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Learning to use Topological Memory for Visual Navigation
Obin Kwon,Songhwai Oh 제어로봇시스템학회 2020 제어로봇시스템학회 국제학술대회 논문집 Vol.2020 No.10
We propose a new method of using topological memory in visual navigation problem. In our method, an agent builds a topological map during the navigation and simultaneously reasoning on the built map. The proposed method can efficiently use the elements of the graph memory using GCN and Transformer network. We evaluated our method on the visual target navigation problem which need some exploration strategies. The agent is trained using Deep Reinforcement Learning in photo-realistic Habitat simulator with Matterport 3d dataset. Using much smaller memory than the baseline, our method achieved competitive performance in visual target navigation problem.
Image-Goal Navigation Algorithm using Viewpoint Estimation
Obin Kwon,Songhwai Oh 제어로봇시스템학회 2021 제어로봇시스템학회 국제학술대회 논문집 Vol.2021 No.10
This paper tackles the image-goal navigation problem, in which a robot needs to find a goal pose based on the target image. The proposed algorithm estimates the geometric information between the target pose and the current pose of the robot. Using the estimated geometric information, the navigation policy predicts the most appropriate actions to reach the target pose. We evaluated our method using the Habitat simulator with the Gibson dataset, which provides photorealistic indoor environments. The experimental results show that adding an ability to estimate the geometric information helps the agent find the target pose much more successfully and time-efficiently. Furthermore, we investigate how this estimation ability affects navigation performances through various experiments.
Assurance of mitochondrial integrity and mammalian longevity by the p62-Keap1-Nrf2-Nqo1 cascade
Kwon, Jeongho,Han, Eunhye,Bui, Chi‐,Bao,Shin, Woochul,Lee, Junho,Lee, Sejeong,Choi, Young‐,Bong,Lee, Ann‐,Hwee,Lee, Kyong‐,Hoon,Park, Chankyu,Obin, Martin S,Park, Sung Kyu,Seo, EMBO 2012 EMBO reports Vol.13 No.2
mGluR5 in the nucleus accumbens is critical for promoting resilience to chronic stress
Shin, Sora,Kwon, Obin,Kang, Jee In,Kwon, Somin,Oh, Sora,Choi, Jiwon,Kim, Chul Hoon,Kim, Dong Goo NATURE AMERICA 2015 NATURE NEUROSCIENCE Vol.18 No.7
Resilience to aversive events has a central role in determining whether stress leads to the development of depression. mGluR5 has been implicated in the pathophysiology of depression, but the effect of mGluR5 activity on stress resilience remains unexplored. We found that mGluR5<SUP>−/−</SUP> (also known as Grm5<SUP>−/−</SUP>) mice displayed more depression-like behaviors (for example, learned helplessness, social withdrawal and anhedonia) than control mice following exposure to various stressful stimuli. Lentiviral 'rescue' of mGluR5 in the nucleus accumbens (NAc) decreased these depression-like behaviors in mGluR5<SUP>−/−</SUP> mice. In the NAc, ΔFosB, whose induction promotes stress resilience, failed to be upregulated by stress in mGluR5<SUP>−/−</SUP> mice. Notably, targeted pharmacological activation of mGluR5 in the NAc increased ΔFosB expression. Our findings point to an essential role for mGluR5 in promoting stress resilience and suggest that a defect in mGluR5-mediated signaling in the NAc may represent an endophenotype for stress-induced depression.
Angiopoietin-like peptide 4 regulates insulin secretion and islet morphology
Kim, Hyun-Kyong,Kwon, Obin,Park, Kyeong-Han,Lee, Kyung Jin,Youn, Byung-Soo,Kim, Seung-Whan,Kim, Min-Seon Elsevier 2017 Biochemical and biophysical research communication Vol.485 No.1
<P><B>Abstract</B></P> <P>Insulin secretion from pancreatic islet β-cells is primarily regulated by the blood glucose level, and also modulated by a number of biological factors produced inside the islets or released from remote organs. Previous studies have shown that angiopoietin-like protein 4 (Angptl4) controls glucose and lipid metabolism through its actions in the liver, adipose tissue, and skeletal muscles. In this present study, we investigated the possible role of Angptl4 in the regulation of insulin secretion from pancreatic islets. Angptl4 was found to be highly expressed in the α-cells but not β-cells of rodent islets. Moreover, treatment of rodent islets with Angptl4 peptide potentiated glucose-stimulated insulin secretion through a protein kinase A-dependent mechanism. Consistently, Angptl4 knockout mice showed impaired glucose tolerance. In the cultured islets from Angptl4 knockout mice, glucose-stimulated insulin secretion was significantly lower than in islets from wild type mice. Angptl4 peptide replacement partially reversed this reduction. Moreover, Angptl4 knockout mice had dysmorphic islets with abnormally distributed α-cells. In contrast, the β-cell mass and distribution were not significantly altered in these knockout mice. Our current data collectively suggest that Angptl4 may play a critical role in the regulation of insulin secretion and islet morphogenesis.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Angptl4 is expressed in pancreatic α-cells. </LI> <LI> Angptl4 stimulates insulin secretion from pancreatic islets. </LI> <LI> Angptl4-deficient mice show impaired insulin secretion and dysmorphic islets. </LI> </UL> </P>
혼합정수 프로그래밍 기법을 이용한 진보된 Time-Cost Trade-Off Model
권오빈,이승현,손재호,Kwon, Obin,Lee, Seunghyun,Son, Jaeho 한국건설관리학회 2015 한국건설관리학회 논문집 Vol.16 No.6
공기비용 트레이드오프 모델은 건설프로젝트의 계획 및 관리에 있어 매우 중요하다. TCTO 모델은 연속모델과 분절모델 두 가지 모델이 개발되어왔다. 그러나 한 종류의 모델만을 사용하여 현실적인 공기단축 시나리오를 적용하기에는 한계가 있다. 이에 TCTO 의 연속적인 모델과, 분절모델을 결합하여 진보된 모델을 제시하였으며 또한, 비선형 관계, 인센티브 및 지체보상금 고려가 가능하도록 TCTO모델에 포함되어 있다. 이런 특성들은 건설프로젝트에 적용가능하다. 6개의 activities로 구성된 CPM 네트워크는 연구에서 제안된 모델을 설명하기 위해 사용되었다. 제시한 모델은 모든 제약 조건을 만족시키는 최적 스케쥴 계산이 가능하다. 결과적으로 본 연구에서 제시한 진보된 TCTO모델은 기존의 모델보다 최적화된 공기단축이 가능하다. Time-Cost Trade-Off (TCTO) model is an important model in the construction project planning and control area. Two types of Existing TCTO model, continuous and discrete TCTO model, have been developed by researchers. However, Using only one type of model has a limitation to represent a realistic crash scenario of activities in the project. Thus, this paper presents a comprehensive TCTO model that combines a continuous and discrete model. Additional advanced features for non-linear relationship, incentive, and liquidated damage are included in the TCTO model. These features make the proposed model more applicable to the construction project. One CPM network with 6 activities is used to explain the proposed model. The model found an optimal schedule for the example to satisfy all the constraints. The results show that new model can represent more flexible crash scenario in TCTO model.