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A Novel Eccentric Intrusion Detection Model Based on Recurrent Neural Networks with Leveraging LSTM

Computers, Materials & Continua 2024年第3期78卷 3089-3127页

作者： Navaneetha Krishnan Muthunambu Senthil Prabakaran Balasubramanian Prabhu Kavin Kishore Senthil Siruvangur Kavitha Chinnadurai Jehad Ali department of Computer Applications Karpagam College of EngineeringCoimbatore641032India department of Computer Science and engineering Karpagam College of EngineeringCoimbatore641032India department of Data Science and Business systems College of Engineering and TechnologySRM Institute of Science and TechnologyKattankulathur603203India department of Computer Science and engineering Sathyabama Institute of Science and TechnologyJeppiaar NagarRajiv Gandhi SalaiChennai600119India department of AI Convergence Network Ajou UniversitySuwon16499Korea

The extensive utilization of the Internet in everyday life can be attributed to the substantial accessibility of online services and the growing significance of the data transmitted via the ***,this development has expanded the potential targets that hackers might *** adequate safeguards,data transmitted on the internet is significantly more susceptible to unauthorized access,theft,or *** identification of unauthorised access attempts is a critical component of cybersecurity as it aids in the detection and prevention of malicious *** research paper introduces a novel intrusion detection framework that utilizes Recurrent Neural Networks(RNN)integrated with Long Short-Term Memory(LSTM)*** proposed model can identify various types of cyberattacks,including conventional and distinctive *** networks,a specific kind of feedforward neural networks,possess an intrinsic memory *** Neural Networks(RNNs)incorporating Long Short-Term Memory(LSTM)mechanisms have demonstrated greater capabilities in retaining and utilizing data dependencies over extended *** such as data types,training duration,accuracy,number of false positives,and number of false negatives are among the parameters employed to assess the effectiveness of these models in identifying both common and unusual *** are utilised in conjunction with LSTM to support human analysts in identifying possible intrusion events,hence enhancing their decision-making capabilities.A potential solution to address the limitations of Shallow learning is the introduction of the Eccentric Intrusion Detection *** model utilises Recurrent Neural Networks,specifically exploiting LSTM *** proposed model achieves detection accuracy(99.5%),generalisation(99%),and false-positive rate(0.72%),the parameters findings reveal that it is superior to state-of-the-art techniques.

关键词： Cybersecurity intrusion detection machine learning leveraging long short-term memory(LLSTM) CICIDS2019 dataset innovative cyberattacks

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Deep optics preconditioner for modulation-free pyramid wavefront sensing

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Photonics research 2024年第2期12卷 301-312页

作者： FELIPE GUZMÁN JORGE TAPIA CAMILO WEINBERGER NICOLÁS HERNÁNDEZ JORGE BACCA BENOIT NEICHEL ESTEBAN VERA School of Electrical engineering Pontificia Universidad Católica de Valparaı´soValparaı´soChile department of systems engineering Universidad Industrial de SantanderBucaramangaColombia Laboratoire d’Astrophysique de Marseille MarseilleFrance

The pyramid wavefront sensor(PWFS)can provide the sensitivity needed for demanding adaptive optics applications,such as imaging exoplanets using the future extremely large telescopes of over 30 m of diameter(D).However,its exquisite sensitivity has a limited linear range of operation,or dynamic range,although it can be extended through the use of beam modulation—despite sacrificing sensitivity and requiring additional optical *** by artificial intelligence techniques,this work proposes to train an optical layer—comprising a passive diffractive element placed at a conjugated Fourier plane of the pyramid prism—to boost the linear response of the pyramid sensor without the need for cumbersome *** develop an end-2-end simulation to train the diffractive element,which acts as an optical preconditioner to the traditional least-square modal phase estimation *** results with a large range of turbulence conditions show a noticeable improvement in the aberration estimation performance equivalent to over 3λ∕D of modulation when using the optically preconditioned deep PWFS(DPWFS).Experimental results validate the advantages of using the designed optical layer,where the DPWFS can pair the performance of a traditional PWFS with 2λ∕D of *** and adding an optical preconditioner to the PWFS is just the tip of the iceberg,since the proposed deep optics methodology can be used for the design of a completely new generation of wavefront sensors that can better fit the demands of sophisticated adaptive optics applications such as ground-to-space and underwater optical communications and imaging through scattering media.

关键词： process optics pyramid

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Explainable Conformer Network for Detection of COVID-19 Pneumonia from Chest CT Scan: From Concepts toward Clinical Explainability

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Computers, Materials & Continua 2024年第1期78卷 1171-1187页

作者： Mohamed Abdel-Basset Hossam Hawash Mohamed Abouhawwash S.S.Askar Alshaimaa A.Tantawy Faculty of Computers and Informatics Zagazig UniversityZagazig44519Egypt department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt department of Statistics and operations research College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia

The early implementation of treatment therapies necessitates the swift and precise identification of COVID-19 pneumonia by the analysis of chest CT *** study aims to investigate the indispensable need for precise and interpretable diagnostic tools for improving clinical decision-making for COVID-19 *** paper proposes a novel deep learning approach,called Conformer Network,for explainable discrimination of viral pneumonia depending on the lung Region of Infections(ROI)within a single modality radiographic CT ***,an efficient U-shaped transformer network is integrated for lung image ***,a robust transfer learning technique is introduced to design a robust feature extractor based on pre-trained lightweight Big Transfer(BiT-L)and finetuned on medical data to effectively learn the patterns of infection in the input ***,this work presents a visual explanation method to guarantee clinical explainability for decisions made by Conformer *** evaluation of real-world CT data demonstrated that the diagnostic accuracy of ourmodel outperforms cutting-edge studies with statistical *** Conformer Network achieves 97.40% of detection accuracy under cross-validation *** model not only achieves high sensitivity and specificity but also affords visualizations of salient features contributing to each classification decision,enhancing the overall transparency and trustworthiness of our *** findings provide obvious implications for the ability of our model to empower clinical staff by generating transparent intuitions about the features driving diagnostic decisions.

关键词： Deep learning COVID-19 multi-modal medical image fusion diagnostic image fusion

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Self-Powered Absorptive Reconfigurable Intelligent Surfaces for Securing Satellite-Terrestrial Integrated Networks

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China Communications 2024年第9期 276-291页

作者： Lin Zhi Niu Hehao He Yuanzhi An Kang Zhong Xudong Chu Zheng Xiao Pei College of Electronic engineering National University of Defense Technology Sixty-Third research Institute National University of Defense Technology Institute of systems engineering Academy of Military Science department of Electrical and Electronic engineering University of Nottingham Ningbo China Institute for Communication systems University of Surrey

Satellite communications have attracted significant interests due to its advantages of large footprint and massive ***,the commonly used onboard beamforming is hard to achieve reliable security because of the highly correlated legitimate and wiretap downlink *** exploit the benefits of satellite-terrestrial integrated network(STIN) and a novel absorptive reconfigurable intelligent surface(RIS) for improving the security of satellite downlink communications(SDC) in the presence of eavesdroppers(Eves).This paper aims to maximize the achievable secrecy rate of the earth station(ES)while satisfying the signal reception constraints,harvested power threshold at the RIS,and total transmit power *** solve this nonconvex problem,we propose a penalty-function based dual decomposition scheme,which firstly transforms the original problem into a two-layer optimization ***,the outer layer and inner problems are solved by utilizing the successive convex approximation,Lagrange-dual and Rayleigh quotient methods to obtain the beamforming weight vectors and the reflective coefficient ***,simulation results verify the effectiveness of the proposed scheme for enhancing the SDC security.

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Exploring Deep Learning Methods for Computer Vision Applications across Multiple Sectors:Challenges and Future Trends

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Computer Modeling in engineering & Sciences 2024年第4期139卷 103-141页

作者： Narayanan Ganesh Rajendran Shankar Miroslav Mahdal Janakiraman SenthilMurugan Jasgurpreet Singh Chohan Kanak Kalita School of Computer Science and engineering Vellore Institute of TechnologyChennai600127India department of Computer Science and engineering Koneru Lakshmaiah Education FoundationVaddeswaram522502India department of Control systems and Instrumentation Faculty of Mechanical EngineeringVSB-Technical University of OstravaOstrava70800Czech Republic department of Computer Science and engineering Vel Tech High Tech Dr.Rangarajan Dr.Sakunthala Engineering CollegeChennai600062India department of Mechanical engineering and University Centre for research&Development Chandigarh UniversityMohali140413India department of Mechanical engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyAvadi600062India

Computer vision(CV)was developed for computers and other systems to act or make recommendations based on visual inputs,such as digital photos,movies,and other *** learning(DL)methods are more successful than other traditional machine learning(ML)methods *** techniques can produce state-of-the-art results for difficult CV problems like picture categorization,object detection,and face *** this review,a structured discussion on the history,methods,and applications of DL methods to CV problems is *** sector-wise presentation of applications in this papermay be particularly useful for researchers in niche fields who have limited or introductory knowledge of DL methods and *** review will provide readers with context and examples of how these techniques can be applied to specific areas.A curated list of popular datasets and a brief description of them are also included for the benefit of readers.

关键词： Neural network machine vision classification object detection deep learning

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3D printing for ultra-precision machining:current status,opportunities,and future perspectives

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Frontiers of Mechanical engineering 2024年第4期19卷 1-28页

作者： Tao HE Wai Sze YIP Edward Hengzhou YAN Jiuxing TANG Muhammad REHAN Long TENG Chi Ho WONG Linhe SUN Baolong ZHANG Feng GUO Shaohe ZHANG Suet TO State Key Laboratory of Ultra-precision Machining Technology Department of Industrial and Systems EngineeringThe Hong Kong Polytechnic UniversityHong KongChina department of Industrial and systems engineering The Hong Kong Polytechnic UniversityHong KongChina department of Physics The Hong Kong University of Science and TechnologyHong KongChina School of Geosciences and Info-Physics Central South UniversityChangsha 410083China

Additive manufacturing,particularly 3D printing,has revolutionized the manufacturing industry by allowing the production of complex and intricate parts at a lower cost and with greater ***,3D-printed parts frequently require post-processing or integration with other machining technologies to achieve the desired surface finish,accuracy,and mechanical ***-precision machining(UPM)is a potential machining technology that addresses these challenges by enabling high surface quality,accuracy,and repeatability in 3D-printed *** study provides an overview of the current state of UPM for 3D printing,including the current UPM and 3D printing stages,and the application of UPM to 3D *** the presentation of current stage perspectives,this study presents a detailed discussion of the benefits of combining UPM with 3D printing and the opportunities for leveraging UPM on 3D printing or supporting each *** particular,future opportunities focus on cutting tools manufactured via 3D printing for UPM,UPM of 3D-printed components for real-world applications,and post-machining of 3D-printed ***,future prospects for integrating the two advanced manufacturing technologies into potential industries are *** study concludes that UPM is a promising technology for 3D-printed components,exhibiting the potential to improve the functionality and performance of 3D-printed products in various *** also discusses how UPM and 3D printing can complement each other.

关键词： ultra-precision machining 3D printing additive manufacturing future perspectives start-of-the-art-review

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Towards designing high mechanical performance low-alloyed wrought magnesium alloys via grain boundary segregation strategy:A review

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Journal of Magnesium and Alloys 2024年第5期12卷 1774-1791页

作者： Zhi Zhang Jinshu Xie Jinghuai Zhang Xu-Sheng Yang Ruizhi Wu Key Laboratory of Superlight Material and Surface Technology Ministry of EducationCollege of Materials Science and Chemical EngineeringHarbin Engineering UniversityHarbin 150001China State Key Laboratory of Ultra-Precision Machining Technology Department of Industrial and Systems EngineeringThe Hong Kong Polytechnic UniversityHung HomKowloonHong KongChina Hong Kong Polytechnic University Shenzhen research Institute Shenzhen 518060China

Low-alloyed magnesium(Mg)alloys have emerged as one of the most promising candidates for lightweight ***,their further application potential has been hampered by limitations such as low strength,poor plasticity at room temperature,and unsatisfactory *** address these challenges,grain refinement and grain structure control have been identified as crucial factors to achieving high performance in low-alloyed Mg *** effective way for regulating grain structure is through grain boundary(GB)*** review presents a comprehensive summary of the distribution criteria of segregated atoms and the effects of solute segregation on grain size and growth in Mg *** analysis encompasses both single element segregation and multi-element co-segregation behavior,considering coherent interfaces and incoherent ***,we introduce the high mechanical performance low-alloyed wrought Mg alloys that utilize GB segregation and analyze the potential impact mechanisms through which GB segregation influences materials *** upon these studies,we propose strategies for the design of high mechanical performance Mg alloys with desirable properties,including high strength,excellent ductility,and good formability,achieved through the implementation of GB *** findings of this review contribute to advancing the understanding of grain boundary engineering in Mg alloys and provide valuable insights for future alloy design and optimization.

关键词： Magnesium alloys Grain boundary segregation High strength High plasticity High formability

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Robust Facial Biometric Authentication System Using Pupillary Light Reflex for Liveness Detection of Facial Images

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Computer Modeling in engineering & Sciences 2024年第4期139卷 725-739页

作者： Puja S.Prasad Adepu Sree Lakshmi Sandeep Kautish Simar Preet Singh Rajesh Kumar Shrivastava Abdulaziz S.Almazyad Hossam M.Zawbaa Ali Wagdy Mohamed CSE department Geethanjali College of EngineeringHyderabadTelangana501301India department of Computer Science LBEF CampusKathmandu44600Nepal School of Computer Science engineering and Technology(SCSET) Bennett UniversityGreater Noida201310India department of Computer engineering College of Computer and Information SciencesKing Saud UniversityP.O.Box 51178Riyadh11543Saudi Arabia CeADAR Ireland’s Centre for AI Technological University DublinDublinD07 EWV4Ireland operations research department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science research Center Applied Science Private UniversityAmman11937Jordan

Pupil dynamics are the important characteristics of face spoofing *** face recognition system is one of the most used biometrics for authenticating individual *** main threats to the facial recognition system are different types of presentation attacks like print attacks,3D mask attacks,replay attacks,*** proposed model uses pupil characteristics for liveness detection during the authentication *** pupillary light reflex is an involuntary reaction controlling the pupil’s diameter at different light *** proposed framework consists of two-phase *** the first phase,the pupil’s diameter is calculated by applying stimulus(light)in one eye of the subject and calculating the constriction of the pupil size on both eyes in different video *** above measurement is converted into feature space using Kohn and Clynes model-defined *** Support Vector Machine is used to classify legitimate subjects when the diameter change is normal(or when the eye is alive)or illegitimate subjects when there is no change or abnormal oscillations of pupil behavior due to the presence of printed photograph,video,or 3D mask of the subject in front of the *** the second phase,we perform the facial recognition ***-invariant feature transform(SIFT)is used to find the features from the facial images,with each feature having a size of a 128-dimensional *** features are scale,rotation,and orientation invariant and are used for recognizing facial *** brute force matching algorithm is used for matching features of two different *** threshold value we considered is 0.08 for good *** analyze the performance of the framework,we tested our model in two Face antispoofing datasets named Replay attack datasets and CASIA-SURF datasets,which were used because they contain the videos of the subjects in each sample having three modalities(RGB,IR,Depth).The CASIA-SURF datasets showed an 89.9%Equal Err

关键词： SIFT pupil CASIA-SURF pupillary light reflex replay attack dataset brute force

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Large-disturbance Stability Analysis of Power systems with Synchronous Generator and Converter-interfaced Generation

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Journal of Modern Power systems and Clean Energy 2024年第3期12卷 997-1002页

作者： Lei Chen Yong Min Liangshuai Hao Guangzheng Xing Yalou Li Shiyun Xu department of Electrical engineering Tsinghua UniversityBeijing 100084China China Electric Power research Institute Beijing 100192China

This letter studies large-disturbance stability of the power system with a synchronous generator(SG)and a converter-interfaced generation(CIG)connected to infinite *** power system is multi-timescale and first *** is shown that the boundary of region of attraction(ROA)of the simplified model is composed of stable manifolds of unstable equilibrium point(UEP)or semi-singular point(SSP),named anchor points,and singular surface *** type of anchor point determines the dominant instability pattern of the power *** the anchor point is UEP or SSP,the dominant instability pattern is the instability of rotor angle of SG or the instability of phase-locked loop and outer control loop(OCL)of CIG,*** of dominant instability pattern can be analyzed with the relative position relationship between UEP and *** effect of OCL is *** the OCL is activated,the ROA becomes smaller and the system is more prone to instability of *** is necessary to consider the OCL when studying the large-disturbance stability of the power system.

关键词： Converter-interfaced generation large-disturbance stability outer control loop phase-locked loop synchronous generator voltage source converter

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Next generation multiple access for IMT towards 2030 and beyond

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Science China(Information Sciences) 2024年第6期67卷 448-450页

作者： Zhiguo DING Robert SCHOBER Pingzhi FAN H.Vincent POOR department of Computer and Information engineering Khalifa University department of Electrical and Electronic engineering University of Manchester Institute for Digital Communications Friedrich Alexander-University Erlangen-Nurnberg (FAU) CSNMT International Cooperation research Center (MoST) Southwest Jiaotong University department of Electrical and Computer engineering Princeton University

Multiple access techniques are fundamental to the design of wireless communication systems,since many crucial components of such systems depend on the choice of the multiple access technique[1].For example,the use of ...

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