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Federated Machine Learning Based Fetal Health Prediction Empowered with Bio-Signal Cardiotocography

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Computers, Materials & Continua 2024年第3期78卷 3303-3321页

作者： Muhammad Umar Nasir Omar Kassem Khalil Karamath Ateeq Bassam SaleemAllah Almogadwy Muhammad Adnan Khan Muhammad Hasnain Azam Khan Muhammad Adnan Department of Computer Sciences Bahria University Lahore CampusLahore54000Pakistan Faculty of information Technology Liwa CollegeAbu Dhabi00000United Arab Emirates Department of computing Skyline University CollegeSharjah1797United Arab Emirates Department of Computer Science Taibah UniversityMedina42353Saudi Arabia Riphah School of computing and innovation Faculty of ComputingRiphah International UniversityLahore CampusLahore54000Pakistan Department of Engineering and Development Dubizzle LabsLahore54000Pakistan Department of Software Faculty of Artificial Intelligence and SoftwareGachon UniversitySeongnam-si13120Korea

Cardiotocography measures the fetal heart rate in the fetus during pregnancy to ensure physical health because cardiotocography gives data about fetal heart rate and uterine shrinkages which is very beneficial to detect whether the fetus is normal or suspect or *** cardiotocography measures infer wrongly and give wrong predictions because of human *** traditional way of reading the cardiotocography measures is the time taken and belongs to numerous human errors as *** condition is very important to measure at numerous stages and give proper medications to the fetus for its *** the current period Machine learning(ML)is a well-known classification strategy used in the biomedical field on various issues because ML is very fast and gives appropriate results that are better than traditional *** techniques play a pivotal role in detecting fetal disease in its early *** research article uses Federated machine learning(FML)and ML techniques to classify the condition of the *** study proposed a model for the detection of bio-signal cardiotocography that uses FML and ML techniques to train and test the ***,the proposed model of FML used numerous data preprocessing techniques to overcome data deficiency and achieves 99.06%and 0.94%of prediction accuracy and misprediction rate,respectively,and parallel the proposed model applying K-nearest neighbor(KNN)and achieves 82.93%and 17.07%of prediction accuracy and misprediction accuracy,***,by comparing both models FML outperformed the KNN technique and achieved the best and most appropriate prediction results as compared with previous studies the proposed study achieves the best and most accurate results.

关键词： Cardiotocography ML FML fetal disease bio-signal

A Survey on the Evolution of Bootkits Attack and Defense Techniques

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China Communications 2024年第1期21卷 102-130页

作者： Yilin Zhou Guojun Peng Zichuan Li Side Liu Key Laboratory of Aerospace information Security and Trust computing Ministry of EducationWuhan 430072China School of Cyber Science and Engineering Wuhan UniversityWuhan 430072China

According to the boot process of modern computer systems,whoever boots first will gain control *** advantage of this feature,a malicious code called bootkit can hijack the control before the OS bootloader and bypass security mechanisms in boot *** makes bootkits difficult to detect or clean up *** the improvement of security mechanisms and the emergence of UEFi,the attack and defense techniques for bootkits have constantly been *** first introduce two boot modes of modern computer systems and present an attack model of bootkits by some sophistical *** we discuss some classic attack techniques used by bootkits from their initial appearance to the present on two axes,including boot mode axis and attack phase ***,we evaluate the race to the bottom of the system and the evolution process between bootkits and security *** last,we present the possible future direction for bootkits in the context of continuous improvement of OS and firmware security mechanisms.

关键词： bootkit hook legacy BiOS security mechanisms UEFi

Adaptive joint configuration optimization for collaborative inference in edge-cloud systems

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Science China(information Sciences) 2024年第4期67卷 335-336页

作者： Zheming YANG Wen Ji Zhi WANG institute of computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Peng Cheng Laboratory Tsinghua Shenzhen international Graduate School Tsinghua University

With the rapid development of technologies such as deep learning and the internet of Things(ioT), the deployment and application of various ioT devices are becoming increasingly widespread, resulting in the inference tasks generated increasing dramatically [1]. Many deep neural network(DNN) models are deployed on servers for performing inference tasks.

关键词： inference engines

Modelling dynamic pantograph loads with combined numerical analysis

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Railway Engineering Science 2024年第1期32卷 81-94页

作者： F.F.Jackson R.Mishra J.M.Rebelo J.Santos P.Antunes J.Pombo H.Magalhaes L.Wills M.Askill School of computing and Engineering University of HuddersfieldHuddersfieldUK School of computing and Engineering Institute of Railway ResearchUniversity of HuddersfieldHuddersfieldUK iDMEC Instituto Superior TecnicoUniversidade de LisboaLisbonPortugal iSEL Instituto Politecnico de LisboaLisbonPortugal Hitachi Rail Newton AycliffeUK Wabtec/Brecknell Willis ChardUK

Appropriate interaction between pantograph and catenary is imperative for smooth operation of electric *** heights of overhead lines to accommodate level crossings,overbridges,and tunnels pose significant challenges in maintaining consistent current collection performance as the pantograph aerodynamic profile,and thus aerodynamic load changes significantly with operational *** research aims to analyse the global flow characteristics and aerodynamic forces acting on individual components of an HSX pantograph operating in different configurations and orientations,such that the results can be combined with multibody simulations to obtain accurate dynamic insight into contact ***,computational fluid dynamics simulations are used to investigate the pantograph component loads in a representative setting,such as that of the recessed cavity on a Class 800 *** an aerodynamic perspective,this study indicates that the total drag force acting on non-fixed components of the pantograph is larger for the knuckle-leading orientation rather than the knuckle-trailing,although the difference between the two is found to reduce with increasing pantograph *** the aerodynamic loads acting on individual components with multibody tools allows for realistic dynamic insight into the pantograph *** results obtained show how considering aerodynamic forces enhance the realism of the models,leading to behaviour of the pantograph-catenary contact forces closely matching that seen in experimental tests.

关键词： Pantograph-catenary interaction Pantograph aerodynamics Computational fluid dynamics Pantograph loads Current collection performance

Decoupled deep hough voting for point cloud registration

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Frontiers of Computer Science 2024年第2期18卷 147-155页

作者： Mingzhi YUAN Kexue FU Zhihao Li Manning WANG Digital Medical Research Center School of Basic Medical SciencesFudan UniversityShanghai 200032China Shanghai Key Laboratory of Medical image computing and Computer Assisted intervention Shanghai 200032China

Estimating rigid transformation using noisy correspondences is critical to feature-based point cloud ***,a series of studies have attempted to combine traditional robust model fitting with deep *** them,DHVR proposed a hough voting-based method,achieving new state-of-the-art ***,we find voting on rotation and translation simultaneously hinders achieving better ***,we proposed a new hough voting-based method,which decouples rotation and translation ***,we first utilize hough voting and a neural network to estimate *** based on good initialization on rotation,we can easily obtain accurate rigid *** experiments on 3DMatch and 3DLoMatch datasets show that our method achieves comparable performances over the state-of-the-art *** further demonstrate the generalization of our method by experimenting on KiTTi dataset.

关键词： point cloud registration robust model fitting deep learning hough voting

Towards High-Performance Graph Processing: From a Hardware/Software Co-Design Perspective

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Journal of Computer Science & Technology 2024年第2期39卷 245-266页

作者：廖小飞赵文举金海姚鹏程黄禹王庆刚赵进郑龙张宇邵志远 National Engineering Research Center for Big Data Technology and System School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Services computing Technology and System Laboratory School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Cluster and Grid computing Laboratory School of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Zhejiang Lab Hangzhou 311121China

Graph processing has been widely used in many scenarios,from scientific computing to artificial *** processing exhibits irregular computational parallelism and random memory accesses,unlike traditional ***,running graph processing workloads on conventional architectures(e.g.,CPUs and GPUs)often shows a significantly low compute-memory ratio with few performance benefits,which can be,in many cases,even slower than a specialized single-thread graph *** domain-specific hardware designs are essential for graph processing,it is still challenging to transform the hardware capability to performance boost without coupled software *** article presents a graph processing ecosystem from hardware to *** start by introducing a series of hardware accelerators as the foundation of this ***,the codesigned parallel graph systems and their distributed techniques are presented to support graph ***,we introduce our efforts on novel graph applications and hardware *** results show that various graph applications can be efficiently accelerated in this graph processing ecosystem.

关键词： graph processing hardware accelerator software system high performance ecosystem

Adaptive and augmented active anomaly detection on dynamic network traffic streams

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Frontiers of information Technology & Electronic Engineering 2024年第3期25卷 446-460页

作者： Bin Li Yijie WANG Li CHENG National Key Laboratory of Parallel and Distributed computing College of ComputerNational University of Defense TechnologyChangsha 410073China College of System Engineering National University of Defense TechnologyChangsha 410073China

Active anomaly detection queries labels of sampled instances and uses them to incrementally update the detection model,and has been widely adopted in detecting network ***,existing methods cannot achieve desirable performance on dynamic network traffic streams because(1)their query strategies cannot sample informative instances to make the detection model adapt to the evolving stream and(2)their model updating relies on limited query instances only and fails to leverage the enormous unlabeled instances on *** address these issues,we propose an active tree based model,adaptive and augmented active prior-knowledge forest(A3PF),for anomaly detection on network trafic streams.A prior-knowledge forest is constructed using prior knowledge of network attacks to find feature subspaces that better distinguish network anomalies from normal *** one hand,to make the model adapt to the evolving stream,a novel adaptive query strategy is designed to sample informative instances from two aspects:the changes in dynamic data distribution and the uncertainty of *** the other hand,based on the similarity of instances in the neighborhood,we devise an augmented update method to generate pseudo labels for the unlabeled neighbors of query instances,which enables usage of the enormous unlabeled instances during model *** experiments on two benchmarks,CiC-iDS2017 and UNSW-NB15,demonstrate that A3PF achieves significant improvements over previous active methods in terms of the area under the receiver operating characteristic curve(AUC-ROC)(20.9%and 21.5%)and the area under the precision-recall curve(AUC-PR)(44.6%and 64.1%).

关键词： Active anomaly detection Network traffic streams Pseudo labels Prior knowledge of network attacks

Transformer and GAN-Based Super-Resolution Reconstruction Network for Medical images

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Tsinghua Science and Technology 2024年第1期29卷 197-206页

作者： Weizhi Du Shihao Tian Arts&Sciences College Washington University in St.LouisSt.LouisMO 63130USA Department of Electric and computing Engineering Cornell UniversityIthacaNY 14850USA

Super-resolution reconstruction in medical imaging has become more demanding due to the necessity of obtaining high-quality images with minimal radiation dose,such as in low-field magnetic resonance imaging(MRi).However,image super-resolution reconstruction remains a difficult task because of the complexity and high textual requirements for diagnosis *** this paper,we offer a deep learning based strategy for reconstructing medical images from low resolutions utilizing Transformer and generative adversarial networks(T-GANs).The integrated system can extract more precise texture information and focus more on important locations through global image matching after successfully inserting Transformer into the generative adversarial network for picture ***,we weighted the combination of content loss,adversarial loss,and adversarial feature loss as the final multi-task loss function during the training of our proposed model *** comparison to established measures like peak signal-to-noise ratio(PSNR)and structural similarity index measure(SSiM),our suggested T-GAN achieves optimal performance and recovers more texture features in super-resolution reconstruction of MRi scanned images of the knees and belly.

关键词： super-resolution image reconstruction Transformer generative adversarial network(GAN)

Nanophononic metamaterials induced proximity effect in heat flux regulation

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Frontiers of physics 2024年第2期19卷 149-156页

作者： Jian Zhang Haochun Zhang Gang Zhang School of Energy Science and Engineering Harbin Institute of TechnologyHarbin 150001China institute of High Performance computing Agency for ScienceTechnology and Research(A*STAR)Singapore 138632Singapore

Recent studies have shown that the construction of nanophononic metamaterials can reduce thermal conductivity without affecting electrical properties,making them promising in many fields of application,such as energy conversion and thermal ***,although extensive studies have been carried out on thermal conductivity reduction in nanophononic metamaterials,the local heat flux characteristic is still *** this work,we construct a heat flux regulator which includes a silicon nanofilm with silicon *** regulator has remarkable heat flux regulation ability,and various impacts on the regulation ability are ***,even in the region without nanopillars,the local heat current is still lower than that in pristine silicon nanofilms,reduced by the neighboring nanopillars through the thermal proximity *** combine the analysis of the phonon participation ratio with the intensity of localized phonon modes to provide a clear *** findings not only provide insights into the mechanisms of heat flux regulation by nanophononic metamaterials,but also will open up new research directions to control local heat flux for a broad range of applications,including heat management,thermoelectric energy conversion,thermal cloak,and thermal concentrator.

关键词： nanophononic metamaterials proximity effect