against the Islamic world, it seems the U.S. has been pushing its own militaristic security road map of the Greater Middle East democratic initiative, justifying it as a means to retaliate and eradicate the terrorist threats towards themselves. However, with its five-year lopsided victories that cost the nation almost four thousand military casualties, and the war expenses that could match the Vietnam war, the U.S. does not yet seem to be totally emancipated from the fears of terrorism. Terrorism, in itself, is a means of resisting forced rules a form of alternative competition by the weak against the strong, and a way of expressing a dismissive response against dictatorial ideas or orders which allow for no normal changes. Intrinsically, the nature of terrorism is a reaction opposing power logics. Confronted with the absolute military power of the U.S., the Islamic strategies of terrorism have begun to rapidly evolve into a new stage. The new strategies take advantage of their civilization and circumstances, they train and inspire their front-line fighters on the Internet, and issue their orders through the clandestine network of the Al Qaeda operatives. These spontaneously generated strategies have been gained speed among the second, and third Islamic generations, many of whom are now spread throughout western societies. This represents a failure of the power-driven, one-sided overseas security initiatives by the U.S., and is creating a culture of fear and distrust in western societies. It is feared that the U.S. war campaigns have made the clash of religions far worse than before, and may ever lead to global ethnic separations and large-scale population movements. Eventually, it may result in the terrorist groups, enlarged and secretly supported by the huge sums of oil money, driving all mankind into a series of irreparable catastrophes.

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Development of deep learning network based low-quality image enhancement techniques for improving foreign object detection performance (이물 객체 탐지 성능 개선을 위한 딥러닝 네트워크 기반 저품질 영상 개선 기법 개발)

  • Ki-Yeol Eom;Byeong-Seok Min
    • Journal of Internet Computing and Services
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    • v.25 no.1
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    • pp.99-107
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    • 2024
  • Along with economic growth and industrial development, there is an increasing demand for various electronic components and device production of semiconductor, SMT component, and electrical battery products. However, these products may contain foreign substances coming from manufacturing process such as iron, aluminum, plastic and so on, which could lead to serious problems or malfunctioning of the product, and fire on the electric vehicle. To solve these problems, it is necessary to determine whether there are foreign materials inside the product, and may tests have been done by means of non-destructive testing methodology such as ultrasound ot X-ray. Nevertheless, there are technical challenges and limitation in acquiring X-ray images and determining the presence of foreign materials. In particular Small-sized or low-density foreign materials may not be visible even when X-ray equipment is used, and noise can also make it difficult to detect foreign objects. Moreover, in order to meet the manufacturing speed requirement, the x-ray acquisition time should be reduced, which can result in the very low signal- to-noise ratio(SNR) lowering the foreign material detection accuracy. Therefore, in this paper, we propose a five-step approach to overcome the limitations of low resolution, which make it challenging to detect foreign substances. Firstly, global contrast of X-ray images are increased through histogram stretching methodology. Second, to strengthen the high frequency signal and local contrast, we applied local contrast enhancement technique. Third, to improve the edge clearness, Unsharp masking is applied to enhance edges, making objects more visible. Forth, the super-resolution method of the Residual Dense Block (RDB) is used for noise reduction and image enhancement. Last, the Yolov5 algorithm is employed to train and detect foreign objects after learning. Using the proposed method in this study, experimental results show an improvement of more than 10% in performance metrics such as precision compared to low-density images.