• Journal of Convergence for Information Technology
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• v.12 no.1
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• pp.172-179
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• 2022

Unlike other processes such as washing, the ironing process in the laundry process is difficult to standardize and thus relies on manual labor. Unlike upper garments, pants have pleats at the waist as well as a crease line below the waist, Therefore, two separate ironing devices have been developed and used. However, in this method, problems such as additional worker input, space loss, and wrinkling of pants occur due to manual movement between processes, Consequently, a pants ironing device that combines the two equipments is required. The all-in-one pants ironing system described in this paper automatically sequentially irons the upper part and side of the pants regardless of the length, shape, and upper pleats of the pants. It also performs a self-diagnosis function while displaying the ironing progress on the user's monitor. As a result of this study, it became possible to double the amount of ironing and reduce power consumption by more than 20% compared to the case of using two independent equipment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.35-42
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• 2022

In this paper, a method to increase the combining efficiency and isolation of the combiner, the core module of SSPA (solid state amplifier), was studied. Specifically, the isolation was secured by matching the common port and the isolation port in the waveguide combiner. The matching structure for matching is in the form of a circular disk and is engraved inside the waveguide combiner. The structure is very simple, so it is possible to secure stable performance. And this structure showed more than 60 times higher critical power performance compared to previous studies, confirming that it is suitable for high output. And by combining 1-stage T-junction and 2, 3 stage MagicT combiner, miniaturization was achieved and the combining efficiency was optimized by reducing the insertion loss. The fabricated waveguide coupler obtained an isolation of 16dB or more and a coupling efficiency of 86.2%.

• Journal of the Korean Society of Propulsion Engineers
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• v.25 no.4
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• pp.43-52
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• 2021

In this study, performance modeling and simulation of a gas turbine engine, a constituent module, was performed for the integrated control of the CODOG structure, mechanical propulsion systems. The engine model used MATLAB/Simulink to facilitate integration with the host controller and other components, and was configured to enable input/output settings suitable for the system configuration and purpose. In general, engine manufacturers do not provide performance data for the engine and components. Therefore, as a modeling method for a gas turbine, a CMF method that obtains performance data by scaling the map of components was applied. Using the generated model and simulation program, steady-state and dynamic simulation analysis tests were performed, and reliability within 5% of the maximum error was secured for the final output of power.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.9
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• pp.78-84
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• 2022

An air circuit breaker (ACB) is an electrical protection device that interrupts abnormal fault currents that result from overloads or short circuits in a low-voltage power distribution line. The ACB consists of a main circuit part for current flow, mechanism part for the opening and closing operation of movable conductors, and arc-extinguishing part for arc extinction during the breaking operation. The driving mechanism of the ACB is a spring energy charging type. The faster the contact opening speed of the movable conductors during the opening process, the better the breaking performance. However, there is a disadvantage that the durability of mechanism decreases in inverse proportion to the use of a spring capable of accumulating high energy to configure the breaking speed faster. Therefore, to simultaneously satisfy the breaking performance and mechanical endurance of the ACB, its driving mechanism must be optimized. In this study, a dynamic model of the ACB was developed using the MDO(Mechanism Dynamics Option) module of CREO, which is widely used in multibody dynamics analysis. To improve the opening velocity, the Taguchi design method was applied to optimize the design parameters of an ACB with many linkages. In addition, to evaluate the improvement in the operating characteristics, the simulation and experimental results were compared with the MDO model and improved prototype sample, respectively.

• Journal of the Earthquake Engineering Society of Korea
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• v.25 no.2
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• pp.71-81
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• 2021

This paper presents a real-time, false-pick filter based on deep learning to reduce false alarms of an onsite Earthquake Early Warning (EEW) system. Most onsite EEW systems use P-wave to predict S-wave. Therefore, it is essential to properly distinguish P-waves from noises or other seismic phases to avoid false alarms. To reduce false-picks causing false alarms, this study made the EEWNet Part 1 'False-Pick Filter' model based on Convolutional Neural Network (CNN). Specifically, it modified the Pick_FP (Lomax et al.) to generate input data such as the amplitude, velocity, and displacement of three components from 2 seconds ahead and 2 seconds after the P-wave arrival following one-second time steps. This model extracts log-mel power spectrum features from this input data, then classifies P-waves and others using these features. The dataset consisted of 3,189,583 samples: 81,394 samples from event data (727 events in the Korean Peninsula, 103 teleseismic events, and 1,734 events in Taiwan) and 3,108,189 samples from continuous data (recorded by seismic stations in South Korea for 27 months from 2018 to 2020). This model was trained with 1,826,357 samples through balancing, then tested on continuous data samples of the year 2019, filtering more than 99% of strong false-picks that could trigger false alarms. This model was developed as a module for USGS Earthworm and is written in C language to operate with minimal computing resources.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.275-286
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• 2021

While art and culture always actively intervene and send messages to social issues and issues, there are critics who say that the way they show them goes against environmental issues. Therefore, this study compared and analyzed the environment-friendly methods applied to four types of exhibitions held at existing domestic art museums in order to derive environmentally sustainable exhibition content planning and operation plans. By deriving the method commonly applied to the four exhibitions, the wooden temporary walls that are discarded through local remanufacturing, use of waste resources, and prefabricated module walls were minimized. In addition, when printing/publishing, there were methods such as grafting eco-friendly inks and materials or avoiding the production of unnecessary printed matter. Based on these common factors, a plan that can be applied to each stage of exhibition hall construction and construction, printing and publishing, and exhibition hall operation was derived. However, it is necessary to approach more diverse cases in the future, and it is necessary to supplement the points to enhance scientific explanatory power in quantitative terms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.11
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• pp.4065-4083
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• 2021

Super-resolution can improve the clarity of low-resolution (LR) images, which can increase the accuracy of high-level compute vision tasks. Portable devices have low computing power and storage performance. Large-scale neural network super-resolution methods are not suitable for portable devices. In order to save the computational cost and the number of parameters, Lightweight image processing method can improve the processing speed of portable devices. Therefore, we propose the Enhanced Information Multiple Distillation Network (EIMDN) to adapt lower delay and cost. The EIMDN takes feedback mechanism as the framework and obtains low level features through high level features. Further, we replace the feature extraction convolution operation in Information Multiple Distillation Block (IMDB), with Ghost module, and propose the Enhanced Information Multiple Distillation Block (EIMDB) to reduce the amount of calculation and the number of parameters. Finally, coordinate attention (CA) is used at the end of IMDB and EIMDB to enhance the important information extraction from Spaces and channels. Experimental results show that our proposed can achieve convergence faster with fewer parameters and computation, compared with other lightweight super-resolution methods. Under the condition of higher peak signal-to-noise ratio (PSNR) and higher structural similarity (SSIM), the performance of network reconstruction image texture and target contour is significantly improved.

• Resources Recycling
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• v.31 no.5
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• pp.52-58
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• 2022

Silicon carbide powder was prepared from carbon black and silicon recovered from waste solar panels. In the solar power generation market, the number of crystalline silicon modules exceeds 90%. As the expiration date of a photovoltaic module arrives, the development of technology for recovering and utilizing silicon is very important from an environmental and economic point of view. In this study, silicon was recovered as silicon carbide from waste solar panels: 99.99% silicon powder was recovered through purification from a 95.74% purity waste silicon wafer. To examine the synthesis characteristics of SiC powder, purified 99.99% silicon powder and carbon powder were mixed and heat-treated (1,300, 1,400 and 1,500 ℃) in an Ar atmosphere. The characteristics of silicon and silicon carbide powders were analyzed using particle size distribution analyzer, XRD, SEM, ICP, FT-IR, and Raman analysis.

• Current Photovoltaic Research
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• v.10 no.3
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• pp.77-83
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• 2022

Renewable energy is receiving attention again as a way to realize carbon neutrality to overcome the climate change crisis. Among renewable energy sources, the installation of Photovoltaic is continuously increasing, and as of 2020, the global cumulative installation amount is about 590 GW and the domestic cumulative installation amount is about 17 GW. Accordingly, O&M technology that can analyze the power generation and fault diagnose about PV plants the is required. In this paper, a study was conducted to diagnose fault using I-V curves of PV strings and deep learning. In order to collect the fault I-V curves for learning in the deep learning, faults were simulated. It is partial shade and voltage mismatch, and I-V curves were measured on a sunny day. A two-step data pre-processing technique was applied to minimize variations depending on PV string capacity, irradiance, and PV module temperature, and this was used for learning and validation of deep learning. From the results of the study, it was confirmed that the PV fault diagnosis using I-V curves and deep learning is possible.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.31-36
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• 2022

In this paper, we present the design, manufacture and test results of Backend unit for SAR(Synthetic Aperture Radar) that can be applied on a small satellite. The Backend unit for SAR was designed with a control/storage board, TRX(transmission and receiving) board and a power supply board as a single unit in consideration of the applying of a small satellite. The control/storage board uses RFSoC to generate wideband chirp signal, generate operating timings, and perform control and calculations for SAR operation. The TRX board is designed to convert the wideband chirp signal generated by the control/storage board to the operating frequency of X-band by up-converting the frequency. Since small size, light weight, and low cost are important consideration for small satellite, MIL/Industrial grade components were appropriately applied and the at the same time it was designed to ensure mission life through the radiation test, analysis and space environment tests.