• International conference on construction engineering and project management
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• 2022.06a
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• pp.1243-1244
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• 2022

In recent years, the growing interest in off-site construction has led to factories scaling up their manufacturing and production processes in the construction sector. Consequently, continuous large-scale site monitoring in low-variability environments, such as prefabricated components production plants (precast concrete production), has gained increasing importance. Although many studies on computer vision-based site monitoring have been conducted, challenges for deploying this technology for large-scale field applications still remain. One of the issues is collecting and transmitting vast amounts of video data. Continuous site monitoring systems are based on real-time video data collection and analysis, which requires excessive computational resources and network traffic. In addition, it is difficult to integrate various object information with different sizes and scales into a single scene. Various sizes and types of objects (e.g., workers, heavy equipment, and materials) exist in a plant production environment, and these objects should be detected simultaneously for effective site monitoring. However, with the existing object detection algorithms, it is difficult to simultaneously detect objects with significant differences in size because collecting and training massive amounts of object image data with various scales is necessary. This study thus developed a large-scale site monitoring system using edge computing and a small-object detection system to solve these problems. Edge computing is a distributed information technology architecture wherein the image or video data is processed near the originating source, not on a centralized server or cloud. By inferring information from the AI computing module equipped with CCTVs and communicating only the processed information with the server, it is possible to reduce excessive network traffic. Small-object detection is an innovative method to detect different-sized objects by cropping the raw image and setting the appropriate number of rows and columns for image splitting based on the target object size. This enables the detection of small objects from cropped and magnified images. The detected small objects can then be expressed in the original image. In the inference process, this study used the YOLO-v5 algorithm, known for its fast processing speed and widely used for real-time object detection. This method could effectively detect large and even small objects that were difficult to detect with the existing object detection algorithms. When the large-scale site monitoring system was tested, it performed well in detecting small objects, such as workers in a large-scale view of construction sites, which were inaccurately detected by the existing algorithms. Our next goal is to incorporate various safety monitoring and risk analysis algorithms into this system, such as collision risk estimation, based on the time-to-collision concept, enabling the optimization of safety routes by accumulating workers' paths and inferring the risky areas based on workers' trajectory patterns. Through such developments, this continuous large-scale site monitoring system can guide a construction plant's safety management system more effectively.

• Steel and Composite Structures
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• v.18 no.1
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• pp.135-148
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• 2015

The cutout hole locating at the place of rib-to-diaphragm welded connection is adopted to minimize the restraint, which is caused by the floor-beam web to rib rotation at the support due to the unsymmetrical loads in orthotropic deck. In practice, an inevitable problem is that there is a large number of welding joint's cracks formed at the edge of cutout hole. In this study, a comparative experiment is carried out with two types of cutout hole, the circular arc transition and the vertical transition. The fatigue life estimation of specimens is investigated with the application of the structural hot spot stress approach by finite element analyses. The results are compared with the ones of the fatigue tests which are carried out on these full-scale specimens. Factors affecting the stress range are also studied.

• 한국정보디스플레이학회:학술대회논문집
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• 2004.08a
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• pp.623-624
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• 2004

The coating and estimation of gas and moisture barriers on polymer and glass substrates are receiving very much attention in passivation of organic light emitting devices (OLEDs). In this study, the encapsulation and lifetime measurement techniques of OLEDs were presented. The degradation mechanisms of bare and encapsulated OLEDs were investigated by the visual lifetime measurement (VLM) system with the parameters such as a pixel luminance(L), a luminance rms roughness(dL), a brightness area ratio(R), an edge degradation depth(D), etc.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.476-479
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• 2003

The Rough transform (HT) is often used for extracting global features in binary images, for example curve and line segments, from local features such as single pixels. The HT is useful due to its insensitivity to missing edge points and occlusions, and robustness in noisy images. However, it possesses some disadvantages, such as time and memory consumption due to the number of input data and the selection of an optimal and efficient resolution of the accumulator space can be difficult. Another problem of the HT is in the difficulty of peak detection due to the discrete nature of the image space and the round off in estimation. In order to resolve the problem mentioned above, a possibilistic C-means approach to clustering [1] is used to cluster neighboring peaks. Several experimental results are given.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.245-250
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• 2002

A successful on-line monitoring system for conventional machining operations has the potential to reduce cost, guarantee consistency of product quality, improve productivity and provide a safer environment for the operator. In fee-shape machining, typical signs of tool problems such as vibration, noise, chip flow characteristics and visual signs are almost unnoticeable without the use of special equipment. These characteristics increase the importance of automatic monitoring in fine-shape machining; however, sensing and interpretation of signals are more complex. In addition, the shafts of the micro-tools break before the typical extensive cutting edge of the tool gets damaged. In this study, the existence of a relationship between the characteristics of the cutting force and tool usage was investigated, and tool breakage detection algorithm was developed and the fellowing results are obtained. In data analysis, didn't use a relative error compare which mainly used in established experiment and investigated tool breakage detection algorithm in time domain which can detect AE and cutting force signals more effective and accurate.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.1
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• pp.8-15
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• 2003

The cylindrical object such as a water pipe or an oil pipeline are widely used in the infrastructure. Those pipes should be inspected periodically by human or a robot. However, since there is no edge or vertex in the pipe, it is very difficult for the robot to navigate along the pipe. In this paper in order to guide the robot along the axis of the pipe, an algorithm which find the axis using the measured range data from the robot to the pipe wall is developed The algorithm is verified using both the simulated range data and the measured one.

• International Journal of Aeronautical and Space Sciences
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• v.1 no.1
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• pp.92-102
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• 2000

In this study, the 750kW medium scale composite blade for the horizontal axis wind turbine system was designed and manufactured, and it was tested and evaluated by the specific structural test rig. In the test, it was found that local bucklings at the trailing edge of the blade and excessive deflections at the blade tip were happened. In order to solve these problems, the design of blade structure was modified. After improving the design, the abrupt change of deflection at the blade tip was reduced by smooth variation of the spar thickness and the local buckling was removed by extending the web length. The modified design was analyzed by the FEM, the safety and stability of the blade structure. And Fatigue life over 20 years was confirmed by using S-N linear damage method, Spera's method, etc.

• Journal of the Korean Institute of Navigation
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• v.14 no.3
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• pp.15-33
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• 1990

In recent years, propellers with various blade configurations such as highly skewed propellers are often fitted to ships from the viewpoint of reduction of vibration and noise. In the design of such propellers, design charts based on methodical series tests are to be complemented by theoretical calculations for accurate estimation of propeller open-water characteristics. The author intended to develop a method to estimate propeller open-water characteristics based on Quasi -Vortex - Lattice Method originally developed by Lan for solving planar thin wings, The Quasi - Vortex - Lattice Method has the simplicity and flexibility of Vortex - Lattice Method. Its accuracy is comparable to that of the Vortex - Lattice Method. Converged solution can be obtained with a small number of control points and further, leading edge suction force can be calculated directly. In the present paper, a numerical method to estimate propeller open-water characteristics based on the Quasi - Vortex - Lattice Method is reviewed and its application to marine propellers is described in detail. Comparison of propeller open-water characteristics obtained by the present method with experimental data showed good agreement for a wide variety of propellers including highly skewed propellers.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.4
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• pp.2109-2123
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• 2017

This paper presents a super-resolution reconstruction method based on sparse representation for two-dimensional bar code images. Considering the features of two-dimensional bar code images, Kirsch and LBP (local binary pattern) operators are used to extract the edge gradient and texture features. Feature extraction is constituted based on these two features and additional two second-order derivatives. By joint dictionary learning of the low-resolution and high-resolution image patch pairs, the sparse representation of corresponding patches is the same. In addition, the global constraint is exerted on the initial estimation of high-resolution image which makes the reconstructed result closer to the real one. The experimental results demonstrate the effectiveness of the proposed algorithm for two-dimensional bar code images by comparing with other reconstruction algorithms.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.11
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• pp.2768-2775
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• 1996

VariableBlock Matching algorithm is effective for the estimation of motion vector at complexor edge region by means of using variable block size with respect to the image block. But since VBM algorithm requires considerable number of operations, to solve this problem, we present an algorithm which uses difference images and quad tree structure, and estimates motion using various fast block matching algorithms.