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| 1 | Framework for Artificial Intelligence Analysis in Large-scale Power Grids Based on Digital Simulation显示文摘The planning,design,operation,control and scientific research of power systems all require a variety of simulation analysis.Thus power grid simulation analysis is a fundamental supporting technology of large-scale power grids.In power grid simulation analysis,in addition to simulation calculations,there are many links for analysis and decision-making,relying on specialists.The introduction of advanced artificial intelligence technology provides a new method to improve the efficiency and accuracy of power grid simulation analysis.Nevertheless,the research of the related artificial intelligence technologies face a great deal of new challenges due to the complexity of the largescale power grid simulation data,including massive volumes,high dimensionality,strong coupling and complex correlations.Also a great deal of knowledge and experience need to be integrated in the process of analysis.In order to deal with these challenges,based on the existing works,this paper focuses on the core scientific problem of artificial intelligence analysis and decision making related to the massive simulation results of large-scale power grids,and proposes an artificial intelligence analysis method framework for large-scale power grids based on digital simulation,which includes the power grid simulation analysis knowledge model with application method,the power grid simulation knowledge mining method and the artificial intelligence models with transfer learning ability of diversified grids as well as analyzing and calculation adjusting for largescale power grid simulation results,etc.This work is expected to open up a new technical approach for large-scale power grid simulation analysis and provide strong technical support for the safe and stable operation of large-scale power grids. | Yong Tang Yanhao Huang Hongzhi Wang Can Wang Qiang Guo Wei Yao | 2018 | CSEE Journal of Power and Energy Systems2018，4，4： | 12 |
| 2 | Biomarkers of aging显示文摘Aging biomarkers are a combination of biological parameters to(i)assess age-related changes,(ii)track the physiological aging process,and(iii)predict the transition into a pathological status.Although a broad spectrum of aging biomarkers has been developed,their potential uses and limitations remain poorly characterized.An immediate goal of biomarkers is to help us answer the following three fundamental questions in aging research:How old are we?Why do we get old?And how can we age slower?This review aims to address this need.Here,we summarize our current knowledge of biomarkers developed for cellular,organ,and organismal levels of aging,comprising six pillars:physiological characteristics,medical imaging,histological features,cellular alterations,molecular changes,and secretory factors.To fulfill all these requisites,we propose that aging biomarkers should qualify for being specific,systemic,and clinically relevant. | Aging Biomarker Consortium Hainan Bao Jiani Cao Mengting Chen Min Chen Wei Chen Xiao Chen Yanhao Chen Yu Chen Yutian Chen Zhiyang Chen Jagadish K Chhetri Yingjie Ding Junlin Feng Jun Guo Mengmeng Guo Chuting He Yujuan Jia Haiping Jiang Ying Jing Dingfeng Li Jiaming Li Jingyi Li Qinhao Liang Rui Liang Feng Liu Xiaoqian Liu Zuojun Liu Oscar Junhong Luo Jianwei Lv Jingyi Ma Kehang Mao Jiawei Nie Xinhua Qiao Xinpei Sun Xiaoqiang Tang Jianfang Wang Qiaoran Wang Siyuan Wang Xuan Wang Yaning Wang Yuhan Wang Rimo Wu Kai Xia Fu-Hui Xiao Lingyan Xu Yingying Xu Haoteng Yan Liang Yang Ruici Yang Yuanxin Yang Yilin Ying Le Zhang Weiwei Zhang Wenwan Zhang Xing Zhang Zhuo Zhang Min Zhou Rui Zhou Qingchen Zhu Zhengmao Zhu Feng Cao Zhongwei Cao Piu Chan Chang Chen Guobing Chen Hou-Zao Chen Jun Chen Weimin Ci Bi-Sen Ding Qiurong Ding Feng Gao Jing-Dong JHan Kai Huang Zhenyu Ju Qing-Peng Kong Ji Li Jian Li Xin Li Baohua Liu Feng Liu Lin Liu Qiang Liu Qiang Liu Xingguo Liu Yong Liu Xianghang Luo Shuai Ma Xinran Ma Zhiyong Mao Jing Nie Yaojin Peng Jing Qu Jie Ren Ruibao Ren Moshi Song Zhou Songyang Yi Eve Sun Yu Sun Mei Tian Shusen Wang Si Wang Xia Wang Xiaoning Wang Yan-Jiang Wang Yunfang Wang Catherine CL Wong Andy Peng Xiang Yichuan Xiao Zhengwei Xie Daichao Xu Jing Ye Rui Yue Cuntai Zhang Hongbo Zhang Liang Zhang Weiqi Zhang Yong Zhang Yun-Wu Zhang Zhuohua Zhang Tongbiao Zhao Yuzheng Zhao Dahai Zhu Weiguo Zou Gang Pei Guang-Hui Liu | 2023 | Science China(Life Sciences)2023，66，5： | 2 |
| 3 | Pressureless two-step sintering of ultrafine-grained refractory metals:Tungsten-rhenium and molybdenum显示文摘The challenge of sintering ultrafine-grained refractory metals and alloys to full density is hereby addressed by pressureless two-step sintering in tungsten-rhenium alloy and pure molybdenum. Using properly processed nano powders(~50 nm average particle size), we are able to sinter W-10Re alloy to 98.4% density below 1200 ℃ while maintaining a fine grain size of 260 nm, and sinter molybdenum to 98.3% density below 1120 ℃ while maintaining a fine grain size of 290 nm. Compared to normal sintering,two-step sintering offers record-fine grain sizes and better microstructural uniformity, which translates to better mechanical properties with higher hardness(6.3 GPa for tungsten-rhenium and 4.0 GPa for molybdenum, both being the highest in all pressurelessly sintered samples of the respective material system)and larger Weibull modulus. Together with our previous demonstration in tungsten, we believe that twostep sintering is a general effective method to produce high-quality fine-grained refractory metals and alloys, and the lessons learned here are transferable to other materials for powder metallurgy. | Zhongyou Que Zichen Wei Xingyu Li Lin Zhang Yanhao Dong Mingli Qin Junjun Yang Xuanhui Qu Ju Li | 2022 | Journal of Materials Science & Technology2022，，31： | 1 |
| 4 | Carbon dioxide-digi-tal subtrac tion angiography features of hepatocellular carcinoma显示文摘 | Wei Lu Yanhao Li Yong Chen | 1999 | J Vasc Interv Rad iol1999，10，22： | 1 |
| 5 | Ferrofluids Containing Fe3O4 Nanoparticles in Solidified Photoresist Carrier显示文摘 | YU Yanhao SHI Qing WANG Gong LU Chao GUAN Wei ZHANG Xiaogang XU Ying XIN Chunmei | 2016 | Chemical Research in Chinese Universities2016，32，3： | 0 |
| 6 | Soft coarse-grained particle model for particle-fluid systems显示文摘By modeling a group of neighboring real particles as a single coarse-grained particle(CGP),discrete particle method(DPM)is now capable of simulating industrial-scale particle-fluid systems.However,a systematic approach to determine the CGP properties and develop their interaction models is still lacking,which casts uncertainty on the predictivity of the method.In this study,collisions between predefined particle groups are analyzed to construct kernel functions for modeling the CGPs and then the model parameters are determined by equating the statistical properties of the CGPs and the real particles in the physical process studied.This approach is implemented for homogeneous cooling of granular gas,then demonstrated effective in simulating experimental fluidized beds. | Yanhao Ye Ji Xu Wei Ge | 2024 | Particuology2024，84，1： | 0 |
| 7 | A Hand Features Based Fusion Recognition Network with Enhancing Multi-Modal Correlation显示文摘Fusing hand-based features in multi-modal biometric recognition enhances anti-spoofing capabilities.Additionally,it leverages inter-modal correlation to enhance recognition performance.Concurrently,the robustness and recognition performance of the system can be enhanced through judiciously leveraging the correlation among multimodal features.Nevertheless,two issues persist in multi-modal feature fusion recognition:Firstly,the enhancement of recognition performance in fusion recognition has not comprehensively considered the inter-modality correlations among distinct modalities.Secondly,during modal fusion,improper weight selection diminishes the salience of crucial modal features,thereby diminishing the overall recognition performance.To address these two issues,we introduce an enhanced DenseNet multimodal recognition network founded on feature-level fusion.The information from the three modalities is fused akin to RGB,and the input network augments the correlation between modes through channel correlation.Within the enhanced DenseNet network,the Efficient Channel Attention Network(ECA-Net)dynamically adjusts the weight of each channel to amplify the salience of crucial information in each modal feature.Depthwise separable convolution markedly reduces the training parameters and further enhances the feature correlation.Experimental evaluations were conducted on four multimodal databases,comprising six unimodal databases,including multispectral palmprint and palm vein databases from the Chinese Academy of Sciences.The Equal Error Rates(EER)values were 0.0149%,0.0150%,0.0099%,and 0.0050%,correspondingly.In comparison to other network methods for palmprint,palm vein,and finger vein fusion recognition,this approach substantially enhances recognition performance,rendering it suitable for high-security environments with practical applicability.The experiments in this article utilized amodest sample database comprising 200 individuals.The subsequent phase involves preparing for the extension of the method to larger databases. | Wei Wu Yuan Zhang Yunpeng Li Chuanyang Li YanHao | 2024 | Computer Modeling in Engineering & Sciences2024，140，7： | 0 |
| 8 | Reducing power grid cascading failure propagation by minimizing algebraic connectivity in edge addition显示文摘Analyzing network robustness under various circumstances is generally regarded as a challenging problem.Robustness against failure is one of the essential properties of large-scale dynamic network systems such as power grids,transportation systems,communication systems,and computer networks.Due to the network diversity and complexity,many topological features have been proposed to capture specific system properties.For power grids,a popular process for improving a network’s structural robustness is via the topology design.However,most of existing methods focus on localized network metrics,such as node connectivity and edge connectivity,which do not encompass a global perspective of cascading propagation in a power grid.In this paper,we use an informative global metric algebraic connectivity because it is sensitive to the connectedness in a broader spectrum of graphs.Our process involves decreasing the average propagation in a power grid by minimizing the increase in its algebraic connectivity.We propose a topology-based greedy strategy to optimize the robustness of the power grid.To evaluate the network robustness,we calculate the average propagation using MATCASC to simulate cascading line outages in power grids.Experimental results illustrate that our proposed method outperforms existing techniques. | Supaporn LONAPALAWONG Jiangzhe YAN Jiayu LI Deshi YE Wei CHEN Yong TANG Yanhao HUANG Can WANG | 2022 | Frontiers of Information Technology & Electronic Engineering2022，23，3： | 0 |
| 9 | Modulating the p-band center of carbon nanofibers derived from Co spin state as anode for high-power sodium storage显示文摘Carbon nanofibers(CNFs)have received extensive and in-depth studied as anodes for sodium-ion batteries(SIBs),and yet their initial Coulombic efficiency and rate capability remain enormous challenge at practical level.Herein,CNFs anchored with cobalt nanocluster(CNFs-Co)were prepared using chemical vapor deposition and thermal reduction methods.The as-prepared CNFs-Co shows a high initial Coulombic efficiency of 91%and a high specific discharge capacity of 246 mAh/g at 0.1 A/g after 200 cycles as anode for SIBs.Meanwhile,the CNFs-Co anode still delivers a high cycling stability with 108 mAh/g after 1000 cycles at 10 A/g.These excellent electrochemical properties could be attributed to the involved spin state Co,which endows CNFs with large interplanar spacing(0.39 nm)and abundant vacancy defects.Importantly,the spin state Co downshifts the p-band center of carbon and strengthens the Na+adsorption energy from-2.33 eV to-2.64 eV based on density functional theory calculation.This novel strategy of modulating the carbon electronic structure by the spin state of magnetic metals provides a reference for the development of high-performance carbon-based anode materials. | Zhijia Zhang Yuwen Zhao Yanhao Wei Mengmeng Zhang Chunsheng Li Yan Sun Jianmin Ma Yong Jiang | 2024 | Chinese Chemical Letters2024，35，1： | 0 |
| 10 | WaveLines:towards effective visualization and analysis of stability in power grid simulation显示文摘Closely related to the safety and stability of power grids,stability analysis has long been a core topic in the electric industry.Conventional approaches employ computational simulation to make the quantitative judgement of the grid stability under distinctive conditions.The lack of in-depth data analysis tools has led to the difficulty in analytical tasks such as situation-aware analysis,instability reasoning and pattern recognition.To facilitate visual exploration and reasoning on the simulation data,we introduce WaveLines,a visual analysis approach which supports the supervisory control of multivariate simulation time series of power grids.We design and implement an interactive system that supports a set of analytical tasks proposed by domain experts and experienced operators.Experiments have been conducted with domain experts to illustrate the usability and effectiveness of WaveLines. | Tianye ZHANG Qi WANG Liwen LIN Jiazhi XIA Xiwang XU Yanhao HUANG Xiaonan LUO Wenting ZHENG Wei CHEN | 2021 | Frontiers of Computer Science2021，15，6： | 0 |
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