• Clean Technology
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• v.28 no.4
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• pp.316-322
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• 2022

The flow pattern at the inlet of the catalyst layer in a selective catalytic reduction (SCR) system is one of the key parameters influencing the performance of the denitrification process. In the curved diffusing parts between the ammonia injection grids and the catalyst layers, guide vanes are installed to improve flow uniformity. In the present study, a numerical simulation has been performed to investigate the effect of the geometrical configuration of the guide vanes on the aerodynamic characteristics of a denitrification facility. This application has been made to the existing SCR process in a large-scaled coal-fired power plant. The flow domain to be solved covers the whole region of the flow passages from the exit of the ammonia injection gun to the exit of the catalyst layers. ANSYS-Fluent was used to calculate the three-dimensional steady viscous flow fields with the proper turbulence model fitted to the flow characteristics. The root mean square of velocity and the pressure drop inside the flow passages were chosen as the key performance parameters. Four types of guides vanes were proposed to improve the flow quality compared to the current configuration. The numerical results showed that the type 4 configuration was the most effective at improving the aerodynamic performance in terms of flow uniformity and pressure loss.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.9
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• pp.305-316
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• 2022

With the flood of digital data owing to the Internet of Things and big data, cloud service providers that process and store vast amount of data from multiple users can apply duplicate data elimination technique for efficient data management. The user experience can be improved as the notion of edge computing paradigm is introduced as an extension of the cloud computing to improve problems such as network congestion to a central cloud server and reduced computational efficiency. However, the addition of a new edge device that is not entirely reliable in the edge computing may cause increase in the computational complexity for additional cryptographic operations to preserve data privacy in duplicate identification and elimination process. In this paper, we propose an efficiency-improved duplicate data elimination protocol while preserving data privacy with an optimized user-edge-cloud communication framework by utilizing a trusted execution environment. Direct sharing of secret information between the user and the central cloud server can minimize the computational complexity in edge devices and enables the use of efficient encryption algorithms at the side of cloud service providers. Users also improve the user experience by offloading data to edge devices, enabling duplicate elimination and independent activity. Through experiments, efficiency of the proposed scheme has been analyzed such as up to 78x improvements in computation during data outsourcing process compared to the previous study which does not exploit trusted execution environment in edge computing architecture.

• Journal of Bio-Environment Control
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• v.31 no.3
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• pp.255-260
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• 2022

This study aimed to develop a service model that uses a deep learning algorithm for detecting diseases and pests in strawberries through image data. In addition, the pest detection performance of deep learning models was further improved by proposing segmented image data sets specialized in disease and pest symptoms. The CNN-based YOLO deep learning model was selected to enhance the existing R-CNN-based model's slow learning speed and inference speed. A general image data set and a proposed segmented image dataset was prepared to train the pest and disease detection model. When the deep learning model was trained with the general training data set, the pest detection rate was 81.35%, and the pest detection reliability was 73.35%. On the other hand, when the deep learning model was trained with the segmented image dataset, the pest detection rate increased to 91.93%, and detection reliability was increased to 83.41%. This study concludes with the possibility of improving the performance of the deep learning model by using a segmented image dataset instead of a general image dataset.

• Korean Journal of Optics and Photonics
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• v.33 no.2
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• pp.74-83
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• 2022

The entire process, from the raw material to the final system qualification test, has been developed to fabricate a large-diameter, lightweight reflective-telescope system for a satellite observation. The telescope with 3 anastigmatic mirrors has an aperture of 700 mm and a total mass of 66 kg. We baked a silicon carbide substrate body from a carbon preform using a reaction sintering method, and tested the structural and chemical properties, surface conditions, and crystal structure of the body. We developed the polishing and coating methods considering the mechanical and chemical properties of the silicon carbide (SiC) body, and we utilized a chemical-vapor-deposition method to deposit a dense SiC thin film more than 170 ㎛ thick on the mirror's surface, to preserve a highly reflective surface with excellent optical performance. After we made the SiC mirrors, we measured the wave-front error for various optical fields by assembling and aligning three mirrors and support structures. We conducted major space-environment tests for the components and final assembly by temperature-cycling tests and vibration-shock tests, in accordance with the qualifications for the space and launch environment. We confirmed that the final telescope achieves all of the target performance criteria.

• Journal of Aerospace System Engineering
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• v.17 no.1
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• pp.42-50
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• 2023

In this study, hexagonal ferrite powder with chemical formula SrZn_2-xCo_xFe₁₆O₂₇ was synthesized by a solid-state reaction method and its electromagnetic (EM) wave absorption characteristics were evaluated in the frequency range of 0.1-18 GHz with absorber thickness range of 0 - 10 mm. Reflection loss (RL) affecting electromagnetic wave absorption performance was calculated based on the transmission line theory using measured complex permeabilities and permittivities. RL spectra were also directly measured for some samples. They were well matched with calculated results. High-frequency complex permeability characteristics were changed gradually according to the amount of Co substitution (x). The EM wave absorption frequency band could be tuned accordingly. Hexaferrite samples with x = 1.0, 1.25, and 1.5 exhibited remarkable maximum electromagnetic wave absorption performances with minimum RL (RL_min) lowered than -50 dB. They also showed a very broad frequency band (Δf > 10 GHz) in which more than 90% of the EM wave energy absorption occurred (RL ≤ -10 dB).

• Journal of Internet Computing and Services
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• v.24 no.4
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• pp.57-64
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• 2023

The ROK military faces a significant challenge in its vigilance mission due to demographic problems, particularly the current aging population and population cliff. This study demonstrates the crucial role of the 4th industrial revolution and its core artificial intelligence algorithm in maximizing work efficiency within the Command&Control room by mechanizing simple tasks. To achieve a fully developed military surveillance system, we have chosen multi-object tracking (MOT) technology as an essential artificial intelligence component, aligning with our goal of an intelligent and automated surveillance system. Additionally, we have prioritized data visualization and user interface to ensure system accessibility and efficiency. These complementary elements come together to form a cohesive software application. The CCTV video data for this study was collected from the CCTV cameras installed at the 1st and 2nd main gates of the 00 unit, with the cooperation by Command&Control room. Experimental results indicate that an intelligent and automated surveillance system enables the delivery of more information to the operators in the room. However, it is important to acknowledge the limitations of the developed software system in this study. By highlighting these limitations, we can present the future direction for the development of military surveillance systems.

• Journal of Advanced Navigation Technology
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• v.27 no.2
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• pp.190-196
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• 2023

Recently, following the development of LIDAR technology which can detect distance from the object, the interest for LIDAR based 3D object detection network is getting higher. Previous networks generate inaccurate localization results due to spatial information loss during voxelization and downsampling. In this study, we propose an attention-based convergence method and a camera-LIDAR convergence system to acquire high-level features and high positional accuracy. First, by introducing the attention method into the Voxel-RCNN structure, which is a grid-based 3D object detection network, the multi-scale sparse 3D convolution feature is effectively fused to improve the performance of 3D object detection. Additionally, we propose the late-fusion mechanism for fusing outcomes in 3D object detection network and 2D object detection network to delete false positive. Comparative experiments with existing algorithms are performed using the KITTI data set, which is widely used in the field of autonomous driving. The proposed method showed performance improvement in both 2D object detection on BEV and 3D object detection. In particular, the precision was improved by about 0.54% for the car moderate class compared to Voxel-RCNN.

• Journal of agriculture & life science
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• v.50 no.3
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• pp.31-41
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• 2016

This study was conducted to develop a handy earth auger for use in sloppy and rugged forest terrains in order to reduce labor cost which comprises a major part of the production costs in forest afforestation projects. The first prototype is developed consist of two parts, the soil-digging screw and the battery power source. The specifications of the first prototype screw are: length of 170mm, a top diameter of 60mm, bottom diameter of 47mm, 23° angle for each helix, and a 50mm awl-head tip. The use of a single line of screw was selected for reduced weight. In addition, a power source of rotary DC Motor(WD-6G2425, WONILL, Korea) with a maximum torque of 30kgf-cm, rotation of 20-30rpm, K6G30C decelerator with a reduction ratio of 30:1 which could be used with no load for 48 was operated. In consideration of its weight, a lithium battery was utilized in line with the goal of developing a lightweight auger. In order to evaluate the performance of the first prototype, test sites were selected as 6 areas. The rotational force was found to be highest in area A(Solid area), followed by areas F(Mounted slope 40° area) and E(Mounted slope 30° area). It was also observed that in general, the rotational force increased along with the increase in soil depth with the maximum rotational force recorded at 10cm.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.4
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• pp.395-406
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• 2023

The first technological advance to improve the output and efficiency of the latest steam turbines operating in co-generation plants in Korea can be said to be progress in the field of materials that can use high-temperature, high-pressures steam. As a result of design efforts to improve the internal efficiency of steam turbines along with the development of materials, only a few manufacturers of steam turbine have produced high efficiency steam turbines. The internal efficiency of a steam turbine on the steam path operating for a long period of time is gradually lost owing to the limit of mechanical life, and efficiency and output decrease. Therefore, this study aims to develop a model that can analyze the steam flow path performance of HP (High Pressure) and IP (Intermediate Pressure) steam turbine for a co-generation plant using a commercial program and propose a performance calculation method. Owing to the complex performance calculation method of steam turbines, major variables are presented to serve as practically useful references for steam turbine practitioners. In addition, the thermal dynamic analysis(such as heat balance diagram calculation) and the the thermal dynamic calculation required for steam turbine performance calculation and the suitability of the steam turbine performance calculation results were compared with the performance test results.

• Convergence Security Journal
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• v.23 no.2
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• pp.27-36
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• 2023

In recent years, ransomware attacks have become more organized and specialized, with the sophistication of attacks targeting specific individuals or organizations using tactics such as social engineering, spear phishing, and even machine learning, some operating as business models. In order to effectively respond to this, various researches and solutions are being developed and operated to detect and prevent attacks before they cause serious damage. In particular, honeypots can be used to minimize the risk of attack on IT systems and networks, as well as act as an early warning and advanced security monitoring tool, but in cases where ransomware does not have priority access to the decoy file, or bypasses it completely. has a disadvantage that effective ransomware response is limited. In this paper, this honeypot is optimized for the user environment to create a reliable real-time dynamic honeypot file, minimizing the possibility of an attacker bypassing the honeypot, and increasing the detection rate by preventing the attacker from recognizing that it is a honeypot file. To this end, four models, including a basic data collection model for dynamic honeypot generation, were designed (basic data collection model / user-defined model / sample statistical model / experience accumulation model), and their validity was verified.