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AI-Driven Learning Management Systems:Modern Developments, Challenges and Future Trends during theAge of ChatGPT

Computers, Materials & Continua 2024年第8期80卷 3289-3314页

作者： Sameer Qazi Muhammad Bilal Kadri Muhammad Naveed Bilal AKhawaja Sohaib Zia Khan Muhammad Mansoor Alam Mazliham Mohd Su’ud Department of Computer Science Faculty of EngineeringScience and TechnologyIQRA UniversityKarachi75500Pakistan College of Computer and information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia faculty of engineering Department of Electrical EngineeringIslamic University of MadinahP.O.BOX 170Madinah41411Saudi Arabia faculty of engineering Department of Mechanical EngineeringIslamic University of MadinahP.O.BOX 170Madinah41411Saudi Arabia faculty of Computing Riphah International UniversityIslamabad46000Pakistan faculty of Computing and Informatics(FCI)Multimedia University Cyberjaya63100Malaysia faculty of engineering and information technology School of Computer ScienceUniversity of Technology SydneySydneyNSW 2007Australia

COVID-19 pandemic restrictions limited all social activities to curtail the spread of the *** foremost and most prime sector among those affected were schools,colleges,and *** education system of entire nations had shifted to online education during this *** shortcomings of Learning Management Systems(LMSs)were detected to support education in an online mode that spawned the research in Artificial Intelligence(AI)based tools that are being developed by the research community to improve the effectiveness of *** paper presents a detailed survey of the different enhancements to LMSs,which are led by key advances in the area of AI to enhance the real-time and non-real-time user *** AI-based enhancements proposed to the LMSs start from the Application layer and Presentation layer in the form of flipped classroom models for the efficient learning environment and appropriately designed UI/UX for efficient utilization of LMS utilities and resources,including AI-based *** layer enhancements are also required,such as AI-based online proctoring and user authentication using *** extend to the Transport layer to support real-time and rate adaptive encrypted video transmission for user security/privacy and satisfactory working of *** also needs the support of the Networking layer for IP-based geolocation features,the Virtual Private Network(VPN)feature,and the support of Software-Defined Networks(SDN)for optimum Quality of Service(QoS).Finally,in addition to these,non-real-time user experience is enhanced by other AI-based enhancements such as Plagiarism detection algorithms and Data Analytics.

关键词： Learning management systems chatbots ChatGPT online education Internet of Things(IoT) artificial intelligence(AI) convolutional neural networks natural language processing

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Graphene oxide-coated microbottle resonators for relative humidity sensing

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Optoelectronics Letters 2024年第7期20卷 400-405页

作者： Huda Adnan Zain Malathy Batumalay Md Ashadi Md Johari Hazli Rafis Abdul Rahim Sulaiman Wadi Harun Department of Electrical engineering Faculty of EngineeringUniversity of MalayaKuala Lumpur 50603Malaysia faculty of Data Science and information technology INTI International UniversityNilai 71800Malaysia1 faculty of Electrical and Electronic engineering technology Universiti Teknikal Malaysia MelakaMelaka 76100Malaysia faculty of Electronic and Computer engineering Universiti Teknikal Malaysia MelakaMelaka 76100Malaysia

Graphene oxide(GO)is a 2D coating material used to improve fiber optics sensors’response to relative *** resonators(MBRs)have garnered more attention as sensing media *** MBR with a 190μm diameter was coated with ***,tapered fiber light coupling was used to investigate the relative humidity sensing performance in the range of 35—70%RH at 25℃.The MBR showed a higher Q factor before and after GO *** sensitivity of 0.115 dB/%RH was recorded with the 190μm GO-coated MBR sample compared to a sensitivity of 0.022 dB/%RH for the uncoated MBR *** results show that the MBR can be used in fiber optic sensing applications for environmental sensing.

关键词： humidity oxide bottle

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Experimental realization of fractal fretwork metasurface for sound anomalous modulation

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Chinese Physics B 2024年第5期33卷 473-478页

作者：何佳杰于书萌江雪他得安 Department of Biomedical engineering School of Information Science and TechnologyFudan UniversityShanghai 200433China Academy for engineering and technology Fudan UniversityShanghai 200433China

Natural creatures and ancient cultures are full of potential sources to provide inspiration for applied *** by the fractal geometry in nature and the fretwork frame in ancient culture,here we design the acoustic metasurface to realize sound anomalous modulation,which manifests itself as an incident-dependent propagation behavior:sound wave propagating in the forward direction is allowed to transmit with high efficiency while in the backward direction is obviously *** quantitatively investigate the dependences of asymmetric transmission on the propagation direction,incident angle and operating frequency by calculating sound transmittance and energy *** compact fractal fretwork metasurface for acoustic anomalous modulation would promote the development of integrated acoustic devices and expand versatile applications in acoustic communication and information encryption.

关键词： acoustic metasurface fractal geometry sound anomalous modulation

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Resource Allocation for Space-Air-Ground Integrated Networks:A Comprehensive Review

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Journal of communications and information Networks 2024年第1期9卷 1-23页

作者： Hui Liang Zhiqing Yang Guobin Zhang Hanxu Hou School of Electrical engineering and Intelligentization Dongguan University of TechnologyDongguan 523808China Peng Cheng Laboratory Shenzhen 518055China School of Electronics and information engineering Shenzhen UniversityShenzhen 518061China School of Electrical engineering and Intelligentization Dongguan University of TechonologyDongguan 523808China School of information and communication engineering Guangzhou Maritime UniversityGuangzhou 510725China

The space-air-ground integrated networks (SAGIN) has emerged as a critical paradigm to address the growing demands for global connectivity and enhanced communication services. This paper gives a thorough review of the strategies and methodologies for resource allocation within SAGIN, focusing on the challenges and solutions within its complex structure. With the advent of technologies such as 6G, the dynamics of resource optimization have become increasingly complex, necessitating innovative approaches for efficient management. We examine the application of mathematical optimization, game theory, artificial intelligence (AI), and dynamic optimization techniques in SAGIN,offering insights into their effectiveness in ensuring optimal resource distribution, minimizing delays, and maximizing network throughput and stability. The survey highlights the significant advances in AI-based methods,particularly deep learning and reinforcement learning, in tackling the inherent challenges of SAGIN resource allocation. Through a critical review of existing literature, this paper categorizes various resource allocation strategies, identifies current research gaps, and discusses potential future directions. Our findings highlight the crucial role of integrated and intelligent resource allocation mechanisms in realizing the full potential of SAGIN for next-generation communication networks.

关键词： space-air-ground integrated networks resource allocation 6G optimization theory game theory artificial intelligence

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Deep Transfer Learning Techniques in Intrusion Detection System-Internet of Vehicles: A State-of-the-Art Review

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Computers, Materials & Continua 2024年第8期80卷 2785-2813页

作者： Wufei Wu Javad Hassannataj Joloudari Senthil Kumar Jagatheesaperumal Kandala N.V.P.SRajesh Silvia Gaftandzhieva Sadiq Hussain Rahimullah Rabih Najibullah Haqjoo Mobeen Nazar Hamed Vahdat-Nejad Rositsa Doneva School of information engineering Nanchang UniversityNanchang330031China Department of Computer engineering Technical and Vocational University(TVU)Tehran***Iran Department of Computer engineering University of BirjandBirjand***Iran Department of Computer engineering Babol BranchIslamic Azad UniversityBabol***Iran Department of Electronics&communication engineering Mepco Schlenk Engineering CollegeSivakasi626005India School of Electronics engineering VIT-AP UniversityNear Vijayawada522237India faculty of Mathematics and Informatics University of Plovdiv Paisii HilendarskiPlovdiv4000Bulgaria Examination Branch Dibrugarh UniversityDibrugarh786004India Department of Computer engineering Faculty of EngineeringUniversity of BirjandBirjand***Iran faculty of Electrical and Computer engineering University of BirjandBirjand***Iran Malaysian Institute of information technology Universiti Kuala LumpurKuala Lumpur50250Malaysia faculty of Physics and technology University of Plovdiv Paisii HilendarskiPlovdiv4000Bulgaria

The high performance of IoT technology in transportation networks has led to the increasing adoption of Internet of Vehicles(IoV)*** functional advantages of IoV include online communication services,accident prevention,cost reduction,and enhanced traffic *** these benefits,IoV technology is susceptible to cyber-attacks,which can exploit vulnerabilities in the vehicle network,leading to perturbations,disturbances,non-recognition of traffic signs,accidents,and vehicle *** paper reviews the state-of-the-art achievements and developments in applying Deep Transfer Learning(DTL)models for Intrusion Detection Systems in the Internet of Vehicles(IDS-IoV)based on anomaly ***-IoV leverages anomaly detection through machine learning and DTL techniques to mitigate the risks posed by *** systems can autonomously create specific models based on network data to differentiate between regular traffic and *** these techniques,transfer learning models are particularly promising due to their efficacy with tagged data,reduced training time,lower memory usage,and decreased computational *** evaluate DTL models against criteria including the ability to transfer knowledge,detection rate,accurate analysis of complex data,and *** review highlights the significant progress made in the field,showcasing how DTL models enhance the performance and reliability of IDS-IoV *** examining recent advancements,we provide insights into how DTL can effectively address cyber-attack challenges in IoV environments,ensuring safer and more efficient transportation networks.

关键词： Cyber-attacks internet of things internet of vehicles intrusion detection system

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High-Precision DOA Estimation Method Based on Synthetic Aperture Technique

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Journal of Beijing Institute of technology 2024年第2期33卷 111-118页

作者： Yongjia Dou Guangcai Sun Yuqi Wang Mengdao Xing National Key Laboratory of Radar Signal Processing Xidian UniversityXi’an 710071China School of communication and information engineering Xi’an University of Science and TechnologyXi’an 710054China

The existing direction-of-arrival(DOA)estimation methods only utilize the current received signals,which are susceptible to *** this paper,a method for DOA estimation based on a motion platform is proposed to achieve high-precision DOA estimation by utilizing past and present *** concept of synthetic aperture is introduced to construct a linear DOA estima-tion model.A DOA fine-tuning method based on the linear model is proposed to eliminate the lin-ear DOA variation,achieving a non-coherent accumulation of DOA ***,the baseband modulation and the phase modulation caused by the range history are compensated to achieve the coherent accumulation of all the DOA *** results show that the proposed method can significantly improve the DOA estimated accuracy at low signal-to-noise ratios(SNR).

关键词： synthetic aperture direction-of-arrival(DOA)estimation coherent accumulation

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Joint Transmit and Reflective Beamforming Design for Active IRS-Aided SWIPT Systems

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Chinese Journal of Electronics 2024年第2期33卷 536-548页

作者： Weiping SHI Qingqing WU Di WU Feng SHU Jiangzhou WANG School of Electronic and Optical engineering Nanjing University of Science and Technology Department of Electronic engineering Shanghai Jiao Tong University School of information and communication engineering Hainan University Department of Automation Shanghai Jiao Tong University School of engineering University of Kent

To further improve the performance of passive intelligent reflecting surface(IRS)-assisted communication systems and mitigate the serious path loss due to “double-fading ” of IRS-assisted links, an active IRS-aided simultaneous wireless information and power transfer(SWIPT) system is investigated. This paper jointly optimizes the transmit beamforming at the base station(BS) and the phase shifts at the active IRS in order to maximize the power collected by the energy harvesting receiver under both perfect and imperfect channel state information(CSI)states, subject to the signal-to-interference-noise ratio constraint of the information decoding receiver, and the power constraints of the BS/IRS. Under perfect CSI, the alternating optimization algorithm is utilized for obtaining the transmit beamforming at the BS and the phase shifts at the active IRS. For each subproblem, we first transform nonconvex objective function and constraints into convex ones by performing a first-order Taylor expansion. Then, each subproblem is solved by using the interior point method. Given that obtaining perfect CSI is impractical, two robust beamforming designs are proposed for imperfect CSI case. Under the bounded CSI error model, we first transform the non-convex optimization problem into two semidefinite programming subproblems, and then solve each subproblem based on S-procedure and sequential rank-one constraint relaxation(SROCR) techniques. Under the stochastic CSI error model, the alternating optimization method is applied in an iterative manner based on Bernstein-type inequality and SROCR technique. Simulation results show that both robust and non-robust schemes for active IRS-assisted SWIPT systems can achieve extremely superior performance over conventional passive IRS-assisted systems under the same overall power budget.

关键词： Wireless communication Semidefinite programming Array signal processing Simulation Stochastic processes Transforms Receivers

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Direction finding of bistatic MIMO radar in strong impulse noise

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Journal of Systems engineering and Electronics 2024年第4期35卷 888-898页

作者： CHEN Menghan GAO Hongyuan DU Yanan CHENG Jianhua ZHANG Yuze College of information and communication engineering Harbin Engineering UniversityHarbin 150001China College of Intelligent Systems Science and engineering Harbin Engineering UniversityHarbin 150001China

For bistatic multiple-input multiple-output(MIMO)radar,this paper presents a robust and direction finding method in strong impulse noise *** means of a new lower order covariance,the method is effective in suppressing impulse noise and achieving superior direction finding performance using the maximum likelihood(ML)estimation method.A quantum equilibrium optimizer algorithm(QEOA)is devised to resolve the corresponding objective function for efficient and accurate direc-tion *** results of simulation reveal the capability of the presented method in success rate and root mean square error over existing direction-finding methods in different application situations,e.g.,locating coherent signal sources with very few snapshots in strong impulse *** than that,the Cramér-Rao bound(CRB)under impulse noise environment has been drawn to test the capability of the presented method.

关键词： bistatic multiple-input multiple-output(MIMO)radar impulse noise direction finding lower order covariance quan-tum equilibrium optimizer algorithm(QEOA) maximum likeli-hood estimation method Cramér-Rao bound(CRB)

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Machine learning based models for predicting compressive strength of geopolymer concrete

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Frontiers of Structural and Civil engineering 2024年第7期18卷 1028-1049页

作者： Quang-Huy LE Duy-Hung NGUYEN Thanh SANG-TO Samir KHATIR Hoang LE-MINH Amir H.GANDOMI Thanh CUONG-LE Center for engineering Application and technology Solutions Ho Chi Minh City Open UniversityHo Chi Minh 700000Vietnam Institute of Civil engineering Ho Chi Minh City University of TransportHo Chi Minh 700000Vietnam faculty of engineering&information technology University of Technology SydneyUltimoNSW 2007Australia

Recently,great attention has been paid to geopolymer concrete due to its advantageous mechanical and environmentally friendly *** effort has been made in experimental studies to advance the understanding of geopolymer concrete,in which compressive strength is one of the most important *** facilitate engineering work on the material,an efficient predicting model is *** this study,three machine learning(ML)-based models,namely deep neural network(DNN),K-nearest neighbors(KNN),and support vector machines(SVM),are developed for forecasting the compressive strength of the geopolymer concrete.A total of 375 experimental samples are collected from the literature to build a database for the development of the predicting models.A careful procedure for data preprocessing is implemented,by which outliers are examined and removed from the database and input variables are standardized before feeding to the fitting *** standard K-fold cross-validation approach is applied for evaluating the performance of the models so that overfitting status is well managed,thus the generalizability of the models is *** effectiveness of the models is assessed via statistical metrics including root mean squared error(RMSE),mean absolute error(MAE),correlation coefficient(R),and the recently proposed performance index(PI).The basic mean square error(MSE)is used as the loss function to be minimized during the model fitting *** three ML-based models are successfully developed for estimating the compressive strength,for which good correlations between the predicted and the true values are obtained for DNN,KNN,and *** numerical results suggest that the DNN model generally outperforms the other two models.

关键词： geopolymer concrete compressive strength prediction machine-learning based model deep neural network K-nearest neighbor support vector machines

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Thin-film flow technology in controlling the organization of materials and their properties Special Collection:Distinguished Australian Researchers

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Aggregate 2024年第1期5卷 115-129页

作者： Clarence Chuah Xuan Luo Javad Tavakoli Youhong Tang Colin L.Raston Flinders Institute for Nanoscale Science and technology College of Science and EngineeringFlinders UniversityAdelaideSouth AustraliaAustralia Centre for Health Technologies School of Biomedical EngineeringFaculty of Engineering and Information TechnologyUniversity of Technology SydneySydneyNew South WalesAustralia

Centrifugal and shear forces are produced when solids or liquids *** systems and devices that use these forces,such as dynamic thin-film flow technology,are evolving continuously,improve material structure-property relationships at the nanoscale,representing a rapidly thriving and expanding field of research high with green chemistry metrics,consolidated at the inception of *** vortex fluidic device(VFD)provides many advantages over conventional batch processing,with fluidic waves causing high shear and producing large surface areas for micro-mixing as well as rapid mass and heat transfer,enabling reactions beyond diffusion *** these abilities allows for a green and innovative approach to altering materials for various research and industry applications by controlling small-scale flows and regulating molecular and macromolecular chemical reactivity,self-organization phenomena,and the synthesis of novel *** review highlights the aptitude of the VFD as clean technology,with an increase in efficiency for a diversity of top-down,bottom-up,and novel material transformations which benefit from effective vortex-based processing to control material structure-property relationships.

关键词： material nanoscale structure-property relationship thin film flow technology vortex fluidic device

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