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SSRN 2024年

作者： Zhuang, Quan Li, Xiangli School of Mathematics and Computing Science Guilin University of Electronic Technology Guangxi 541004 China Guangxi Colleges and University Key Laboratory of Data Analysis and Computation Guangxi 541004 China Center for Applied Mathematics of Guangxi Guangxi 541004 China

Density peak clustering (DPC) is an effective clustering method that is widely used in various *** idea of the density peak clustering is very simplistic, which can quickly select the cluster density peaks and the clustering process requires no iteration. However, DPC still has the following drawbacks:The calculation of the local density of the DPC algorithm is highly dependent on the calculation of the cut-off ***, the number of cluster centers is very challenging to determine and to select. Lastly, the straightforward allocation strategy makes the presence of domino effect, which greatly reduces the clustering performance of the DPC. To overcome the limitations presented above, we propose a density clustering algorithm based on effective neighbors and multistage allocation strategy(DCMS). We redeffne the density by introducing the concept of effective neighbors and identify the underlying structure of each *** addition, we combine the idea of outlier detection to divide the objects into different types of ***, we propose an multistage assignment strategy to generate initial clusters and assign the remaining points to obtain the ffnal clustering *** results on synthetic and UCI datasets validate that the proposed algorithm outperforms several famous clustering algorithms. © 2024, The Authors. All rights reserved.

关键词： Clustering algorithms

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Non-Regular Pseudo-Differential Operators on Matrix Weighted Besov-Triebel-Lizorkin Spaces

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数学研究（英文） 2024年第1期57卷 84-100页

作者： Tengfei Bai Jingshi Xu School of Mathematics and Statistics Hainan Normal UniversityHaikouHainan 571158China Center for Applied Mathematics of Guangxi Guangxi Colleges and Universities Key Laboratory of Data Analysis and ComputationSchool of Mathematics and Computing ScienceGuilin University of Electronic TechnologyGuilin 54100China

In this paper we obtain the boundedness of non-regular pseudo-differential operators with symbols in Besov spaces on matrix-weighted Besov-Triebel-Lizorkin *** symbols include the classical Hörmander classes.

关键词： Besov space matrix weight Pseudo-differential operator Triebel-Lizorkin space

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A Neurobehavioral Evaluation of the Efficacy of 1mA Longitudinal, Anodal TDCS on Multitasking and Transfer Performance

A Neurobehavioral Evaluation of the Efficacy of 1mA Longitud...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Akash K Rao Shashank Uttrani Darshil Shah Vishnu K Menon Arnav Bhavsar Shubhajit Roy Chowdhury Ramsingh Negi Varun Dutt Manipal Academy of Higher Education Applied Cognitive Science Laboratory Indian Institute of Technology Mandi School of Computing and Electrical Engineering Indian Institute of Technology Mandi Cognitive Control and Machine Learning Group at the Institute of Nuclear Medicine and Allied Sciences Defence Research and Development Organization

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

Multitasking requires rapid switching of attention and cognitive resources between different tasks in a dynamic environment, relying on cognitive processes, such as working memory, executive control, and selective attention. Although studies have investigated the efficacy of various neurobehavioral interventions in improving multitasking capabilities, the effects of longitudinal anodal transcranial direct current stimulation (tDCS) in enhancing multitasking performance have not been investigated. This research investigated the efficacy of 1mA anodal tDCS administered longitudinally on multitasking performance. 42 participants were randomly and equally divided into the experimental and placebo control conditions in this study conducted for 10 days. All participants executed two multitasking tasks on day 1 and received 1mA anodal/placebo tDCS during task training from day 2 to day 8. Various behavioral and neurophysiological measures have been measured. The findings revealed that tDCS had the propensity to augment multitasking capabilities in the trained task but had limited transfer capabilities. EEG-based brain connectivity analysis also revealed the formation of network hubs in the prefrontal and frontal regions, indicating enhanced cortical activation in the beta band. We intend to use these findings to design interventional frameworks to enhance multitasking performance using tDCS.

关键词： Training Atmospheric measurements Memory management Switches Multitasking Particle measurements Dynamic scheduling Control systems Transcranial direct current stimulation Cybernetics

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Application of Electrical Network Frequency as an Entropy Generator in Distributed Systems

Application of Electrical Network Frequency as an Entropy Ge...

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2023 IEEE National Aerospace and Electronics Conference, NAECON 2023

作者： Nagothu, Deeraj Xu, Ronghua Chen, Yu Blasch, Erik Ardiles-Cruz, Erika Intelligent Fusion Technology Inc. GermantownMD20876 United States Michigan Technological University Dept. of Applied Computing HoughtonMI49931 United States Binghamton University Dept. of Electrical and Computer Engineering BinghamtonNY13902 United States The U.S. Air Force Research Laboratory RomeNY13441 United States

ISBN: (纸本)9798350338782

The development of public information technology (IT) infrastructures using modern edge devices has revolutionized the smart city ecosystem. As the number of devices in the ecosystem exponentially increases, the power grid infrastructure has continued to function as the backbone of smart cities and support the growing requirements for electricity, such as multimedia services. Media authentication technology leveraging the power system frequency, the Electrical Network Frequency (ENF) signal, has gained traction as an environmental fingerprint to counteract visual layer attacks targeted toward multimedia-based edge devices. Due to the unique and similar fluctuation patterns throughout the grid, the ENF signal is reliable in applications like multimedia synchronization, authentication, and source identification. ENF -based systems are inevitably targeted by perpetrators to bypass their detection schemes;however, such attacks are successful only if the ENF fingerprint can be pre-dicted. In this work, we studied the randomization nature of ENF signals and the societal impacts on its fluctuation patterns due to power grid consumption. Leveraging the ENF signal fluctuations, we integrate ENF as a source of randomness for the Random Bit Generator (RBG) system in cryptographic applications. An RBG-based encrypted communication and committee election mechanism is proposed for an enhanced distribution multimedia system. The paper further discusses the potential applications of the ENF -based randomness generator. © 2023 IEEE.

关键词： Entropy

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Tuning 2D magnetism in Fe3+XGeTe2 films by element doping

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National Science Review 2022年第6期9卷 163-170页

作者： Shanshan Liu Zihan Li Ke Yang Enze Zhang Awadhesh Narayan Xiaoqian Zhang Jiayi Zhu Wenqing Liu Zhiming Liao Masaki Kudo Takaaki Toriyama Yunkun Yang Qiang Li Linfeng Ai Ce Huang Jiabao Sun Xiaojiao Guo Wenzhong Bao Qingsong Deng Yanhui Chen Lifeng Yin Jian Shen Xiaodong Han Syo Matsumura Jin Zou Yongbing Xu Xiaodong Xu Hua Wu Faxian Xiu State Key Laboratory of Surface Physics and Department of Physics Fudan University Institute for Nanoelectronic Devices and Quantum Computing Fudan University College of Science University of Shanghai for Science and Technology Laboratory for Computational Physical Sciences(MOE) Fudan University Solid State and Structural Chemistry Unit Indian Institute of Science School of Electronic Science and Engineering Nanjing University Department of Physics University of Washington Department of Electronic Engineering Royal Holloway University of London Materials Engineering The University of Queensland Beijing Key Laboratory of Microstructure and Property of Advanced Materials Institute of Microstructure and Property of Advanced Materials Beijing University of Technology The Ultramicroscopy Research Center Kyushu University State Key Laboratory of ASIC and System School of Microelectronics Fudan University Collaborative Innovation Center of Advanced Microstructures Department of Applied Quantum Physics and Nuclear Engineering Kyushu University Centre for Microscopy and Microanalysis The University of Queensland Shanghai Research Center for Quantum Sciences

Two-dimensional（2D） ferromagnetic materials have been discovered with tunable magnetism and orbital-driven nodal-line features. Controlling the 2D magnetism in exfoliated nanoflakes via electric/magnetic fields enables a boosted Curie temperature（TC） or phase transitions. One of the challenges, however, is the realization of high TC2D magnets that are tunable, robust and suitable for large scale fabrication. Here, we report molecular-beam epitaxy growth of wafer-scale Fe3+XGeTe2films with TCabove room temperature. By controlling the Fe composition in Fe3+XGeTe2, a continuously modulated TCin a broad range of 185–320 K has been achieved. This widely tunable TCis attributed to the doped interlayer Fe that provides a 40% enhancement around the optimal composition X = 2. We further fabricated magnetic tunneling junction device arrays that exhibit clear tunneling signals. Our results show an effective and reliable approach, i.e. element doping, to producing robust and tunable ferromagnetism beyond room temperature in a large-scale 2D Fe3+XGeTe2fashion.

关键词： 2D ferromagnetic material Fe3+XGeTe2 film element doping above room temperature TC tunability

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Hybrid cat-transmon architecture for scalable, hardware-efficient quantum error correction

arXiv

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arXiv 2024年

作者： Hann, Connor T. Noh, Kyungjoo Putterman, Harald Matheny, Matthew H. Iverson, Joseph K. Fang, Michael T. Chamberland, Christopher Painter, Oskar Brandão, Fernando G.S.L. AWS Center for Quantum Computing PasadenaCA91125 United States IQIM California Institute of Technology PasadenaCA91125 United States Thomas J. Watson Sr. Laboratory of Applied Physics California Institute of Technology PasadenaCA91125 United States

Dissipative cat qubits are a promising physical platform for quantum computing, since their large noise bias can enable more hardware-efficient quantum error correction. In this work we theoretically study the long-term prospects of a hybrid cat-transmon quantum computing architecture where dissipative cat qubits play the role of data qubits, and error syndromes are measured using ancillary transmon qubits. The cat qubits' noise bias enables more hardware-efficient quantum error correction, and the use of transmons allows for practical, high-fidelity syndrome measurement. While correction of the dominant cat Z errors with a repetition code has recently been demonstrated in experiment, here we show how the architecture can be scaled beyond a repetition code. In particular, we propose a cat-transmon entangling gate that enables the correction of residual cat X errors in a thin rectangular surface code, so that logical error can be arbitrarily suppressed by increasing code distance. We numerically estimate logical memory performance, finding significant overhead reductions in comparison to architectures without biased noise. For example, with current state-of-the-art coherence, physical error rates of 10−3 and noise biases in the range 103 − 104 are achievable. With this level of performance, the qubit overhead required to reach algorithmically-relevant logical error rates with the cat-transmon architecture matches that of an unbiased-noise architecture with physical error rates in the range 10−5 − 10−4 Copyright © 2024, The Authors. All rights reserved.

关键词： Qubits

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Multi-Layer Perceptron Regression Model for Material Characterization in the Microwave Frequency Range with Cross-Dataset Validation 7

Multi-Layer Perceptron Regression Model for Material Charact...

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7th International Youth Conference on Radio Electronics, Electrical and Power Engineering, REEPE 2025

作者： Hanima Kannan, C.H. Gupta, Deepa Mathur, Parul Kurup, Dhanesh G. Chaudhari, Tilesh Sanjay Mathur, Priyanka Amrita School of Engineering Amrita Vishwa Vidyapeetham Rf and Wireless Systems Laboratory Department of Electronics and Communication Engineering Bengaluru India Amrita School of Computing Amrita Vishwa Vidyapeetham Department of Computer Science and Engineering Bengaluru India Indian Institute of Technology Creative and Advanced Research Based on Nanomaterials Laboratory Department of Chemical Engineering Hyderabad India School of Engineering and Applied Science Bennett University U.P. Greater Noida India

ISBN: (纸本)9798331531836

This paper presents a Multi-Layer Perceptron (MLP) based regression model for characterizing materials at micrwave frequency range. A mathematical model and experimental setup of the Open-Ended Coaxial Probe (OECP) sensor interacting with the material under test (MUT) generate a cross-dataset to validate the MLP regression model, utilizing the frequency-dependent complex dielectric constant for material characterization. This paper utilizes the frequency-dependent response of the OECP sensor (scattering parameters) as input features for the MLP model, while the complex dielectric constant of the MUT serves as the output feature. The optimized MLP model has an R² of 99.991% and MSE of 6.65 × 10^-5, with predictions closely aligning with literature values for standard loads such as distilled water, acetone, and ethanol, obtained using a commercially available dielectric assessment software kit. This cost-effective model enables precise dielectric property estimation, with future work extending to unknown materials, mixtures, and electrolyte solutions. © 2025 IEEE.

关键词： Complex Permittivity Cross-Dataset Generation Material Characterization Multi-Layer Perceptron Open-Ended Coaxial Probe Stan-dard Reference Loads

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A Medical Pre-diagnosis Scheme Based on Neural Network and Inner Product Function Encryption

A Medical Pre-diagnosis Scheme Based on Neural Network and I...

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Electronic Communication and Artificial Intelligence (IWECAI), International Workshop on

作者： Xu Cui Hao Liu Min Tang Yihong Ma School of Mathematics and Computing Science Guangxi Colleges and Universities Key Laboratory of Data Analysis and Computation Guilin University of Electronic Technology Guilin China Center for Applied Mathematics of Guangxi (GUET) Guilin China

Artificial neural networks are widely used in various fields, such as intelligent road networks, Internet of Things, and smart medical systems due to their ability to process large amounts of data in parallel, store information in a distributed manner, and self-organize and self-learn. Cloud computing technology has further expanded the development of neural network applications. However, user data often contains sensitive information, and once the data management right is transferred to the cloud, it faces serious security and privacy issues. In the medical field, privacy-preserving implementation of classification algorithms is crucial for ensuring the privacy of electronic medical diagnosis services. Current privacy-preserving medical pre-diagnosis schemes based on homomorphic encryption impose a significant computational and communication burden on users and servers. This paper proposes an efficient privacy-preserving medical pre-diagnosis scheme based on neural networks and inner product function encryption that protects user privacy during pre-diagnosis while having small computational and communication overheads.

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Unusual thermal properties of graphene origami crease:A molecular dynamics study

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Green Energy & Environment 2022年第1期7卷 86-94页

作者： Ning Wei Yang Chen Kun Cai Yingyan Zhang Qingxiang Pei Jin-Cheng Zheng Yiu-Wing Mai Junhua Zhao Jiangsu Key Laboratory of Advanced Food Manufacturing Equipment and Technology Jiangnan UniversityWuxi214122China Shanghai Institute of Applied Mathematics and Mechanics Shanghai Key Laboratory of Mechanics in Energy EngineeringShanghai UniversityShanghai200072China School of Engineering RMIT UniversityBundooraVIC3083Australia Institute of High Performance Computing A^(*)STAR138632Singapore Department of Physics and the Collaborative Innovation Center for Optoelectronic Semiconductors and Efficient Devices Xiamen UniversityXiamen361005China Xiamen University Malaysia 439000SepangSelangorMalaysia Centre for Advanced Materials Technology(CAMT) School of AerospaceMechanical and Mechatronic Engineering J07The University of SydneySydneyNSW2006Australia

Graphene is a two-dimensional material that can be folded into diverse and yet interesting nanostructures like macro-scale paper *** of graphene not only makes different morphological configurations but also modifies their mechanical and thermal *** by paper origami,herein we studied systemically the effects of creases,where sp^(2)to sp^(3)bond transformation occurs,on the thermal properties of graphene origami using molecular dynamics(MD)*** MD simulation results show that tensile strain reduces(not increases)the interfacial thermal resistance owing to the presence of the *** unusual phenomenon is explained by the micro-heat flux migration and stress *** findings on the graphene origami enable the design of the next-generation thermal management devices and flexible electronics with tuneable properties.

关键词： Graphene Origami Bond transformation Interfacial thermal resistance Molecular dynamics

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Timing Jitter Remover for Optical Non-Gaussian State Preparation

Timing Jitter Remover for Optical Non-Gaussian State Prepara...

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Frontiers in Optics, FiO 2022

作者： Sonoyama, Tatsuki Takahashi, Kazuma Takasu, Sachiko Hattori, Kaori Fukuda, Daiji Asavanant, Warit Takase, Kan Fukui, Kosuke Yoshikawa, Jun-Ichi Endo, Mamoru Furusawa, Akira Department of Applied Physics School of Engineering The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo113-8656 Japan National Institute of Advanced Industrial Science and Technology Ibaraki Tsukuba305-8563 Japan AIST-UTokyo Advanced Operando-Measurement Technology Open Innovation Laboratory Ibaraki Tsukuba305-8563 Japan Optical Quantum Computing Research Team RIKEN Center for Quantum Computing 2-1 Hirosawa Saitama Wako351-0198 Japan

In this work, we remove the timing jitter of the photon-number-resolving detector which limited non-Gaussian state preparation using a continuous-wave light source, and generate a Schrödinger cat state with Wigne...

ISBN: (纸本)9781557528209

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