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4th International Conference on IoT and Big Data Technologies for Health Care, IotCare 2023

作者： Chen, Shuwen Wang, Jiaji Zhu, Huisheng School of Physics and Information Engineering Jiangsu Second Normal University Jiangsu Nanjing210016 China State Key Laboratory of Millimeter Waves Southeast University Nanjing210096 China School of Computing and Mathematical Sciences University of Leicester LeicesterLE1 7RH United Kingdom

ISBN: (纸本)9783031900839

Efficient and accurate COVID-19 detection methods are paramount in the ongoing battle against the global pandemic. In this study, we present a novel approach that leverages the Tabu Search Particle Swarm Optimization (TS-PSO) algorithm for COVID-19 detection. Unlike conventional methods, our approach combines the strengths of both global and local search strategies, enhancing the accuracy of diagnosis. We conducted extensive experiments, benchmarking our TS-PSO-based approach against established methods. The results reveal that our TS-PSO method achieves competitive performance, with improvements in sensitivity, specificity, precision, accuracy, F1 score, MCC, and FMI. This innovative approach not only advances the field of COVID-19 detection but also demonstrates its potential as a valuable tool for healthcare professionals in the ongoing fight against the pandemic. © ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering 2025.

关键词： Tabu search

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RobNODDI: Robust NODDI Parameter Estimation with Adaptive Sampling Under Continuous Representation 15th

RobNODDI: Robust NODDI Parameter Estimation with Adaptive S...

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15th International Workshop on Computational Diffusion MRI, CDMRI 2024, held in conjunction with 27th International Conference on Medical Image computing and Computer-Assisted Intervention, MICCAI 2024

作者： Xiao, Taohui Cheng, Jian Fan, Wenxin Yang, Jing Li, Cheng Dong, Enqing Wang, Shanshan School of Mechanical Electrical and Information Engineering Shandong University Weihai264209 China State Key Laboratory of Software Development Environment Beihang University Beijing China Key Laboratory of Data Science and Intelligent Computing Institute of International Innovation Beihang University Zhejiang Hangzhou China Paul C. Lauterbur Research Center for Biomedical Imaging Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China Peng Cheng Laboratory Guangdong Shenzhen China

ISBN: (纸本)9783031869198

Neurite Orientation Dispersion and Density Imaging (NODDI) is an important imaging technology used to evaluate the microstructure of brain tissue, which is of great significance for the discovery and treatment of various neurological diseases. Current deep learning-based methods perform parameter estimation through diffusion magnetic resonance imaging (dMRI) with a small number of diffusion gradients. These methods speed up parameter estimation and improve accuracy. However, the diffusion directions used by most existing deep learning models during testing needs to be strictly consistent with the diffusion directions during training. This results in poor generalization and robustness of deep learning models in dMRI parameter estimation. In this work, we first verify that the parameter estimation performance of current mainstream methods will significantly decrease when the testing diffusion directions and the training diffusion directions are inconsistent. A robust NODDI parameter estimation method with adaptive sampling under continuous representation (RobNODDI) is proposed. Furthermore, long short-term memory (LSTM) units and fully connected layers are selected to learn continuous representation signals. To this end, we use a total of 100 subjects to conduct experiments based on the Human Connectome Project (HCP) dataset, of which 60 are used for training, 20 are used for validation, and 20 are used for testing. The test results indicate that RobNODDI improves the generalization performance and robustness of the deep learning model, enhancing the stability and flexibility of deep learning NODDI parameter estimatimation applications. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Deep learning

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A Further Understanding of Differential-Linear Cryptanalysis

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Chinese Journal of Electronics 2020年第4期29卷 660-666页

作者： REN Jiongjiong CHEN Shaozhen State Key Laboratory of Mathematical Engineering and Advanced Computing State Key Laboratory of Cryptology

Differential-linear cryptanalysis has attracted much attention since proposed to attack DES in 1994, and then some generalized theories are developed to complement and unify the ***, the links between differential-linear cryptanalysis and other important cryptanalysis methods have been still *** motivation is to fix the *** establishing some boolean equations, we propose the mathematical links among differential, linear and differential-linear *** then generalise the definition of capacity and present some properties of the capacity of differential *** links and properties are employed to explore the relationships between multidimensional differential-linear hulls and integral *** show that a multidimensional differential-linear hull of certain correlation always implies the existence of an integral distinguisher and a zero-correlation linear hull, while a special integral distinguisher indicates the existence of a multidimensional differential-linear hull.

关键词： Block cipher Differential cryptanalysis Linear cryptanalysis Differential-linear cryptanalysis Integral distinguisher Zero-correlation

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Implementation of Positive Operator-Valued Measure in Passive Faraday Mirror Attack

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Communications in Theoretical Physics 2015年第3期63卷 296-302页

作者：王卫龙高明马智 State Key Laboratory of Mathematical Engineering and Advanced Computing

Passive Faraday-mirror(PFM) attack is based on imperfect Faraday mirrors in practical quantum cryptography systems and a set of three-dimensional Positive Operator-Valued Measure(POVM) operators plays an important role in this *** this paper,we propose a simple scheme to implement the POVM in PFM attack on an FaradayMichelson quantum cryptography *** the POVM can not be implemented directly with previous methods,in this scheme it needs to expand the states sent by Alice and the POVM operators in the attack into four-dimensional Hilbert space first,without changing the attacking effect by *** on the methods proposed by Ahnert and Payne,the linear-optical setup for implementing the POVM operators is *** last,the complete setup for realizing the PFM attack is presented with all ***,our scheme can also be applied to realize PFM attack on a plug-and-play system by changing the parameters in the setup.

关键词： Faraday mirrors passive Faraday mirror attack POVM linear optics

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Super-Resolution of Diffusion-Weighted Images via TDI-Conditioned Diffusion Model 15th

Super-Resolution of Diffusion-Weighted Images via TDI-Cond...

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作者： Ma, Jiquan Teng, Yujun Chen, Geng Jiang, Haotian Zhang, Kai Liu, Feihong Rekik, Islem Shen, Dinggang School of Computer Science and Technology Heilongjiang University Harbin China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology School of Computer Science and Engineering Northwestern Polytechnical University Xi’an China School of Biomedical Engineering and State Key Laboratory of Advanced Medical Materials and Devices ShanghaiTech University Shanghai China School of Information Science and Technology Northwest University Xi’an China BASIRA Lab Imperial-X and Department of Computing Imperial College London London United Kingdom

ISBN: (纸本)9783031869198

Diffusion-Weighted Imaging (DWI) is a significant technique for studying white matter. However, it suffers from low-resolution obstacles in clinical settings. Post-acquisition Super-Resolution (SR) can enhance the resolution of DWIs and has gained increasing research interest in recent years. An advanced generative model, the Diffusion Model (DM), exhibits particularly promising performance in image SR. However, effective conditions are required to bootstrap the DM for DWI SR. To this end, we proposed the first DM-based DWI SR model with two effective conditions based on low-solution DWIs and Track Density Imaging (TDI) maps, which possess rich high-resolution prior knowledge Additionally, we consider another condition based on features from low-resolution DWIs. These two conditions are integrated into our model, which comprises three components: DWI Resolution Enhancer (DRE), DWI Feature Extractor (DFE), and TDI Feature Extractor (TFE). DRE combines low-resolution DWI features from DFE with TDI features from TFE to progressively generate high-resolution DWIs. We performed extensive experiments on DWIs of normal subjects from human connectome projects and patients with Parkinson’s disease. The results demonstrate that our model outperforms existing DWI SR models, both qualitatively and quantitatively. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Neurodegenerative diseases

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Low-power technologies in high-performance computer: trends and perspectives

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National Science Review 2016年第1期3卷 23-25页

作者： Xianghui Xie State Key Laboratory of Mathematical Engineering and Advanced Computing

INTRODUCTION With the breakdown of Dennard’s scaling rule,chip power for a given area size is not constant as transistors shrink from generation to generation[1].In particular,the power wall problem worsens with the ... 详细信息

关键词： HPC high trends and perspectives Low-power technologies in high-performance computer GPU CPU

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Solid-state stepwise temperature-programmable synthesis of bioinspired Fe-N-C oxygen reduction electrocatalyst featuring Fe-N_(5)configuration

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Nano Research 2025年第3期18卷 654-665页

作者： Wei Sang Somboon Chaemchuen Longyang Zhang Zechen Wang Xingchuan Li Cocoro Andrew Nagasaka Mo Xiong Naoki Ogiwara Cheng Chen Zhao Wang Jian Zhang Francis Verpoort Shichun Mu Zongkui Kou Tingting Wang State Key Laboratory of Advanced Technology for Materials Synthesis and Processing Wuhan University of TechnologyWuhan 430070China Department of Basic Science School of Arts and SciencesThe University of TokyoKomabaMeguro-kuTokyo 153-8902Japan MOE Key Laboratory for Non-Equilibrium Synthesis and Modulation of Condensed Matter School of PhysicsXi’an Jiao tong UniversityXi’an 710049China Sanya Science and Education Innovation Park of Wuhan University of Technology Sanya 572000China Department of Chemical Engineering Faculty of EngineeringMahidol UniversityNakhon Pathom 73170Thailand School of Mathematical&Physical Sciences Wuhan Textile UniversityWuhan 430200China Joint Institute of Chemical Research(FFMiEN) Peoples Friendship University of Russia(RUDN University)6 Miklukho-Maklaya Str.117198 MoscowRussia National Research Tomsk Polytechnic University Lenin Avenue 30634050 TomskRussia Hubei Key Laboratory of Ferro &Piezo-electric Materials and DevicesFaculty of Physics and Electronic SciencesHubei UniversityWuhan 430062China School of Chemistry and Chemical Engineering Hainan UniversityHaikou 57022China

The bioinspired Fe-N-C features an asymmetric Fe-N_(5)configuration to produce active metal-oxygen intermediates by introducing axial N ligand into a symmetric Fe-N_(4) structure,enabling highly active oxygen reduction reaction(ORR).However,the artificial creation of active Fe-N_(5)configuration with a direct,facile and green method has been rarely developed yet,as current techniques involve complex processes and costly ***,we advance a novel solid-state stepwise temperature-programmable(SST)route to directly produce bioinspired Fe-N_(5)-*** then demonstrate that such a Fe-N_(5)-C exhibits a quite higher half-wave potential(0.92 V)with 22-fold faster ORR kinetics(15.6 mA·cm^(−2)@0.85 V)over that of the commercial Pt/C ***,we perform density functional theory(DFT)to find that the Fe is discharged with an extra 0.1 e^(−)through the axially coordinate N ligand,which significantly enhances the ability to activate O_(2) and enables an easier desorption of the crucial intermediate ^(*)OH on the Fe-N_(5)configuration over the conventional Fe-N_(4) structure.

关键词： single atom catalysts Fe-N_(5)coordination solvent-free synthesis oxygen reduction reaction(ORR) metal-air battery

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Extracting embedded messages using adaptive steganography based on optimal syndrome-trellis decoding paths

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Digital Communications and Networks 2022年第4期8卷 455-465页

作者： Jialin Li Xiangyang Luo Yi Zhang Pei Zhang Chunfang Yang Fenlin Liu State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450000China

Privacy protection is the key to maintaining the Internet of Things(IoT)communication *** is an important way to achieve covert communication that protects user data *** technology is the key to checking steganography security,and its ultimate goal is to extract embedded *** methods cannot extract under known cover *** this end,this paper proposes a method of extracting embedded messages under known cover ***,the syndrome-trellis encoding process is ***,a decoding path in the syndrome trellis is obtained by using the stego sequence and a certain parity-check matrix,while the embedding process is simulated using the cover sequence and parity-check *** the decoding path obtained by the stego sequence and the correct parity-check matrix is optimal and has the least distortion,comparing the path consistency can quickly filter the coding parameters to determine the correct matrices,and embedded messages can be extracted *** proposed method does not need to embed all possible messages for the second time,improving coding parameter recognition *** experimental results show that the proposed method can identify syndrome-trellis coding parameters in stego images embedded by adaptive steganography quickly to realize embedded message extraction.

关键词： Information security Image steganography STC coding Parameter recognition

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Cooperative computing Techniques for a Deeply Fused and Heterogeneous Many-Core Processor Architecture

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Journal of Computer Science & Technology 2015年第1期30卷 145-162页

作者：郑方李宏亮吕晖过锋许晓红谢向辉 State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214125 China

Due to advances in semiconductor techniques, many-core processors have been widely used in high performance computing. However, many applications still cannot be carried out efficiently due to the memory wall, which has become a bottleneck in many-core processors. In this paper, we present a novel heterogeneous many-core processor architecture named deeply fused many-core （DFMC） for high performance computing systems. DFMC integrates management processing ele- ments （MPEs） and computing processing elements （CPEs）, which are heterogeneous processor cores for different application features with a unified ISA （instruction set architecture）, a unified execution model, and share-memory that supports cache coherence. The DFMC processor can alleviate the memory wall problem by combining a series of cooperative computing techniques of CPEs, such as multi-pattern data stream transfer, efficient register-level communication mechanism, and fast hardware synchronization technique. These techniques are able to improve on-chip data reuse and optimize memory access performance. This paper illustrates an implementation of a full system prototype based on FPGA with four MPEs and 256 CPEs. Our experimental results show that the effect of the cooperative computing techniques of CPEs is significant, with DGEMM （double-precision matrix multiplication） achieving an efficiency of 94%, FFT （fast Fourier transform） obtaining a performance of 207 GFLOPS and FDTD （finite-difference time-domain） obtaining a performance of 27 GFLOPS.

关键词： heterogeneous many-core processor data stream transfer register-level communication mechanism hardwaresynchronization technique processor prototype

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Angle-resolved magneto-chiral anisotropy in a non-centrosymmetric atomic layer superlattice

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Science Bulletin 2025年第9期70卷 1406-1409页

作者： Cheng, Long Bao, Mingrui Zhang, Xue Zhang, Jingxian Yang, Qun Li, Qiang Cao, Hui Qiu, Dawei Li, Hui Cheng, Guanglei Zhou, Hua Zuo, Jian-Min Zhou, Xiaodong Shen, Jian Zhu, Zhifeng Wang, Wenbo Zhai, Xiaofang School of Physical Science and Technology ShanghaiTech University Shanghai201210 China CAS Key Laboratory of Microscale Magnetic Resonance and School of Physical Sciences University of Science and Technology of China Hefei230026 China School of Information Science and Technology ShanghaiTech University Shanghai201210 China State Key Laboratory of Surface Physics and Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai200433 China X-ray Science Division Advanced Photon Source Argonne National Laboratory LemontIL60439 United States Institutes of Physical Science and Information Technology Anhui University Hefei230601 China Department of Materials Science and Engineering and Materials Research Laboratory University of Illinois Urbana–Champaign UrbanaIL61801 United States ShanghaiTech Laboratory for Topological Physics ShanghaiTech University Shanghai201210 China

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