• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.1
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• pp.113-119
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• 2020

Large sensor networks require the collection and analysis of data from a large number of sensors. The number of sensors that can be controlled per micro controller is limited. In this paper, we propose how to aggregate sensor data from a large number of sensors using a large number of microcontrollers and multiple bridge nodes, and design and implement an efficient communication system for sensor data collection. Bridge nodes aggregate data from multiple microcontrollers using SPI communication, and transfer the aggregated data to PC servers using wireless TCP/IP communication. In this paper, the communication system was constructed using the Open H/W Aduo Mini and ESP8266 and performance of the system was analyzed. The performance analysis results showed that more than 30 sensing data can be collected per second from more than 700 sensors.

• Journal of The Korean Astronomical Society
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• v.53 no.6
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• pp.161-168
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• 2020

We report the discovery of a giant exoplanet in the microlensing event OGLE-2017-BLG-1049, with a planet-host star mass ratio of q = 9.53 ± 0.39 × 10-3 and a caustic crossing feature in Korea Microlensing Telescope Network (KMTNet) observations. The caustic crossing feature yields an angular Einstein radius of θE = 0.52 ± 0.11 mas. However, the microlens parallax is not measured because the time scale of the event, tE ≃ 29 days, is too short. Thus, we perform a Bayesian analysis to estimate physical quantities of the lens system. We find that the lens system has a star with mass Mh = 0.55+0.36-0.29 M⊙ hosting a giant planet with Mp = 5.53+3.62-2.87 MJup, at a distance of DL = 5.67+1.11-1.52 kpc. The projected star-planet separation is a⊥ = 3.92+1.10-1.32 au. This means that the planet is located beyond the snow line of the host. The relative lens-source proper motion is μrel ~ 7 mas yr-1, thus the lens and source will be separated from each other within 10 years. After this, it will be possible to measure the flux of the host star with 30 meter class telescopes and to determine its mass.

• Composites Research
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• v.34 no.4
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• pp.264-268
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• 2021

In this study, we propose a method for fabricating hydrophobic coatings/films with three-dimensional (3D) hierarchical nanostructured organic/inorganic composite surfaces. An epoxy-based, large-area 3D ordered nanoporous template is first prepared through an advanced photolithography technique called Proximity-field nanoPatterning (PnP). Then, a hierarchically structured surface is generated by densely impregnating the template with silica nanoparticles with an average diameter of 22 nm through dip coating. Due to the coexisting micro- and nano-scale roughness on the surface, the fabricated composite film exhibits a higher contact angle (>137 degrees) for water droplets compared to the reference samples. Therefore, it is expected that the materials and processes developed through this study can be used in various ways in the traditional coating/film field.

• Atmosphere
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• v.33 no.4
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• pp.413-422
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• 2023

Urban Air Mobility (UAM) is promising, sustainable and efficient air transportation in a metropolitan area. Korean government has recently announced operation demonstration plans as a step toward commercialization of UAM. However, there is lack of understanding on the potential impact of weather on UAM operation. We collected weather observations from Gimpo International Airport and 5 automatic weather stations (AWS) along UAM corridor of the Han-River to assess weather barriers such as low visibility, wind gust and wind shear. The results show the frequency of low visibility near the corridor fluctuated significantly from year to year depending on the concentration of fine particulate matter (PM_2.5) in Seoul. The frequency of high wind speed-shift calculated using 1-minute wind observations was increased not only during the spring season (March, April, and May) but also the beginning of rainy season (Jun). In addition, a chance of high wind shear from 1-minute wind observations varied by the stations, suggesting that the condition is largely affected by topography including a river and high-rise buildings. These basic weather properties suggest that there are substantial weather barriers to UAM operations along the Han-River Corridor, while they cannot properly surveil micro-scale weather conditions in detail such as wind gust and wind shear over the corridor. Thus, this study suggests that potential barriers related to adverse weather need to be evaluated, building high-density weather observations infrastructure prior to UAM demonstration and commercialization.

• Journal of Hydrogen and New Energy
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• v.33 no.6
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• pp.845-855
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• 2022

In response to climate change, the world is continuing efforts to reduce fossil fuels, expand renewable energy, and improve energy efficiency with the goal of achieving carbon neutrality. In particular, R&D is being made on the value chain covering the entire cycle of hydrogen production, storage, transportation, and utilization in order to shift the energy supply system to focus on hydrogen energy. Hydrogen-based energy sources can produce heat and electricity at the same time, so it is possible to utilize heat energy, which can increase overall efficiency. In this study, calculation of the optimal scale for hydrogen-based cogeneration and the composition of heat sources were reviewed. It refers to a method of the optimal heat source size according to the external heat supply and heat storage to be considered. The results of this study can be used as basic data for establishing a hydrogen-based energy supply model in the future.

• Journal of the Korean Geosynthetics Society
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• v.22 no.2
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• pp.13-21
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• 2023

Mean sea level has recently been rising due to global warming causing coastal erosion. As Korea is peninsula, the land loss due to coastal erosion is critical. An approach in this study is cementing the coastal area using bacteria, which is called microbially induced carbonate precipitation (MICP). This study tried to see how fresh water and sea water work with MICP as a solvent. Ureolytic activity during the MICP reaction was measured with deionized and sea water. A soil column was prepared to evaluate the strength of MICP-treated sand. Sands were treated by MICP with surface percolation method. As the treatmen t style was different with other conventional methods, several methods were proposed to properly evaluate the MICP-treated sand surface. A micro-scale evaluation was performed to assess the mineral structure treated by different solvents. As results, sea water rendered the ureolytic reaction slower. A needle penetrometer worked well to evaluate the MICP-treated sand surface. This study confirmed the utilization of sea water is feasible as the solvent of MICP.

• Journal of The Korean Society of Integrative Medicine
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• v.11 no.2
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• pp.221-230
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• 2023

Purpose : This study was performed to evaluate the effects of virtual reality combined robot assist gait training (VRG) on improvement of balance and respiratory function in chronic stroke patients. Methods : A single-blind, randomized controlled trial (RCT) was conducted with 35 chronic stroke patients. They were randomly allocated 2 groups; VRG group (n=18) and conservative treatment group (CG; n=17). The VRG group received 30 minutes robot assisted gait training combined virtual reality training, robot assisted gait training was conducted in parallel using a virtual reality device (2 sessions of 15 minutes in a 3D-recorded walking environment and 15 minutes in a downtown walking environment). In the conservative treatment group, neurodevelopmental therapy and exercise therapy were performed according to the function of stroke patients. Each group performed 30 minutes a day 3 times a week for 8 weeks. The primary outcome balance and respiratory function were measured by a balance measurement system (BioRescue, Marseille, France), Berg balance scale, functional reach test for balance, Spirometry (Cosmed Micro Quark, Cosmed, Italy) for respiratory function Forced vital capacity (FVC), forced expiratory volume in 1 second (FEV₁), and maximum expiratory volume (PEF) were measured according to the protocol. The measurement were performed before and after the 8 weeks intervention period. Results : Both groups demonstrated significant improvement of outcome in balance and respiratory function during intervention period. VRG revealed significant differences in balance and respiratory function as compared to the CG groups (p<.05). Our results showed that VRG was more effective on balance and respiratory function in patients with chronic stroke. Conclusion : Our findings indicate that VRG can improve balance and respiratory function, highlight the benefits of VRG. This study will be able to be used as an intervention data for recovering balance and respiratory function in chronic stroke patients.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.3
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• pp.265-274
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• 2022

MSMEs in the food and beverage industry play a critical role in the Indonesian economy since they account for the majority of the manufacturing sector's GDP. Despite its importance, it is unable to compete on a worldwide scale due to a lack of technological adoption. As a result, the purpose of this study is to look into the concerns and challenges that F&B MSMEs have when it comes to technology adoption. An online survey of 626 MSMEs and in-depth interviews as well as focus groups with diverse stakeholders from four provinces, namely West Java, East Java, South Sulawesi, and North Sumatera, provided the data for this study. To be thorough, the approach used in the study is based on the Technology, Organization, and Environment (TOE) framework. According to the findings, the majority of MSMEs use technology for marketing and sales, mainly through e-commerce. Meanwhile, for a variety of reasons, most of them continue to rely on traditional and semi-automatic technologies for production. According to the TOE framework, MSMEs lack those three parts of the technology adoption framework, particularly the environmental aspect, which is mostly due to a lack of cooperation among stakeholders. Finally, as a policy proposal, we offer a comprehensive technology adoption strategy based on the findings through an integrated MSMEs development information system including many important stakeholders.

• Composites Research
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• v.36 no.5
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• pp.329-334
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• 2023

The classical multiscale finite element (FE² ) method involves iterative calculations of micro-boundary value problems for representative volume elements at every integration point in macro scale, making it a computationally time and data storage space. To overcome this, we developed the data-driven multiscale analysis method based on the mean-field homogenization (MFH). Data-driven computational mechanics (DDCM) analysis is a model-free approach that directly utilizes strain-stress datasets. For performing multiscale analysis, we efficiently construct a strain-stress database for the microstructure of composite materials using mean-field homogenization and conduct data-driven computational mechanics simulations based on this database. In this paper, we apply the developed multiscale analysis framework to an example, confirming the results of data-driven computational mechanics simulations considering the microstructure of a hyperelastic composite material. Therefore, the application of data-driven computational mechanics approach in multiscale analysis can be applied to various materials and structures, opening up new possibilities for multiscale analysis research and applications.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.6
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• pp.245-254
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• 2022

Proteins are the basic unit of all life activities, and understanding them is essential for studying life phenomena. Since the emergence of the machine learning methodology using artificial neural networks, many researchers have tried to predict the function of proteins using only protein sequences. Many combinations of deep learning models have been reported to academia, but the methods are different and there is no formal methodology, and they are tailored to different data, so there has never been a direct comparative analysis of which algorithms are more suitable for handling protein data. In this paper, the single model performance of each algorithm was compared and evaluated based on accuracy and speed by applying the same data to CNN, LSTM, and GRU models, which are the most frequently used representative algorithms in the convergence research field of predicting protein functions, and the final evaluation scale is presented as Micro Precision, Recall, and F1-score. The combined models CNN-LSTM and CNN-GRU models also were evaluated in the same way. Through this study, it was confirmed that the performance of LSTM as a single model is good in simple classification problems, overlapping CNN was suitable as a single model in complex classification problems, and the CNN-LSTM was relatively better as a combination model.