• Ecology and Resilient Infrastructure
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• 제7권4호
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• pp.274-283
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• 2020

A large amount of fine dust is generated during the process of pavement cutting. Consequently, reducing the amount of fine dust generated during pavement cutting is crucial for the overall management of fine dust. Based on this premise, in this study, a conceptual model is proposed for a device that can be employed for recovering scattered dust generated at the site of pavement cutting. The economic feasibility associated with the incorporation of the proposed model was analyzed. Results obtained from the economic feasibility analysis of the proposed conceptual model indicate that the benefit ratio is 2.96, which is significantly higher than 1. The rate of return is found to be 62.78%, which significantly exceeds the minimum expected rate of return (i.e., 10%), as established on the basis of interviews conducted with companies that implement pavement cutting. Furthermore, the break-even point is found to be at approximately 21.6 months. Hence, the proposed pavement cutter, which features dust suction and a low noise level, is economically feasible.

• Journal of the Korea Academia-Industrial cooperation Society
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• 제22권1호
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• pp.338-344
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• 2021

In this study, an actual test procedure was considered for the effective operation of a bulletproof test. The problems of the existing system were drawn in two ways. First, it is difficult to mount items of various shapes. Second, various test standards cannot be applied. To improve these problems, an automated and standardized mounting system was designed/applied to mount various items. The multi-purpose mount was compatible with the backing support for body armor testing. The sample holding frame was located inside and was designed to mount samples of various sizes and shapes through vertical movement and fixation without a separate detachment/attachment process. A comparison of the economics before and after the introduction of the item mounting system confirmed the effectiveness of the system by the increased number of daily tests and equipment utilization and reduced hourly cost.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• 제21권3호
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• pp.7-14
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• 2021

The emergence of the automated smart grid has become an essential device for responding to these problems and is bringing progress toward a smart grid-based society. Smart grid is a new paradigm that enables two-way communication between electricity suppliers and consumers. Smart grids have emerged due to engineers' initiatives to make the power grid more stable, reliable, efficient and safe. Smart grids create opportunities for electricity consumers to play a greater role in electricity use and motivate them to use electricity wisely and efficiently. Therefore, this study focuses on power demand management through machine learning. In relation to demand forecasting using machine learning, various machine learning models are currently introduced and applied, and a systematic approach is required. In particular, the GP learning model has advantages over other learning models in terms of general consumption prediction and data visualization, but is strongly influenced by data independence when it comes to prediction of smart meter data.

• Journal of the Korea Institute of Information Security & Cryptology
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• 제18권1호
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• pp.67-75
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• 2008

RFID(Radio Frequency Identification) system is an automated identification system that consists of tags and readers. They communicate with each other by RF signal. As a reader can identify many tags in contactless manner using RF signal, RFID system is expected to do a new technology to substitute a bar-code system. But RFID system creates new threats to the security and privacy of individuals, Because tags and readers communicate with each other in insecure channel using RF signal. So many people are trying to study various manners to solve privacy problems against attacks, but it is difficult to apply to RFID system based on low-cost Gen2. Therefore, We will propose a new encryption scheme using matrix based on Gen2 in RFID system in paper, and We will analyze our encryption scheme in view of the security and efficiency through a simulation and investigate application environments to use our encryption scheme.

• Journal of the Institute of Convergence Signal Processing
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• 제22권1호
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• pp.1-6
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• 2021

Recently, unmanned facilities have been introduced and operated in a way that reduces the cost and development of IT technology. Although unmanned facilities have advantages in terms of efficiency and economy, they have disadvantages such as failure of unmanned facilities and malfunctions, causing damage to facilities caused by intruders, and information leakage. In addition, it is necessary to visit the person in charge at all times to inspect the unmanned facilities, resulting in management costs. In this paper, we designed a system that checks the status of unmanned surveillance facilities in real time to check and automatically recover problems such as malfunctions, and to notify managers of situations by text messages in real time. The system to be designed consists of an integrated network video server (NVR) that receives and determines information on the operation status of the main equipment such as video, sound, and lighting, and a real-time text message using an SMS server.

• Journal of Aerospace System Engineering
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• 제15권1호
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• pp.56-62
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• 2021

The purpose of this study was to address a Remote Airborne Control Simulator that could simulate manned-unmanned teaming (MUM-T mission) for fixed wing UAV. With rapid technological development of unmanned aerial vehicle (UAV), the mission capability of UAV has tremendously grown. The role of UAV extends from simple reconnaissance to highly automated wingman. Accordingly, the requirement of UAV ground simulator should be modified as well to meet function requirements for simulating a MUM-T mission. A developed remote airborne control simulator was developed for conducting fixed wing UAV MUM-T operation simulations on the ground. The newest MUM-T examples, usage, and application of the developed remote airborne control simulator for MUM-T simulation are also presented in this study.

• Journal of The Korean Society of Agricultural Engineers
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• 제64권2호
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• pp.37-45
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• 2022

In-situ pilot experiment was carried out to establish a countermeasure on the soil loss from the hill side uplands that was rehabilitated by soil remediation method nearby abandoned mine sites for 2 years. It was considered that the affect of an inclination of cover surface, a stabilization treatment of cover layer by lime and steel refining slag (SRS) and a vegetation of soil surface as an effect factors in the experiment. It was constructed 4 lysimeters (plots, 22 m long, 4 m width) on the hilly side (37% inclination). One plot was control and two plots was treated by 1% lime and SRS. A remind one plot was modified a inclination to 27% to compare the affect of inclination on the amount of cover soil loss. It was attached a reservior tank and water level gauge in the end of lysimeters to measure the amount of the surface water flow and soil loss. It was also installed the automated sensors that could be collect the precipitation, soil moisture content, tension of cover layer in each plots. It was observed that the event of precipitation were caused the soil loss and it were related the physical and chemical properties of cover soil and inclination of surface layer of plots. During the experiment, it was exceeded the national regulation (50 t/ha/yr) in 37% inclination plots even though it was vegetated on the cover soil surface. However, in 27% inclination plot, it was shown that the amount of soil loss was maintained below the national regulation and, more ever, vegetation could reduce the the amount of soil loss. Therefore it was expected that such results could be applied to the future design of rehabilitation projects on the polluted farmland nearby abandoned mine sites.

• Journal of IKEEE
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• 제26권3호
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• pp.401-407
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• 2022

Recently, image processing technology for autonomous driving by recognizing objects and lanes through camera images to realize autonomous vehicles is being studied. Haze reduces the visibility of images captured by the camera and causes malfunctions of autonomous vehicles. To solve this, it is necessary to apply the haze removal function that can be processed in real time to the camera. Therefore, in this paper, the fog removal method of Sim with excellent performance is implemented with hardware capable of real-time processing. The proposed hardware was designed using Verilog HDL, and FPGA was implemented by setting Xilinx's xc7z045-2ffg900 as the target device. As a result of logic synthesis using Xilinx Vivado program, it has a maximum operating frequency of 276.932MHz and a maximum processing speed of 31.279fps in a 4K (4096×2160) high-resolution environment, thus satisfying the real-time processing standard.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제26권5호
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• pp.675-681
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• 2022

Recently, with the development of IoT technology and AI, unmanned and automated in various fields, interest in video processing, which is the basis for automation such as object recognition and object classification, is increasing. Various studies have been conducted on noise removal in the video processing process, which has a significant impact on image quality and system accuracy and reliability, but there is a problem that it is difficult to restore images for areas with high impulse noise density. In this paper proposes a filter algorithm based on partial mask and Lagrange interpolation to restore the damaged area of impulse noise in the image. In the proposed algorithm, the filtering process was switched by comparing the filtering mask with the noise estimate and the purge weight was calculated based on the low frequency component and the high frequency component of the image to restore the image.

• Journal of the Korea Institute of Information and Communication Engineering
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• 제27권1호
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• pp.41-46
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• 2023

Recently, big data analysis can use various techniques according to the development of machine learning. Big data collected in reality lacks an automated refining technique for the same or similar terms based on semantic analysis of the relationship between words. Since most of the big data is described in general sentences, it is difficult to understand the meaning and terms of the sentences. To solve these problems, it is necessary to understand the morphological analysis and meaning of sentences. Accordingly, NLP, a technique for analyzing natural language, can understand the word's relationship and sentences. Among the NLP techniques, the transformer has been proposed as a way to solve the disadvantages of RNN by using self-attention composed of an encoder-decoder structure of seq2seq. In this paper, transformers are used as a way to form associations between words in order to understand the words and phrases of sentences extracted from big data.