• Transactions of the Korean Society of Mechanical Engineers B
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• v.41 no.3
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• pp.205-209
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• 2017

Unlike spherical drop impact, ellipsoidal drop impact can control the bouncing height on a heated surface by significantly altering impact behavior. To scrutinize the effect of the aspect ratio (AR) of the drop on the bounce suppression, in this study, non-axisymmetric spreading behaviors are observed from two side views and characterized based on the spreading width of the drop for horizontal principal axes. In addition, the maximum spreading width is investigated for various ARs. The results show that as the AR increases, the maximum spreading width of the minor axis increases, whereas that of the major axis shows no significant variation. In the regime of high AR and high impact velocity, liquid fragmentations by three parts are observed during bouncing. These fragmentations are discussed in this work. The hydrodynamic features of ellipsoidal drop impact will help understand bouncing control on non-wetting surfaces for several applications, such as self-cleaning and spray cooling.

• Microbiology and Biotechnology Letters
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• v.23 no.2
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• pp.236-242
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• 1995

Biological control of soilborne plant pathogens by the addition of antagonistic microorganisms to the soil may offer a practical supplement or alternative to existing disease management strategies that depend heavily on chemical pesticides. Soil amendment with antagonistic microbes was non-effective because of high cost, low efficacy, and inconvenient usage on the treatment course. Therefore, seed coating formulation for the application of biological seed treatments has been being to apply successful disease suppression for many important crops. The objectives of this study were to investigate the optimal condition for the spore production of biocontrol agent Bacillus subtilis YBL-7 and the liquid coating formulation that contained a suspension of a proper aqueous binder, as well as a ground fine solid particulate material. The maximum yield has been obtained from 60 hrs-old culture at 30$\circ$C in spore forming (SF) medium containing 0.8% nutrient broth, 0.05% yeast extract, 10$^{-1}$ M MgCl$^{2}$, 10$^{-4}$ M MnCl$^{2}$, 10$^{-5}$ M dipicolinic acid, and pH 6.5. The optimal condition of dried spore preparation was achieved when cells of B. subtilis YBL-7 was heat-dried with 50$\circ$C for 2 hrs.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.77-80
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• 2013

SURF algorithm is an algorithm to extract feature points and to generate descriptors from input images. It is robust to change of environment such as scale, rotation, illumination and view points. Because of these features, it is used for many image processing applications such as object recognition, constructing panorama pictures and 3D image restoration. But there is disadvantage for real time operation because many recognition algorithms such as SURF algorithm requires a lot of calculations. In this paper, we propose a design of feature extractor and descriptor generator based on SURF for high memory efficiency. The proposed design reduced a memory access and memory usage to operate in real time.

• Journal of Institute of Control, Robotics and Systems
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• v.11 no.5
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• pp.423-428
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• 2005

This paper proposes a new edge detection method using a $3{\times}3$ ideal binary pattern and lookup table (LUT) for the mobile robot localization without any parameter adjustments. We take the mean of the pixels within the $3{\times}3$ block as a threshold by which the pixels are divided into two groups. The edge magnitude and orientation are calculated by taking the difference of average intensities of the two groups and by searching directional code in the LUT, respectively. And also the input image is not only partitioned into multiple groups according to their intensity similarities by the histogram, but also the threshold of each group is determined by fuzzy reasoning automatically. Finally, the edges are determined through non-maximum suppression using edge confidence measure and edge linking. Applying this edge detection method to the mobile robot localization using projective invariance of the cross ratio. we demonstrate the robustness of the proposed method to the illumination changes in a corridor environment.

• Journal of the Korea Institute of Military Science and Technology
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• v.22 no.1
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• pp.1-10
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• 2019

In this paper, we propose the track initiation algorithm based on the weighted score for TWS radar tracking. This algorithm utilizes radar velocity information to calculate the probabilistic track score and applies the Non-Maximum-Suppression(NMS) to confirm the targets to track. This approach is understood as a modification of a conventional track initiation algorithm in a probabilistic manner. Also, we additionally apply the weighted Hough transform to compensate a measurement error, and it helps to improve the track detection probability. We designed the simulator in order to demonstrate the performance of the proposed track initiation algorithm. The simulation result show that the proposed algorithm, which reduces about 40 % of a false track probability, is better than the conventional algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3608-3626
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• 2021

The detection of bolts is an important task in high-speed train inspection systems, and it is frequently performed to ensure the safety of trains. The difficulty of the vision-based bolt inspection system lies in small sample defect detection, which makes the end-to-end network ineffective. In this paper, the problem is resolved in two stages, which includes the detection network and cascaded classification networks. For small bolt detection, all bolts including defective bolts and normal bolts are put together for conducting annotation training, a new loss function and a new boundingbox selection based on the smallest axis-aligned convex set are proposed. These allow YOLOv3 network to obtain the accurate position and bounding box of the various bolts. The average precision has been greatly improved on PASCAL VOC, MS COCO and actual data set. After that, the Siamese network is employed for estimating the status of the bolts. Using the convolutional Siamese network, we are able to get strong results on few-shot classification. Extensive experiments and comparisons on actual data set show that the system outperforms state-of-the-art algorithms in bolt inspection.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.34 no.1
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• pp.73-77
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• 2021

Inorganic-organic hybrid perovskite solar cells have demonstrated considerable improvements, reaching 25.5% of certified power conversion efficiency in 2020 from 3.8% in 2009. In normal structured perovskite solar cells, TiO2 electron-transporting materials require heat treatment process at a high temperature over 450℃ to induce crystallinity. Inverted perovskite solar cells have also been studied to exclude the additional thermal process by using [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) as a non-oxide electron-transporting layer. However, the drawback of the PCBM layer is a charge accumulation at the interface between PCBM and a metal electrode. The impact of bathocuproin (BCP) buffer layer on photovoltaic performance has been investigated herein to solve the problem of PCBM. 2-mM BCP-modified perovskite solar cells were observed to exhibit a maximum efficiency of 12.03% compared with BCP-free counterparts (5.82%) due to the suppression of the charge accumulation at the PCBM-Au interface and the resulting reduction of the charge recombination between perovskite and the PCBM layer.

• International journal of advanced smart convergence
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• v.11 no.2
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• pp.22-29
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• 2022

In this paper, for the purpose of designing an real-time unmanned monitoring system, the YOLOv5s (small) object detection model was applied on the NVIDIA TX2^TM AI (Artificial Intelligence) edge computing platform in order to design the fundamental function of an unmanned monitoring system that can detect objects in real time. YOLOv5s was applied to the our real-time unmanned monitoring system based on the performance evaluation of object detection algorithms (for example, R-CNN, SSD, RetinaNet, and YOLOv5). In addition, the performance of the four YOLOv5 models (small, medium, large, and xlarge) was compared and evaluated. Furthermore, based on these results, the YOLOv5s model suitable for the design purpose of this paper was ported to the NVIDIA TX2^TM AI edge computing system and it was confirmed that it operates normally. The real-time unmanned monitoring system designed as a result of the research can be applied to various application fields such as an security or monitoring system. Future research is to apply NMS (Non-Maximum Suppression) modification, model reconstruction, and parallel processing programming techniques using CUDA (Compute Unified Device Architecture) for the improvement of object detection speed and performance.

• Smart Structures and Systems
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• v.33 no.2
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• pp.105-118
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• 2024

In order to realize tiny bridge crack discovery by UAV-based machine vision, a novel method combining deep learning and tensor voting is proposed. Firstly, the grid images of crack are detected and descripted based on SE-ResNet50 to generate feature points. Then, the probability significance map of crack image is calculated by tensor voting with feature points, which can define the direction and region of crack. Further, the crack detection anchor box is formed by non-maximum suppression from the probability significance map, which can improve the robustness of tiny crack detection. Finally, a case study is carried out to demonstrate the effectiveness of the proposed method in the Xiangjiang-River bridge inspection. Compared with the original tensor voting algorithm, the proposed method has higher accuracy in the situation of only 1-2 pixels width crack and the existence of edge blur, crack discontinuity, which is suitable for UAV-based bridge crack discovery.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.125-126
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• 2021

In order to improve the housing culture, construction changes for the utilization of diverse and multifunctional spaces are appearing in response to the increasing diverse needs of consumers. Cellular Light-weight Concrete (CLC) is being developed for use in fire-resistant heat-insulating walls and non-bearing walls. However, manufacturing non-uniformity has become a problem as a drawback due to the use of foamed bubbles and normal temperature curing, and additional research is required. Therefore, in order to suppress cracks due to drying shrinkage, silica sand is mixed with CLC to try to understand its characteristics. In the experiment, the compressive strength from 7 to 28 days of age was measured via a constant temperature and humidity chamber, and the drying shrinkage was analyzed according to each condition using a strain gauge. The compressive strength of matrix tends to decrease as the substitution rate of silica sand increases. This is judged by the result derived from the fact that the specific surface area of silica sand is smaller than that of slag. Based on KS F 2701 (ALC block), the compressive strength of 0.6 products is 4.9 MPa or more as a guide, so the maximum replacement rate of silica sand that satisfies this can be seen at 60%. Looking at the change in drying shrinkage for just 7 days, the shrinkage due to temperature change and drying is 0.7 mm, and the possibility of cracking due to shrinkage can be seen, and it seems that continuous improvement and supplementation are needed in the future.