• Particle and aerosol research
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• v.18 no.1
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• pp.1-8
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• 2022

Since 2019, the corona virus has been continuously affect human life. In particular, in the indoor space where people live, infection by airborne transmission of viruses is a problem. Among them, the spread in the subway, which is the main mode of transport for humans, can be serious. To solve this problem, our research team developed an ionic wind collector to collect and remove corona virus using an ionic wind collector and ozone. In order to apply the ionic wind collector to the subway, it must operate in two modes. Because large amounts of ozone are harmful to the human body. There is a mode that collects bio-aerosol from the air using ionic wind and a mode that inactivates viruses floating in the air by generating a large amount of ozone. As the applied voltage increased, the cleaning ability of the ionic wind collector increased, and the farther the distance between the discharge electrode and the ground plate, the higher the cleaning ability even at low current. In addition, clean air delivery rate (CADR) of an ionic wind collector was up to 5.5 m³/min. As a result of measuring the amount of ozone generated, it was confirmed that 50 ppb to 250 ppb was generated, and it was confirmed that ozone generation was controllable in the ionic wind dust collector.

• The Research Journal of the Costume Culture
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• v.30 no.1
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• pp.66-87
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• 2022

This study explores the possibility of creating new experimental hanbok designs by accommodating the latest world fashion trends and the changing needs of consumers, in order to attempt to overcome the limitations of traditional Korean fashion design. To do so, We analyze works by contemporary Korean fashion designers to investigate current developments in Korean fashion design and to identify areas of improvement within hanbok design. The results show that most contemporary hanbok designs repeat stereotypes of traditional hanbok with minor modifications. So there arises a need to create new hanbok designs that are clearly distinct from traditional hanbok but also maintain its core features. To develop such designs, I apply the techniques of deconstruction fashion, which allow making experiments with form, composition, and materials use to realize new aesthetics. The use of CLO 3D fashion design software also proves to be very efficient for developing experimental designs. The study results make meaningful contributions to the development of virtual clothing and 3D fashion for hanbok, particularly as metaBUS, a cloud-based research synthesis platform, is rapidly gaining ground, and reality and virtual reality are increasingly mixed in everyday life. This attempt at 3D design of hanbok is expected to trigger more creative experimentation in hanbok design.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.5
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• pp.111-116
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• 2022

The causes of motor burnout include overload, phase loss, restraint, interlayer short circuit, winding ground fault, instantaneous overvoltage, and the rotor contacting the stator, leading to insulation breakdown, leading to breakdown or electrical accidents. Therefore, equipment failure causes not only loss due to cost required for equipment maintenance/repair, but also huge economic loss due to productivity decrease due to process stop because the process itself including the motor is stopped. The current level of technology for diagnosing motor failures uses vibration, heat, and power analysis methods, but there is a limit to analyzing the problems only after a considerable amount of time has passed according to the failure. Therefore, in this paper, a device and algorithm for measuring insulation resistance using DC AMP signal was applied to an industrial motor to solve this problem. And by following the insulation resistance state value, we propose a diagnosis of deterioration and failure of the motor that cannot be solved by the existing method.

• Current Optics and Photonics
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• v.6 no.2
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• pp.171-182
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• 2022

A single-photon laser and mid-wave infrared (MWIR) common aperture optical system was designed and developed to detect and range a long-distance civil aviation aircraft. The secondary mirror of the Ritchey-Chretien (R-C) optical system was chosen as a dichroic lens to realize the design of a common aperture system for the laser and MWIR. Point spread function (PSF) ellipticity was introduced to evaluate the coupling efficiency of the laser receiving system. A small aperture stop and narrow filter were set in the secondary image plane and an afocal light path of the laser system, respectively, and the stray light suppression ability of the small aperture stop was verified by modeling and simulation. With high-precision manufacturing technology by single point diamond turning (SPDT) and a high-efficiency dichroic coating, the laser/MWIR common aperture optical system with a 𝜑300 mm aluminum alloy mirror obtained images of buildings at a distance of 5 km with great quality. A civil aviation aircraft detection experiment was conducted. The results show that the common aperture system could detect and track long-distance civil aviation aircraft effectively, and the coverage was more than 450 km (signal-to-noise ratio = 6.3). It satisfied the application requirements for earlier warning and ranging of long-range targets in the area of aviation, aerospace and ground detection systems.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.296-302
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• 2022

This paper proposes a center of plantar foot pressure (CoP) trajectory estimation method based on Gaussian process regression, with the aim to show robust results regardless of the regions and numbers of FSRs of the insole sensor. This method can bring an interpolation between the measurement points inside the wearable insole sensor, and two experiments are conducted for performance evaluation. For this purpose, the input data used in the experiment are generated in three types (13 FSRs, 8 FSRs, 5 FSRs) according to the regions and numbers of FSRs. First, the estimation results of the CoP trajectory are compared using Gaussian process regression and weighted mean. As a result of each method, the estimation results of the two methods were similar in the case of 13 FSRs data. On the other hand, in the case of the 8 and 5 FSRs data, the weighted mean varies depending on the regions and numbers of FSRs, but the estimation results of Gaussian process regression showed similar results in spite of reducing the regions and numbers. Second, the estimation results of the CoP trajectory based on Gaussian process regression during several gait cycles are analyzed. In five gait cycles, the previous cycle and the current estimation results are compared, and it was confirmed that similar trajectories appeared in all. In this way, the method of estimating the CoP trajectory based on Gaussian process regression showed robust results, and stability was confirmed by yielding similar results in several gait cycles.

• Korean Journal of Remote Sensing
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• v.38 no.4
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• pp.343-353
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• 2022

An attempt to derive the surface temperature from the Korea Multi-purpose Satellite (KOMPSAT)-3A mid-wave infrared (MWIR) data acquired over the southern California on Nov. 14, 2015 has been made using the MODerate resolution atmospheric TRANsmission (MODTRAN) radiative transfer model. Since after the successful launch on March 25, 2015, the KOMPSAT-3A spacecraft and its two payload instruments - the high-resolution multispectral optical sensor and the scanner infrared imaging system (SIIS) - continue to operate properly. SIIS uses the MWIR spectral band of 3.3-5.2 ㎛ for data acquisition. As input data for the realistic simulation of the KOMPSAT-3A SIIS imaging conditions in the MODTRAN model, we used the National Centers for Environmental Prediction (NCEP) atmospheric profiles, the KOMPSAT-3Asensor response function, the solar and line-of-sight geometry, and the University of Wisconsin emissivity database. The land cover type of the study area includes water,sand, and agricultural (vegetated) land located in the southern California. Results of surface temperature showed the reasonable geographical pattern over water, sand, and agricultural land. It is however worthwhile to note that the surface temperature pattern does not resemble the top-of-atmosphere (TOA) radiance counterpart. This is because MWIR TOA radiances consist of both shortwave (0.2-5 ㎛) and longwave (5-50 ㎛) components and the surface temperature depends solely upon the surface emitted radiance of longwave components. We found in our case that the shortwave surface reflection primarily causes the difference of geographical pattern between surface temperature and TOA radiance. Validation of the surface temperature for this study is practically difficult to perform due to the lack of ground truth data. We therefore made simple comparisons with two datasets over Salton Sea: National Aeronautics and Space Administration (NASA) Jet Propulsion Laboratory (JPL) field data and Salton Sea data. The current estimate differs with these datasets by 2.2 K and 1.4 K, respectively, though it seems not possible to quantify factors causing such differences.

• The Journal of Engineering Geology
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• v.33 no.1
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• pp.137-149
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• 2023

In order to intuitively grasp the earth pressure direction acting on the structure and displacement state, displacement data in the horizontal and vertical directions were processed using the sigmoid function. A displacement coordinate system was set up for each axis. The system can intuitively check the current displacement and assess the management stage of each point. A displacement path can be compiled from continuously recorded points, allowing trends in the displacement's history and stress direction to be known. Analysis of data measured for excavated ground, found that displacement occurred in the direction of destressing at all points, and that the points' management state steady. Similar behavior trends were found among measurement points with high spatial correlation, whereas differing behavior trends occurred among measurement points with low spatial correlation. If the correlation analysis of the precursor and behavior area is performed using the continuously distributed surface settlement data and displacement coordinate system, it will be possible to predict the failure time and area.

• Geomechanics and Engineering
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• v.31 no.6
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• pp.545-556
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• 2022

Evaluation and optimization of tunnel wall convergence (TWC) plays a vital role in preventing potential problems during tunnel construction and utilization stage. When convergence occurs at a high rate, it can lead to significant problems such as reducing the advance rate and safety, which in turn increases operating costs. In order to design an effective solution, it is important to accurately predict the degree of TWC; this can reduce the level of concern and have a positive effect on the design. With the development of soft computing methods, the use of deep learning algorithms and neural networks in tunnel construction has expanded in recent years. The current study aims to employ the long-short-term memory (LSTM) deep neural network predictor model to predict the TWC, based on 550 data points of observed parameters developed by collecting required data from different tunnelling projects. Among the data collected during the pre-construction and construction phases of the project, 80% is randomly used to train the model and the rest is used to test the model. Several loss functions including root mean square error (RMSE) and coefficient of determination (R²) were used to assess the performance and precision of the applied method. The results of the proposed models indicate an acceptable and reliable accuracy. In fact, the results show that the predicted values are in good agreement with the observed actual data. The proposed model can be considered for use in similar ground and tunneling conditions. It is important to note that this work has the potential to reduce the tunneling uncertainties significantly and make deep learning a valuable tool for planning tunnels.

• Journal of Astronomy and Space Sciences
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• v.40 no.2
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• pp.45-57
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• 2023

This study examined the effect of solar flux (F10.7) and sunspots number (R) on the daily variation of equatorial electrojet (EEJ) and morning/afternoon counter electrojet (MCEJ/ACEJ) in the ionospheric E region across the eight longitudinal sectors during quiet days from January 2008 to December 2013. In particular, we focus on both minimum and maximum solar cycle of 24. For this purpose, we have collected a 6-year ground-based magnetic data from multiple stations to investigate EEJ/CEJ climatology in the Peruvian, Brazilian, West & East African, Indian, Southeast Asian, Philippine, and Pacific sectors with the corresponding F10.7 and R data from satellites simultaneously. Our results reveal that the variations of monthly mean EEJ intensities were consistent with the variations of solar flux and sunspot number patterns of a cycle, further indicating that there is a significant seasonal and longitudinal dependence. During the high solar cycle period, F10.7 and R have shown a strong peak around equinoctial months, consequently, the strong daytime EEJs occurred in the Peruvian and Southeast Asian sectors followed by the Philippine regions throughout the years investigated. In those sectors, the correlation between the day Maxima EEJ and F10.7 strengths have a positive value during periods of high solar activity, and they have relatively higher values than the other sectors. A predominance of MCEJ occurrences is observed in the Brazilian (TTB), East African (AAE), and Peruvian (HUA) sectors. We have also observed the CEJ dependence on solar flux with an anti-correlation between ACEJ events and F10.7 are observed especially during a high solar cycle period.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.8
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• pp.243-252
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• 2023

Satellite imageries are at a greatest importance for land cover examining. Numerous studies have been conducted with satellite images and uses semantic segmentation techniques to extract information which has higher altitude viewpoint. The device which is taking these images must employee wireless communication links to send them to receiving ground stations. Wireless communications from a satellite are inevitably affected due to transmission errors. Evidently images which are being transmitted are distorted because of the information loss. Current semantic segmentation techniques are not made for segmenting distorted images. Traditional image enhancement methods have their own limitations when they are used for satellite images enhancement. This paper proposes an auto-encoder based image pre-enhancing method for satellite images. As a distorted satellite images dataset, images received from a real radio transmitter were used. Training process of the proposed auto-encoder was done by letting it learn to produce a proper approximation of the source image which was sent by the image transmitter. Unlike traditional image enhancing methods, the proposed method was able to provide more applicable image to a segmentation model. Results showed that by using the proposed pre-enhancing technique, segmentation results have been greatly improved. Enhancements made to the aerial images are contributed the correct assessment of land resources.