• Journal of the Korean Society of Industry Convergence
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• v.24 no.3
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• pp.363-371
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• 2021

Forest operations like timber harvesting have already been mechanized to reduce hazards to the worker and increase productivity. However, timber harvesting operations have still been considered potentially dangerous and expensive on steep terrain. Teleoperation, to control the timber harvesting machine at a distance, has the potential to improve the safety, productivity and efficiency of harvesting operations on steep terrain. To verify the effects of teleoperation, an experimental prototype system of a monitor image-based teleoperation was constructed using a real forestry machine. In this study, the productivity of excavator based grapple loader, which is one of the most used mechanized harvesting equipment in the timber production, was analyzed using time-study method. Factors like skill and age of operators, influencing loader productivity in timber loading operation were also evaluated by statistical analysis. Productivity analysis results showed that less experienced operators were more productive than experienced operators for teleoperation through image of monitors in the operator cabin. These results are shown to be unfamiliar to the monitor image and different loading operation pattern by operators. According to the results, the monitor image-based teleoperation system of forestry machine need to improve the resolution and installation position of camera. It was expected that additional studies will be needed for real-time remote control of forestry machine in the future.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.4
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• pp.99-105
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• 2023

In this paper, an intelligent CCTV was designed and experimentally developed by using an IOT device, Raspberry Pi, and artificial intelligence technology. Object Detection technology was used to detect the number of people on the CCTV screen, and Action Detection technology provided by OpenPose was used to detect emergency situations. The proposed system has a structure of CCTV, server and client. CCTV uses Raspberry Pi and USB camera, server uses Linux, and client uses iPhone. Communication between each subsystem was implemented using the MQTT protocol. The system developed as a prototype could transmit images at 2.7 frames per second and detect emergencies from images at 0.2 frames per second.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.6
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• pp.3455-3459
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• 2014

This paper reports the design and experiments for a high drive force of projectile in a coil gun system. Currently, the coil gun has been studied to apply an electromagnetic launcher. A coil gun launches a projectile by the attractive magnetic force of the electromagnetic coil. The drive force of projectile is proportional to the magnetic force generated by the electromagnetic coil. The current affects the life of the coil and the current limit exists. Therefore, the coil gun design, which does not exceed the current limit and the magnetic forces are at the maximum, is required. For this purpose, this study calculated the magnetic flux density and forces of the coil gun system and determined the current limit of the coil using the Onderdonk's equation. Based on the design result, a prototype was manufactured and an experiment was conducted to measure the muzzle velocity of the projectile. The fired projectile was analyzed using a CCD camera, and the muzzle velocity was 21m/s. In addition, a comparison of the experimental value and analysis value using commercial electromagnetic analysis software MAXWELL revealed an error of approximately 9.5%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.1-8
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• 2020

Air ducts installed for ventilation inside buildings accumulate contaminants during their service life. Robots are installed to clean the air duct at low cost, but they are still not fully automated and depend on manpower. In this study, an intersection detection algorithm for autonomous driving was applied to an air duct cleaning robot. Autonomous driving of the robot was achieved by calculating the distance and angle between the extracted point and the center point through the intersection detection algorithm from the camera image mounted on the robot. The training data consisted of CAD images of the duct interior as well as the cross-point coordinates and angles between the two boundary lines. The deep learning-based CNN model was applied as a detection algorithm. For training, the cross-point coordinates were obtained from CAD images. The accuracy was determined based on the differences in the actual and predicted areas and distances. A cleaning robot prototype was designed, consisting of a frame, a Raspberry Pi computer, a control unit and a drive unit. The algorithm was validated by video imagery of the robot in operation. The algorithm can be applied to vehicles operating in similar environments.

• Journal of Korea Multimedia Society
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• v.8 no.10
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• pp.1369-1382
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• 2005

Vehicle segmentation, which extracts vehicle areas from road scenes, is one of the fundamental opera tions in lots of application areas including Intelligent Transportation Systems, and so on. We present a vehicle segmentation approach for still images captured from outdoor CCD cameras mounted on the supporting poles. We first divided the input image into a set of two-dimensional grids and then calculate the feature values of the edges for each grid. Through analyzing the feature values statistically, we can find the optimal rectangular grid area of the vehicle. Our preprocessing process calculates the statistics values for the feature values from background images captured under various circumstances. For a car image, we compare its feature values to the statistics values of the background images to finally decide whether the grid belongs to the vehicle area or not. We use dynamic programming technique to find the optimal rectangular gird area from these candidate grids. Based on the statistics analysis and global search techniques, our method is more systematic compared to the previous methods which usually rely on a kind of heuristics. Additionally, the statistics analysis achieves high reliability against noises and errors due to brightness changes, camera tremors, etc. Our prototype implementation performs the vehicle segmentation in average 0.150 second for each of $1280\times960$ car images. It shows $97.03\%$ of strictly successful cases from 270 images with various kinds of noises.

• The Journal of the Korea Contents Association
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• v.10 no.11
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• pp.20-29
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• 2010

The typical Kinetic Family Drawing (KFD) Web database system, a form of prototype system, has been developed, relying on the suggestions from family art therapists, with an aim to handle large amounts of assessment data and to facilitate effective implement of assessment activities. However, unfortunately such a system has an intrinsic problem that it fails to collect clients' behaviors, attitudes, facial expressions, voices, and other critical information observed while they are drawing. Accordingly we propose the ontology based video event analysis and video retrieval system in this paper, in order to enhance the function of a KFD Web database system by using a web camera and drawing tool. More specifically, a newly proposed system is designed to deliver two kinds of services: the client video retrieval service and the sketch video retrieval service, accompanied by a summary report of occurred events and dynamic behaviors relative to each family member object, respectively. The proposed system can support the reinforced KFD assessments by providing quantitative and subjective information on clients' working attitudes and behaviors, and KFD preparation processes.

• Journal of The Korean Association of Information Education
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• v.11 no.4
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• pp.471-482
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• 2007

These days UCC(User-created content) is being made and shared increasingly in entertainment and sports area, but its life cycle seems to be very short and the cases that it is used for an education or a learning purposes are not common yet. In this study a new methodology is suggested for adapting a UCC to a distance education. A teacher upload the movie that he or she made for the distance education system, so the students can carry out the self-centered learning procedure. After that, the students send their own movie files to the teacher, and get a feedback from the teacher as a evaluation of the course. In this study a distance education system was established as a prototype, and a short bamboo flute class was chosen for this study from the specialty developmental education program of the elementary school. According to the result of the questionnaire the students thought that their performance skill was improved a lot and they were satisfied with the learning program and the method of evaluation. They also answered that their skills dealing with a camera, a camcorder and a computer got much better. Moreover, most of the students thought that the relationships with their friends and their parents got better also because they spent lots of time together making and watching the movie files for this education program.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.73-87
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• 2021

Special theaters were created to provide a sense of immersion and spectacles due to differentiated screens, sound, seating facilities, and advanced services, and also expanded screens. The purpose of this study is to perform comparative analysis of the technical characteristics formats shown in special theaters(3D film, 4DX, IMAX, ScreenX, and VR) in order to identify and find ways to overcome the technological limitations in production. The various formats show differences in field of view depending on the exhibition technology and these differences affect the mise-en-scene, narrative, and editing of the film and consequently result in changes in the production environment and process. Therefore, directors and creators must understand the technological features and limitations of the new formats before making their approach. However, a new format encounters limitations on production sets due to the decline of technical education and succession. In situations where shooting with a special camera is essential, the particular characteristics of each format should be carefully considered from the planning stage but financial problems arise due to increase in production period and cost. To overcome these various obstacles, it is essential to first identify problems and present alternatives through in-depth research on the production set of each format. Finally, this research aims to explore the prototype of each format and analyze the current state of production technology with formats that have not been adapted to the market trends by combining with the other formats and showing that they can survive in new ways.

• Geophysics and Geophysical Exploration
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• v.8 no.4
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• pp.270-279
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• 2005

Under the research project supported by Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT), we have conducted the development of GPR systems for landmine detection. Until 2005, we have finished development of two prototype GPR systems, namely ALIS (Advanced Landmine Imaging System) and SAR-GPR (Synthetic Aperture Radar-Ground Penetrating Radar). ALIS is a novel landmine detection sensor system combined with a metal detector and GPR. This is a hand-held equipment, which has a sensor position tracking system, and can visualize the sensor output in real time. In order to achieve the sensor tracking system, ALIS needs only one CCD camera attached on the sensor handle. The CCD image is superimposed with the GPR and metal detector signal, and the detection and identification of buried targets is quite easy and reliable. Field evaluation test of ALIS was conducted in December 2004 in Afghanistan, and we demonstrated that it can detect buried antipersonnel landmines, and can also discriminate metal fragments from landmines. SAR-GPR (Synthetic Aperture Radar-Ground Penetrating Radar) is a machine mounted sensor system composed of B GPR and a metal detector. The GPR employs an array antenna for advanced signal processing for better subsurface imaging. SAR-GPR combined with synthetic aperture radar algorithm, can suppress clutter and can image buried objects in strongly inhomogeneous material. SAR-GPR is a stepped frequency radar system, whose RF component is a newly developed compact vector network analyzers. The size of the system is 30cm x 30cm x 30 cm, composed from six Vivaldi antennas and three vector network analyzers. The weight of the system is 17 kg, and it can be mounted on a robotic arm on a small unmanned vehicle. The field test of this system was carried out in March 2005 in Japan.