• Proceedings of the Korea Air Pollution Research Association Conference
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• 2001.11a
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• pp.399-400
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• 2001

최근 대도시의 대기 오염은 자동차에 의한 선오염원이 차지하는 비중이 전체 오염원 중에서 상대적으로 크게 증가하고 있고, 선오염원에 의한 영향도 분석에는 대기확산모델을 주로 이용한다. 우리나라에서 사용하는 선오염원 모델에는 HIWAY2, PAL, CALINE3, CAL3QHC, CAL3QHCR 등이 있다. 이와 같은 모델은 주로 환경영향평가에 이용되고 있는데, 현재 국내 환경영향평가에서 주로 사용되고있는 선오염원 예측 모델은 CALINE3이다. (중략)

• Proceedings of the Korea Air Pollution Research Association Conference
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• 2002.04a
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• pp.105-106
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• 2002

산업이 발달함에 따라 대기 환경의 중요성이 강조되면서 대기 확산 모델을 이용하여 오염물질의 영향을 파악하는 일이 많아졌다. 그러나 대기 확산 모델은 수치계산으로 나온 값으로 자연현상의 모든 영향을 파악하기 어렵다는 한계점을 가지고 있다. 이러한 대기 확산 모델이 자연현상을 어느 정도 반영하는가를 평가하기 위해서는 추적자 물질을 이용하여 대기 오염물질의 확산 농도를 측정한 실측자료를 통하여 기존 모델을 평가하고 개선하는 것이 일반적인 방법이다. (중략)

• Journal of Korean Philosophical Society
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• v.144
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• pp.257-283
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• 2017

The purpose of this paper is primarily to examine models of collective decision-formation and decision-making. The goal is to propose a model of decision-formation and decision-making that is appropriate for a democratic society. Habermas distinguishes these models of decision-formation and decision-making by liberal, republican, and deliberative political models according to their justification types. Axel Honneth, on the other hand, is divided into three models of liberalism, proceduralism, and republicanism. I want to divide the model of possible decision-making in democratic society into three, that is, the model based on force, the model based on procedure, and the republican model. This distinction will identify the characteristics of each decision-making model and this confirmation will help us find the best decision-making model for a democratic society. In the end, I will combine the republican model with the procedural model. For this synthesis, I will also propose three conditions in modern society. I will argue that the three conditions of collective intelligence, active freedom, and horizontal networks are necessary.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3A
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• pp.465-471
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• 2006

To describe hysteretic behavior of steel structures under dynamic loading such as earthquake, the dynamic cyclic plasticity model considering stress-strain relationship and characteristics of used steel materials under static-dynamic deforming is required. In this paper, mechanical characteristics and stress-strain relationship of SM490 was clarified by carrying out static-dynamic monotonic and cyclic loading test. A dynamic cyclic plasticity model of SM490 was proposed based on the test results and applied 3-dimensional finite element analysis using finite deformation theory. An analytical method developed by the authors was verified validity and accuracy by comparing both analysis and test results. The comparison result shows that the analytical method developed by the authors can predict static-dynamic hysteretic behavior of steel structures with accuracy.

• Journal of the Korean Institute of Gas
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• v.19 no.1
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• pp.28-37
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• 2015

This study presents the development of a well placement optimization model, combining an artificial neural network, which enables high-speed calculation, with a simulated annealing algorithm. The conventional FDM simulator takes excessive time when used to perform a field scale reservoir simulation. In order to solve this problem, an artificial neural network was applied to the model to allow the simulation to be executed within a short time. Also by using the given result, the optimization method, SA algorithm, was implemented to automatically select the optimal location without taking any subjective experiences into consideration. By comparing the result of the developed model with the eclipse simulator, it was found that the prediction performance of the developed model has become favorable, and the speed of calculation performance has also been improved. Especially, the optimum value was estimated by performing a sensitivity analysis for the cooling rate and the initial temperature, which is the control parameter of SA algorithm. From this result, it was verified that the calculation performance has been improved, as well. Lastly, an optimization for the well placement was performed using the model, and it concluded the optimized place for the well by selecting regions with great productivity.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.2A
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• pp.259-267
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• 2008

The ultimate strengths of reinforced concrete deep beams are governed by the capacity of the shear resistance mechanism composed of concrete and shear reinforcing bars, and the structural behaviors of the beams are mainly controlled by the mechanical relationships according to the shear span-to-effective depth ratio, flexural reinforcement ratio, load and support conditions, and material properties. In this study, a simple indeterminate strut-tie model reflecting all characteristics of the ultimate strengths and complicated structural behaviors is presented for the design of simply supported reinforced concrete deep beams. In addition, a load distribution ratio, defined as a magnitude of load transferred by a vertical truss mechanism, is proposed to help structural designers perform the design of simply supported reinforced concrete deep beams by using the strut-tie model approaches of current design codes. In the determination of a load distribution ratio, a concept of balanced shear reinforcement ratio requiring a simultaneous failure of inclined concrete strut and vertical steel tie is introduced to ensure the ductile shear failure of reinforced concrete deep beams, and the prime design variables including the shear span-to-effective depth ratio, flexural reinforcement ratio, and compressive strength of concrete influencing the ultimate strength and behavior are reflected upon based on various and numerous numerical analysis results. In the companion paper, the validity of presented model and load distribution ratio was examined by employing them to the evaluation of the ultimate strengths of various simply supported reinforced concrete deep beams tested to failure.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.7A
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• pp.682-688
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• 2006

In this paper, a soft-decision method for initial PN code acquisition in pilot-channel aided Direct Sequence Code Division Multiple Access (DS-CDMA) systems is proposed in order to improve the acquisition performance. We apply this technique to the conventional hybrid search algorithm and analyze it in terms of mean code acquisition time. For the analysis, we present mathematical model of proposed algorithm and also perform the simulation under IMT-2000 channel models. Numerical results show that our proposed scheme outperforms the conventional one by 0.2 - 0.4 sec with respect to the mean code acquisition time because the soft decision technique can mitigate the possible decline in search performance caused by the use of a hard-decision technique.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.285-285
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• 2020

본 연구에서는 국내 시설농업단지의 수리지질 특성을 고려한 개념 모델을 설정하여 수리전도도와 이격거리(주입정과 양수정 사이의 거리)에 대한 민감도 분석을 수행하였다. 개념 모델에는 자연적 특성(지형과 지질, 강수량, 수리전도도 등)과 인공적 특성(주입정과 양수정의 이격거리, 주입량과 양수량 등)이 입력되었으며, 민감도 분석은 수리전도도(10^-1 cm/sec, 10^-2 cm/sec, 10^-3 cm/sec, 10^-4 cm/sec)와 이격거리(10 m, 50 m, 100 m)를 조합한 12개의 시나리오로 수행하였다. 양수정의 하류부에 설정된 관측정의 지하수위 강하량은 수리전도도가 감소하고 이격거리가 멀어질수록 증가하였다. 동일한 이격거리에서 수리전도도에 의한 지하수위 강하량의 회귀분석을 통해 인공함양 대수층의 지하수위 변동은 수리전도도에 의해 지배적인 영향을 받음을 알 수 있었다. 인공함양 대수층의 수리전도도가 10^-2 cm/sec 이상인 조건에서는 주입정과 양수정의 이격거리에 따른 지하수위의 영향반경은 20 m 이내이었지만, 수리전도도가 10^-3 cm/sec 이하인 조건에서는 이격거리가 멀어질수록 지하수위의 영향반경이 급격하게 증가함을 확인하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.530-531
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• 2023

딥러닝에서 지식 증류 기법은 큰 모델의 지식을 작은 모델로 전달하여 작은 모델의 성능을 개선하는 방식이다. 지식 증류 기법은 모델 경량화, 학습 속도 향상, 학습 정확도 향상 등에 활용될 수 있는데, 교사 모델이라 불리는 큰 모델은 일반적으로 학습된 딥러닝 모델을 사용한다. 본 연구에서는 학습된 딥러닝 모델 대신에 수치 기반 시뮬레이션 모델을 사용함으로써 어떠한 효과가 있는지 검증하였으며, 수치 모델을 활용한 기상 예측 모델에서의 지식 증류는 기존 단독 딥러닝 모델 학습 대비 더 작은 학습 횟수(epoch)에서도 동일한 에러 수준(RMSE)까지 도달하여, 학습 속도 측면에서 이득이 있음을 확인하였다.

• KIPS Transactions on Computer and Communication Systems
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• v.12 no.10
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• pp.309-318
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• 2023

Recently, each country has been moving to introduce an LCA (Life Cycle Assessment) to regulate greenhouse gas emissions. The LCA is a mean of measuring and evaluating greenhouse gas emissions generated over the entire life cycle of a vehicle. Reliable data for each electric vehicle component is needed to increase the reliability of the LCA results. To this end, studies on life cycle evaluation models using blockchain technology have been conducted. However, in the existing model, key product information is exposed to other participants. And each time parts data information is updated, it must be recorded in the blockchain ledger in the form of a transaction, which is inefficient. In this paper, we proposed a DID(Decentralized Identity)-based data collection model for LCA to collect vehicle component data and verify its validity effectively. The proposed model increases the reliability of the LCA by ensuring the validity and integrity of the collected data and verifying the source of the data. The proposed model guarantees the validity and integrity of collected data. As only user authentication information is shared on the blockchain ledger, the model prevents indiscriminate exposure of data and efficiently verifies and updates the source of data.