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Memristive computing and applications (ICMCA), IEEE International Conference on

作者： Hui Zhao Lei Zhou Qingjie Wang Aidi Liu Jingliang Peng Shandong Provincial Key Laboratory of Network Based Intelligent Computing School of Information Science and Engineering University of Jinan Jinan China College of Information Science and Engineering Northeastern University Shenyang China Collaborative Innovation Center of Memristive Computing Application Qilu Institute of Technology Jinan China

This article proposes a new predefined-time (PDT) stability theorem, which offers more evident advantages compared to previous predefined-time stability. Firstly, based on the limitations of existing PDT stability, this theorem relaxed the limitations of sufficient conditions, which fill the gap in the research on PDT stability. Secondly, the PDT synchronization of multi-modal memristive neural networks (MM-MNN) is analyzed by the usability of the new judgment theorem. A matching PDT controller is designed and sufficient synchronization control conditions is obtained by utilizing generalized Lyapunov functional method, set-valued mapping, inequality analysis technique and differential inclusion theory. Meanwhile, the topological characteristics of multi-modal neuron and its impact on network synchronization behavior are presented. Finally, we provide some confirmatory numerical simulations.

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Effects of Minor CE Doping on the Microstructure and Mechanical Performances of a Eh47 Grade Hsla Steel for Ship and Ocean Engineering

SSRN

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SSRN 2023年

作者： Xiao, Jiuhan Yan, Ling Zhang, Peng Li, Guanglong Li, Boyong Zhao, Tan Wang, Hua Chen, Lijia Wang, Dong State Key Laboratory of Metal Material for Marine Equipment and Application Anshan114021 China Anshan Iron and Steel Group Company Limited Anshan114021 China School of Materials Science and Engineering Shenyang University of Technology Shenyang110870 China Shi-changxu Innovation Center for Advanced Materials Institute of Metal Research Chinese Academy of Sciences Shenyang110016 China

The influence of minor Ce doping on the evolution mechanisms of microstructure and mechanical performances of EH47 grade HSLA steel for marine engineering was investigated by microstructure observation and analysis. In the present work, the chemical composition of steels with different Ce contents was designed, and the TMCP hot-rolling process was applied to obtain a portion of bainitic microstructure for the purpose of achieve the performance indicators. The microstructures, precipitates, and inclusions of Ce-free and Ce-containing steels were observed and analyzed by using scanning electron microscopy (SEM) equipped with electron backscatter diffraction (EBSD) detector and transmission electron microscope (TEM) equipped with energy dispersive X-ray spectrometers (EDS). The strength, plasticity, and impact toughness of the experimental steels was measured and evaluated. According to the results, after adding rare earth Ce, the microstructures including grains, M-A constituents, and inclusions of steel were refined and optimized significantly. Then, the influencing mechanisms of Ce doping on precipitates and inclusions formation were further discussed in detail. Simultaneously, a clear variation tendency of mechanical properties was presented by Ce addition. The strength and hardness enhanced significantly, and the total elongation declined slightly. Moreover, the impact absorbed energy enhanced from 56 J to 152 J. © 2023, The Authors. All rights reserved.

关键词： Scanning electron microscopy

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Galvanic Corrosion Behavior of Cu-Fe-Zn Trimetallic Couple in Acidic Media

SSRN

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SSRN 2022年

作者： Chen, Lei Daniel, Enobong Felix Wang, Changgang Liu, Chen Li, Chao Ma, Chaojiang Wu, Liping Bian, Guixue Chen, Shaofeng Ma, Rongyao Dong, Junhua Chen, Yiqing School of Materials Science and Engineering University of Science and Technology of China Shenyang110016 China Shenyang National Laboratory for Materials Science Institute of Metal Research Chinese Academy of Sciences Shenyang110016 China Naval Aviation University Qingdao Campus Qingdao266041 China Shi-changxu Innovation Center for Advanced Materials Institute of Metal Research Chinese Academy of Sciences Shenyang110016 China State Key Laboratory of Metal Material for Marine Equipment and Application Anshan114009 China

The galvanic corrosion behavior of Cu-Fe-Zn trimetallic couple and its factors were investigated in acidic chloride solution using electrochemical and numerical methods. Results demonstrated that the potential difference of galvanic couple reflects only the thermodynamic tendency of galvanic corrosion, while the cathodic kinetic process controls the galvanic corrosion rate. It is found that the galvanic effect between Cu and Zn is much less than that between Zn and Fe when ohmically coupled. This is opposite to the theory of galvanic series. Despite possessing the maximum corrosion potential difference as the driving force, the galvanic current of Zn-Cu couple was less than that of Zn-Fe couple with equal area ratio. This drove the intermediate metal (Fe) to act as the main cathode in Cu-Fe-Zn trimetallic couple. Furthermore, it is found that Fe can be transformed into the anode due to the area change of Cu. The electrochemical experimental results are in good agreement with the FEM, suggesting that this method can accurately predict the galvanic corrosion behavior of multielectrode systems. © 2022, The Authors. All rights reserved.

关键词： Galvanic corrosion

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Research on the Current State of Privacy Risks in Children's Mobile applications 4

Research on the Current State of Privacy Risks in Children's...

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4th International Symposium on Computer Technology and Information Science, ISCTIS 2024

作者： Geng, Xinrui Liu, Tao Shang, Chong Chen, Jianxiang Lu, Yueran Zhang, Yan Wang, Lifeng Xi'an Jiaotong-Liverpool University School of AI and Advanced Computing Suzhou China MIIT Key Laboratory of Mobile Application Innovation and Governance Technology Beijing China Chinese Academy of Sciences Institute of Information Engineering Beijing China Shanxi Agricultural University School of Agricultural Engineering China Tianjin Normal University School of Software Engineering Tianjin China University of Chinese Academy of Sciences Institute of Information Engineering Chinese Academy of Sciences School of Cyber Security Beijing China Shandong Yeda Smart City Operation Technology Co. Ltd. Shandong China

ISBN: (纸本)9798350354560

In the digital age, children increasingly access a vast world of information through mobile applications. Despite global regulations and protective measures by app stores, privacy breaches in these apps persist. This study investigates privacy issues and threats in children's mobile applications by comparing APKs and legal provisions across different countries. It examines 70 representative children's apps from China, Europe, the U.S., and Japan through static code analysis and dynamic runtime testing. Using a mixed-methods approach, the research identifies integrated third-party services, data transmission protocols, permission requests, and conducts code audits to assess privacy compliance. It also simulates real usage scenarios to track data flow and detect unauthorized data collection and sharing practices. Furthermore, the study compares national privacy laws, focusing on data minimization, parental consent mechanisms, data encryption, and storage duration regulations. The goal is to provide empirical evidence and recommendations for optimizing global children's online privacy protection policies. © 2024 IEEE.

关键词： Differential privacy

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SVM-based deep stacking networks

arXiv

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arXiv 2019年

作者： Wang, Jingyuan Feng, Kai Wu, Junjie MOE Engineering Research Center of Advanced Computer Application Technology School of Computer Science Engineering Beihang University Beijing100191 China Beijing Key Laboratory of Emergency Support Simulation Technologies for City Operations School of Economics and Management Beihang University Beijing100191 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China

The deep network model, with the majority built on neural networks, has been proved to be a powerful framework to represent complex data for high performance machine learning. In recent years, more and more studies turn to nonneural network approaches to build diverse deep structures, and the Deep Stacking Network (DSN) model is one of such approaches that uses stacked easy-to-learn blocks to build a parameter-training-parallelizable deep network. In this paper, we propose a novel SVM-based Deep Stacking Network (SVM-DSN), which uses the DSN architecture to organize linear SVM classifiers for deep learning. A BP-like layer tuning scheme is also proposed to ensure holistic and local optimizations of stacked SVMs simultaneously. Some good math properties of SVM, such as the convex optimization, is introduced into the DSN framework by our model. From a global view, SVM-DSN can iteratively extract data representations layer by layer as a deep neural network but with parallelizability, and from a local view, each stacked SVM can converge to its optimal solution and obtain the support vectors, which compared with neural networks could lead to interesting improvements in anti-saturation and interpretability. Experimental results on both image and text data sets demonstrate the excellent performances of SVM-DSN compared with some competitive benchmark models. Copyright © 2019, The Authors. All rights reserved.

关键词： Convex optimization

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Research on Intelligent Joint Detection Technology for application Privacy Behavior Compliance

Research on Intelligent Joint Detection Technology for Appli...

引用

IEEE International Conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Ruoding Zhang Tao Liu Qifeng Shi Yan Zhang Xiaoyi Song Xinrui Geng Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China Key Laboratory of Mobile Application Innovation and Governance Technology MIIT Chinese Academy of Information and Communications Technologys Beijing China School of AI and Advanced Computing Xi’an Jiaotong-Liverpool University Suzhou China

ISBN: (数字)9798331506209

ISBN: (纸本)9798331506216

The surge in mobile applications has introduced substantial challenges in protecting user privacy. Despite the global enactment of privacy protection laws, ensuring compliance in mobile applications remains complex. We propose a deep learning-based detection technique that focuses on detecting the compliance of mobile applications at the level of privacy policy statements and code behaviors. We have developed a hierarchical classification system that sorts privacy statements into primary and secondary categories, aligning them with relevant privacy regulations and associated code actions. Our research introduces an automated dual-detection system that utilizes the BERT pre-trained model alongside convolutional neural networks to execute multilabel classification of privacy statements, thus pinpointing the privacy management actions they describe. By employing static analysis, the study decomposes Android application package files to scrutinize their behavior and assess the alignment between code actions and privacy statements. The results of our experiments indicate that the proposed dual-detection system effectively identifies compliance issues in mobile applications, providing an innovative technical solution to enhance user privacy protection.

关键词： Privacy Codes Surge protection Static analysis Multi label classification Regulation Mobile applications Convolutional neural networks Protection Surges

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Anomalous Contribution to the Nematic Electronic States from the Structural Transition in FeSe Revealed by Time- and Angle-Resolved Photoemission Spectroscopy

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Physical Review Letters 2022年第24期128卷 246401-246401页

作者： Yuanyuan Yang Qisi Wang Shaofeng Duan Hongliang Wo Chaozhi Huang Shichong Wang Lingxiao Gu Dao Xiang Dong Qian Jun Zhao Wentao Zhang Key Laboratory of Artificial Structures and Quantum Control (Ministry of Education) Shenyang National Laboratory for Materials Science School of Physics and Astronomy Shanghai Jiao Tong University Shanghai 200240 China State Key Laboratory of Surface Physics and Department of Physics Fudan University Shanghai 200433 China Key Laboratory for Laser Plasmas (Ministry of Education) School of Physics and Astronomy Shanghai Jiao Tong University Shanghai 200240 China Tsung-Dao Lee Institute Shanghai Jiao Tong University Shanghai 200240 China Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing 210093 China Institute of Nanoelectronics and Quantum Computing Fudan University Shanghai 200433 China

High-resolution time- and angle-resolved photoemission measurements were made on FeSe superconductors. With ultrafast photoexcitation, two critical excitation fluences that correspond to two ultrafast electronic phase transitions were found only in the dyz-orbit-derived band near the Brillouin-zone center within our time and energy resolution. Upon comparison to the detailed temperature dependent measurements, we conclude that there are two equilibrium electronic phase transitions (at approximately 90 and 120 K) above the superconducting transition temperature, and an anomalous contribution on the scale of 10 meV to the nematic states from the structural transition is experimentally determined. Our observations strongly suggest that the electronic phase transition at 120 K must be taken into account in the energy band development of FeSe, and, furthermore, the contribution of the structural transition plays an important role in the nematic phase of iron-based high-temperature superconductors.

关键词： Electronic structure Iron-based superconductors Strongly correlated systems Time & angle resolved photoemission spectroscopy

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Electron quasi-itinerancy intertwined with quantum order by disorder in pyrochlore iridate magnetism

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Physical Review Research 2020年第4期2卷 043273-043273页

作者： Gang Chen Xiaoqun Wang Department of Physics and HKU-UCAS Joint Institute for Theoretical and Computational Physics at Hong Kong The University of Hong Kong Hong Kong China State Key Laboratory of Surface Physics and Department of Physics Institute of Nanoelectronics and Quantum Computing Fudan University Shanghai 200433 China Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing 210093 China School of Physics and Astronomy Tsung-Dao Lee Institute Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of Artificial Structures and Quantum Control Ministry of Education Shenyang National Laboratory for Materials Science Shenyang 110016 China

We point out the emergence of magnetism from the interplay of electron quasi-itinerancy and quantum order by disorder in pyrochlore iridates. Like other Mott insulating iridates, the Ir4+ ion in pyrochlore iridates develops an effective J=1/2 moment from the on-site spin-orbit coupling. We consider the generic symmetry-allowed exchange between these local moments on a pyrochlore lattice and obtain the mean-field phase diagram. Assuming the superexchange is mediated by direct and/or indirect electron hopping via intermediate oxygens, we derive the exchange interactions in the strong-coupling regime from the Hubbard model. This exchange has a degenerate classical ground-state manifold, and quantum fluctuation selects a noncoplanar ground state, known as quantum order by disorder. Extending to the intermediate-coupling regime, the same noncoplanar order is selected from the degenerate manifold by the kinetic energy, which is dubbed “electron quasi-itinerancy.” We discuss the experimental relevance of our results and electron quasi-itinerancy among other iridates and 4d/5d magnets.

关键词： Dzyaloshinskii-Moriya interaction Exchange interaction Magnetic anisotropy Magnetic order Spin texture Spin-orbit coupling Iridates Extended Hubbard model

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Simultaneous q-Space Sampling Optimization and Reconstruction for Fast and High-fidelity Diffusion Magnetic Resonance Imaging

arXiv

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arXiv 2024年

作者： Yang, Jing Cheng, Jian Li, Cheng Fan, Wenxin Zou, Juan Wu, Ruoyou Wang, Shanshan Paul C. Lauterbur Research Center for Biomedical Imaging Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China University of Chinese Academy of Sciences Beijing China State Key Laboratory of Software Development Environment Beihang University Beijing China Peng Cheng Laboratory Guangdong Shenzhen China Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application Guangdong China Key Laboratory of Data Science and Intelligent Computing Institute of International Innovation Beihang University Yuhang District Hangzhou China

Diffusion Magnetic Resonance Imaging (dMRI) plays a crucial role in the noninvasive investigation of tissue microstructural properties and structural connectivity in the in vivo human brain. However, to effectively capture the intricate characteristics of water diffusion at various directions and scales, it is important to employ comprehensive q-space sampling. Unfortunately, this requirement leads to long scan times, limiting the clinical applicability of dMRI. To address this challenge, we propose SSOR, a Simultaneous q-Space sampling Optimization and Reconstruction framework. We jointly optimize a subset of q-space samples using a continuous representation of spherical harmonic functions and a reconstruction network. Additionally, we integrate the unique properties of diffusion magnetic resonance imaging (dMRI) in both the q-space and image domains by applying l1-norm and total-variation *** experiments conducted on HCP data demonstrate that SSOR has promising strengths both quantitatively and qualitatively and exhibits robustness to noise. Copyright © 2024, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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Electron quasi-itinerancy intertwined with quantum order by disorder in pyrochlore iridate magnetism

arXiv

引用

arXiv 2020年

作者： Chen, Gang Wang, Xiaoqun Department of Physics HKU-UCAS Joint Institute for Theoretical and Computational Physics at Hong Kong University of Hong Kong Hong Kong State Key Laboratory of Surface Physics Department of Physics Institute of Nanoelectronics and Quantum Computing Fudan University Shanghai200433 China Collaborative Innovation Center of Advanced Microstructures Nanjing University Nanjing210093 China School of Physics and Astronomy Tsung-Dao Lee Institute Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of Artificial Structures and Quantum Control of MOE Shenyang National Laboratory for Materials Science Shenyang110016 China

We point out the emergence of magnetism from the interplay of electron quasi-itinerancy and quantum order by disorder in pyrochlore iridates. Like other Mott insulating iridates, the Ir4+ ion in pyrochlore iridates develops an effective J = 1/2 moment from the on-site spin-orbit coupling. We consider the generic symmetry-allowed exchange between these local moments on a pyrochlore lattice and obtain the mean-field phase diagram. Assuming the superexchange is mediated by direct and/or indirect electron hopping via intermediate oxygens, we derive the exchange interactions in the strong coupling regime from the Hubbard model. This exchange has a degenerate classical ground state manifold and quantum fluctuation selects a non-coplanar ground state, known as quantum order by disorder. Extending to the intermediate coupling regime, the same non-coplanar order is selected from the degenerate manifold by the kinetic energy, which is dubbed "electron quasi-itinerancy". We discuss the experimental relevance of our results and electron quasi-itinerancy among other iridates and 4d/5d magnets. Copyright © 2020, The Authors. All rights reserved.

关键词： Electrons

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