• Geomechanics and Engineering
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• v.30 no.6
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• pp.503-515
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• 2022

The permeability coefficient is an essential parameter for the study of seepage flow in fractured rock mass. This paper discusses the feasibility and application value of using readily available RQD (rock quality index) data to estimate mine water inflow and grouting quantity. Firstly, the influence of different fracture frequencies on permeability in a unit area was explored by combining numerical simulation and experiment, and the relationship between fracture frequencies and pressure and flow velocity at the monitoring point in fractured rock mass was obtained. Then, the stochastic function generation program was used to establish the flow analysis model in fractured rock mass to explore the relationship between flow velocity, pressure and analyze the universal law between fracture frequency and permeability. The concepts of fracture width and connectivity are introduced to modify the permeability calculation formula and grouting formula. Finally, based on the on-site grouting water control example, the rock mass quality index is used to estimate the mine water inflow and the grouting quantity. The results show that it is feasible to estimate the fracture frequency and then calculate the permeability coefficient by RQD. The relationship between fracture frequency and RQD is in accordance with exponential function, and the relationship between structure surface frequency and permeability is also in accordance with exponential function. The calculation results are in good agreement with the field monitoring results, which verifies the rationality of the calculation method. The relationship between the rock mass RQD index and the rock mass permeability established in this paper can be used to invert the mechanical parameters of the rock mass or to judge the permeability and safety of the rock mass by using the mechanical parameters of the rock mass, which is of great significance to the prediction of mine water inflow and the safety evaluation of water inrush disaster management.

• Clean Technology
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• v.29 no.1
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• pp.53-58
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• 2023

This study shows the summary of the economic performance of excess electricity conversion to hydrogen as well as methane and returned conversion to electricity using a fuel cell. The methane production process has been examined in a previous study. Here, this study focuses on the conversion of methane to electricity. As a part of this study, capital expenditure (CAPEX) is estimated under various sized plants (0.3, 3, 9, and 30 MW). The study shows a method for economic optimization of electricity generation using a fuel cell. The CAPEX and operating expenditure (OPEX) as well as the feed cost are used to calculate the discounted cash flow. Then the levelized cost of returned electricity (LCORE) is estimated from the discounted cash flow. This study found the LCORE value was ¢10.2/kWh electricity when a 9 MW electricity generating fuel cell was used. A methane production plant size of 1,500 Nm³/hr, a methane production cost of $11.47/mcf, a storage cost of $1/mcf, and a fuel cell efficiency of 54% were used as a baseline. A sensitivity analysis was performed by varying the storage cost, fuel cell efficiency, and excess electricity cost by ±20%, and fuel cell efficiency was found as the most dominating parameter in terms of the LCORE sensitivity. Therefore, for the best cost-performance, fuel cell manufacturing and efficiency need to be carefully evaluated. This study provides a general guideline for cost performance comparison with LCORE.

• Journal of Korean Society of Disaster and Security
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• v.15 no.4
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• pp.71-78
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• 2022

Recently, mountain disasters such as landslides and debris flows have flowed along mountain streams and hit residential areas and roads, increasing damage. In this study, in order to reduce damage and analyze causes of mountain disasters, field surveys and Terrestrial LiDAR terrain analysis were conducted targeting debris flow areas, and debris flow flow processes were simulated using FLO-2D and RAMM models, which are numerical models of debris flows. In addition, the debris flow deposition area was calculated and compared and analyzed with the actual occurrence section. The sedimentation area of the debris flow generation section of the LiDAR scan data was estimated to be approximately 21,336 ㎡, and was analyzed to be 20,425 ㎡ in the FLO-2D simulation and 19,275 ㎡ in the case of the RAMMS model. The constructed topographical data can be used as basic data to secure the safety of disaster risk areas.

• Journal of the Korean Geotechnical Society
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• v.22 no.12
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• pp.89-98
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• 2006

In this paper the behavior of saturated sand deposits where liquefaction occurred before is studied for successive earthquakes. The relationship between past pore pressure generation and reliquefaction resistance is examined by using cyclic direct simple shear tests. If the soil sample in direct simple shear produced nearly 90% of excess pore pressure during first time loading, its liquefaction resistance increased during following cyclic loading after consolidation. However, a fully liquefied soil during first time loading has a densely packed condition but shows less liquefaction resistance for the following cyclic loading. UBCSAND model that can account for pore pressure change and stiffness loss of soil during shaking is used to analyze the centrifuge test simulating reliquefaction. The pore pressure rise during first time cyclic loading controls liquefaction resistance. The measurements from reliquefaction centrifuge test are compared with numerical predictions. By considering frequent earthquakes having occurred at the Southern Korea near Japan, such effective stress approach is necessary for reliquefaction study.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.18 no.4
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• pp.12-21
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• 2022

Steam assisted gravity drainage(SAGD) is a process that drills well in the underground oil sands layer, injects hightemperature steam, lowers the viscosity of buried bitumen, and recovers it to the ground. Recently, direct contact steam generator(DCSG) is being developed to maximize steam efficiency for SAGD process. The DCSG requires high technology to achieve pressurized combustion and steam generation in accordance with underground pressurized conditions. Therefore, it is necessary to develop a combustion technology that can control the heat load and exhaust gas composition. In this study, process analysis of high-pressurized DCSG was conducted to apply oxygen enrichment technology in which nitrogen of the air was partially removed for increasing steam production and reducing fuel consumption. As the process analysis conditions, methane as the fuel and normal air or oxygen enriched air as the oxidizing agent were applied to high-pressurized DCSG process model. A simple combustion reaction program was used to calculate the property variations for combustion temperature, steam ratio and residual heat in exhaust gas. As a major results, the steam production efficiency of DCSG using the pure oxygen was about 6% higher than that of the normal air due to the reducing nitrogen in the air. The results of this study will be used as operating data to test the demonstration device.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.11
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• pp.1720-1728
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• 2022

The industrial 4.0 era has been opened with the development of artificial intelligence technology, and the realization of smart farms incorporating ICT technology is receiving great attention in the livestock industry. Among them, the quality management technology of livestock products and livestock operations incorporating computer vision-based artificial intelligence technology represent key technologies. However, the insufficient number of livestock image data for artificial intelligence model training and the severely unbalanced ratio of labels for recognizing a specific defective state are major obstacles to the related research and technology development. To overcome these problems, in this study, combining oversampling and adversarial case generation techniques is proposed as a method necessary to effectively utilizing small data labels for successful defect detection. In addition, experiments comparing performance and time cost of the applicable techniques were conducted. Through experiments, we confirm the validity of the proposed methods and draw utilization strategies from the study results.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.447-457
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• 2022

Form design for information registration should consider and classify various possible cases and each user case and reflect it in the design. In this paper, I analyzed the visual and emotional factors of information design that elicit positive emotions from the user experience point of view, focusing on the birth certificate of among other public documents issued by the government. In order to derive problems and supplements from the user's overall writing experience point of view, Keller's Motivational Behavior Construction Model was used. The process of writing the birth registration form creates recognition, reasoning, relationship, establishment, achievement, expectation. In order to more actively draw an emotional point of view, it is essential to set of information and to materialize the information experience. It is hoped that this will be a good guideline in the process of presenting a new perspective on information design and improving the experience.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.3
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• pp.291-300
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• 2017

Quantum-dot cellular automata(QCA) is a computing model designed to be similar to cellular automata, and an alternative technology for next generation using high performance and low power consumption. QCA is undergoing various studies with recent experimental results, and it is one of the paradigms of transistors that can solve device density and interconnection problems as nano-unit materials. An XOR gate is a gate that operates so that the result is true when either one of the logic is true. The proposed XOR gate consists of five layers. The first layer consists of OR gates, the third and fifth layers consist of AND gates, and the second and fourth layers are designed as passages in the middle. The half adder consists of an XOR gate and an AND gate. The proposed half adder is designed by adding two cells to the proposed XOR gate. The proposed half adder consists of fewer cells, total area, and clock than the conventional half adder.

• Korean Journal of Remote Sensing
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• v.39 no.3
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• pp.339-353
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• 2023

As the availability of high-resolution satellite imagery increases, improvement of positioning accuracy of satellite images is required. The importance of orthorectified images is also increasing, which removes relief displacement and establishes true localization of man-made structures. In this paper, we performed automated extraction of building rooftops and total building areas within original satellite images using the existing building height database. We relocated the rooftop sin their true position and generated an orthorectified building layer. The extracted total building areas were used to blank out building areas and generate true orthographic non-building layer. A final orthorectified image was provided by overlapping the building layer and non-building layer.We tested the proposed method with KOMPSAT-3 and KOMPSAT-3A satellite images and verified the results by overlapping with a digital topographical map. Test results showed that orthorectified building layers were generated with a position error of 0.4m.Through the proposed method, the feasibility of automated true orthoimage generation within dense urban areas was confirmed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1872-1879
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• 2022

Recently, with the development of artificial intelligence technology, research to use artificial intelligence to detect hacking attacks is being actively conducted. However, the fact that security data is a representative imbalanced data is recognized as a major obstacle in composing the learning data, which is the key to the development of artificial intelligence models. Therefore, in this paper, we propose a W-VAE oversampling technique that applies VAE, a deep learning generation model, to data extraction for oversampling, and sets the number of oversampling for each class through weight calculation using K-NN for sampling. In this paper, a total of five oversampling techniques such as ROS, SMOTE, and ADASYN were applied through NSL-KDD, an open network security dataset. The oversampling method proposed in this paper proved to be the most effective sampling method compared to the existing oversampling method through the F1-Score evaluation index.