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Qimeng Zhang,Hae Won Byun(변혜원) 한국컴퓨터그래픽스학회 2017 컴퓨터그래픽스학회논문지 Vol.23 No.5
본 논문은 나뭇가지 패턴을 의자의 골격에 임의로 합성하는(Tree-Inspired Chair) 모델링 기법을 제안한다. 여러 개의입력모델을 합성하는 기존 기법과 다르게, 제안 기법은 하나의 메쉬만 사용하여, 사용자가 원하는 부분의 contour mesh 로부터 나무 성장 시뮬레이션으로 생성된 패턴을 갖는 의자 모델링이 가능하다. 우리는 나뭇가지 패턴을 생성시킬 영역 contour mesh를 효율적으로 추출하기 위하여 새로운 기법을 제안한다. 우선, 입력된 모델의 face 면적에 기반한 contour mesh를 생성하고, 그 메쉬의 앞뒷면 정보를 이용하여 연결정보가 복원된 skeleton mesh를 생성한다. 또한, 입력 모델의 형상과 유사하게 나뭇가지 패턴을 생성하기 위해 형상 표면의 tangent vector를 고려하는 3-way 나무성장 시뮬레이션기법을 제안한다. 제안기법은 기존의 가구 모델을 이용하여 간단한 파라미터의 조작만으로 나뭇가지 형상과 가구 모델의 골격을 결합하는 새로운 형태의 가구 모델링을 보여준다. 우리는 실험을 통하여 제안 기법의 성능과 유효성을 보여주었다. We propose a method for tree-inspired chair modeling that can generate a tree-branch pattern in the skeleton of an arbitrary chair shape. Unlike existing methods that merge multiple-input models, the proposed method requires only one mesh as input, namely the contour mesh of the user’s desired part, to model the chair with a branch pattern generated by tree-growth simulation. We propose a new method for the efficient extraction of the contour-mesh region in the tree-branch pattern. First, we extract the contour mesh based on the face area of the input mesh. We then use the front and back mesh information to generate a skeleton mesh that reconstructs the connection information. In addition, to obtain the tree-branch pattern matching the shape of the input model, we propose a three-way tree-growth simulation method that considers the tangent vector of the shape surface. The proposed method reveals a new type of furniture modeling by using an existing furniture model and simple parameter values to model tree branches shaped appropriately for the input model skeleton. Our experiments demonstrate the performance and effectiveness of the proposed method.
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Wang Yu,Yao Qingxu,Zhang Quanhu,Zhang He,Lu Yunfeng,Fan Qimeng,Jiang Nan,Yu Wangtao 한국원자력학회 2022 Nuclear Engineering and Technology Vol.54 No.12
Radionuclide identification is an important part of the nuclear material identification system. The development of artificial intelligence and machine learning has made nuclide identification rapid and automatic. However, many methods directly use existing deep learning models to analyze the gammaray spectrum, which lacks interpretability for researchers. This study proposes an explainable radionuclide identification algorithm based on the convolutional neural network and class activation mapping. This method shows the area of interest of the neural network on the gamma-ray spectrum by generating a class activation map. We analyzed the class activation map of the gamma-ray spectrum of different types, different gross counts, and different signal-to-noise ratios. The results show that the convolutional neural network attempted to learn the relationship between the input gamma-ray spectrum and the nuclide type, and could identify the nuclide based on the photoelectric peak and Compton edge. Furthermore, the results explain why the neural network could identify gamma-ray spectra with low counts and low signal-to-noise ratios. Thus, the findings improve researchers’ confidence in the ability of neural networks to identify nuclides and promote the application of artificial intelligence methods in the field of nuclide identification.
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( Qinqin Liang ),( Yanyang ),( Junxi Zhang ),( Xujie Yuan ),( Qimeng Chen ) 한국부식방식학회(구 한국부식학회) 2018 Corrosion Science and Technology Vol.17 No.2
The effect of external DC electric field on atmospheric corrosion behavior of zinc under a thin electrolyte layer (TEL) was investigated by measuring open circuit potential (OCP), cathodic polarization curve, and electrochemical impedance spectroscopy (EIS). Results of OCP vs. time curves indicated that the application of external DC electric field resulted in a negative shift of OCP of zinc. Results of cathodic polarization curves measurement and EIS measurement showed that the reduction current of oxygen increased while charge transfer resistance (R<sub>ct</sub>) decreased under the external DC electric field. Variation of OCP negative shift, reduction current of oxygen, and R<sub>ct</sub> increase with increasing of external DC electric field strength as well as the effect of external DC electric field on double-layer structure in the electrode/electrolyte interface and ions distribution in thin electrolyte layer were analyzed. All results showed that the external DC electric field could accelerate the corrosion of zinc under a thin electrolyte layer.
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Qi Meng,Jianguo Duan,Ying-Jie Zhang,Peng Dong 한국공업화학회 2019 Journal of Industrial and Engineering Chemistry Vol.80 No.-
In this study, a novel efficient and environmentally friendly recycling process is developed to recoverspent LiMn2O4 powder as raw materials for high-performance LiMnPO4/C nanocomposites. The processcomprises a mechanochemical liquid-phase activation of the precursor mixture followed by a single-stepsolid-state heat treatment. The results indicate that the recovered LiMnPO4/C nano-composite has apromising electrochemical performance with discharge capacities of 148.5, 136.1, and 116.5 mA h g 1 at0.05, 0.2, and 1C rate, respectively, in the voltage range of 2.5–4.5 V. A perfect cyclic performance is alsodisplayed with a capacity retention of 98% after 100 cycles at 1C rate.
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Qi Meng,Ying-Jie Zhang,Peng Dong,Feng Liang 한국공업화학회 2018 Journal of Industrial and Engineering Chemistry Vol.61 No.-
A novel process of electrochemical cathode reduction has been developed for leaching of metals from spent LiNi1/3Co1/3Mn1/3O2 material. The leaching efficiencies of Li, Ni, Co and Mn reached to 100, 99.87, 99.58 and 99.82%, respectively with 1.5 mol/L malic acid and working voltage of 8 V at 300 r/min and 60 °C for 30 min. Kinetics analysis indicates that leaching process is controlled by surface chemical reaction. The Ea for Li, Ni, Co and Mn was 41.71, 42.83, 44.38 and 43.17 kJ/mol, respectively. Based on EIS analysis, leaching process is mainly controlled by charge transfer resistance of the surface chemical reaction.
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