• Korean Journal of Metals and Materials
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• v.48 no.5
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• pp.445-448
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• 2010

For an enhanced thermoelectric performance, one-dimensional heterostructure nanowires were created that consisted of aBi core and Te shell. The structure was fabricated by depositing Te in-situ onto a Bi nanowire grown by our unique OFF-ON (on-film formation of nanowires) method. After examining a cross-sectional TEM image, it was found that diffusive interface was formed between Bi and Te. Selected area electron diffraction revealed that the crystallinity of the Te shell was some what lower compared to the highly single-crystalline Bi core. The Bi-Te core/shell nanowires can be a smart structure that suppresses phonon transport by several scattering mechanisms, making the OFF-ON method the simplest way to realize that structure.

• Korean Journal of Metals and Materials
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• v.48 no.5
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• pp.462-468
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• 2010

Carbon Nanotubes (CNTs) have recently emerged as a material with outstanding properties. It has shown promising potential for applications in many engineering fields as electronic devices, thermal conductors, and light-weight composites. Researchers have investigated their use as reinforcements in themetal matrix composites of CNTs. In the present work, we decorated CNTs with Ni particles by electroless plating. The CNTs were wet-ball milled for various milling times with a nickel sulfate solution. The precipitated Ni particles were observed mainly by FESEM. In this study, the dispersion of the CNTs and Ni particles was improved with the addition of the surfactant. Also, as the CNTs were shortened and widened by an increased ball milling time, the size of the precipitated Ni particles increased. It was estimated that the CNTs were deformed and caused some defects on their surface during the ball milling process. Those defects were assumed to be heterogeneous nucleation sites for the Ni particles.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1777-1783
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• 2021

The use of drones is gradually increasing for the efficient maintenance of large-scale renewable energy power generation complexes. For a long time, photovoltaic panels have been photographed with drones to manage panel loss and contamination. Various approaches using artificial intelligence are being tried for efficient maintenance of large-scale photovoltaic complexes. Recently, semantic segmentation-based application techniques have been developed to solve the image classification problem. In this paper, we propose a classification model using semantic segmentation to determine the presence or absence of failures such as arcs, disconnections, and cracks in solar panel images obtained using a drone equipped with a thermal imaging camera. In addition, an efficient classification model was implemented by tuning several factors such as data size and type and loss function customization in U-Net, which shows robust classification performance even with a small dataset.

• Composites Research
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• v.34 no.6
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• pp.421-425
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• 2021

In this study, thermoplastic composites were manufactured using a thermoplastic resin (PEEK) with the same melting temperature and a highly heat-resistant carbon UD tapes with different carbon fibers (Type A, Type B). And the bonding characteristics and mechanical characteristics of each of the two produced thermoplastic composites by induction heating welding were examined. The bonding characteristics and mechanical characteristics of the thermoplastic composites were performed using C-Scan and B-Scan, which is a non-destructive inspection, and the single lap shear test, respectively. The temperature of the carbon composites surface was monitored using a thermal image camera.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.2
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• pp.193-198
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• 2022

Recently, place that you need to check wearing mask and body temperature to prevent the proliferation of COVID-19 increased. But these things often measured by man manually or by machine one by one, result may be different by measuring ways, so it wastes workforce. Also, the machine generally just measures the highest temperature of the face, criteria for fever can't be trusted too. A bottleneck may occur due to crowding of people at the entrance, and because most of the measurement sites are at one entrance, it is inconvenient to track the movement of COVID-19 Confirmed cases. Thus, in this study, we intend to propose a method for suppressing the spread of infection by automatically classifying and displaying in real time using camera, thermal camera, Haar Cascade, and result selection algorithm.

• Current Optics and Photonics
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• v.7 no.4
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• pp.435-442
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• 2023

These days, the size of a reflective telescope has been increasing for astronomical observation. An additional optical system usually assists a large ground telescope for image analysis or the compensation of air turbulence. To guide collimated light to the external optical system through a designated path, a coudé mirror is usually adopted. Including a collimator, a coudé mirror of a ground telescope is affected by gravity, depending on the telescope's pointing direction. The mirror surface is deformed by the weight of the mirror itself and its mount, which deteriorates the optical performance. In this research, we propose an optimization method for the coudé mirror assembly for a 1-m class ground telescope that minimizes the gravitational surface error (SFE). Here the mirror support positions and the sizes of the mount structure are optimized using finite element analysis and the response surface optimization method in both the horizontal and vertical directions, considering the telescope's altitude angle. Throughout the whole design process, the coefficients of the Zernike polynomials are calculated and their amplitude changes are monitored to determine the optimal design parameters. At the same time, the design budgets for the thermal SFE and the mass and size of the mount are reflected in the study.

• Journal of People, Plants, and Environment
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• v.22 no.3
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• pp.233-239
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• 2019

This study was conducted in order to predict the vase life of cut lily 'Woori Tower' flowers using a non-destructive thermal imaging technique. It was found that the temperature of cut lily flowers was maintained at 20℃ and was slightly lower than the air temperature until they bloomed. On the 11th day, when flowers bloomed, the temperature of leaves and flowers was measured to be 18.75±0.38℃ and 19.23±0.32℃ respectively, and their difference with ambient temperature was over 3℃. The flower temperature increased slightly when the vase life of cut lily flowers ended, and the temperature difference between the air and leaf temperature (1.77℃) and between the air and flower temperature (1.39℃) got smaller. No visible aging symptom was observed, but it was found that the temperature had risen due to water losses and less functional stomata. The vase life of cut lily flowers can be predicted based on changes in temperature and it will be also possible to predict the potential quality and vase life of cut flowers before harvesting them in greenhouses.

• Korean Journal of Artificial Intelligence
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• v.11 no.4
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• pp.1-8
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• 2023

In this paper, we propose a black ice detection platform framework using Convolutional Neural Networks (CNNs). To overcome black ice problem, we introduce a real-time based early warning platform using CNN-based architecture, and furthermore, in order to enhance the accuracy of black ice detection, we apply a multi-scale dilation convolution feature fusion (MsDC-FF) technique. Then, we establish a specialized experimental platform by using a comprehensive dataset of thermal road black ice images for a training and evaluation purpose. Experimental results of a real-time black ice detection platform show the better performance of our proposed network model compared to conventional image segmentation models. Our proposed platform have achieved real-time segmentation of road black ice areas by deploying a road black ice area segmentation network on the edge device Jetson Nano devices. This approach in parallel using multi-scale dilated convolutions with different dilation rates had faster segmentation speeds due to its smaller model parameters. The proposed MsCD-FF Net(2) model had the fastest segmentation speed at 5.53 frame per second (FPS). Thereby encouraging safe driving for motorists and providing decision support for road surface management in the road traffic monitoring department.

• Journal of Information Processing Systems
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• v.19 no.6
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• pp.791-802
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• 2023

The manual inspection of photovoltaic (PV) panels to meet the requirements of inspection work for large-scale PV power plants is challenging. We present a hot spot detection and positioning method to detect hot spots in batches and locate their latitudes and longitudes. First, a network based on the YOLOv3 architecture was utilized to identify hot spots. The innovation is to modify the RU_1 unit in the YOLOv3 model for hot spot detection in the far field of view and add a neural network residual unit for fusion. In addition, because of the misidentification problem in the infrared images of the solar PV panels, the DeepLab v3+ model was adopted to segment the PV panels to filter out the misidentification caused by bright spots on the ground. Finally, the latitude and longitude of the hot spot are calculated according to the geometric positioning method utilizing known information such as the drone's yaw angle, shooting height, and lens field-of-view. The experimental results indicate that the hot spot recognition rate accuracy is above 98%. When keeping the drone 25 m off the ground, the hot spot positioning error is at the decimeter level.

• Elastomers and Composites
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• v.58 no.4
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• pp.208-215
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• 2023

In this study, the properties of polyurethane-polydimethylsiloxane (PU-PDMS) hybrid foams containing different types and contents of physical blowing agents (PBAs) were investigated. Two types of blowing agents, namely physical blowing agents and thermally expandable microspheres (TEM), were applied. The apparent density was measured using precisely cut foam samples, and the pore size was measured using image software. In addition, the microstructure of the foam was confirmed via scanning electron microscopy and transmission electron microscopy. The thermal conductivities related to the microstructures of the different foams were compared. When 0.5 phr of the hydrocarbon-based PBA was added, the apparent density and pore size of the foam were minimal; however, the pore size was larger than that of neat foam. In contrast, the addition of 3 phr of TEM effectively reduced both the apparent density and pore size of the PBAs. The increase in resin viscosity owing to TEM could enhance bubble production stability, leading to the formation of more uniform and smaller pores. These results indicate that TEM is a highly efficient PBA that can be employed to decrease the weight and pore size of PU-PDMS hybrid foams.