• The Journal of Engineering Geology
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• v.9 no.1
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• pp.1-15
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• 1999

An artificial recharge test was performed to analyze the source of seepage observed inside the Songsanri tombs Kongju during the rainy season. In order to simulate simulate the test, a two-dimensional unsaturated groundwater flow model was developed. By the measured water level variation in the observation wells and in the artificail water tank, the model was cailbrated to estimate the model parameters such as fitting parameters in the constitutive relations(n and $\alpha$), the saturated volumetric water content, the residual volumetric water content, and the saturated hydraulic conductivity. Using the calibrated parameters, the recharge test was simulated. The results of the test and simulation show that the major source of the seepage is the downward groundwater flow through cracks in the protection layer the tombs. It was also analyzed by the steady state simulation that, with a perfect protection layer, a long-term precipitation that, with a perfect protection layer, a long-term precitation could cause only 10% increase of the effective saturation around the north side of the Muryong royal tomb by infiltration of the unsaturated groundwater from the North. Therefore, it is concluded that the most urgent protection plan for the tombs with respect to seepage is to reconstruct an effective waterproof-layer rather than a trenched drainage system.

• Journal of Korea Water Resources Association
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• v.37 no.2
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• pp.97-108
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• 2004

Recently the ground-water development using the ground-water dam was proposed for the efficient use of the limited water resources especially for islands or seaside area. But in operating the ground-water dam adjacent to seaside an excessive pumping causes the sea-water intrusion which is caused by the drawdown of ground-water level. In this study, the effect of the recharging well method to reduce the sea-water intrusion was evaluated, and was applied to the downstream of the Ssangcheon ground-water dam site. The SUTRA model was used to simulate the salinity transport in the unsaturated and saturated zone. As the results, the effect of recharging method on the downstream of the ground-water dam was proven to be very efficient to reduce the salinity in the pumping well, and especially the best result was shown at the case that the recharging well is located at 40∼60m from the cutoff wall and the recharging rate is up to 6∼7％.

• Magazine of the Korean Society of Agricultural Engineers
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• v.58 no.3
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• pp.59-63
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• 2016

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.3
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• pp.421-426
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• 2023

Among artificial intelligence convergence technologies, Chatbot is an artificial intelligence-based interactive system and refers to a system that can provide interaction with humans. Chatbots are being re-examined as chatbots develop into NLP, NLU, and NLG. However, artificial intelligence chatbots can provide biased information based on learned data and cause serious damage such as privacy infringement and cybersecurity concerns, and it is essential to understand artificial intelligence technology and foster AI literacy. With the continued evolution and universalization of artificial intelligence, AI Literacy will also expand its scope and include new areas. This study is meaningful in raising awareness of artificial intelligence technology and proposing the use of human respect technology that is not buried in technology by cultivating human AI literacy capabilities.

• Water for future
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• v.23 no.2
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• pp.239-250
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• 1990

The method for artificial grondwater recharge can be categorized into two groups, one is well method and the other one is scattering method. Underground piping method belongs to the latter group and it is to infiltrate water from porous pipes buried underground. This paper shows the result of indoor experiment and numerical analysis concerning this method. The purpose of the study is to maky the infiltration aspects and groundwater recharge in underground piping method. We have found that the recharge height is effect by the difference of water level and a distance of pipe laying.

• Proceedings of the Korea Water Resources Association Conference
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• 1990.07a
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• pp.61-79
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• 1990

The method for artificial groundwater recharge can be categorized into two groups, one is well method and the other one is scattering method. Underground piping method belongs to the latter group and it is to infiltrate water from porous pipes buried underground. This paper shows the result of indoor experiment and numerical analysis concerning this method. The purpose of the study is to make the infiltration aspects and groundwater recharge in underground piping method. We have fround that the recharge height is effect by the difference of water level and a distance of pipe laying.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.388-388
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• 2017

낙동강 하류 일대에는 수질과 수량 두 가지 요건을 모두 충족하는 강변여과수를 새로운 수자원 확보 대안으로 활용하고 있다. 일부 지역의 경우 과도한 취수량으로 인한 지하수 고갈을 우려하여 개발을 반대하거나 이로 인한 피해보상 범위가 명확치 않아 간접편입부지의 주민들이 피해를 우려하고 있는 실정이다. 따라서 해당 지역에서의 취수량은 인근 주민들에게 피해가 가지 않는 한도 내에서 이루어 져야한다. 하지만 타 지역으로 원수를 공급하게 되어 필요이상의 지하수를 개발하게 되거나 목표취수량에 부합하지 않아 추가 양수정을 시공하는 경우와 같이 수요량과 적정 취수량사이에 문제가 발생하는 경우가 있다. 이러한 배후 지하수위 감소영향과 추가취수량 확보를 위해 주입정을 활용한 인공함양 방법이 적용될 수 있다. 본 연구에서는 강변여과 취수 시 배후 지역의 지하수가 유입되어 인근 지역의 지하수위 강하량을 감소시키기 위한 최적 주입 위치 및 주입량을 산정하는 프로그램을 개발하였다. 고려된 최적화 결정변수는 주입정 개수와 위치, 그리고 주입량이며 제약 조건으로는 기 설치된 양수정 위치, 초기 자연 평형상태의 배후 지하수위에 근사하는 주입정 위치에 따른 최소 주입량 그리고 추가 생산 가능량 이다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.01a
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• pp.227-228
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• 2023

정부의 인공지능 국가전략을 통해 인공지능 교육은 초등학교에서도 필수교육으로 대두되고 있다. 또한 인공지능 소양을 습득하기 위해 타 교과와 융합한 인공지능 융합 교육의 필요성이 증가하고 있고, 인공지능 발달에 대한 수학의 역할을 고려하여 수학 교과를 통해 인공지능의 이해를 기르는 것이 강조되고 있다. 따라서 본 연구에서는 수학 교과와 인공지능 교과가 융합한 인공지능 융합 교육 프로그램을 개발하기 위해 초등학교 3~4학년 수학 교과의 도형 분류를 의사 결정 나무 모델을 활용하여 가르치는 인공지능 융합 교육 프로그램을 개발하였다. 본 연구를 통해 개발된 프로그램은 초등학생의 인공지능 개념학습을 통한 인공지능 기초소양 함양뿐만 아니라 수학 교과의 이해 및 성취도 향상에 도움이 될 것으로 기대된다.

• Journal of Korean Society of Environmental Engineers
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• v.30 no.4
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• pp.385-392
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• 2008

In this study, seawater intrusion was assessed employing a kind of biological parameters such as Escherichia coli and Enterococcus faecalis while lab-prepared reclaimed water was recharged to prevent seawater intrusion. Chemical factors indicating seawater intrusion such as Cl$^-$, Ca$^{2+}$, Mg$^{2+}$ and specific conductivity were also simultaneously investigated where an ion exchange between a matrix in artificial aquifer and cations in solution was estimated. Both Escherichia coli and Enterococcus faecalis were shown to be very sensitive against degree of salinity during saline water intrusion. Enterococcus faecalis more strongly resisted against salinity than that of Escherichia coli. The ratio of Enterococcus faecalis divided by E. coli in the process of seawater intrusion increased up to more than 50$\sim$100 times in 18 hours whereas E. coli was died off more than 90% during pumping and recharge rate kept at 10 mL/min. However, when the rates of both recharge and pumping was kept at 5 mL/min, Enterococcus faecalis / Escherichia coli was sustained in the range of 2.5$\sim$5.0, while Escherichia coli showed dimished death rate. Chemical factors such as Cl$^-$, Ca$^{2+}$, Mg$^{2+}$ and specific conductivity showed more than 0.9 of high correlation each other well explaining the degree of seawater intrusion. The degree of ion exchange between artificial aquifer and saline water can be efficiently interpreted by both minus $\Delta$Na, $\Delta$Mg variation and positive $\Delta$Ca variation.

• Journal of Industrial Convergence
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• v.20 no.5
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• pp.83-92
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• 2022

As cases of social and ethical problems caused by artificial intelligence technology have occurred, artificial intelligence ethics are drawing attention along with social interest in the risks and side effects of artificial intelligence. Artificial intelligence ethics should not just be known and felt, but should be actionable and practiced. Therefore, this study proposes an artificial intelligence ethics education model to strengthen the practical ability of artificial intelligence ethics. The artificial intelligence ethics education model derived educational goals and problem-solving processes using artificial intelligence through existing research analysis, applied teaching and learning methods to strengthen practical skills, and compared and analyzed the existing artificial intelligence education model. The artificial intelligence ethics education model proposed in this paper aims to cultivate computing thinking skills and strengthen the practical ability of artificial intelligence ethics. To this end, the problem-solving process using artificial intelligence was presented in six stages, and artificial intelligence ethical factors reflecting the characteristics of artificial intelligence were derived and applied to the problem-solving process. In addition, it was designed to unconsciously check the ethical standards of artificial intelligence through preand post-evaluation of artificial intelligence ethics and apply learner-centered education and learning methods to make learners' ethical practices a habit. The artificial intelligence ethics education model developed through this study is expected to be artificial intelligence education that leads to practice by developing computing thinking skills.