|
|
|
题名
|
作者
|
年代
|
出处
|
被引量
|
| 1 | 纯铜高压扭转压缩阶段塑性变形的实验及有限元分析(英文)显示文摘利用实验及有限元分析等手段,对纯铜高压扭转压缩阶段的塑性变形行为、硬度及显微组织分布进行了研究,结果表明,试样经压缩后,其硬度分布极为不均匀,边缘硬度高,轴心部位硬度低,而中间部位硬度变化较为平缓。模拟结果显示,试样在压缩过程中的应力应变呈不均匀变化,由此引起试样各部位显微组织及晶粒变形不均匀。进一步研究表明,试样与模具间的摩擦对于压缩阶段试样变形具有重要影响。 | 王文珂 宋月鹏 高东升 JungHwan Lee EunYoo Yoon DongJun Lee ChongSoo Lee HyoungSeop Kim | 2013 | 稀有金属材料与工程2013，42，S2： | 4 |
| 2 | A new algorithm to locate power-quality event source with improved realization of distributed monitoring scheme显示文摘 | WON Dongjun CHUNG Ilyop KIM Joongmoon | 2006 | IEEE Trans on Power Delivery2006，21，3： | 1 |
| 3 | Gallbladder Removal Simulation for Laparoscopic Surgery Training: A Hybrid Modeling Method显示文摘Laparoscopic surgery has many advantages, but it is difficult for a surgeon to achieve the necessary surgical skills. Recently, virtual training simulations have been gaining interest because they can provide a safe and efficient learning environment for medical students and novice surgeons. In this paper, we present a hybrid modeling method for simulating gallbladder removal that uses both the boundary element method (BEM) and the finite element method (FEM). Each modeling method is applied according to the deformable properties of human organs: BEM for the liver and FEM for the gallbladder. Connective tissues between the liver and the gallbladder are also included in the surgical simulation. Deformations in the liver and the gallbladder models are transferred via connective tissue springs using a mass-spring method. Special effects and techniques are developed to achieve realistic simulations, and the software is integrated into a custom-designed haptic interface device. Various computer graphical techniques are also applied in the virtual gallbladder removal laparoscopic surgery training. The detailed techniques and the results of the simulations are described in this paper. | Youngjun Kim Dongjune Chang Jungsik Kim Sehyung Park | 2013 | Journal of Computer Science & Technology2013，28，3： | 0 |
| 4 | Novel endogenous endoplasmic reticulum transmembrane protein SURF4 suppresses cell death by negatively regulating the STING-STAT6 axis inmyeloid leukemia显示文摘Dear Editor,Myeloid differentiation was shown to be associated with reduced leukemic cell burden and leukemia-initiating cells and improved survival[1].Reactive oxygen species(ROS)are associated with leukemia and can induce endoplasmic reticulum(ER)stress.ER stress induces several mechanisms,including cell death[2].The stimulator of interferon genes(STING)is also an ER transmembrane protein and promotes anti-tumor immunity by linking innate and adaptive immunity[3].Signal transducer and activator of transcription 6(STAT6)plays a prominent role in adaptive immunity by transducing signals fromextracellular cytokines and inducing apoptosis in cancer cells[4]. | Jayoung Kim Hansong Lee Chae Mi Hong Ji Ho Nam Hye Ju Yeo Woo Hyun Cho Hyung-Sik Kim Changwan Hong Yun Hak Kim Dongjun Lee | 2023 | Cancer Communications2023，43，3： | 0 |
| 5 | A systematic correlation between morphology of porous carbon cathode and electrolyte in lithium-sulfur battery显示文摘Porous carbon has been applied for lithium-sulfur battery cathodes,and carbonized metal-organic framework(MOF)is advantageous in tuning the morphology.Herein,we have systematically synthesized water-distorted MOF(WDM)derived porous carbon via controlling the proportion of both water in a mixed solvent(dimethylformamide and water)and ligand in MOF-5 precursors(metal and ligand),which is categorized by its morphology(i.e.Cracked stone(closed),Tassel(open)and Intermediate(semi-open)).For example,decrease in water and increase in ligand content induce Cracked stone WDMs which showed the highest specific surface area(2742-2990 m^(2)/g)and pore volume(2.81-3.28 cm^(3)/g)after carbonization.Morphological effect of carbonized WDMs(CWDMs)on battery performance was examined by introducing electrolytes with different sulfur reduction mechanisms(i.e.DOL/DME and ACN_(2) LiTFSITTE):Closed framework effectively confines polysulfide,whereas open framework enhances electrolyte accessibility.The initial capacities of the batteries were in the following order:Cracked stone>Intermediate>Tassel for DOL/DME and Intermediate>Tassel>Cracked stone for ACN_(2) LiTFSI-TTE.To note,Intermediate CWDM exhibited the highest initial capacity and retained capacity after 100 cycles(1398 and 747 mAh/g)in ACN_(2) LiTFSI-TTE electrolyte having advantages from both open and closed frameworks.In sum,we could correlate cathode morphology(openness and pore structure)and electrolyte type(i.e.polysulfide solubility)with lithium-sulfur battery performance. | Jihyeon Park Seoyoung Yoon Seoyeah Oh Jiyoon Kim Dongjun Kim Geonho Kim Jiyeon Lee Myeong Jun Song Ilto Kim Kwonnam Sohn Jiwon Kim | 2021 | Journal of Energy Chemistry2021，30，10： | 0 |
| 6 | Graph Construction Method for GNN-Based Multivariate Time-Series Forecasting显示文摘Multivariate time-series forecasting(MTSF)plays an important role in diverse real-world applications.To achieve better accuracy in MTSF,time-series patterns in each variable and interrelationship patterns between variables should be considered together.Recently,graph neural networks(GNNs)has gained much attention as they can learn both patterns using a graph.For accurate forecasting through GNN,a well-defined graph is required.However,existing GNNs have limitations in reflecting the spectral similarity and time delay between nodes,and consider all nodes with the same weight when constructing graph.In this paper,we propose a novel graph construction method that solves aforementioned limitations.We first calculate the Fourier transform-based spectral similarity and then update this similarity to reflect the time delay.Then,we weight each node according to the number of edge connections to get the final graph and utilize it to train the GNN model.Through experiments on various datasets,we demonstrated that the proposed method enhanced the performance of GNN-based MTSF models,and the proposed forecasting model achieve of up to 18.1%predictive performance improvement over the state-of-the-art model. | Wonyong Chung Jaeuk Moon Dongjun Kim Eenjun Hwang | 2023 | Computers, Materials & Continua2023，，6： | 0 |
您所在的机构暂未开通此部分的功能，请联系管理员