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회분식 실험을 통한 제지슬러지의 카드뮴 및 비소 흡착능 평가
Baek, Jongchan,Yeo, Seulki,Park, Junboum,Back, Jonghwan,Song, Youngwoo,Igarashi, T.,Tabelin, C.B. 한국지하수토양환경학회 2014 지하수토양환경 Vol.19 No.1
The purpose of this study is to promote utilization of paper mill sludge as an adsorbent for stabilizing heavy metals in contaminated water by measuring the adsorption capacity of paper mill sludge for cadmium and arsenic. To measure adsorption capacity of paper mill sludge, sorption isotherm experiments were analyzed by Langmuir and Freundlich isotherm models. Also, two methods of chemical modifications were applied to improve the adsorption capacities of paper-mill-sludge: the first method used sodium hydroxide (NaOH), called PMS-1, and the second method used the NaOH and tartaric acid ($C_4H_6O_6$) together, called PMS-2. For Cd adsorption, PMS-1 presented the increase of reactivity while PMS-2 presented the decline of reactivity compared to that of untreated paper-mill-sludge. In case of As adsorption, both PMS-1 and PMS-2 showed the decrease of adsorption capacities. This is because zeta-potential of paper mill sludge was changed to more negative values during chemical modification process due to the hydroxyl group in NaOH and the carboxyl group in $C_4H_6O_6$, respectively. Therefore, we may conclude that the chemical treatment process increases adsorption capacity of paper mill sludge for cation heavy metals such as Cd but not for As.
Yoo, Jongchan,Jeon, Pilyong,Tsang, Daniel C.W.,Kwon, Eilhann E.,Baek, Kitae Elsevier 2018 Environmental pollution Vol.243 No.1
<P><B>Abstract</B></P> <P>Sediments nearby harbors are dredged regularly, and the sediments require the stringent treatment to meet the regulations on reuse and mitigate the environmental burdens from toxic pollutants. In this study, FeCl<SUB>3</SUB> was chosen as an extraction agent to treat marine sediment co-contaminated with Cu, Zn, and total petroleum hydrocarbons (TPH). In chemical extraction process, the extraction efficiency of Cu and Zn by FeCl<SUB>3</SUB> was compared with the conventional one using inorganic acids (H<SUB>2</SUB>SO<SUB>4</SUB> and HCl). Despite the satisfactory level for extraction of Cu (78.8%) and Zn (73.3%) by HCl (0.5 M) through proton-enhanced dissolution, one critical demerit, particularly acidified sediment, led to the unwanted loss of Al, Fe, and Mg by dissolution. Moreover, the vast amount of HCl required the huge amounts of neutralizing agents for the post-treatment of the sediment sample via the washing process. Despite a low concentration, extraction of Cu (70.1%) and Zn (69.4%) was done by using FeCl<SUB>3</SUB> (0.05 M) through proton-enhanced dissolution, ferric-organic matter complexation, and oxidative dissolution of sulfide minerals. Ferric iron (Fe<SUP>3+</SUP>) was reduced to ferrous iron (Fe<SUP>2+</SUP>) with sulfide (S<SUP>2-</SUP>) oxidation during FeCl<SUB>3</SUB> extraction. In consecutive chemical oxidations using hydrogen peroxide (H<SUB>2</SUB>O<SUB>2</SUB>) and persulfate (S<SUB>2</SUB>O<SUB>8</SUB> <SUP>2-</SUP>), the resultant ferrous iron was used to activate the oxidants to effectively degrade TPH. S<SUB>2</SUB>O<SUB>8</SUB> <SUP>2-</SUP> using FeCl<SUB>3</SUB> solution (molar ratio of ferrous to S<SUB>2</SUB>O<SUB>8</SUB> <SUP>2-</SUP> is 19.8–198.3) removed 42.6% of TPH, which was higher than that by H<SUB>2</SUB>O<SUB>2</SUB> (molar ratio of ferrous to H<SUB>2</SUB>O<SUB>2</SUB> is 1.2–6.1). All experimental findings suggest that ferric is effectively accommodated to an acid washing step for co-contaminated marine sediments, which leads to enhanced extraction, cost-effectiveness, and less environmental burden.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Ferric chloride is the most suitable to remediate contaminated marine sediments. </LI> <LI> Protons generated by hydrolysis of ferric iron preferentially extract labile metals. </LI> <LI> Ferric iron enhances the metal removal via oxidative dissolution of metal-sulfides. </LI> <LI> Ferric chloride reduces further chemical costs in chemical remediation processes. </LI> <LI> Ferric chloride has less influence on damaging to sediment destruction. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>
Automatic Data Augmentation by Upper Confidence Bounds for Deep Reinforcement Learning
Yoonhee Gil,Jongchan Baek,Jonghyuk Park,Soohee Han 제어로봇시스템학회 2021 제어로봇시스템학회 국제학술대회 논문집 Vol.2021 No.10
In visual reinforcement learning (RL), various approaches succeeded to improve data efficiency. However, the approaches fail to show generalization capabilities if different colors or backgrounds are applied to its environment. The lack of generalization capabilities can hinder the use of RL in real-world environment, which contains lot of distractions and noises. In this paper, a novel automatic data augmentation method that can improve generalization capabilities of an RL agent. In the experiments, the proposed method shows better generalization capabilities than other approaches. These results provide a simple automatic data augmentation method for RL that can improve generalization capabilities.
지하 터널 환경에서 3차원 라이다를 이용한 모바일 로봇 자율주행
정민욱(Minwook Jeong),백종찬(Jongchan Baek),김해연(Hayeon Gim),길윤희(Yoonhee Gil),우정욱(Jeongwook Woo),한수희(Soohee Han) 대한전기학회 2021 대한전기학회 학술대회 논문집 Vol.2021 No.7
본 연구에서는 3D 라이다 기반의 모바일 로봇 플랫폼을 활용하여, 지하터널 구조에서도 높은 정확도를 가지는 자율주행 알고리즘을 제안한다. 제안된 논문은 gMapping과 AMCL을 기반으로, 동일 구조가 연속적으로 나타나 자율주행을 위한 특징점을 찾기 어려운 지하 터널 구조에서도 목표 지점까지 정확하게 자율주행을 할 수 있는 알고리즘을 포함한다. 또한, 터널 내부에 존재하는 장애물과의 충돌을 방지하기 위해, 장애물을 인지하고, 통로와 로봇의 폭 그리고 장애물의 길이를 고려한 회피 알고리즘을 포함한다. 전력구 환경에서의 실험을 통해, 그 성능과 강인성을 검증하도록 한다.
Improved Robustness of Reinforcement Learning Based on Uncertainty and Disturbance Estimator
Jinsuk Choi,Hyunbeen Park,Jongchan Baek,Soohee Han 제어로봇시스템학회 2022 제어로봇시스템학회 국제학술대회 논문집 Vol.2022 No.11
This paper proposes a method to improve the robustness of RLs based on model-free uncertainty and disturbance estimator (RL-based UDE). In the real environment, instead of using optimal trajectory and control techniques to perform complex tasks, it learns through RL and supplements robustness by using uncertainty and disturbance estimator (UDE). From UDE, the robotics system can be improved the stability by appropriately canceling the uncertainty and disturbance without efforts to obtain model information; hence the UDE can compensate for the performance degradation of RL when system is non-stationary. In addition, the performance can be improved by reducing the sensor noise from low-pass filter of UDE. It is shown through an experiment that the proposed RL-based UDE provides robustness.