• Advances in Computational Design
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• v.8 no.2
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• pp.97-112
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• 2023

The Finite Element (FE) modeling of Reinforced Concrete (RC) under seismic loading has a sensitive impact in terms of getting good contribution compared to experimental results. Several idealized model types for simulating the nonlinear response have been developed based on the plasticity distribution alone the model. The Continuum Models are the most used category of modeling, to understand the seismic behavior of structural elements in terms of their components, cracking patterns, hysteretic response, and failure mechanisms. However, the material modeling, contact and nonlinear analysis strategy are highly complex due to the joint operation of concrete and steel. This paper presents a numerical simulation of a chosen RC column under monotonic and cyclic loading using the FE Abaqus, to assessthe hysteretic response and failure mechanisms in the RC columns, where the perfect bonding option is used for the contact between concrete and steel. While results of the numerical study under cyclic loading compared to experimental tests might be unsuccessful due to the lack of bond-slip modeling. The monotonic loading shows a good estimation of the envelope response and deformation components. In addition, this work further demonstrates the advantage and efficiency of the damage distributions since the obtained damage distributions fit the expected results.

• New & Renewable Energy
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• v.18 no.1
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• pp.1-16
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• 2022

Climatic characteristics were described using the LiDAR (Light Detection and Ranging) and the met-mast on Dongbok·Bukchon region. The influences of meteorological conditions on the power performance of wind turbines were presented using the data of Supervisory Control And Data Acquisition (SCADA) and met-mast of the Dongbok·Bukchon Wind Farm (DBWF) located in Jeju Island. The stability was categorized into three parameters (Richardson number, Turbulence intensity, and Wind shear exponent). DBWF was dominant in unstable atmospheric conditions. At wind speeds of 14 m/s or more, the proportion of slightly unstable conditions accounted for more than 50%. A clear difference in the power output of the wind turbine was exhibited in the category of atmospheric stability and turbulence intensity (TI). Particularly, a more sensitive difference in power performance was showed in the rated wind speeds of the wind turbine and wind regime with high TI. When the flow had a high turbulence at low wind speeds and a low turbulence at rated wind speeds, a higher wind energy potential was produced than that in other conditions. Finally, the high-efficiency of the wind farm was confirmed in the slightly unstable atmospheric stability. However, when the unstable state become stronger, the wind farm efficiency was lower than that in the stable state.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.3
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• pp.251-258
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• 2023

This study (1) explored spatio-temporal population distribution patterns in Jeonju by using emerging hot spot analysis and (2) identified the influential factors to determine the spatio-temporal patterns by using multinomial logit model. The major findings are as follows. First, the results of emerging hot spot analysis indicated that the 100*100m grid in the urban area of Jeonju was found to have a category of hot spots, whereas most of the cold spot series was concentrated in the outskirts of the city. Also, new towns such as Jeonju Eco City, Jeonbuk Innovation City, and Hyocheon District were persistent or intensifying hot spots, Third, the results of multinomial logit model revealed that the factors influencing deterrmining the spatio-temporal patterns were accessibility to schools, hospitals, parks, and walfare services. This study offered a deeper understanding of urbanization and regional changes in Jeonju, and important information for urban planning.

• International Journal of Computer Science & Network Security
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• v.23 no.11
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• pp.183-189
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• 2023

A stroke is a medical disease where a blood vessel in the brain ruptures, causes damage to the brain. If the flow of blood and different nutrients to the brain is intermittent, symptoms may occur. Stroke is other reason for loss of life and widespread disorder. The prevalence of stroke is high in growing countries, with ischemic stroke being the high usual category. Many of the forewarning signs of stroke can be recognized the seriousness of a stroke can be reduced. Most of the earlier stroke detections and prediction models uses image examination tools like CT (Computed Tomography) scan or MRI (Magnetic Resonance Imaging) which are costly and difficult to use for actual-time recognition. Machine learning (ML) is a part of artificial intelligence (AI) that makes software applications to gain the exact accuracy to predict the end results not having to be directly involved to get the work done. In recent times ML algorithms have gained lot of attention due to their accurate results in medical fields. Hence in this work, Stroke disease identification system by using Machine Learning algorithm is presented. The ML algorithm used in this work is Artificial Neural Network (ANN). The result analysis of presented ML algorithm is compared with different ML algorithms. The performance of the presented approach is compared to find the better algorithm for stroke identification.

• Asia pacific journal of information systems
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• v.32 no.2
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• pp.226-248
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• 2022

The existing model for sentiment analysis of product reviews learned from past data and new data was labeled based on training. But new data was never used by the existing system for making a decision. The proposed Aspect-based multi-agent Deep Reinforcement learning Sentiment Analysis (ADRSA) model learned from its very first data without the help of any training dataset and labeled a sentence with aspect category and sentiment polarity. It keeps on learning from the new data and updates its knowledge for improving its intelligence. The decision of the proposed system changed over time based on the new data. So, the accuracy of the sentiment analysis using deep reinforcement learning was improved over supervised learning and unsupervised learning methods. Hence, the sentiments of premium customers on a particular site can be explored to other customers effectively. A dynamic environment with a strong knowledge base can help the system to remember the sentences and usage State Action Reward State Action (SARSA) algorithm with Bidirectional Encoder Representations from Transformers (BERT) model improved the performance of the proposed system in terms of accuracy when compared to the state of art methods.

• Korean Journal of Medicinal Crop Science
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• v.27 no.6
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• pp.397-403
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• 2019

Background: Oplopanax elatus is widely distributed at high altitudes (about 1,100 m) in China, Russia and Korea. It is hard to propagate, breed, and difficult to grow. Hence, it has been designated as a rare and endangered medicinal plant. A study was conducted to establish a system for large scale seedling production of Oplopanax elatus in vitro and to find the ideal environment for its seedling growth. Methods and Results: In this study, the explants produced under in vitro conditions during our previous study were grouped into three categories (under 10 mm, 10 mm - 30 mm and above 30 mm) based on plant height and were transferred to the growth-chamber and greenhouse for two weeks in each setting for acclimatization. The plantlet category of above 30 mm showed good performance, and was further evaluated under three acclimatization methods as follows: three different growth media (commercial soil, commercial soil + perlite, commercial soil + sand), four shading levels (0%, 50%, 70%, 90%) and four altitude levels (157 m, 218 m, 601 m, 870 m) in Gangwon province of South Korea. As results, O. elatus seedlings showed better growth characteristics at 870 m of altitude, 70% shading level and in the commercial soil compared to other treatments. Conclusions: The regenerated seedlings of Oplopanax elatus obtained through plant tissue culture would be advantageous for use in large scale seedling production systems paired with a good acclimation method. For obtaining optimal results, it is recommended that seedling be acclimatized in a high altitude environment.

• Korean Journal of Environment and Ecology
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• v.30 no.6
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• pp.1067-1072
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• 2016

In this study, we determined the ecological characteristics of Strix aluco, which is designated as an endangered category II species. Towards this, we identified the actual home range of Strix aluco that breed in Korea, and collected the data necessary for protecting, preserving and managing owl populations. This study was conducted from April 14 to May 20 of 2016 during the breeding season of Strix aluco as part of the 4th National Ecosystem Survey and in accordance with the Natural Environment Conservation Act. We captured and subsequently released a female owl with a total length of 423.5mm and a weight of 550g in Kyungbuk area, succeeded in tracking it for the first time in Korea and secured 6 points of direct observation and satellite tracking observation. The distance from the nest to the farthest point was 93m. As a result of the analysis of habitat points within a100m-radius during breeding period, it was established that their habitat consists of 34.2% of non-irrigated land, 30.6% of mixed forest land, 10.5% of orchard, and 9.4% of natural grassland. These findings are consistent with the previous estimate of home range studies. Further research based on follow-up studies on males or other individuals is required to develop a stronger basis for protection and conservation of endangered wildlife class II owls.

• Journal of Korea Water Resources Association
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• v.41 no.2
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• pp.212-228
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• 2008

Five representative reference evapotranspiration(RET) equations were selected, and these equations were compared with pan evaporation by correlation analysis. Pan coefficients were also estimated. Furthermore, five selected RET equations were compared to find the similarity among those at the 21 meteorological stations located in South Korea. Five RET equations selected from 4 different category were Penman(combination approach), FAO Penman-Monteith(FAO P-M) (single source approach), Makkink and Priestley-Taylor (radiation approach) and Hargreaves(temperature approach) equations. In this study, the geographical and topographical conditions were considered for the selection of study stations. The daily meteorological data measured from 1970 at an interval of 5 years were applied in this study. The evapotranspiration estimates obtained by applying evapotranspiration equations were evaluated with numerical and graphical methods. The correlation coefficients between pan evaporation and RET in study stations were above 0.9 indicating very high correlation; however, the slopes of the individual regression lines show the values greater or less than 1.0. Hargreaves equation(temperature approach) shows the most similar evapotranspiration estimates to those of FAO P-M equation from 12 study stations, which are located near to seashore except Daegu station. On the other hand, Priestley-Taylor equation(radiation approach) shows the most similar evapotranspiration estimates to those of FAO P-M equation from 8 study stations, which are located in inland.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.13-13
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• 2011

The Rio Grande Compact Commission, in collaboration with local water management entities, water users and universities established a three state Rio Grande The Rio Grande Compact Commission, in collaboration with local water management entities, water users and universities established a three state Rio Grande Salinity Management Program. The objectives of the Rio Grande Project Salinity Management Program are to reduce salinity concentrations, loading, and salinity impacts in the Rio Grande basin for the 270 mile river reach from San Acacia, New Mexico to Fort Quitman, Texasto increase usable water supplies for agricultural, urban, and environmental purposes. The focus of this first phase of the program is the development of baseline salinity and hydrologic information and a preliminary assessment of the economic impacts of salinity. An assessment of the economic impacts of salinity in this region was conducted by scientists at Texas A&M University's AgriLife Research Center at El Paso and New Mexico State University. Economic damages attributable to high salinity of Rio Grandewater were estimated for residential, agricultural, municipal, and industrial uses. The major impact issues addressed were: who is being affected the types of economic impacts the magnitude of economic damages overall and by user category and identification of threshold-effect levels for different types of water use. Salinity concentrations in this 270 mile reach of the river typically range from 480 ppm to 1,200 ppm, but can exceed 3,000 ppm in the lower section of this reach. Economic impacts include reductions in agricultural yields, reduced water appliance life, equipment replacement costs, and increased water supply costs. This preliminary economic assessment indicates annual damages of $10.5 million from increased water salinity. Under current water uses, municipal and industrial uses account for 75% of the total estimated impacts. However, agricultural impacts are based on current crop pattern yield reductions and, salinity leaching requirements and do not account for the impacts of reduced revenue from having to grow salinity tolerant, lower value crops. Actual damages are anticipated to be significantly higher with the inclusion of these additional agricultural impacts plus the future impacts from the growing population in the region. A more comprehensive economic analysis is planned for the second phase of this program. Results of the economic analysis are being used to determine the feasiblity of salinity control alternatives and what salinity reduction control measures will be pursued.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.851-857
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• 2018

In this research, LCA analysis of the manufacturing process of pot bearing for fixed, movable in all directions, movable in one direction was carried out to analyze the environmental load using the LCA methodology. Especially, the water footprint that has been and issue in recent years was analyzed. As a result of LCA, it was analyzed that the contribution of the plate was more than 64.2% in all of the six impact categories in the case of fixed pot bearing base, and more than 94% in the category of resource depletion and photochemical oxidant creation. In the case of all direction pot bearing and one direction pot bearing, the contribution of PTFE was the highest in the global warming and stratospheric ozone depletion, and the contribution by the plate was higher in the other impact categories. The water footprint of each type of pot bearing was analyzed as $22.4m^3\;H_2O\;eq/kg$ for one direction pot bearing, $17.1m^3\;H_2O\;eq/kg$ for fixed pot bearing, and $14.1m^3\;H_2O\;eq/kg$ for all direction pot bearing. As a result of life cycle analysis, the contribution of water use in manufacturing was more than 65% in all three types. The results of this study can be used as basic data for decision making in construction method and material selection of bridges in the future.