• Earthquakes and Structures
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• v.22 no.6
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• pp.539-548
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• 2022

Steel plate shear walls (SPSWs) are one of the most important and widely used lateral load-bearing systems. The reason for this is easier execution than reinforced concrete (RC) shear walls, faster construction time, and lower final weight of the structure. However, the main drawback of SPSWs is premature buckling in low drift ratios, which affects the energy absorption capacity and global performance of the system. To address this problem, two groups of SPSWs under cyclic loading were investigated using the finite element method (FEM). In the first group, several series of circular rings have been used and in the second group, a new type of SPSW with concentric circular rings (CCRs) has been introduced. Numerous parameters include in yield stress of steel plate wall materials, steel panel thickness, and ring width were considered in nonlinear static analysis. At first, a three-dimensional (3D) numerical model was validated using three sets of laboratory SPSWs and the difference in results between numerical models and experimental specimens was less than 5% in all cases. The results of numerical models revealed that the full SPSW undergoes shear buckling at a drift ratio of 0.2% and its hysteresis behavior has a pinching in the middle part of load-drift ratio curve. Whereas, in the two categories of proposed SPSWs, the hysteresis behavior is complete and stable, and in most cases no capacity degradation of up to 6% drift ratio has been observed. Also, in most numerical models, the tangential stiffness remains almost constant in each cycle. Finally, for the innovative SPSW, a relationship was suggested to determine the shear capacity of the proposed steel wall relative to the wall slenderness coefficient.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.8
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• pp.1180-1187
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• 2022

As the likelihood of occurrence of the localized microbursts or severe flooding is increased due to the unusual weather changes, it is the very urgent problem to detect these weather hazards with a local weather radar. For a local weather radar of this purpose, it is essential to detect the low altitude and the fast varying weather conditions. Therefore, the very fast update of the weather information and the efficient clutter removal is very important. To achieve this goal, the appropriate method should be applied which does not need the mechanical elevation scanning and has the capability of the efficient clutter removal. Therefore, in this paper, the usefulness of the implementation of elevational filter banks with the spatial FFT algorithm was analyzed and investigated using a simple array antenna. It is shown that the suggested method can be used for both the minimization of the ground clutter and the fast update of weather information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.1
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• pp.16-37
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• 2022

Accurate liver segment segmentation based on radiological images is indispensable for the preoperative analysis of liver tumor resection surgery. However, most of the existing segmentation methods are not feasible to be used directly for this task due to the challenge of exact edge prediction with some tiny and slender vessels as its clinical segmentation criterion. To address this problem, we propose a novel deep learning based segmentation model, called Boundary-Aware Dual Attention Liver Segment Segmentation Model (BADA). This model can improve the segmentation accuracy of liver segments with enhancing the edges including the vessels serving as segment boundaries. In our model, the dual gated attention is proposed, which composes of a spatial attention module and a semantic attention module. The spatial attention module enhances the weights of key edge regions by concerning about the salient intensity changes, while the semantic attention amplifies the contribution of filters that can extract more discriminative feature information by weighting the significant convolution channels. Simultaneously, we build a dataset of liver segments including 59 clinic cases with dynamically contrast enhanced MRI(Magnetic Resonance Imaging) of portal vein stage, which annotated by several professional radiologists. Comparing with several state-of-the-art methods and baseline segmentation methods, we achieve the best results on this clinic liver segment segmentation dataset, where Mean Dice, Mean Sensitivity and Mean Positive Predicted Value reach 89.01%, 87.71% and 90.67%, respectively.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.1
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• pp.15-38
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• 2022

Recently, tunnel technology in Korea has shown various achievements such as long tunnel and large section by tunnel construction using TBM in Korea and abroad. Especially subsea tunnels are frequently designed and constructed. The Ga-deok subsea tunnel was completed in December 2010, and the Incheon North Port Tunnel was opened and operated in 2017, and the Bo-ryeong subsea tunnel between Dae-cheon Port and Won-san Island will be completed in 2021. In foreign countries, many subsea tunnels have been constructed and operated in such as Norway and Japan. The main technical problem in the construction of subsea tunnel is to secure stability due to high water pressure conditions and large-scale seawater inflow in fault zones and weak zones. In this paper, various risk factors and solutions are described in the subsea tunnel planning of national road 77 construction work between Abhae and Hwawon.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.1
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• pp.19-28
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• 2022

Recently, cryptocurrency has attracted much attention, and price prediction studies of cryptocurrency have been actively conducted. Especially, efforts to improve the prediction performance by applying the deep learning model are continuing. LSTM (Long Short-Term Memory) model, which shows high performance in time series data among deep learning models, is applied in various views. However, it shows low performance in cryptocurrency price data with high volatility. Although, to solve this problem, new input features were found and study was conducted using them, there is a lack of study on input features that drop predictive performance. Thus, in this paper, we collect the recent trends of six cryptocurrencies including Bitcoin and Ethereum and analyze effects of input features on the cryptocurrency price predictive performance through statistics and deep learning. The results of the experiment showed that cryptocurrency price predictive performance the best when open price, high price, low price, volume and price were combined except for rate of closing price fluctuation.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.803-815
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• 2021

As the world's aging population increases, the aging problem in China, which has a huge population, has reached a serious situation. Therefore, this study intends to present the CCRC model of smart home care. Seven application factors of CCRC of smart home care and problems of CCRC of smart home care in China were derived through theoretical review and case analysis. Based on this, this study presented a value proposition for the 7 application elements of smart home care CCRC tailored to China's aging status and future technology demand. First, it improves the environmental atmosphere and increases the comfort of the spatial environment. Second, we value the physical and environmental safety of the elderly. Third, online convenience services are provided. Fourth, we guarantee the health and psychological health of the elderly. Fifth, it increases the efficiency of responding to unexpected situations. Sixth, predict the physical condition and surrounding environment of the elderly. Seventh, add more recreational rides. Through this, we expect to improve the quality of life by providing a safe and comfortable smart service environment for the elderly.

• The Journal of Engineering Geology
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• v.31 no.4
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• pp.523-532
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• 2021

The treatment of acid rock drainage was reviewed and evaluated for the case of pyrite rocks distributed in a highway embankment. During the highway's construction, neutralization using alkaline water repellent was applied to the embankment section to prevent acid rock drainage. However, it still occurred long after the construction was completed owing to rain infiltration, and the acid rock drainage polluted the surrounding soils and streams. To solve this problem, treatment facilities such as SAPS (Successive Alkalinity Producing Systems) or ecological wetlands and sand filtration were installed. After the installation of the treatment facilities, the effluent and soils contaminated by acid rock drainage nearby the outlet of the facilities were analyzed and evaluated for a period of years. Measurements of the pH of the effluent and analysis of the heavy metal contamination of the soils confirmed that the neutralization treatment for acid rock drainage is being performed properly and that contamination of heavy metals in the acid rock drainage is also being stably controlled by the treatment facilities.

• Journal of the Korea Convergence Society
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• v.12 no.11
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• pp.319-328
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• 2021

The purpose of this study is to develop core competencies for gifted education by utilizing Delphi survey methods and to present behavioral element selection and scale questions based on the definition of competencies. First, the core competence for gifted education was selected through literature analysis, and the first Delphi survey was conducted to verify that the definition of each competency is suitable for the competency name. Subsequently, through a second Delphi survey, detailed questions were developed and verified by expressing the capabilities required to develop core competencies as behavior elements. Through two rounds of Delphi surveys, eight key competencies were finally selected: attitude and practice willingness, communication and collaboration, information processing and tool utilization, creative problem solving, convergence and application, higher-order inference, community spirit, and learning achievement orientation. This study is meaningful in that it selects core competencies and behavior elements for gifted education that are necessary to pursue goals that meet social needs and it presents tools to measure the degree of competency improvement for gifted education.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1914-1919
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• 2021

With the development of advanced industries, research on image processing hardware is essential, and timing verification at the gate level is required for actual chip operation. For FPGA-based verification, DDR3 memory interface was previously applied. But recently, as the FPGA specification has improved, DDR4 memory is used. In this case, when a previously used memory interface is applied, the timing mismatch of signals may occur and thus cannot be used. This is due to the difference in performance between CPU and memory. In this paper, the problem is solved through state optimization of the existing interface system FSM. In this process, data read speed is doubled through AXI Data Width modification. For actual case analysis, ZC706 using DDR3 memory and ZCU106 using DDR4 memory among Xilinx's SoC boards are used.

• Asian Journal of Innovation and Policy
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• v.11 no.1
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• pp.1-29
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• 2022

Climate action is at the top of the agenda in the international community, as demonstrated at the 2021 G7 Summit and the 2021 UN Climate Summit. Major developed countries are scrambling to make a transition to a green economy and create a new growth momentum. Following the Paris Climate Agreement in 2016, they focus on "carbon neutrality" as an effective means of tackling climate change. The Republic of Korea, a high-carbon economy, submitted its second Nationally Determined Contribution and announced carbon neutrality as a top policy priority. Accordingly, the country increases government budget in research and development (R&D) and science and technology (S&T) policies. Against this backdrop, this study analyzed policies on carbon-neutral S&T and R&D in major advanced countries. The analysis was made by identifying globally pending issues in carbon-neutral policies and climate technology. In addition, focus group interviews were conducted six times with 10 experts to come up with three R&D strategies and action plans for government-funded research institutes to achieve carbon neutrality. To be specific, the following measures were suggested. First, creative and innovative R&D programs are required to solve the problem of carbon emissions. Second, it is necessary to establish carbon neutrality policies and infrastructure which are sustainable to run and manage. Third, it is crucial to promote cooperation in climate technology based on excellence. In conclusion, the strategies proposed in this study are expected to provide directions and implications for policymakers, researchers, and scholars in science and technology to develop effective strategies to achieve national carbon neutrality.