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A Novel Attack on Complex APUFs Using the Evolutionary Deep Convolutional Neural Network

Intelligent Automation & Soft Computing 2023年第9期37卷 3059-3081页

作者： ali ahmadi shahrakht Parisa Hajirahimi Omid Rostami Diego Martín Department of Industrial Engineering Sharif University of TechnologyTehran14588-89694Iran Department of Business Administration Boston UniversityBostonMA02215USA Department of Industrial Engineering University of HoustonHoustonTX77204USA ETSI de Telecomunicación Universidad Politécnica de MadridMadrid28040Spain

As the internet of things(IoT)continues to expand rapidly,the significance of its security concerns has grown in recent *** address these concerns,physical unclonable functions(PUFs)have emerged as valuable tools for enhancing IoT *** leverage the inherent randomness found in the embedded hardware of IoT ***,it has been shown that some PUFs can be modeled by attackers using machine-learning-based *** this paper,a new deep learning(DL)-based modeling attack is introduced to break the resistance of complex *** training DL models is a problem that falls under the category of NP-hard problems,there has been a significant increase in the use of meta-heuristics(MH)to optimize DL ***,it is widely recognized that finding the right balance between exploration and exploitation when dealing with complex problems can pose a significant *** address these chal-lenges,a novel migration-based multi-parent genetic algorithm(MBMPGA)is developed to train the deep convolutional neural network(DCNN)in order to achieve a higher rate of accuracy and convergence speed while decreas-ing the run-time of the *** the proposed MBMPGA,a non-linear migration model of the biogeography-based optimization(BBO)is utilized to enhance the exploitation ability of GA.A new multi-parent crossover is then introduced to enhance the exploration ability of *** behavior of the proposed MBMPGA is examined on two real-world optimization *** benchmark problems,MBMPGA outperforms other MH algorithms in convergence *** proposed model are also compared with previous attacking models on several simulated challenge-response pairs(CRPs).The simulation results on the XAPUF datasets show that the introduced attack in this paper obtains more than 99%modeling accuracy even on *** addition,the proposed MBMPGA-DCNN outperforms the state-of-the-art modeling attacks in a reduced timeframe and with a smaller number of requi

关键词： IoT security PUFs modeling attacks evolutionary deep learning migration-based multi-parent genetic algorithm

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Model Reference Adaptive Controller for Simultaneous Voltage and Frequency Restoration of Autonomous AC Microgrids

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Journal of Modern Power Systems and Clean Energy 2024年第4期12卷 1194-1202页

作者： Farahnaz ahmadi Yazdan Batmani Hassan Bevrani Department of Electrical Engineering University of KurdistanSanandajIran

In an autonomous droop-based microgrid,the sys-tem voltage and frequency(VaF)are subject to deviations as load *** the existence of various control methods aimed at correcting system frequency deviations at the second-ary control level without any communication network,the chal-lenges associated with these methods and their abilities to simul-taneously restore microgrid VaF have not been fully *** this paper,a multi-input multi-output(MIMO)model ref-erence adaptive controller(MRAC)is proposed to achieve VaF restoration while accurate power sharing among distributed generators(DGs)is *** proposed MRAC,without any communication network,is designed based on two meth-ods:droop-based and inertia-based *** the microgrid,the suggested design procedure is started by defining a model reference in which the control objectives,such as the desired settling time,the maximum tolerable overshoot,and steady-state error,are ***,a feedback-feedforward con-troller is established,of which the gains are adaptively tuned by some rules derived from the Lyapunov stability *** some simulations in MATLAB/SimPowerSystem Tool-box,the proposed MRAC demonstrates satisfactory perfor-mance.

关键词： AC microgid communication-free secondary control droop-based method inertia-based method model reference adaptive controller(MRAC) simultaneous voltage and frequency restoration

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Numerical study of the near-wall vortical structures in particle-laden turbulent flow by a new vortex identification method-Liutex

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Journal of Hydrodynamics 2024年第1期36卷 53-60页

作者： Farid Rousta Goodarz ahmadi Bamdad Lessani Chaoqun Liu Department of Mechanical and Aerospace Engineering Clarkson UniversityPotsdamNYUSA Mechanical Engineering and Engineering Science The University of North Carolina at CharlotteNCUSA Department of Mathematics University of Texas at ArlingtonArlingtonTXUSA

This study investigates turbulent particle-laden channel flows using direct numerical simulations employing the Eulerian-Lagrangian method.A two-way coupling approach is adopted to explore the mutual interaction between particles and fluid *** considered cases include flow with particle Stokes number varying from St=2 up to St=100 while maintaining a constant Reynolds number of Reτ=180 across all cases.A novel vortex identification method,Liutex(Rortex),is employed to assess its efficacy in capturing near-wall turbulent coherent structures and their interactions with *** Liutex method provides valuable information on vortex strength and vectors at each location,enabling a detailed examination of the complex interaction between fluid and particulate *** widely acknowledged,the interplay between clockwise and counterclockwise vortices in the near-wall region gives rise to low-speed streaks along the *** low-speed streaks serve as preferential zones for particle concentration,depending upon the particle Stokes *** is shown that the Liutex method can capture these vortices and identify the location of low-speed ***,it is observed that the particle Stokes number(size)significantly affects both the strength of these vortices and the streaky structure exhibited by ***,a quantitative analysis of particle behavior in the near-wall region and the formation of elongated particle lines was carried *** involved examining the average fluid streamwise velocity fluctuations at particle locations,average particle concentration,and the normal velocity of particles for each set of particle Stokes *** investigation reveals the intricate interplay between particles and near-wall structures and the significant influence of particles Stokes *** study contributes to a deeper understanding of turbulent particle-laden channel flow dynamics.

关键词： Turbulent channel flow particle-laden flow direct numerical simulation(DNS) Eulerian-Lagrangian vortex identification turbulence coherent structures Liutex

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Special Issue:International Conference on Sustainable Energy Sources,Technologies and Systems 2023(ICSESTS-2023)

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Clean Energy 2024年第3期8卷 136-137页

作者： Ravinder Kumar Mohammad Hossein ahmadi School of Mechanical Engineering Lovely Professional UniversityPhagwra-144411PunjabIndia Faculty of Mechanical Engineering Shahrood University of TechnologyShahroodIran

The Division of Research and Development at Lovely Professional University,Punjab organized the International Conference on Sustainable Energy Sources,Technologies and Systems 2023(ICSESTS-2023),which took place on 3-... 详细信息

关键词： solar energy storage wind energy geothermal hydropower biofuels batteries

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Surveying organic matter， thermal maturity level， and paleo-environmental conditions by considering biomarker and stable carbon isotopic analysis

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Journal of Earth Science 2024年

作者： Meysam Hemmati Yaser ahmadi Behzad Vaferi ali Hosin alibak David A.Wood DWA Energy Limited School of Geology， College of Science， University of Tehran Petroleum Engineering Department， Faculty of Engineering， Soran University Department of Chemical Engineering， Shiraz Branch， Islamic Azad University Chemical and Petroleum Engineering Department， Ilam University

Biomarker and stable carbon isotope analyses are presented for the Garau formation of the Cretaceous age， an important source rock in western Iran， to reveal its potential as an oil-prone source rock. The C28/C29sterane ratio value range (0.72 to 0.83) of bitumen samples from the formation suggests that they were likely formed during phytoplankton blooms. Sterane， hopane， and isoprenoid/n-alkane ratios indicate that the formation’s organic matter predominantly consists of algae， and bacteria， accompanied by some reworked material derived from higher plants. Due to the predominance of anoxic conditions and the actions of sulfate-reducing bacteria， the bitumen present is enriched with sulfur compounds. The percentages of saturates， aromatics， and nitrogen-sulfur-oxygen (NSO) fractions in the bitumen samples classify them as naphthenic oils. Isotope analysis reveals that biodegradation and water-washing have reduced the concentrations of some volatile saturates and low molecular weight aromatics in the bitumen samples. These actions have resulted in distinctive δ13C values for the formation’s kerogen and bitumen fractions. The formation’s organic matter has been subjected to high-temperature thermal regimes and has entered the oil-generation window at the sampled localities， with vitrinite reflectance (%RC) varying between 0.7% and 0.75%.

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Studying the effect of surfactant assisted low-salinity water flooding on clay-rich sandstones

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Petroleum 2024年第2期10卷 306-318页

作者： Saeed Khezerloo-ye Aghdam alireza Kazemi Mohammad ahmadi Department of Petroleum Engineering Amirkabir University of Technology(AUT)TehranIran Department of Petroleum and Chemical Engineering College of EngineeringSultan Qaboos UniversityMuscatOman

Sandstone reservoirs often contain clay particles that can cause damage and reduce permeability during low-salinity water *** this study,the effect of surfactants on fine migration in clay-rich sandstones and its impact on oil recovery was ***,the impact of surfactants on interparticle forces in fine-matrix,fine-fine,and oil-matrix systems was *** results showed that both CTAB(cetyltrimethyl ammonium bromide)and QS(quillaja saponin)cause EDL compaction,weakening the repulsive ***,SDS(sodium dodecyl sulfate)and TX(triton X-100)do not affect the ***,the effect of surfactants on IFT reduction and wettability alteration was experimentally *** surfactants reduced IFT due to the surface excessive concentration *** wettability alteration experiment illustrated that although QS and CTAB compact EDL around oil and matrix particles leading to attraction force augmentation,they both alter wettability through adsorption on matrix and carboxylic groups present in crude oil,*** aqueous solutions were then injected into various clay-rich sandstone sanpacks,which resulted in increased oil ***,the mechanisms leading to enhanced oil recovery variedby surfactant *** increased recovery by 10%through IFT reduction and wettability alteration,while SDS and TX increased recovery by 12%and 9%,respectively,through wettability alteration and extreme fine *** contrast,partial fine migration in the QS flooding experiment reached a recovery increase of 18%.Permeability trends through experiments were also *** CTAB injection,permeability did not reduce,while QS aqueous solution reduced rock permeability to 5 m *** and TX reduced the magnitude of permeability to 2 m *** conclusion,this study demonstrates that surfactants can effectively improve oil recovery in clay-rich sandstones by altering the interparticle forces,reducing IFT,and changing *** results

关键词： Surfactant flooding Smart water Fine migration Recovery factor

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RoGRUT: A Hybrid Deep Learning Model for Detecting Power Trapping in Smart Grids

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Computers, Materials & Continua 2024年第5期79卷 3175-3192页

作者： Farah Mohammad Saad Al-ahmadi Jalal Al-Muhtadi Center of Excellence in Information Assurance(CoEIA) King Saud UniversityRiyadh11543Saudi Arabia College of Computer&Information Sciences King Saud UniversityRiyadh11543Saudi Arabia

Electricity theft is a widespread non-technical issue that has a negative impact on both power grids and electricity *** hinders the economic growth of utility companies,poses electrical risks,and impacts the high energy costs borne by *** development of smart grids is crucial for the identification of power theft since these systems create enormous amounts of data,including information on client consumption,which may be used to identify electricity theft using machine learning and deep learning ***,there also exist different solutions such as hardware-based solutions to detect electricity theft that may require human resources and expensive ***-based solutions are presented in the literature to identify electricity theft but due to the dimensionality curse,class imbalance issue and improper hyper-parameter tuning of such models lead to poor *** this research,a hybrid deep learning model abbreviated as RoGRUT is proposed to detect electricity theft as amalicious and non-malicious *** key steps of the RoGRUT are data preprocessing that covers the problem of class imbalance,feature extraction and final theft *** advanced-level models like RoBERTa is used to address the curse of dimensionality issue,the near miss for class imbalance,and transfer learning for *** effectiveness of the RoGRUTis evaluated using the dataset fromactual smartmeters.A significant number of simulations demonstrate that,when compared to its competitors,the RoGRUT achieves the best classification *** performance evaluation of the proposed model revealed exemplary results across *** accuracy achieved was 88%,with precision at an impressive 86%and recall reaching 84%.The F1-Score,a measure of overall performance,stood at 85%.Furthermore,themodel exhibited a noteworthyMatthew correlation coefficient of 78%and excelled with an area under the curve of 91%.

关键词： Electricity theft smart grid RoBERTa GRU transfer learning

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Molecular insights into oil detachment from hydrophobic quartz surfaces in clay-hosted nanopores during steam-surfactant co-injection

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Petroleum Science 2024年第4期21卷 2457-2468页

作者： Ben-Jie-Ming Liu Xuan-Tong Lei Mohammadali ahmadi Zhangxin Chen Department of Chemical and Petroleum Engineering University of Calgary Eastern Institute of Technology

Thermal recovery techniques for producing oil sands have substantial environmental impacts. Surfactants can efficiently improve thermal bitumen recovery and reduce the required amount of steam. Such a technique requires solid knowledge about the interaction mechanism between surfactants, bitumen,water, and rock at the nanoscale level. In particular, oil sands ores have extremely complex mineralogy as they contain many clay minerals(montmorillonite, illite, kaolinite). In this study, molecular dynamics simulation is carried out to elucidate the unclear mechanisms of clay minerals contributing to the bitumen recovery under a steam-anionic surfactant co-injection process. We found that the clay content significantly influenced an oil detachment process from hydrophobic quartz surfaces. Results reveal that the presence of montmorillonite, illite, and the siloxane surface of kaolinite in nanopores can enhance the oil detachment process from the hydrophobic surfaces because surfactant molecules have a stronger tendency to interact with bitumen and quartz. Conversely, the gibbsite surfaces of kaolinite curb the oil detachment process. Through interaction energy analysis, the siloxane surfaces of kaolinite result in the most straightforward oil detachment process. In addition, we found that the clay type presented in nanopores affected the wettability of the quartz surfaces. The quartz surfaces associated with the gibbsite surfaces of kaolinite show the strongest hydrophilicity. By comparing previous experimental findings with the results of molecular dynamics(MD) simulations, we observed consistent wetting characteristics. This alignment serves to validate the reliability of the simulation outcomes. The outcome of this paper makes up for the lack of knowledge of a surfactant-assisted bitumen recovery process and provides insights for further in-situ bitumen production engineering designs.

关键词： Clay minerals Bitumen Contact angle Interaction energy Surfactant Molecular dynamics

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GAN‐MD:A myocarditis detection using multi‐channel convolutional neural networks and generative adversarial network‐based data augmentation

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CAAI Transactions on Intelligence Technology 2024年第4期9卷 866-878页

作者： Hengame ahmadi Golilarz alireza Azadbar Roohallah alizadehsani Juan Manuel Gorriz Department of Medical Radiation Engineering Faculty of EngineeringLahijan BranchIslamic Azad UniversityLahijanIran Department of Medical Radiation Engineering Lahijan BranchIslamic Azad UniversityLahijanIran Institute for Intelligent Systems Research and Innovation(IISRI) Deakin UniversityWaurn PondsVictoriaAustralia Data Science and Computational Intelligence Institute University of GranadaGranadaSpain

Myocarditis is a significant public health concern because of its potential to cause heart failure and sudden *** standard invasive diagnostic method,endomyocardial bi-opsy,is typically reserved for cases with severe complications,limiting its widespread ***,non‐invasive cardiac magnetic resonance(CMR)imaging presents a promising alternative for detecting and monitoring myocarditis,because of its high signal contrast that reveals myocardial *** assist medical professionals via artificial intelligence,the authors introduce generative adversarial networks‐multi discriminator(GAN‐MD),a deep learning model that uses binary classification to diagnose myocarditis from CMR *** approach employs a series of convolutional neural networks(CNNs)that extract and combine feature vectors for accurate *** authors suggest a novel technique for improving the classification precision of *** generative adversarial networks(GANs)to create synthetic images for data augmentation,the authors address challenges such as mode collapse and unstable *** a reconstruction loss into the GAN loss function requires the generator to produce images reflecting the discriminator features,thus enhancing the generated images'quality to more accurately replicate authentic data ***,combining this loss function with other reg-ularisation methods,such as gradient penalty,has proven to further improve the perfor-mance of diverse GAN models.A significant challenge in myocarditis diagnosis is the imbalance of classification,where one class dominates over the *** mitigate this,the authors introduce a focal loss‐based training method that effectively trains the model on the minority class *** GAN‐MD approach,evaluated on the Z‐alizadeh Sani myocarditis dataset,achieves superior results(F‐measure 86.2%;geometric mean 91.0%)compared with other deep learning models and traditional machine learning methods.

关键词： 2‐D 3‐D

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Recent advances in heterogeneous catalysis of solar-driven carbon dioxide conversion

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Journal of Environmental Sciences 2024年第6期140卷 165-182页

作者： Jun Xu Farzaneh Arabpour Roghabadi Ying Luo Vahid ahmadi Qian Wang Zheng Wang Hong He State Key Joint Laboratory of Environment Simulation and Pollution Control Research Center for Eco-Environmental SciencesChinese Academy of SciencesBeijing 100085China College of Chemistry and Chemical Engineering Henan Polytechnic UniversityJiaozuoHenan 454000China Department of Process Engineering Faculty of Chemical EngineeringTarbiat Modares UniversityTehranIran Optoelectronics and Nanophotonics Research Group Faculty of Electrical and Computer EngineeringTarbiat Modares UniversityTehranIran Graduate School of Engineering Nagoya UniversityFuro-choChikusa-kuNagoya 464-8603Japan

Solar-driven carbon dioxide(CO_(2))conversion including photocatalytic(PC),photoelectrochemical(PEC),photovoltaic plus electrochemical(PV/EC)systems,offers a renewable and scalable way to produce fuels and high-value chemicals for environment and energy *** review summarizes the basic fundament and the recent advances in the field of solar-driven CO_(2)*** the visible-light absorption is an important strategy to improve solar energy conversion *** separation and migration of photogenerated charges carriers to surface sites and the surface catalytic processes also determine the photocatalytic *** engineering including co-catalyst loading,defect engineering,morphology control,surface modification,surface phase junction,and Z-scheme photocatalytic system construction,have become fundamental strategies to obtain high-efficiency *** to photocatalysis,these strategies have been applied to improve the conversion efficiency and Faradaic efficiency of typical PEC *** PV/EC systems,the electrode surface structure and morphology,electrolyte effects,and mass transport conditions affect the activity and selectivity of electrochemical CO_(2)***,the challenges and prospects are addressed for the development of solar-driven CO_(2)conversion system with high energy conversion efficiency,high product selectivity and stability.

关键词： Solar-driven CO_(2)reduction Photocatalytic system Photoelectrochemical system Photovoltaic plus electrochemical system Surface/interface engineering

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