• 한국의학물리학회지:의학물리
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• 제31권1호
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• pp.1-7
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• 2020

Hadron therapy, such as carbon and helium ions, is increasingly coming to the fore for the treatment of cancers. Such hadron therapy has several advantages over conventional radiotherapy using photons and electrons physically and clinically. These advantages are due to the different physical and biological characteristics of heavy ions including high linear energy transfer and Bragg peak, which lead to the reduced exit dose, lower normal tissue complication probability and the increased relative biological effectiveness (RBE). Despite the promising prospects on the carbon ion radiation therapy, it is in dispute with which bio-mathematical models to calculate the carbon ion RBE. The two most widely used models are local effect model and microdosimetric kinetic model, which are actively utilized in Europe and Japan respectively. Such selection on the RBE model is a crucial issue in that the dose prescription for planning differs according to the models. In this study, we aim to (i) introduce the concept of RBE, (ii) clarify the determinants of RBE, and (iii) compare the existing RBE models for carbon ion therapy.

• Membrane and Water Treatment
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• 제6권6호
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• pp.451-476
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• 2015

Membrane distillation (MD), which can utilize low-grade thermal energy, has been extensively studied for desalination. By incorporating solar thermal energy, the solar membrane distillation desalination system (SMDDS) is a potential technology for resolving the energy and water resource problems. Small-scale SMDDS (s-SMDDS) is an attractive and viable option for the production of fresh water for small communities in remote arid areas. The minimum-cost design and operation of s-SMDDS are determined by a systematic method, which involves a pseudo steady state approach for equipment sizing and the dynamic optimization using overall system mathematical models. The s-SMDDS employing three MD configurations, including the air gap (AGMD), direct contact (DCMD) and vacuum (VMD) types, are optimized. The membrane area of each system is $11.5m^2$. The AGMD system operated for 500 kg/day water production rate gives the lowest unit cost of $5.92/m^3$. The performance ratio and recovery ratio are 0.85 and 4.07%, respectively. For the commercial membrane employed in this study, the increase of membrane mass transfer coefficient up to two times is beneficial for cost reduction and the reduction of membrane heat transfer coefficient only affects the cost of the DCMD system.

• 한국재료학회지
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• 제24권7호
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• pp.381-387
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• 2014

The ${\beta}$-transus temperature in titanium alloys plays an important role in the design of thermo-mechanical treatments. It primarily depends on the chemical composition of the alloy and the relationship between them is non-linear and complex. Considering these relationships is difficult using mathematical equations. A feed-forward neural-network model with a back-propagation algorithm was developed to simulate the relationship between the ${\beta}$-transus temperature of titanium alloys, and the alloying elements. The input parameters to the model consisted of the nine alloying elements (i.e., Al, Cr, Fe, Mo, Sn, Si, V, Zr, and O), whereas the model output is the ${\beta}$-transus temperature. The model developed was then used to predict the ${\beta}$-transus temperature for different elemental combinations. Sensitivity analysis was performed on a trained neural-network model to study the effect of alloying elements on the ${\beta}$-transus temperature, keeping other elements constant. Very good performance of the model was achieved with previously unseen experimental data. Some explanation of the predicted results from the metallurgical point of view is given. The graphical-user-interface developed for the model should be very useful to researchers and in industry for designing the thermo-mechanical treatment of titanium alloys.

• 한국수학교육학회지시리즈C:초등수학교육
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• 제21권2호
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• pp.223-235
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• 2018

본 문헌연구에서는 수학불안을 주제로 국내외 연구 자료들을 분석하여 수학불안의 특징, 측정 방법, 발생원인, 치료방법 등 수학불안과 관련한 기존 연구 결과의 종합적인 고찰을 제공한다. 본 연구는 수학불안과 관련한 문헌 분석을 토대로 학생들의 수학불안 예방 및 치료 과정에 참여하는 초등학교 교사, 수학 교육 연구자들, 수학불안과 관련한 교육 정책 입안가들에게 초등학생의 수학불안에 대한 종합적인 이해를 제공하는데 목적이 있다. 본 연구에서는 수학불안과 관련한 국내외 연구들을 주제어를 중심으로 (1)수학불안이 초등학생의 학습 행동에 미치는 영향 (2) 수학불안 측정 도구 (3) 수학불안 형성 원인 (4) 수학 불안 감소 방안의 네 가지 범주로 구분하여 분석 결과를 제시한다. 본 연구에서는 각 범주별로 관련 연구들에 대한 간략한 설명과 연구의 결과, 그리고 이러한 연구들에 대한 종합적인 해석을 제공한다.

• 한국산학기술학회논문지
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• 제3권1호
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• pp.10-19
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• 2002

본고는 다종, 소규모 회분식 공정 또는 공장을 수학적 프로그래밍 기법으로 최적 설계하는 방법에 대한 것이다. 제안된 일반 회분식 공장문제는 Papageorgaki와 Reklaitis에 의해 혼합정수비선형식(MINLP)으로 수립된 것인데, 최적해답을 보장하며 공장의 확장 등 불확실성을 고려하여 선형화 한 후(MILP) 푸는 방법론이 제시되었다. Bende식 문제분할 방식을 개조하여 몇가지 예제에 대한 풀이를 제시하였다. IBM의 OSL 최적화 패키지를 이용하였고 MILP를 직접 푸는 경우보다 계산시간을 크게 단축할 수 있었다.

• Advances in environmental research
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• 제6권1호
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• pp.35-51
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• 2017

The use of Granular Activated Carbon (GAC) and naturally occurring silica (Sand) as filtration media in water and waste water treatment systems is very common. While GAC offers the additional functionality of being an "adsorptive" filter for dissolved organics it is also more expensive. In this paper we present an experimental evaluation of the performance of a bed of GAC for colloid removal and compare the same with that from an equivalent bed of Sand. The experiments are performed in an "intermittent" manner over extended time, to "simulate" performance over the life of the filter bed. The experiments were continued till a significant drop in water flow rate through the bed was observed. A novel "deposition" and "detachment" rate based transient mathematical model is developed. It is observed that the data from the experiments can be explained by the above model, for different aqueous phase electrolyte concentrations. The model "parameters", namely the "deposition" and "detachment" rates are evaluated for the 2 filter media studied. The model suggests that the significantly better performance of GAC in colloid filtration is probably due to significantly lower detachment of colloids from the same. While the "deposition" rates are higher for GAC, the "detachment" rates are significantly lower, which makes GAC more effective than sand for colloid removal by over an order of magnitude.

• 대한안전경영과학회지
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• 제5권4호
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• pp.169-185
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• 2003

Recently many researchers contributed to the understanding of Quality Control System, but the use of economics in the design of quality assurance system is limited in treatment of the relationship between the average incoming quality level (or average process quality level) of the incoming lot and the average outgoing quality level of this lot. In this study, a traditional concept of sampling inspection plan for the quality assurance system is extended to a consideration of economic aspects in total production system by representing and analyzing the effects between proceeding and succeeding production process including inspection process. This approach recognizes that the decision at each manufacturing process (or assembly process), is to be determined not only by the cost and the average outgoing quality level of that process, but also by the input parameters of the cost and the incoming quality to the succeeding process. By analyzing the effects of the average incoming and outgoing quality, manufacturing or assembly process quality level and sampling inspection plan on the production system, mathematical models and solution technique to minimize the total production cost for a general product manufacturing system with specified average outgoing quality limit are suggested.

• Environmental Engineering Research
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• 제24권2호
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• pp.220-237
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• 2019

Solid waste management (SWM) is one of the poorly rendered services in developing countries - limited resources, increasing population, rapid urbanization and application of outdated systems leads to inefficiency. Lack of proper planning and inadequate data regarding solid waste generation and collection compound the SWM problem. Decision makers need to formulate solutions that consider multiple goals and strategies. Given the large number of available options for SWM and the inter-relationships among these options, identifying SWM strategies that satisfy economic or environmental objectives is a complex task. The paper develops a mathematical model for a municipal Integrated SWM system, taking into account waste generation rates, composition, transportation modes, processing techniques, revenues from waste processing, simulating waste management as closely as possible. The constraints include those linking waste flows and mass balance, processing plants capacity, landfill capacity, transport vehicle capacity and number of trips. The linear programming model integrating different functional elements was solved by LINGO optimization software and various possible waste management options were considered during analysis. The model thus serves as decision support tool to evaluate various waste management alternatives and obtain the least-cost combination of technologies for handling, treatment and disposal of solid waste.

• Nuclear Engineering and Technology
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• 제54권5호
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• pp.1769-1780
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• 2022

A new method of dose calculation algorithm, called GPU-accelerated Monte Carlo and collapsed cone Convolution (GMCC) was developed to improve the calculation speed of BNCT treatment planning system. The GPU-accelerated Monte Carlo routine in GMCC is used to simulate the neutron transport over whole energy range and the Collapsed Cone Convolution method is to calculate the gamma dose. Other dose components due to alpha particles and protons, are calculated using the calculated neutron flux and reaction data. The mathematical principle and the algorithm architecture are introduced. The accuracy and performance of the GMCC were verified by comparing with the FLUKA results. A water phantom and a head CT voxel model were simulated. The neutron flux and the absorbed dose obtained by the GMCC were consistent well with the FLUKA results. In the case of head CT voxel model, the mean absolute percentage error for the neutron flux and the absorbed dose were 3.98% and 3.91%, respectively. The calculation speed of the absorbed dose by the GMCC was 56 times faster than the FLUKA code. It was verified that the GMCC could be a good candidate tool instead of the Monte Carlo method in the BNCT dose calculations.

• 한국수자원학회논문집
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• 제55권spc1호
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• pp.1283-1293
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• 2022

본 연구는 정수장의 수처리 공정에서 계측되고 있는 수량 및 수질데이터의 활용과 수처리 공정제어의 지능화를 위한 것으로 정수장에서 전염소 공정이 수반되는 처리공정에서 침전지 유출수 잔류염소농도 안정화를 위하여 이를 추정할 수 있는 모형을 구축하고자 하였다. 정수장 침전지 유출수의 잔류염소농도를 예측하기 위하여 중회귀모형과 인공지능 알고리즘 중 다층퍼셉트론 신경망, 랜덤포레스트 및 장단기기억(Long Short Term Memory; LSTM) 모형을 활용하였고 그 결과를 비교, 평가하였다. 모형의 입력변수로는 전염소 공정이 도입된 정수장에서의 잔류염소농도, 수온, 탁도, pH, 전기전도도, 유량, 알칼리도 등이 사용되었고 전염소에 따른 침전지의 안정적 운영을 위해 요구되는 침전지 잔류염소농도를 출력변수로 구성하였다. 적용 결과에서는 랜덤포레스트 모형이 가장 양호한 결과를 보여 주었으며 다음으로 LSTM, 다층퍼셈트론 신경망 순으로 나타났다. 수학적 모형인 중회귀모형은 적합도 측면에서 가장 낮은 결과를 보여 주었는데, 이는 수량과 수질데이터의 수치적인 규모나 차원의 차이뿐만 아니라 계절별 수질특성에 따라 염소소비 특성이 매우 다양하게 반응하기 때문으로 판단된다. 따라서 정수장 수처리 공정에서 인공지능 알고리즘의 적용을 위해서는 랜덤포레스트와 같이 의사결정 트리구조의 도입과 적용이 타당한 것으로 나타났다. 본 연구에서 분석된 결과를 근거로 전염소 공정이 도입된 정수장 수처리 공정에서 염소주입량을 실시간으로 예측 가능하게 함으로써 침전지 유출수에서 잔류염소농도를 일정하게 유지하는데 기여할 수 있을 것으로 기대된다.