• Proceedings of the Korean Geotechical Society Conference
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• 2006.03a
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• pp.1159-1164
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• 2006

In this paper an artificial neural network model is developed to estimate the unconfined compression strength of Deep Cement Mixing(DCM) treated soil. A database which consists of a number of unconfined compression test result compiled from 9 clay sites is used to train and test of the artificial neural network model. Developed neural network model requires water content of soil, unit weight of soil, passing percent of #200 sieve, weight of cement, w-c ratio as input variables. It is found that the developed artificial neural network model can predict more precise and reliable unconfined compression strength than the conventional empirical models.

• International Journal of Computer Science & Network Security
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• v.24 no.2
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• pp.1-14
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• 2024

While text-to-image models have made remarkable progress in image synthesis, certain models, particularly generative diffusion models, have exhibited a noticeable bias to- wards generating images related to the culture of some developing countries. This paper introduces an empirical investigation aimed at mitigating the bias of image generative model. We achieve this by incorporating symbols representing Saudi culture into a stable diffusion model using the Dreambooth technique. CLIP score metric is used to assess the outcomes in this study. This paper also explores the impact of varying parameters for instance the quantity of training images and the learning rate. The findings reveal a substantial reduction in bias-related concerns and propose an innovative metric for evaluating cultural relevance.

• Journal of Wetlands Research
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• v.4 no.1
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• pp.51-61
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• 2002

The wetland is a biologically integrated system consisting of water, soil, bacteria, plants, and animals. The wetland helps sustain the ecosystem, control the micro-climate and flood, maintain the ground water level, and provide fishing grounds. From the environmental standpoint, the wetland plays a vital role in reducing water pollution by filtering out sand and other polluted matters, producing oxygen, absorbing chemicals and nutrients. For these reasons, interest in restoring the wetlands has been steadily increasing. Artificial wetland, which is also referred to as created wetland or constructed wetland, is an alternative to natural wetland. Like natural wetland, artificial wetland is environmentally friendly and can effectively lower pollutant levels. The Korea government is actively reviewing the construction of artificial wetlands in mining and water supply areas to decrease nonpoint pollutant sources. This paper attempts to develop a pollutant removal model for the water quality improvement function of artificial wetlands. Artificial wetland can improve the quality of the water; however, depending on the type of water inflow, vegetation and hydrology, its effect can be different.

• The Journal of Engineering Geology
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• v.28 no.4
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• pp.741-753
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• 2018

Local drought in South Korea has recently increased interest in the efficient use of groundwater and then induces a growing need to introduce artificial recharge of groundwater that stores water in sedimentary layer. In order to evaluate the potential artificial recharge sites in the alluvial basins in Chungcheongnamdo province, an AHP (Analytical hierarchy process) model consisting of three primary and seven secondary factors was developed in this study. In the AHP model, adding candidate sites changes final evaluation score through a mathematical calculation process. By contrast ANN (Artificial neural network) model always provides an unchanged score for each candidate area. Therefore, the score can be used as a selection criterion for artificial recharge sites. It is concluded that the possibility of artificial recharge is relatively low if the score of the ANN model is less than about 1.5. Further studies and field surveys on the other regions in Korea will lead to draw out a more applicable ANN model.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.244-247
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• 2005

Although several artificial disc designs have been developed for the treatment of discogenic low back pain and used clinically, biomechanical change with its implantation seldom studied. To evaluate the effect of artificial disc implantation on the biomechanics of lumbar spinal unit, nonlinear three-dimensional finite element model of L1-L5, S1 was developed and strain and stress of vertebral body and surrounding spinal ligaments were predicted. Intact osteoligamentous L1-L5, S1 model was created with 1-mm CT scan of a volunteer and known material property of each element were applied. This model also includes the effect of local muscles which was modeled with pre-strained spring elements. The intact model was validated with reported biomechanical data. Two models implanted with artificial discs, SB Charite or Prodisc, at L4/5 via anterior approach were also developed. The implanted model predictions were compared with that of intact model. Angular motion of vertebral body, force on spinal ligaments, facet joint contact force with $2\sim12$ Nm flexion-extension moment.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.4 s.181
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• pp.176-182
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• 2006

Although several artificial disc designs have been developed for the treatment of discogenic low back pain, biomechanical changes with its implantation were rarely studied. To evaluate the effect of artificial disc implantation on the biomechanics of functional spinal unit, a nonlinear three-dimensional finite element model of L4-L5 was developed with 1-mm CT scan data. Biomechanical analysis was performed for two different types of artificial disc having constrained and unconstrained instant center of rotation(ICR), ProDisc and SB Charite III model. The implanted model predictions were compared with that of intact model. Angular motion of vertebral body, forces on the spinal ligaments and facet joint, and stress distribution of vertebral endplate for flexion-extension, lateral bending, and axial rotation with a compressive preload of 400N were compared. The implanted model showed increased flexion-extension range of motion compared to that of intact model. Under 6Nm moment, the range of motion were 140%, 170% and 200% of intact in SB Charite III model and 133%, 137%, and 138% in ProDisc model. The increased stress distribution on vertebral endplate for implanted cases could be able to explain the heterotopic ossification around vertebral body in clinical observation. As a result of this study, it is obvious that implanted segment with artificial disc suffers from increased motion and stress that can result in accelerated degenerated change of surrounding structure. Unconstrained ICR model showed increased in motion but less stress in the implanted segment than constrained model.

• Journal of Soil and Groundwater Environment
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• v.16 no.6
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• pp.34-45
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• 2011

For the Hancheon drainage area in Jeju island, a groundwater flow model using Visual MODFLOW was developed to simulate artificial recharge through injection wells installed in the Hancheon reservoir. The model was used to analyze changes of the groundwater level and the water budget due to the artificial recharge. The model assumed that $2{\times}10^6m^3$ of storm water would recharge annually through the injection wells during the rainy season. The transient simulation results showed that the water level rose by 39.6 m at the nearest monitoring well and by 0.26 m at the well located 7 km downstream from the injection wells demonstrating a large extent of the affected area by the artificial recharge. It also shown that, at the time when the recharge ended in the 5th year, the water level increased by 81 m at the artificial reservoir and the radius of influence was about 2.1 km downstream toward the coast. The residence time of recharged groundwater was estimated to be no less than 5 years. The model also illustrated that 15 years of artificial recharge could increase the average linear velocity of groundwater up to 1540 m/yr, which showed 100 m/yr higher than before. Increase of groundwater storage due to artificial recharge was calculated to be $2.4{\times}10^6$ and $4.3{\times}10^6m^3$ at the end of the 5th and 10th years of artificial recharge, respectively. The rate of storage increase was gradually diminished afterwards, and storage increase of $5.0{\times}10^6m^3$ was retained after 15 years of artificial recharge. Conclusively, the artificial recharge system could augment $5.0{\times}10^6m^3$ of additional groundwater resources in the Hancheon area.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.349-354
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• 2021

In this study, a model that can converge with artificial intelligence in each subject as software and artificial intelligence education become mandatory in the curriculum revised in 2022 is proposed. The proposed AI convergence education model is based on the content of the subject (accomplishment standard + subject). The second axis is artificial intelligence tools, the third axis is artificial intelligence technology, and the fourth axis is data applied in daily life. In order to apply artificial intelligence to each subject, it is necessary to apply artificial intelligence tools, artificial intelligence technology, and data in daily life to the achievement standards and content of each subject. If the achievement standards and subject contents are structured in this way, it can be seen that the convergence with each subject is good. Therefore, when composing textbooks by achievement standards and topics, it is necessary to add artificial intelligence tools, artificial intelligence technology, and daily data.

• Journal of Environmental Science International
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• v.9 no.6
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• pp.455-462
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• 2000

This study aims at the development of the model for a forecasting of water quality in river basins using artificial neural network technique. Water quality by Artificial Neural Network Model forecasted and compared with observed values at the Sangju q and Dalsung stations in Nakdong river basin. For it, a multi-layer neural network was constructed to forecast river water quality. The neural network learns continuous-valued input and output data. Input data was selected as BOD, CO discharge and precipitation. As a result, it showed that method III of three methods was suitable more han other methods by statistical test(ME, MSE, Bias and VER). Therefore, it showed that Artificial Neural Network Model was suitable for forecasting river water quality.

• Journal of The Korean Association of Information Education
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• v.21 no.1
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• pp.139-149
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• 2017

Artificial intelligence education is very important in the 21st century knowledge information society. Even if it is very important to understand artificial intelligence and practice computer programming in computer education in the fourth industrial revolution, but there is no teaching and learning model to understand artificial intelligence and computer programming education. In this paper, the proposed model consists of problem understanding step, data organizing step, artificial intelligence model setting step, programming step, and report writing step. At the program step, students can choose to copy, transform, create, and challenge steps to their level. In this study, the validity of the model was proved by the Delphi evaluation of elementary school teachers. The results of this study provide a good opportunity for elementary school students to practice artificial intelligence programs.