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Zero-pole cancellation for identity-based aggregators:a constant-size designated verifier-set signature

Frontiers of computer science 2020年第4期14卷 197-210页

作者： E CHEN Yan ZHU Changlu LIN Kewei LV School of Computer and Communication Engineering University of Science and Technology BeijingBeijing100083China College of Mathematics and Informatics Fujian Normal UniversityFuzhou350117China Fujian Provincial Key Lab of Network Security&Cryptology Fujian Normal UniversityFuzhou350007China Institute of Information Engineering DCS Research CenterChinese Academy of SciencesBeijing100093China

In this paper we present a designated verifier-set signature(DVSS),in which the signer allows to designate many verifiers rather than one verifier,and each designated verifier can verify the validity of signature by *** research starts from identity-based aggregator(IBA)that compresses a designated set of verifier’s identities to a constant-size random string in cryptographic *** IBA is constructed by mapping the hash of verifier’s identity into zero or pole of a target curve,and extracting one curve’s point as the result of aggregation according to a specific *** the different types of target curves,these two IBAs are called as zeros-based aggregator and poles-based aggregator,*** on them,we propose a practical DVSS scheme constructed from the zero-pole cancellation method which can eliminate the same elements between zeros-based aggregator and poles-based *** to this design,our DVSS scheme has some distinct advantages:(1)the signature supporting arbitrary dynamic verifiers extracted from a large number of users;and(2)the signature with short and constant *** rigorously prove that our DVSS scheme satisfies the security properties:correctness,consistency,unforgeability and *** is a preview of subscription content,log in to check access.

关键词： designated verifier-set signature aggregator unforgeability exclusivity

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Biaxial strain modulated valence-band engineering in III-V digital alloys

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Physical Review B 2022年第3期106卷 035301-035301页

作者： Sheikh Z. Ahmed Yaohua Tan Jiyuan Zheng Joe C. Campbell Avik W. Ghosh Department of Electrical and Computer Engineering University of Virginia Charlottesville Virginia 22904 USA Synopsys Inc. Mountain View California 94043 USA Beijing National Research Center for Information Science and Technology Tsinghua University 100084 Beijing China Department of Physics University of Virginia Charlottesville Virginia 22904 USA

A series of III-V digital alloy avalanche photodiodes have been recently seen to exhibit very low excess noise. These alloys have low hole ionization coefficients due to enhanced effective mass, a large separation between light-hole and split-off bands in the valence band, and in one case (InAlAs), potentially the creation of a small minigap in computed band structures. Whereas such minigaps would indeed provide a reliable way to suppress hole transport and reduce excess noise, their physical origin is explored here. In this paper, we provide an explanation for the formation of the minigaps as arising from oscillations in certain orbital overlaps. We demonstrate that decreasing the substrate lattice constant would increase the minigap size and mass in the transport direction. This leads to reduced quantum tunneling and phonon scattering of the holes. Finally, we illustrate the band-structure modification with substrate lattice constant for other III-V digital alloys. We, thus, provide a recipe for deterministic engineering of sizable valence-band minigaps as a potential recipe for high gain avalanche photodiodes.

关键词： Strain Band structure methods Strain engineering Tight-binding model

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NeRV-3D-DC: A Nonlinear Dimensionality Reduction Visualization Method for 3D Chromosome Structure Reconstruction with High Resolution Hi-C Data

NeRV-3D-DC: A Nonlinear Dimensionality Reduction Visualizati...

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2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Gong, Haiyan Yang, Yi Zhang, Xiaotong Ma, Fuqiang Li, Minghong Chen, Zhengyuan Zhang, Sichen Chen, Yang University of Science and Technology Beijing School of Computer and Communication Engineering Beijing Advanced Innovation Center for Materials Genome Engineering Beijing China Institute of Basic Medical Sciences School of Basic Medicine Chinese Academy of Medical Sciences Peking Union Medical College The State Key Laboratory of Medical Molecular Biology Department of Biochemistry and Molecular Biology Beijing100005 China University of Science and Technology Shunde Innovation School Foshan Beijing528399 China Electronic Information Industry Co. Ltd China

ISBN: (纸本)9781665468190

Chromosome structure plays an essential role in exploring the relationship between chromosome structure and gene transcription. In recent years, High-resolution Hi-C data allows us to explore the chromosome structures in 3D space. However, most of the existing chromosome structure reconstruction methods can not realize the 3D structure reconstruction at a high resolution (for example, 5 Kilobase (KB)). In this paper, we first proposed the NeRV-3D to reconstruct the 3D chromosome structure at a low resolution based on the nonlinear dimensionality reduction visualization algorithm. Then, we proposed the NeRV-3D-DC to reconstruct and visualize the 3D chromosome structure at a high resolution based on the divide-and-conquer method. Results show that NeRV-3D and NeRV-3DDC perform better than existing methods by comparing the 3D visualization effects and evaluation metrics on simulated and real Hi-C datasets. Implementation of NeRV-3D-DC is available on https://***/ghaiyan/NeRV-3D-DC © 2022 IEEE.

关键词： Visualization

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An advanced approach toward pedestrian safety analysis and prediction: Advances in Multi-Sensor Data Fusion and GIS Techniques

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IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2025年 18卷 15185-15197页

作者： Jie, Tang Khan, Asad Azam, Sheheryar Khalil, Umer Ejaz, Nuaman Afzal, Muhammad Said, Yahia Kucher, Dmitry E. Huzhou Vocational and Technical College School of Economic Management and E-commerce Zhejiang Huzhou 313000 China Guangzhou University Metaverse Research Institute School of Computer Science and Cyber Engineering Guangzhou 510006 China University of Greenwich School of Engineering Faculty of Engineering and Science London United Kingdom University of Twente ITC Faculty of Geo-Information Science and Earth Observation Enschede 7522 Netherlands Tsinghua University State Key Laboratory of Hydroscience and Engineering Department of Hydraulic Engineering Beijing 100084 China Chinese Academy of Sciences State Key Laboratory of Desert and Oasis Ecology Xinjiang Institute of Ecology and Geography Urumqi 830011 China Northern Border University Center for Scientific Research and Entrepreneurship Arar 73213 Saudi Arabia RUDN University Department of Environmental Management Institute of Environmental Engineering Moscow 117198 Russian Federation

A substantial component of a pedestrian safety assessment is classifying and ranking pedestrian collision regions. This research focuses on two pedestrian safety levels that initially identified the zones accumulating a high density of pedestrian crashes, followed by the zonal assessment based on the crash severity. The framework of this research focuses on identifying crash hotspots with three separate methods and comparing results that allow recommendations for further development of pedestrian safety measures in the future. The application of pedestrian crash zone ranking using three methods, namely Kernel Density Estimation (KDE), Kriging Interpolation (KI), and Hotspot Analysis (HA), has been described within the framework for this study using the city of London's central and western ends as the study area. The crash data was obtained from the hidden data handles provided by the Transport for London (TfL) data extraction tool from the website and filtered by severity, type, and coordinates of the incidents. The detailed data files included the past 5 years' data from 2016 to 2020;the 2021 data files are still being published. A semi-variogram showing the correlation of input data was developed, which determines the criteria for clustering for the KI and KDE methods. The results obtained by the KDE method visually represent the areas with the density of accidents based on address-match input only. This study is an experimental approach that can help policymakers form pedestrian safety policies. Moreover, future automation processes integrated with GIS can reduce subjectivity in identifying the hotspot zones from KI and KDE maps. © 2008-2012 IEEE.

关键词： Hotspot Analysis Kernel Density Estimation Kriging Interpolation London city Pedestrian crashes Transport for London

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Hashing Beam Training for Integrated Ground-Air-Space Wireless networks

arXiv

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arXiv 2024年

作者： Xu, Yuan Huang, Chongwen Wei, Li Yang, Zhaohui Al Hammadi, Ahmed Yang, Jun Zhang, Zhaoyang Yuen, Chau Debbah, Mérouane College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China The State Key Laboratory of Integrated Service Networks Xidian University Xi’an710071 China Hangzhou310027 China The College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China The School of Electrical and Electronics Engineering Nanyang Technological University Singapore639798 Singapore The Technology Innovation Institute 9639 Masdar City Abu Dhabi United Arab Emirates The State Key Laboratory of Mobile Network and Mobile Multimedia Technology Shenzhen518055 China Wireless Product R&D Institute ZTE Corporation Shenzhen518057 China Department of Electrical Engineering and Computer Science the KU 6G Center Khalifa University Abu Dhabi127788 United Arab Emirates

In integrated ground-air-space (IGAS) wireless networks, numerous services require sensing knowledge including location, angle, distance information, etc., which usually can be acquired during the beam training stage. On the other hand, IGAS networks employ large-scale antenna arrays to mitigate obstacle occlusion and path loss. However, large-scale arrays generate pencil-shaped beams, which necessitate a higher number of training beams to cover the desired space. These factors motivate our investigation into the IGAS beam training problem to achieve effective sensing services. To address the high complexity and low identification accuracy of existing beam training techniques, we propose an efficient hashing multi-arm beam (HMB) training scheme. Specifically, we first construct an IGAS single-beam training codebook for the uniform planar arrays. Then, the hash functions are chosen independently to construct the multi-arm beam training codebooks for each AP. All APs traverse the predefined multi-arm beam training codeword simultaneously and the multi-AP superimposed signals at the user are recorded. Finally, the soft decision and voting methods are applied to obtain the correctly aligned beams only based on the signal powers. In addition, we logically prove that the traversal complexity is at the logarithmic level. Simulation results show that our proposed IGAS HMB training method can achieve 96.4% identification accuracy of the exhaustive beam training method and greatly reduce the training overhead. Copyright © 2024, The Authors. All rights reserved.

关键词： Antenna grounds

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Thermalization and Criticality on an Analog-Digital Quantum Simulator

arXiv

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arXiv 2024年

作者： Andersen, T.I. Astrakhantsev, N. Karamlou, A.H. Berndtsson, J. Motruk, J. Szasz, A. Gross, J.A. Schuckert, A. Westerhout, T. Zhang, Y. Forati, E. Rossi, D. Kobrin, B. Di Paolo, A. Klots, A.R. Drozdov, I. Kurilovich, V. Petukhov, A. Ioffe, L.B. Elben, A. Rath, A. Vitale, V. Vermersch, B. Acharya, R. Aghababaie Beni, L. Anderson, K. Ansmann, M. Arute, F. Arya, K. Asfaw, A. Atalaya, J. Ballard, B. Bardin, J.C. Bengtsson, A. Bilmes, A. Bortoli, G. Bourassa, A. Bovaird, J. Brill, L. Broughton, M. Browne, D.A. Buchea, B. Buckley, B.B. Buell, D.A. Burger, T. Burkett, B. Bushnell, N. Cabrera, A. Campero, J. Chang, H.-S. Chen, Z. Chiaro, B. Claes, J. Cleland, A.Y. Cogan, J. Collins, R. Conner, P. Courtney, W. Crook, A.L. Das, S. Debroy, D.M. De Lorenzo, L. Del Toro Barba, A. Demura, S. Donohoe, P. Dunsworth, A. Earle, C. Eickbusch, A. Elbag, A.M. Elzouka, M. Erickson, C. Faoro, L. Fatemi, R. Ferreira, V.S. Flores Burgos, L. Fowler, A.G. Foxen, B. Ganjam, S. Gasca, R. Giang, W. Gidney, C. Gilboa, D. Giustina, M. Gosula, R. Grajales Dau, A. Graumann, D. Greene, A. Habegger, S. Hamilton, M.C. Hansen, M. Harrigan, M.P. Harrington, S.D. Heslin, S. Heu, P. Hill, G. Hoffmann, M.R. Huang, H.-Y. Huang, T. Huff, A. Huggins, W.J. Isakov, S.V. Jeffrey, E. Jiang, Z. Jones, C. Jordan, S. Joshi, C. Juhas, P. Kafri, D. Kang, H. Kechedzhi, K. Khaire, T. Khattar, T. Khezri, M. Kieferová, M. Kim, S. Kitaev, A. Klimov, P. Korotkov, A.N. Kostritsa, F. Kreikebaum, J.M. Landhuis, D. Langley, B.W. Laptev, P. Lau, K.-M. Le Guevel, L. Ledford, J. Lee, J. Lee, K.W. Lensky, Y.D. Lester, B.J. Li, W.Y. Lill, A.T. Liu, W. Livingston, W.P. Locharla, A. Lundahl, D. Lunt, A. Madhuk, S. Maloney, A. Mandrà, S. Martin, L.S. Martin, O. Martin, S. Maxfield, C. McClean, J.R. McEwen, M. Meeks, S. Miao, K.C. Mieszala, A. Molina, S. Montazeri, S. Morvan, A. Movassagh, R. Neill, C. Nersisyan, A. Newman, M. Nguyen, A. Nguyen, M. Ni, C.-H. Niu, M.Y. Oliver, W.D. Ottosson, K. Google Research Mountain ViewCA United States Department of Theoretical Physics University of Geneva Quai Ernest-Ansermet 24 Geneva1205 Switzerland Joint Quantum Institute Joint Center for Quantum Information and Computer Science NIST University of Maryland College ParkMD United States Institute of Molecules and Materials Radboud University Nijmegen Netherlands Department of Physics University of Connecticut StorrsCT United States Institute for Quantum Information and Matter Walter Burke Institute for Theoretical Physics Caltech PasadenaCA United States Université Grenoble Alpes CNRS LPMMC Grenoble France Department of Electrical and Computer Engineering University of Massachusetts AmherstMA United States Department of Electrical and Computer Engineering Auburn University AuburnAL United States QSI Faculty of Engineering & Information Technology University of Technology Sydney NSW Australia Department of Electrical and Computer Engineering University of California RiversideCA United States Department of Chemistry and Chemical Biology Harvard University MA United States Laboratory for Theoretical and Computational Physics Paul Scherrer Institute Villigen5232 Switzerland LausanneCH-1015 Switzerland Department of Physics Princeton University PrincetonNJ United States

Understanding how interacting particles approach thermal equilibrium is a major challenge of quantum simulators1,2. Unlocking the full potential of such systems toward this goal requires flexible initial state preparation, precise time evolution, and extensive probes for final state characterization. We present a quantum simulator comprising 69 superconducting qubits which supports both universal quantum gates and high-fidelity analog evolution, with performance beyond the reach of classical simulation in cross-entropy benchmarking experiments. Emulating a two-dimensional (2D) XY quantum magnet, we leverage a wide range of measurement techniques to study quantum states after ramps from an antiferromagnetic initial state. We observe signatures of the classical Kosterlitz-Thouless phase transition3, as well as strong deviations from Kibble-Zurek scaling predictions4 attributed to the interplay between quantum and classical coarsening of the correlated domains5. This interpretation is corroborated by injecting variable energy density into the initial state, which enables studying the effects of the eigenstate thermalization hypothesis (ETH)6-8 in targeted parts of the eigenspectrum. Finally, we digitally prepare the system in pairwise-entangled dimer states and image the transport of energy and vorticity during thermalization. These results establish the efficacy of superconducting analog-digital quantum processors for preparing states across many-body spectra and unveiling their thermalization dynamics. © 2024, CC BY.

关键词： Quantum computers

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Retinal Vascular Segmentation network with Connectivity Guidance

Retinal Vascular Segmentation Network with Connectivity Guid...

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Smart World Congress (SWC), IEEE

作者： Ronghua Wu Chen Tao Hongyu Chen Wenjing Xu Xiao Yan HongZhe Liu XiuMing Zhang Muwei Jian School of Information Science and Engineering Linyi University Linyi China Department of Haematology Ningbo Clinical Research Center for Hematologic Malignancies The First Affiliated Hospital of Ningbo University Ningybo China Beijing Key Laboratory of Information Service Engineering Beijing Union University Beijing China Department of Pathology The First Affiliated Hospital of Zhejiang University College of Medicine Hangzhou China School of Computer Science and Technology Shandong University of Finance and Economics Jinan China

The morphology of the retinal vasculature is closely related to a variety of ophthalmic diseases. Despite significant progresses have been achieved in retinal vessel segmentation with the development of deep learning, several challenging problems still persist. Specifically, some components present in the retina (such as optic discs or lesions) may interfere with or cover the vessels, and current segmentation models rarely focus on the connectivity of the vessels. In this paper, we propose an efficient network to conquer this issue. Firstly, we propose a semantic enhancement module, to insert into the bottom layer of the UNet encoder section for guiding the network to enhance features representation. Secondly, we introduce a skeleton fitting module that maximizes the preservation of the vascular topology using skeleton prior and contrast loss. Finally, we perform a morphological complementation operation on the final output of the decoder by means of a voting mechanism. The designed segmentation network has been evaluated on publicly available datasets and experimental results demonstrate the effectiveness of the method.

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Condition Generative Adversarial network Deep Learning Model for Accurate Segmentation and Volumetric Measurement to Detect Mucormycosis from Lung CT Images

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Open Public Health Journal 2024年 17卷

作者： Chakrapani, Kannan Safa, M. Gururaj, H.L. Ravi, Vinayakumar Ravi, Pradeep Department of Information Technology School of Computing SASTRA Deemed University Tamil Nadu Thanjavur 613401 India Department of Networking and Communications School of Computing College of Engineering and Technology SRM Institute of Science and Technology Kattankulathur Chennai India Department of Information Technology Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Manipal India Center for Artificial Intelligence Prince Mohammad Bin Fahd University Khobar 34754 Saudi Arabia Department of Computer Science and Engineering GSSS Institute of Engineering and Technology for Women Karnataka Mysuru India

Introduction: Mucormycosis (black fungal attack) has recently been identified as a significant threat, specifically to patients who have recovered from coronavirus infection. This fungus enters the body through the nose and first infects the lungs but can affect other body parts, such as the eye and brain, resulting in vision loss and death. Early detection through lung CT scans is crucial for reliable treatment planning and management. Methods: To combat the above problems, this paper introduces a Condition Generative Adversarial network Deep Learning Model (CGAN-DLM) to facilitate the automatic lung CT image segmentation process, contributing to accurately identifying Mucormycosis earlier. This deep learning model employed different pre-processing strategies over raw lung CT images for extracting its ground truth values based on potential morphological operations. It adopted CGAN to segment the region of interest used for diagnosing mucormycosis with the pre-processed images and their related truth values. Results: It also included a volumetric assessment approach that significantly identified the change in lung nodule size before and after the infection of mucormycosis. Conclusion: The extensive experiments of the proposed CGAN-DLM conducted using lung CT images taken from the LIDC-IDRI database confirmed sensitivity of 98.42%, specificity of 98.86% and dice coefficient index of 97.31%, on par with the benchmarked lung CT images-based Mucormycosis detection approaches. © 2024 The Author(s). Published by Bentham Open.

关键词： Condition generative adversarial network (CGAN) Dice coeficient index Lung CT images Lung nodule volumetric assessment Mucormycosis (black fungal attack) Potential morphological operations

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Deep Learning with Greedy Layer-Wise Compound Scaling for Temperature and Humidity Prediction in Solar Dryer Dome

SSRN

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SSRN 2022年

作者： Cenggoro, Tjeng Wawan Elwirehardja, Gregorius Natanael Dominic, Nicholas Setiawan, Karli Eka Rahutomo, Reza Djuana, Endang Gunawan, Fergyanto E. Budiman, Arief S. Romeli, Sugiarto Pardamean, Bens Computer Science Department School of Computer Science Bina Nusantara University Jakarta11480 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Electrical Engineering Department Faculty of Industrial Technology Universitas Trisakti Jakarta11440 Indonesia Industrial Engineering Department BINUS Graduate Program Master of Industrial Engineering Bina Nusantara University Jakarta11480 Indonesia Department of Manufacturing and Mechanical Engineering and Technology Oregon Institute of Technology Klamath FallsOR97601 United States PT. Impack Pratama Industri Jakarta Indonesia

Drying has been an eco-friendly and cost-efficient method to reduce post-harvest losses of agricultural crops. In various countries, the technique has been widely utilized in the form of Solar Dryer Dome (SDD) buildings. Accurate indoor microclimate forecasting is very important to implement smart control systems in SDDs that can maintain the ideal conditions, as the availability of solar energy is limited only at daytimes and the temperature may drop significantly during nighttimes in remote areas. The microclimate variables that play an important role in maintaining ideal environmental conditions include temperature and relative humidity. © 2022, The Authors. All rights reserved.

关键词： Forecasting

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Variational Bayes Inference for Data Detection in Cell-Free Massive MIMO

Variational Bayes Inference for Data Detection in Cell-Free ...

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Asilomar Conference on Signals, Systems & computers

作者： Ly V. Nguyen Hien Quoc Ngo Le-Nam Tran A. Lee Swindlehurst Duy H. N. Nguyen Computational Science Research Center San Diego State University CA USA Institute of Electronics Communications and Information Technology (ECIT) Queen's University Belfast UK School of Electrical and Electronic Engineering University College Dublin Ireland Department of Electrical Engineering and Computer Science University of California Irvine CA USA Department of Electrical and Computer Engineering San Diego State University CA USA

Cell-free massive MIMO is a promising technology for beyond-5G networks. Through the deployment of many cooperating access points (AP), the technology can significantly enhance user coverage and spectral efficiency compared to traditional cellular systems. Since the APs are distributed over a large area, the level of favorable propagation in cell-free massive MIMO is less than the one in colocated massive MIMO. As a result, the current linear processing schemes are not close to the optimal ones when the number of AP antennas is not very large. The aim of this paper is to develop nonlinear variational Bayes (VB) methods for data detection in cell-free massive MIMO systems. Contrary to existing work in the literature, which only attained point estimates of the transmit data symbols, the proposed methods aim to obtain the posterior distribution and the Bayes estimate of the data symbols. We develop the VB methods accordingly to the levels of cooperation among the APs. Simulation results show significant performance advantages of the developed VB methods over the linear processing techniques.

关键词： computers Spectral efficiency Simulation Symbols Channel estimation Massive MIMO Signal processing

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