• Journal of the Institute of Electronics Engineers of Korea CI
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• v.42 no.4 s.304
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• pp.1-10
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• 2005

Recently, most of PLC has been using widely in automation equipment that is needed for field of industry automation. HMI is essential system for effective Control of many numbers of PLC. Even though early HMI system was consists of simple analog devices, however, HMI system could control or supervise PLC through display screen since it embeds various digital parts by development of technology in these days. HMI system consists of three parts as HMI hardware, an operating program for HMI equipment and a HMI screen editor. Among these elements, a Program for editing screen of HMI should provide various screen elements that helps users to edit each screens displayed on HMI. In this study, we design and implement screen edit program by object-oriented method for small HMI equipment and propose Prototype of embedded HMI system.

• Journal of Korean Society for Geospatial Information Science
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• v.7 no.2 s.14
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• pp.47-56
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• 1999

In this study, tie point observation in aerial triangulation was automated by the image processing methods. The technique includes boundary extraction and We matching processes. The procedures were applied to extract points of Interest and to find their conjugate points in the other images. The image coordinates of the identified points were then used to compute their absolute coordinates. An algorithm was developed in this study for the automation of observation in aerial triangulation, which is a manual process of selecting a tie point and recording the image coordinate of the selected point. The developed algorithm automates this process through the application of a mathematical operator to extract points of interest from an arbitrary image. The root m square error of image coordinates of the developed algorithm is $6.8{\mu}m$, which is close to that of the present analytical method. In a manual environment, the accuracy of the result of a photogrammetric process is heavily dependant on the level of skill and experience of the human operator. No such problem exists in an automated system. Also, as a result of the automated system, the time spent in the observation process could be reduced by a factor of 61.2%, thereby reducing the overall cost.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.20 no.3
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• pp.243-253
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• 2002

These days, the application range of digital photogrammetry is being extended actively, so the great variety of research is being progressed about improvement of measurement accuracy. This method can acquisite a high analysis accuracy and can acquisite easily image. But, So this method require a much processing time and effort by increasing a data amount, as the automation of processing must be completed for efficiency improvement of processing. In this study, the automation of image processing stage is established for multi-image aquisition and analysis about a radio telescope. Also, the precise measurement and the accuracy on object were intended to be improved. As a result of this study, the accuracy on the object which demands precise measurement was enhanced from multi image analysis, and also the assembly accuracy of the object could be checked by precise measurement and curve fitting.

• Nuclear Engineering and Technology
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• v.55 no.4
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• pp.1485-1494
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• 2023

The bow of the nuclear fuel assembly is a well-known phenomenon. One of the vital criteria during the history of nuclear fuel development has been fuel assembly's mechanical stability. Once present, the fuel assembly bow can lead to safety issues like excessive water gap and power redistribution or even incomplete rod insertion (IRI). The extensive bow can result in assembly handling and loading problems. This is why the fuel assembly's bow is one of the most often controlled geometrical factors during periodic fuel inspections for VVER when compared e.g. to on-site fuel rod gap measurements or other instrumental measurements performed on-site. Our proposed screening method uses existing video records for fuel inspection. We establish video frames normalization and aggregation for the purposes of bow measurement. The whole process is done by digital image processing algorithms which analyze rotations of video frames, extract angles whose source is the fuel set torsion, and reconstruct torsion schema. This approach provides results comparable to the commonly utilized method. We tested this new approach in real operation on 19 fuel assemblies with different campaign numbers and designs, where the average deviation from other methods was less than 2 % on average. Due to the fact, that the method has not yet been validated during full scale measurements of the fuel inspection, the preliminary results stand for that we recommend this method as a complementary part of standard bow measurement procedures to increase measurement robustness, lower time consumption and preserve or increase accuracy. After completed validation it is expected that the proposed method allows standalone fuel assembly bow measurements.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.1
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• pp.229-237
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• 2024

The logistics industry is converging with digital technology and growing into various logistics automation systems. However, inspection and loading/unloading, which are mainly performed in logistics work, depend on human resources, and the workforce is shrinking due to the decline in the productive population due to the low birth rate and aging. Although much research is being conducted on the development of automated logistics systems to solve these problems, there is a lack of research and development on load stacking stability, which has the potential to cause significant accidents. In this study, loading boxes with various sizes and positions of the center of gravity were set up, and a method for stacking that with high stability is presented. The size of the loading box is measured using a depth camera. The loading box's weight and center of gravity are measured and estimated by a developed device with four loadcells. The measurement error is measured through various repeated experiments and is corrected using the least squares method. The robot arm performs load stacking by determining the target position so that the centers of gravity of the loading boxes with unbalanced masses with a random sequence are transported in alignment. All processes were automated, and the results were verified by experimentally confirming load stacking stability.

• Journal of Digital Convergence
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• v.14 no.11
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• pp.91-100
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• 2016

The purpose of this study was to draw out success factors of port operation for New International Passenger Terminal(NIPT) in Incheon Port using the fuzzy method. In this study, the success factors of port operation were firstly selected by literature review and finally adopted them by in-depth interview with experts who had working experiences over 15 years in the field of Korea-China Carferry shipping business and stevedoring business. Success factors of port operation of the NIPT have been classified into four principal factors such as 'land's use side', 'productivity side', 'cost side' and 'services side', and the comparative analysis was conducted among success factors of port operation. According to the results of analysis, in terms of "land's use side", securing CY space of full-empty containers(0.857) was the most important factor. Among detailed factors of "productivity side", building terminal automation system(0.806) was significantly needed. In the factors of "cost side" and "service side", land rental costs(0.861) and schedule management of berth operation(0.798) were selected as the most important factors. Consequently, new international passenger terminal has implications that the main port operations should focus on reasonable rents calculation, ensuring proper space of CY, and building automation system of terminal, There is a need to proceed to conduct a comparative study of the same operating mode of an international passenger terminal.

• Korean Journal of Construction Engineering and Management
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• v.5 no.2 s.18
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• pp.90-105
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• 2004

Machines for crack sealing automation have been continually developed since the early 1990's because of the effectiveness of crack sealing that would be able to improve safety, quality and productivity. It has been considered challenging problem to detect crack network in pavement which includes noise (oil marks, skid marks, previously sealed cracks and inherent noise). Moreover, it is required to develop crack network mapping and modeling algorithm in order to accurately inject sealant along to the middle of cut crack network. The primary objective of this study is to propose machine vision algorithms (digital image processing algorithm and path planning algorithm) for fully automated pavement crack sealing. It is anticipated that the effective use of the proposed machine vision algorithms would be able to reduce error rate in image processing for detecting, mapping and modeling crack network as well as improving quality and productivity compared to existing vision algorithms.

• Korean Journal of Construction Engineering and Management
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• v.21 no.5
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• pp.55-63
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• 2020

Earthwork automation has emerged as a promising technology in the construction industry, and the application of earthwork automation technology is starting from the acquisition and processing of point cloud data of the site. Point cloud data has more than a million data due to vast extent of the construction site, and the processing time of the original point cloud data is critical because it takes tens or hundreds of hours to generate a Digital Terrain Model (DTM), and enhancement of the processing time can largely impact on the efficiency of the modeling. Currently, a benchmark program (BP) is actively used for the purpose of both point cloud data processing and BIM design as an integrated program in Korea, however, there are some aspects to be modified and refined. This study modified the BP, and developed an updated program by adopting a compile-based development environment, newly designed UI/UX, and OpenGL while maintaining existing PCD processing functions, and expended compatibility of the PCD file formats. We conducted a comparative test in terms of loading speed with different number of point cloud data, and the results showed that 92 to 99% performance increase was found in the developed program. This program can be used as a foundation for the development of a program that reduces the gap between design and construction by integrating PCD and earthwork BIM functions in the future.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.16 no.6
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• pp.392-399
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• 2023

This paper proposes a deep learning model to determine the region and depth of cabbage cores for robotic automation of the cabbage core removal process during the kimchi manufacturing process. In addition, rather than predicting the depth of the measured cabbage, a model was presented that simultaneously detects and classifies the area by converting it into a discrete class. For deep learning model learning and verification, RGB images of the harvested cabbage 522 were obtained. The core region and depth labeling and data augmentation techniques from the acquired images was processed. MAP, IoU, acuity, sensitivity, specificity, and F1-score were selected to evaluate the performance of the proposed YOLO-v4 deep learning model-based cabbage core area detection and classification model. As a result, the mAP and IoU values were 0.97 and 0.91, respectively, and the acuity and F1-score values were 96.2% and 95.5% for depth classification, respectively. Through the results of this study, it was confirmed that the depth information of cabbage can be classified, and that it can be used in the development of a robot-automation system for the cabbage core removal process in the future.

• Journal of the Korea Society for Simulation
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• v.33 no.4
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• pp.1-9
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• 2024

This study addresses 3D simulation technology that models real-world objects and environments to simulate various scenarios. Due to their ability to reduce risk, lower costs, and repeatedly experiment with multiple scenarios, 3D simulators are utilized in various fields such as healthcare, automotive, and aviation industries. In this paper, we aim to introduce the concept of Simultaneous Localization and Mapping (SLAM) technology, which constructs maps in real-time as robots move, with the objective of practical application in simulations for robotic process supply chain automation. This approach focuses on resolving the mismatch issues of conventional map construction methods in real-world environment, thereby producing more accurate and practical simulation results. Specifically, the proposed method enables robots to autonomously understand their environment and construct maps, allowing data obtained in the virtual environment to be immediately and integratively applied to actual robot operations. Through this process, simulations can provide advantages for real-world environments beyond mere testing. This integrated simulation system is expected to enhance robot performance even under complex environmental conditions and significantly improve the accuracy and efficiency of processes.