• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.287-292
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• 2021

Load and resistance factor design is an efficient design approach that provides a system of consistent design solutions. This study aims to determine the load and resistance factors needed for the design of breakwater foundations within a probabilistic framework. In the study, four typical types of Korean breakwaters, namely, rubble mound breakwaters, vertical composite caisson breakwaters, perforated caisson breakwaters, and horizontal composite breakwaters, are investigated. The bearing capacity of breakwater foundations under wave loading conditions is thoroughly examined. Two levels of the target reliability index (RI) of 2.5 and 3.0 are selected to implement the load and resistance factors calibration using Monte Carlo simulations with 100,000 cycles. The normalized resistance factors are found to be lower for the higher target RI as expected. Their ranges are from 0.668 to 0.687 for the target RI of 2.5 and from 0.576 to 0.634 for the target RI of 3.0.

• The Journal of Korean Academy of Prosthodontics
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• v.60 no.2
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• pp.202-210
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• 2022

Recently with the advance in digital dentistry, the fabrication of dentures using computer-aided design and computer-aided manufacturing (CAD-CAM) is on the rise. The denture designed through a CAD software can be produced in a 3-dimensional manufacturing process. This process includes a subtractive processing method such as milling and an additive processing method such as 3D printing and in which it can be applied efficiently in more complex structures. In this case, complete dentures were fabricated using Stereolithography (SLA)-based 3D printing to shorten the production time and interval of visits in patient with physical disabilities due to cerebral infarction. For definitive impression, the existing interim denture was digitally replicated and used as an individual tray. The definitive impression obtained with polyvinyl siloxane impression material was including information about the inclination and length of the maxillary anterior teeth, vertical dimension, and centric relation. In addition, facial scan data with interim denture was obtained so that it can be used as a reference in determination of the occlusal plane and in arrangement of artificial teeth during laboratory work. Artificial teeth were arranged through a CAD program, and a gingival festooning was performed. The definitive dentures were printed by SLA-based 3D printer using a FDA-approved liquid photocurable resin. The denture showed adequate retention, support, and stability, and results were satisfied functionally and aesthetically.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.511-521
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• 2022

Cloud detection and removal from satellite images is an essential process for topographic observation and analysis. Threshold-based cloud detection techniques show stable performance because they detect using the physical characteristics of clouds, but they have the disadvantage of requiring all channels' images and long computational time. Cloud detection techniques using deep learning, which have been studied recently, show short computational time and excellent performance even using only four or less channel (RGB, NIR) images. In this paper, we confirm the performance dependence of the deep learning network according to the heterogeneous learning dataset with different resolutions. The DeepLabV3+ network was improved so that channel features of cloud detection were extracted and learned with two published heterogeneous datasets and mixed data respectively. As a result of the experiment, clouds' Jaccard index was low in a network that learned with different kind of images from test images. However, clouds' Jaccard index was high in a network learned with mixed data that added some of the same kind of test data. Clouds are not structured in a shape, so reflecting channel features in learning is more effective in cloud detection than spatial features. It is necessary to learn channel features of each satellite sensors for cloud detection. Therefore, cloud detection of heterogeneous sensors with different resolutions is very dependent on the learning dataset.

• Journal of Appropriate Technology
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• v.7 no.1
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• pp.72-81
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• 2021

Gravity-driven membrane (GDM) filtration system based on the nanofiber membrane was investigated. This system can be operated with little energy demand due to a gravitational pressure-driven filtration and biological fouling control strategy. Moreover, the optimal module configuration based on the high permeance of nanofiber membrane can provide a significantly high water productivity. In order to evaluate its applicability potential, the pilot-scale (3000-5000 L/day) systems with nanofiber membranes were operated in developing countries (Kiribati and Tuvalu). Our results showed that the 14-92 L/(m²×h) of the permeate flux was determined indicating a stabilized water productivity. In addition, the permeate water indicated a high removal rate (more than 99.99%) of turbidity and bacteria. Consequently, the system can provide a stabilized water production with safe permeate water quality during long-term operation. These findings exemplify an effective approach to decentralized drinking water treatment for developing countries.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.11
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• pp.801-807
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• 2022

In this paper, we propose an ultra compact S-Band PCM/FM telemetry transmitter. The equipment is compact, so it can be applied to a limited space and capable of stable data transmission was designed and manufactured even with specifications set differently for each operating environment and system. RF direct conversion structure is used for the miniaturization of equipment, an RF transmission board, Power distribution board, and a signal processing board were implemented on a single PCB, so that the function of the transmitter could be performed with a minimum device. According to the target specification, variable output of 1~10W and variable data rate of 390kbps~12.5Mbps is possible in S-Band(2,200~2,400MHz) without degradation of performance. To verify the performance of the equipment, the RF performance test and BER measurement test were performed after the equipment was manufactured. It was confirmed that the OBW, null-to-null bandwidth, 1st IMD, Spurious emission, Phase noise specification of the PCM/FM modulated signal which is presented by the IRIG standard were satisfied, and we can confirm the data received using the transmitter inspection equipment were transmitted normally without distortion.

• Membrane Journal
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• v.33 no.4
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• pp.211-221
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• 2023

This study presents a comprehensive study on the synthesis and characterization of PVI-PGMA/LiTFSI polymeric membrane electrolytes and CxNy-C flexible electrodes for energy storage applications. The dual-functional PVI-PGMA copolymer exhibited excellent ionic conductivity, with the PVI-PGMA73/LiTFSI200 membrane electrolyte achieving the highest conductivity of 1.0 × 10^-3 S cm^-1. The electrochemical performance of the CxNy-C electrodes was systematically investigated, with C3N2-C demonstrating superior performance, achieving the highest specific capacitance of 958 F g^-1 and lowest charge transfer resistance (R_ct) due to its highly interconnected hybrid structure comprising nanowires and polyhedrons, along with binary Co/Ni oxides, which provided abundant redox-active sites and facilitated ion diffusion. The presence of a graphitic carbon shell further contributed to the enhanced electrochemical stability during charge-discharge cycles. These results highlight the potential of PVI-PGMA/LiTFSI polymeric membrane electrolytes and CxNy-C electrodes for advanced energy storage devices, such as supercapacitors and lithium-ion batteries, paving the way for further advancements in sustainable and high-performance energy storage technologies.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1283-1293
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• 2022

The purpose of this study is to predict residual chlorine in order to maintain stable residual chlorine concentration in sedimentation basin by using artificial intelligence algorithms in water treatment process employing pre-chlorination. Available water quantity and quality data are collected and analyzed statistically to apply into mathematical multiple regression and artificial intelligence models including multi-layer perceptron neural network, random forest, long short term memory (LSTM) algorithms. Water temperature, turbidity, pH, conductivity, flow rate, alkalinity and pre-chlorination dosage data are used as the input parameters to develop prediction models. As results, it is presented that the random forest algorithm shows the most moderate prediction result among four cases, which are long short term memory, multi-layer perceptron, multiple regression including random forest. Especially, it is result that the multiple regression model can not represent the residual chlorine with the input parameters which varies independently with seasonal change, numerical scale and dimension difference between quantity and quality. For this reason, random forest model is more appropriate for predict water qualities than other algorithms, which is classified into decision tree type algorithm. Also, it is expected that real time prediction by artificial intelligence models can play role of the stable operation of residual chlorine in water treatment plant including pre-chlorination process.

• Journal of the Korean Geotechnical Society
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• v.23 no.7
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• pp.65-76
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• 2007

Recently, there have been many construction projects on soft ground with growth of industry and various construction problems concerning soft soil behavior also have been reported. Especially, foundation piles of abutments and (or) buildings which were constructed on the soft ground have been suffering from a lot of stability problems of inordinary displacement due to lateral flow of soft ground. Although many researches for this phenomena have been carried out, it is still difficult to assess the mechanism of lateral flow on soft ground quantitatively. And reliable design method for judgement of lateral flow occurrence is not established yet. In this study, PNN (probabilistic neural network) and CNN (committee neural network) theories were applied for judgment of lateral flow occurrence based on eat data compiled from Korea and Japan. Predictions of PNN and CNN models for new data which were not used during model development are compared with those predicted by conventional empirical methods. It was found that the developed PNN and CNN models can predict more precise and reliable judgment of lateral flow occurrence than conventional empirical methods.

• Journal of the Korean Regional Science Association
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• v.39 no.2
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• pp.3-18
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• 2023

The aim of this study is to analyze problems with regional development projects by examining their actual conditions and to propose measures to promote such projects based on the size of local cities. To achieve this goal, problems associated with regional development projects were analyzed, and measures for their promotion were derived by dividing these projects into planning, strategy, policy, and institutional sectors according to the size of local cities. The problems identified with regional development projects include diversification leading to similar and overlapping projects, lack of participation by local experts, top-down government structure for designating and supporting regional development projects, and insufficient budget. In order to address these issues, local experts have suggested differential measures based on the size of local cities. Specifically, in the planning sector, it was proposed that economic, cultural, social, and welfare functions be expanded and reorganized primarily around small and medium-sized cities, and that long-term strategies be established for regional large cities through various partnerships and step-by-step procedures. In the policy sector, it was suggested that the implementation of bottom-up development under the leadership of local governments should be focused on small and medium-sized cities, and that the transition from a specific industry-oriented policy to a corporate growth policy needs to be established around large cities. Finally, in the institutional sector, it was recommended that a performance evaluation system for the use of financial resources and a system for expanding financial resources should be established primarily in small and medium-sized cities.

• Journal of Life Science
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• v.33 no.11
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• pp.956-965
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• 2023

In plants, there are many CCCH zinc finger proteins consisting of three cysteine residues and one histidine residue, which bind to zinc ions with finger configuration. CCCH-type zinc finger proteins are divided into tandem CCCH-type zinc finger (TZF) and non-TZF proteins: TZF proteins contain exactly two tandem CCCH-type zinc finger motifs whereas non-TZF proteins have fewer or greater than two CCCH-type zinc finger motifs. The functions of TZF genes, especially plant-specific RR-TZF genes, have been well studied in several plants, whereas the functional roles of non-TZF genes have not been adequately researched compared to TZF genes. Many non-TZF genes have been identified as being involved in the responses to biotic and abiotic stresses, such as pathogen, high salt, drought, cold, heat, and oxidative stresses. Some non-TZF proteins bind to RNA and are involved in the post-transcriptional regulation of stress-responsive genes in the cytoplasm. In addition, other non-TZF proteins act as transcriptional activators or repressors that regulate the expression of stress-responsive genes in the nucleus. Despite these studies, stress signal transduction and upstream and downstream genes of non-TZF genes have not been sufficiently researched, suggesting that additional studies of the functions of non-TZF genes' functions in plants' stress responses are needed. In this review, we describe non-TZF genes involved in biotic abiotic stress responses in plants and their molecular functions.