• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.8B
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• pp.1567-1576
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• 1999

In this paper, we propose new methods to detect a scene cut and a dissolve region in compressed MPEG video sequences. The scene cut detection method uses edge images obtained using DCT AC coefficients and the dissolve detection method utilizes the macroblock type information of the MPEG stream. The proposed scene cut detection method is insensitive to brightness and can detect scene changes more precisely than the methods using DC coefficients since AC edge images can express original images more exactly than DC edge images do. The proposed dissolve detection method using the number of intra macroblocks(MBs) computationally efficient since it does not require the decoding process. Experimental results show that the proposed methods perform better in detection scene changes than conventional other methods.

• Journal of Power System Engineering
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• v.22 no.6
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• pp.28-35
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• 2018

The large-eddy simulation (LES) was carried out to evaluate the instantaneous vector and vorticity profiles of a small-size axial fan (SSAF) at the operating point of full-flowrate. The downstream flow of the SSAF exhibits a shorter axial flow when not fully developed, especially the stronger vortex appears at the edge near the flow end. On the other hand, the downstream flow of the SSAF exhibits a longer axial flow, and the weaker vortex appears at the edge near the flow end when the flow is sufficiently developed. Moreover, in the downstream of the SSAF, a periodic and intermittent flow pattern appears at the edge showing the axial flow, and the instantaneous vorticity contour lines showing the form of a circle group are distributed at specific intervals from the downstream region of the blade tip, which is considered to be the result of the intermittency phenomenon influenced by the number of blades and the number of revolutions.

• Journal of Convergence for Information Technology
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• v.7 no.2
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• pp.77-82
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• 2017

In this paper, a new security algorithm to recognize the type of the vehicle with the vehicle image as a input image is suggested. The vehicle recognition security algorithm is composed of five core parts, such as the input image, background removal, edge areas extraction, pre-processing(binarization), and the vehicle recognition. Therefore, the final recognition rate of the security algorithm for vehicle type recognition can be affected by the function and efficiency of each step. After inputting image into a gray scale image and removing backgrounds, the binarization is performed by extracting only the edge region. After the pre-treatment process for making outlines clear, the type of vehicles is categorized into large vehicles, passenger cars and motorcycles through the ratio of height and width of the vehicle.

• Journal of Sensor Science and Technology
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• v.28 no.3
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• pp.164-170
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• 2019

In this paper, a lane detection and tracking algorithm based on vision sensors and employing a robust filter for inner edge detection is proposed for developing a lane departure warning system (LDWS). The lateral offset value was precisely calculated by applying the proposed filter for inner edge detection in the region of interest. The proposed algorithm was subsequently compared with an existing algorithm having lateral offset-based warning alarm occurrence time, and an average error of approximately 15ms was observed. Tests were also conducted to verify whether a warning alarm is generated when a driver departs from a lane, and an average accuracy of approximately 94% was observed. Additionally, the proposed LDWS was implemented as an embedded system, mounted on a test vehicle, and was made to travel for approximately 100km for obtaining experimental results. Obtained results indicate that the average lane detection rates at day time and night time are approximately 97% and 96%, respectively. Furthermore, the processing time of the embedded system is found to be approximately 12fps.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.912-919
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• 2022

The study is an image-based assessment that uses image processing techniques to determine the condition of concrete with surface cracks. The preparations of the dataset include resizing and image filtering to ensure statistical homogeneity and noise reduction. The image dataset is then segmented, making it more suited for extracting important features and easier to evaluate. The image is transformed into grayscale which removes the hue and saturation but retains the luminance. To create a clean edge map, the edge detection process is utilized to extract the major edge features of the image. The Otsu method is used to minimize intraclass variation between black and white pixels. Additionally, the median filter was employed to reduce noise while keeping the borders of the image. Image processing techniques are used to enhance the significant features of the concrete image, especially the defects. In this study, the tonal zones of the histogram and its properties are used to analyze the condition of the concrete. By examining the histogram, the viewer will be able to determine the information on the image through the number of pixels associated and each tonal characteristic on a graph. The features of the five tonal zones of the histogram which implies the qualities of the concrete image may be evaluated based on the quality of the contrast, brightness, highlights, shadow spikes, or the condition of the shadow region that corresponds to the foreground.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.12
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• pp.3364-3382
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• 2023

Remote sensing image segmentation plays an important role in realizing intelligent city construction. The current mainstream segmentation networks effectively improve the segmentation effect of remote sensing images by deeply mining the rich texture and semantic features of images. But there are still some problems such as rough results of small target region segmentation and poor edge contour segmentation. To overcome these three challenges, we propose an improved semantic segmentation model, referred to as MRU-Net, which adopts the U-Net architecture as its backbone. Firstly, the convolutional layer is replaced by BasicBlock structure in U-Net network to extract features, then the activation function is replaced to reduce the computational load of model in the network. Secondly, a hybrid multi-scale recognition module is added in the encoder to improve the accuracy of image segmentation of small targets and edge parts. Finally, test on Massachusetts Buildings Dataset and WHU Dataset the experimental results show that compared with the original network the ACC, mIoU and F1 value are improved, and the imposed network shows good robustness and portability in different datasets.

• JSTS:Journal of Semiconductor Technology and Science
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• v.14 no.4
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• pp.427-435
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• 2014

Segmented-channel MOSFETs (SegFETs) can achieve both good performance and variation robustness through the use of $HfO_2$ (a high-k material) to create the shallow trench isolation (STI) region and the very shallow trench isolation (VSTI) region in them. SegFETs with both an HTI region and a VSTI region (i.e., the STI region is filled with $HfO_2$, and the VSTI region is filled with $SiO_2$) can meet the device specifications for high-performance (HP) applications, whereas SegFETs with both an STI region and a VHTI region (i.e., the VSTI region is filled with $HfO_2$, and the STI region is filled with $SiO_2$) are best suited to low-standby power applications. AC analysis shows that the total capacitance of the gate ($C_{gg}$) is strongly affected by the materials in the STI and VSTI regions because of the fringing electric-field effect. This implies that the highest $C_{gg}$ value can be obtained in an HTI/VHTI SegFET. Lastly, the three-dimensional TCAD simulation results with three different random variation sources [e.g., line-edge roughness (LER), random dopant fluctuation (RDF), and work-function variation (WFV)] show that there is no significant dependence on the materials used in the STI or VSTI regions, because of the predominance of the WFV.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.643-648
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• 2011

Fatigue crack in most rails take place by rolling contact between wheel and rail in railway industry. Therefore, it is critical to understand the rolling contact phenomena, especially for the three-dimensional situation. In this paper the steady-state rolling contact problem of KTX wheel and rail (UIC60) has been studied with three-dimensional finite element analysis. The variation of contact pressure and contact stresses on rolling contact surface were obtained using the finite element method. The three-dimensional distribution of contact stresses on the contact surface are investigated. Results show that the distribution of shear stress and contact stress (von Mises) on the contact surface varies rapidly as a result of the variation of stick-slip region. The contact stress at the leading edge is greater than at the trailing edge because of stick and slip phenomena.

• Korean Journal of Computational Design and Engineering
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• v.2 no.4
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• pp.253-266
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• 1997

Pencil-curve machining, which is a single-pass ball-end milling along a concave edge on adie surface, is widely employed in die-surface machining. The cutter-path used for pencil-curve machining, which is the trajectory of the “ball-center point” of a ball-endmill sliding along a concave-edge region on the die surface, is called pencil-curve. Presented in the paper is a pencil-curve tracing algorithm in which “concave-type” sharp edges are computed from a “virtually digitized” model of the tool-envelope surface. The resulting “initial” pencil-cures are then refuted by applying a series of fairing operations. illustrative examples and methods for enhancing accuracy are also presented. The proposed pencil-curve tracing algorithm has been successfully implemented in a commercial CAM system specialized in die-machining and in the CAD/CAM system CATIA.

• Journal of Industrial Technology
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• v.17
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• pp.183-189
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• 1997

The computation of the flow around a supercritical airfoil with a divergent trailing edge(DTE) modification(DLBA 243) is compared to that of original supercritical airfoil(DLBA 186). For this computation, Reynolds-Averaged Navier-Stokes equations are solved with a linearized block implicit ADI method and a mixing length turbulence model. Results show the effects of the shock and separated flow regions on drag reduction due to DTE modification. Results also show that DTE modification accelerates the boundary layer flow near the trailing edges which has an effect similar to a chordwise extension that increases circulation and is consistent with the calculated increase in the recirculation region in the wake. Airfoil with DTE modification achieves the same lift coefficient at a lower incidence and thus at a lower drag coefficient, so that lift-to-drag ratio is increased in transonic cruise conditions compared to the original airfoil. The reduction in drag due to DTE modification is associated with weakening of shock strength and delay of shock which is greater than the increase in base drag.