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NiCoP nanoleaves array for electrocatalytic alkaline H2 evolution and overall water splitting

Journal of Energy Chemistry 2020年第11期29卷 395-401页

作者： Lei Chen Yaohao Song Yi Liu Liang Xu Jiaqian Qin Yongpeng Lei Yougen Tang State Key Laboratory of Powder Metallurgy Hunan Provincial Key Laboratory of Chemical Power SourcesCollege of Chemistry and Chemical EngineeringCentral South UniversityChangsha 410083HunanChina Energy Materials Computing Center Jiangxi University of Science and TechnologyNanchang 330013JiangxiChina Research Unit of Advanced Materials for Energy Storage Metallurgy and Materials Science Research InstituteChulalongkorn UniversityBangkok 10330Thailand

The development of non-precious, high-efficient and durable electrocatalysts for H2 evolution in alkaline media is highly desirable. Herein we report NiCoP nanoleaves array vertically grown on Ni foam for H2 evolution and overall water splitting via simple hydrothermal treatment and phosphorization. The selfsupported NiCoP nanoleaves architecture contributes to more exposed active sites, the smaller contact resistance between catalyst and substrate, faster ion diffusion and electron transfer. As a result, the optimized electrode requires only overpotentials of 98 and 173 mV to achieve current densities of 10 and100 m A cm-2 in 1.0 M KOH,respectively. Besides, used as both anode and cathode simultaneously, the electrode delivers current densities of 100 and 200 m A cm-2 at cell voltages of only 1.8 and 1.87 V, respectively. Moreover, the relatively high efficiency of about 11.4% for solar-driven water splitting further illustrates the application of our catalyst to sustainable development based on green technologies.

关键词： Electrocatalysis Hydrogen evolution reaction Alkaline media Water splitting Solar-driven electrolysis

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Stealthy Malware Detection Based on Deep Neural Network 2

Stealthy Malware Detection Based on Deep Neural Network

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2019 2nd International Symposium on Big Data and Applied Statistics, ISBDAS 2019

作者： Lu, Shoupu Li, Qingbao Zhu, Xinbing State Key Laboratory of Mathematical Engineering and Advanced Computing Henan Province Zhengzhou450001 China Henan University of Economics and Law Henan Province Zhengzhou450000 China

Network attacks using advanced local hiding technology have not only increased, but also become a serious threat. However, attacks using these technologies can not be detected through traffic detection, and some attacks imitate benign traffic to avoid detection. To solve these problems, a malware process detection method based on process behavior in possibly infected terminals is proposed. In this method, a deep neural network is introduced to classify malware processes. Firstly, the recurrent neural network is trained to extract the characteristics of process behavior. Secondly, training convolutional neural network is used to classify feature images generated by trained RNN features. The experiments results show that this method can effectively extract the features of malicious processes, and the AUC of ROC curve is 0.97 in the best case. © Published under licence by IOP Publishing Ltd.

关键词： Malware

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Parallelizing Neural Network Models Effectively on GPU by Implementing Reductions Atomically 22

Parallelizing Neural Network Models Effectively on GPU by Im...

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Proceedings of the International Conference on Parallel Architectures and Compilation Techniques

作者： Jie Zhao Cédric Bastoul Yanzhi Yi Jiahui Hu Wang Nie Renwei Zhang Zhen Geng Chong Li Thibaut Tachon Zhiliang Gan State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China Huawei Technologies France SASU Paris France Huawei Technologies Co. Ltd. Beijing China Huawei Technologies Co. Ltd. Hangzhou China Huawei Technologies Co. Ltd. Shenzhen China

ISBN: (纸本)9781450398688

Due to the missing of a good orchestration of loop transformations, existing optimizing compilers for deploying neural networks on GPU either parallelize reductions ineffectively or miss the fusion opportunities with other operators. Neural network models thus exhibit sub-optimal performance on GPU. We present a practical approach called Panamera for the effective parallelization of reductions in neural networks on GPU. Panamera first leverages loop coalescing to flatten the loop dimensions of reductions, converting all reduction operators into canonical forms eligible for the polyhedral model. Next, Panamera uses polyhedral transformations to reduce the data movements caused by unfused reductions and perform multi-block hardware binding not considered by many compilers. Finally, Panamera embeds a highly optimized routine implemented using GPU atomic instructions, further improving the performance of neural network models while guaranteeing the correctness of parallel reductions. The experimental results demonstrate the effectiveness of our approach: for single operators our code obtains a mean speedup of 33.7×, 3.5×, 5.4× and 9.6× over cuDNN, CUB, TVM and Ansor, for sub-graphs our approach outperforms cuDNN, TVM and Ansor by 9.5×, 2.6× and 2.7×, and for end-to-end workloads, a tensor compiler integrated with our approach outperforms them by 122.5%, 19.3% and 15.2%.

关键词： GPU polyhedral compilation deep learning reduction

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IEEE International Conference on Software engineering and Service Sciences (ICSESS)

作者： Duanyi Wang Hui Shu Fei Kang Wenjuan Bu State Key Laboratory of Mathematical Engineering and Advanced Computing Henan Zhengzhou China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou Henan China

ISBN: (数字)9781728165790

ISBN: (纸本)9781728165806

Recently, graph-based malware similarity analysis has been widely used in the field of malware detection. However, the wide application of code obfuscation, polymorphism, and deformation changes the structure of malicious code, which brings great challenges to the malware similarity analysis. To solve these problems, in this paper, we present a new approach to malware similarity analysis based on the network control structure graph (NCSG). This method analyzed the behavior of malware by application program interface (API) association and constructed NCSG. The graph could reflect the command-and-control(C&C) logic of malware. Therefore, it can resist the interference of code obfuscation technology. The structural features extracted from NCSG will be used as the basis of similarity analysis for training the detection model. Finally, we tested the dataset constructed from five known malware family samples, and the experimental results showed that the accuracy of this method for malware variation analysis reached 92.75%. In conclusion, the malware similarity analysis based on NCSG has a strong application value for identifying the same family of malware.

关键词： Training Software algorithms Resists Feature extraction Malware Strain Software engineering

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A Multi-Variant Voting Algorithm Based on Dynamic Feedback

A Multi-Variant Voting Algorithm Based on Dynamic Feedback

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Computer Communication and Network Security (CCNS), International Conference on

作者： Shao Yuwen Zhang Zheng Li Bingzheng Ji Xinsheng State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China R&D Center National Digital Switching System Engineering & Technological Zhengzhou China

Multi-variant execution framework can protect software security. For the problem of performance loss caused by too many voting times in the existing multi-variant execution framework, this paper proposes a multi-variant voting algorithm based on dynamic feedback, which can make the multi-variant continuously improve its corresponding voting strategy at runtime. Using this algorithm, the multi-variant can get a stable voting range, reduce the number of voting, and effectively improve the performance of multi-variant.

关键词： Runtime Heuristic algorithms Software algorithms Network security Software Computer security

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Malware Detection Method based on Control Flow Analysis 2019

Malware Detection Method based on Control Flow Analysis

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Proceedings of the 2019 7th International Conference on Information Technology: IoT and Smart City

作者： Peng Shan Qingbao Li Ping Zhang Yanyang Gu State Key Laboratory of Mathematical Engineering and Advanced Computing China

ISBN: (纸本)9781450376631

With the rapid development of computer technology and the iteration of malware, numerous computer malware detection methods have been proposed, among which malware detection based on machine learning has become an important research direction. Opcode sequences are often used as an important feature of machine learning models for training and testing. However, opcode sequences extracted orderly from raw disassembly text may not adequately reflect the behavior of executables. In order to solve this problem, this paper proposes a new malware detection method based on the control flow of executables. This method analyzes the control flow of executables and extracts execution traces from by the unit of function. This paper uses the execution traces to represent the behavior of the executables and present the execution traces by opcode sequences. In order to improve the training efficiency and reduce the feature dimensionality, this paper propose an x86 intermediate code. Then we convert the opcode sequences into the corresponding intermediate code sequences and vectorize them using Vector Space Model (VSM) for training and testing. This paper implements Naïve Bayes Classifier, Support Vector Machines and Random Forest for classification. The experiment result shows that the Random Forest algorithm has the best performance, with an accuracy of 90.8% and the model establishment time is 22s. Compared with the traditional methods based on disassembly text, the accuracy is improved by 1.4%, compared with the methods using x86 opcode, the efficiency is increased by 62%.

关键词： Control Flow Analysis Machine Learning Intermediate Code Malware Detection

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High-Ni Low-Co High-Capacity Li-Rich Cathode Materials Via Adjusting Li2mno3 Content and Li/Ni Mixing Structures

SSRN

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SSRN 2023年

作者： Wu, Zhen Zou, Kunyang Dai, Xin Zhang, Yu-Han Zhang, Xudong Wang, Hao Hou, Zhufeng Ma, Lijing Liu, Yan Chen, Yuanzhen Guo, Shengwu Liu, Yongning State Key Laboratory for Mechanical Behavior of Materials Xi’an Jiaotong University Xi’an710049 China Qingdao Industrial Energy Storage Research Institute Qingdao Institute of Bioenergy and Bioprocess Technology Chinese Academy of Sciences Qingdao266101 China Center for High Performance Computing Network Information Center Xi’an Jiaotong University Xi’an710049 China Hefei Advanced Computing Center Operation Management Corp Ltd Hefei230088 China State Key Laboratory of Structural Chemistry Fujian Institute of Research the Structure of Matter Chinese Academy of Sciences Fuzhou350002 China International Research Center for Renewable Energy State Key Laboratory of Multiphase Flow in Power Engineering Xi’an Jiaotong University Xi’an710049 China

Li-rich layered oxides (LLOs) are considered as the promising cathode materials for next-generation high energy density lithium-ion batteries (LIBs). However, severe voltage fade and capacity decay hinder their commercial applications. Increasing the Ni content in LLOs effectively improves the stability and discharge voltage, but shows reduced capacities, typically © 2023, The Authors. All rights reserved.

关键词： Lithium compounds

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One-step implementation of Rydberg nonadiabatic noncyclic geometric quantum computation in decoherence-free subspaces

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Physical Review A 2022年第6期105卷 062602-062602页

作者： Li-Na Sun F.-Q. Guo Zheng Shan M. Feng L.-L. Yan Shi-Lei Su School of Physics and Microelectronics Key Laboratory of Materials Physics of Ministry of Education Zhengzhou University Zhengzhou 450001 China State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou 450001 China State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics Wuhan Institute of Physics and Mathematics Innovation Academy of Precision Measurement Science and Technology Chinese Academy of Sciences Wuhan 430071 China Department of Physics Zhejiang Normal University Jinhua 321004 China Research Center for Quantum Precision Measurement Guangzhou Institute of Industry Technology Guangzhou 511458 China

Quantum gates constructed by geometric phase are naturally robust to control errors due to the global nature of the geometric evolution path. Therefore, how to cope with the inevitable decoherence errors is worthy of serious attention for geometric quantum computation. Different from conventional nonadiabatic geometric quantum computation (NGQC), which needs the same evolution time for any geometric rotation angle, we have proposed and experimentally demonstrated nonadiabatic noncyclic geometric quantum computation (NNGQC) without the requirement of the cyclic evolution condition, which thus reduces decoherence errors due to shortened evolution time [J. W. Zhang et al., Phys. Rev. Lett. 127, 030502 (2021)]. In addition, the use of decoherence-free subspaces (DFS) is another effective strategy to protect quantum gates from dephasing error and has been studied in nonadiabatic holonomic quantum computation [G. F. Xu et al., Phys. Rev. Lett. 109, 170501 (2012)]. Motivated by previous studies, we propose a one-step scheme to implement single-qubit NNGQC operation in DFS constructed by two Rydberg atoms, and then generalize the scheme to the two-logical-qubit case in one step. The numerical results show that our scheme is robust against decoherence in contrast to the NGQC counterparts. The present scheme combines the features of NNGQC and DFS and can further reduce the impact of decoherence on gate infidelity, which may provide an option for the realization of Rydberg-atom-based quantum computation in the future.

关键词： Geometric & topological phases Quantum gates Rydberg atoms & molecules

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Malware detection method based on control flow analysis 7

Malware detection method based on control flow analysis

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7th International Conference on Information Technology: IoT and Smart City, ICIT 2019

作者： Shan, Peng Li, Qingbao Zhang, Ping Gu, Yanyang State Key Laboratory Mathematical Engineering and Advanced Computing China

ISBN: (纸本)9781450376631

关键词： Malware

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Highly efficient oxygen evolution and stable water splitting by coupling NiFe LDH with metal phosphides

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Science China Materials 2021年第7期64卷 1662-1670页

作者： Chengye Song Yi Liu Yuchao Wang Shuaihao Tang Wenkui Li Qian Li Jian Zeng Lei Chen Hongcheng Peng Yongpeng Lei State Key Laboratory of Powder Metallurgy Central South UniversityChangsha 410083China School of Materials and Mechanical Engineering Jiangxi Key Laboratory of Surface EngineeringJiangxi Science and Technology Normal UniversityNanchang 330013China Hunan Provincial Key Laboratory of Chemical Power Sources College of Chemistry and Chemical EngineeringCentral South UniversityChangsha 410083China School of Material Science and Engineering Central South University of Forestry and TechnologyChangsha 410004China Energy Materials Computing Center Jiangxi University of Science and TechnologyNanchang 330013China State Key Laboratory of Advanced Chemical Power Sources Guizhou Meiling Power Sources Co.Ltd.Zunyi 563003China

It is a great challenge to develop highly active oxygen evolution reaction(OER)electrocatalysts with superior *** this study,a NiFe layered double hydroxidedecorated phosphide(NiFe LDH@CoP/NiP_(3))was constructed to display satisfactory OER activity and good stability for water splitting in alkaline *** an overpotential of 300 mV,NiFe LDH@CoP/NiP_(3) achieved a current density of 82 mA cm^(-2) for the OER,which was 9.1 and 2.3 times that of CoP/NiP_(3) and NiFe LDH,***,the reconstruction behavior,during which oxyhydroxides formed,was studied by a combination of X-ray photoelectron spectroscopy,Raman spectroscopy,and scanning electron microscopy.A synergistic effect between NiFe LDH and CoP/NiP_(3) was also observed for the hydrogen evolution ***,when NiFe LDH@CoP/NiP_(3) acted as both the cathode and anode for overall water splitting,a high current density of 100 mA cm^(-2) was maintained for more than 275 *** addition,under Xe light irradiation,a solar-to-hydrogen efficiency of 9.89% was achieved for solar-driven water *** work presents the coupling of different active compositions,and can provide a reference for designing bifunctional electrocatalysts.

关键词： bifunctional electrocatalysis oxygen evolution reaction phosphides layered double hydroxides water splitting

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