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An Electrical Impedance Imaging System Towards Edge Intelligence for Non-Destructive Testing of Concrete

Tsinghua Science and Technology 2024年第3期29卷 883-896页

作者： Abolfazl roshanpanah Mahdi Abbasi Hani Attar Ayman Amer mohammad r.khosravi Ahmed A.Solyman Department of Electrical Engineering Islamic Azad UniversityScience and Research BranceTehran ***Iran Department of Computer Engineering Bu-Ali Sina UniversityHamedan ***Iran Department of Energy Engineering Zarqa UniversityZarqa 13110Jordan Department of Computer Engineering Persian Gulf UniversityBushehr ***Iran Department of Electrical and Electronics Engineering Faculty of Engineering and ArchitectureNişantaşıUniversityIstanbul 34398Turkey

In the construction industry,to prevent accidents,non-destructive tests are necessary and *** impedance tomography is a new technology in non-invasive imaging in which the image of the inner part of conductive bodies is reconstructed by the arrays of external electrodes that are connected on the periphery of the *** equipment is cheap,fast,and edge *** this imaging method,the image of electrical conductivity distribution(or its opposite;electrical impedance)of the internal parts of the target object is *** image reconstruction process is performed by injecting a precise electric current to the peripheral boundaries of the object,measuring the peripheral voltages induced from it and processing the collected *** an electrical impedance tomography system,the voltages measured in the peripheral boundaries have a non-linear equation with the electrical conductivity *** paper presents a cheap Electrical Impedance Tomography(EIT)instrument for detecting impurities in the concrete.A voltage-controlled current source,a micro-controller,a set of multiplexers,a set of electrodes,and a personal computer constitute the structure of the *** conducted tests on concrete with impurities show that the designed EIT system can reveal impurities with a good accuracy in a reasonable time.

关键词： non-destructive testing system concrete electrical impedance tomography

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Heating-Cooling Monitoring and Power Consumption Forecasting Using LSTM for Energy-Efficient Smart Management of Buildings: A Computational Intelligence Solution for Smart Homes

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Tsinghua Science and Technology 2024年第1期29卷 143-157页

作者： Omid Akbarzadeh Sahand Hamzehei Hani Attar Ayman Amer Nazanin Fasihihour mohammad r.khosravi Ahmed A.Solyman Department of Electronics and Telecommunications Politecnico di TorinoTurin 10129Italy Department of Energy Engineering Zarqa UniversityZarqa 13110Jordan Shandong Provincial University Laboratory for Protected Horticulture Weifang University of Science and TechnologyWeifang 262799China Department of Electrical and Electronics Engineering Faculty of Engineering and ArchitectureNisantası UniversityIstanbul 25370The Republic of Turkiye

Energy management in smart homes is one of the most critical problems for the Quality of Life(QoL)and preserving energy *** of the relevant issues in this subject is environmental contamination,which threatens the world's *** computing-enabled Artificial Intelligence(Al)algorithms can provide impactful solutions to this *** research proposes using one of the recurrent Neural Network(rNN)algorithms known as Long Short-Term Memory(LSTM)to comprehend how it is feasible to perform the cloud/fog/edge-enabled prediction of the building's *** parameters of power electricity,power heating,power cooling,and total power in an office/home in cold-climate cities are considered as our features in the *** on the collected data,we evaluate the LSTM approach for forecasting parameters for the next year to predict energy consumption and online monitoring of the model's performance under various *** implementing the Al predictive algorithm,several existing tools are *** results have been generated through simulations,and we find them promisingforfutureapplications.

关键词： design-builder Besos smart cities smart building neural network Long Short-Term Memory(LSTM)

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High-Performance Flow Classification of Big Data Using Hybrid CPU-GPU Clusters of Cloud Environments

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Tsinghua Science and Technology 2024年第4期29卷 1118-1137页

作者： Azam Fazel-Najafabadi Mahdi Abbasi Hani H.Attar Ayman Amer Amir Taherkordi Azad Shokrollahi mohammad r.khosravi Ahmed A.Solyman Department of Computer Engineering Faculty of EngineeringBu-Ali Sina UniversityHamedan ***Iran Department of Energy Engineering Zarqa UniversityZarqa 13132Jordan Department of Informatics University of OsloOslo 0316Norway Department of Computer Science MalmöUniversityMalmö20506Sweden Shandong Provincial University Laboratory for Protected Horticulture Weifang University of Science and TechnologyWeifang 261100China Department of Electrical and Electronics Engineering NişantaşıUniversityIstanbul 34481742Türkiye

The network switches in the data plane of Software Defined Networking (SDN) are empowered by an elementary process, in which enormous number of packets which resemble big volumes of data are classified into specific flows by matching them against a set of dynamic rules. This basic process accelerates the processing of data, so that instead of processing singular packets repeatedly, corresponding actions are performed on corresponding flows of packets. In this paper, first, we address limitations on a typical packet classification algorithm like Tuple Space Search (TSS). Then, we present a set of different scenarios to parallelize it on different parallel processing platforms, including Graphics Processing Units (GPUs), clusters of Central Processing Units (CPUs), and hybrid clusters. Experimental results show that the hybrid cluster provides the best platform for parallelizing packet classification algorithms, which promises the average throughput rate of 4.2 Million packets per second (Mpps). That is, the hybrid cluster produced by the integration of Compute Unified Device Architecture (CUDA), Message Passing Interface (MPI), and OpenMP programming model could classify 0.24 million packets per second more than the GPU cluster scheme. Such a packet classifier satisfies the required processing speed in the programmable network systems that would be used to communicate big medical data.

关键词： OpenMP Compute Unified Device Architecture(CUDA) Message Passing Interface(MPI) packet classification medical data tuple space algorithm Graphics Processing Unit(GPU)cluster

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Mobile Multimedia Computing in Cyber-Physical Surveillance Services Through UAV-Borne Video-SAr:A Taxonomy of Intelligent Data Processing for IoMT-Enabled radar Sensor Networks

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Tsinghua Science and Technology 2022年第2期27卷 288-302页

作者： mohammad r.khosravi Sadegh Samadi Department of Electrical and Electronics Engineering Shiraz University of TechnologyShiraz 313-71555Iran

This study investigates the different aspects of multimedia computing in Video Synthetic Aperture radar(Video-SAr)as a new mode of radar imaging for real-time remote sensing and *** research also considers new suggestions in the systematic design,research taxonomy,and future trends of radar data *** the conventional modes of SAr imaging,Video-SAr can generate video sequences to obtain online monitoring and green surveillance throughout the day and night(regardless of light sources)in all ***,an introduction to Video-SAr is ***,some specific properties of this imaging mode are ***,this research covers one of the most important aspects of the Video-SAr systems,namely,the systematic design requirements,and also some new types of visual distortions which are different from the distortions,artifacts and noises observed in the conventional imaging *** addition,some topics on the general features and high-performance computing of Video-SAr towards radar communications through Unmanned Aerial Vehicle(UAV)platforms,Internet of Multimedia Things(IoMT),Video-SAr data processing issues,and real-world applications are investigated.

关键词： Video Synthetic Aperture radar(Video-SAr)imaging radar networks radar image processing high-performance computing Internet of Multimedia Things(IoMT) cybersecurity

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Efficient pipelined flow classification for intelligent data processing in IoT

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Digital Communications and Networks 2022年第4期8卷 561-575页

作者： Seyed Navid Mousavi Fengping Chen Mahdi Abbasi mohammad r.khosravi Milad rafiee Department of Computer Engineering Engineering FacultyBu-Ali Sina UniversityHamedanIran Shandong Provincial University Laboratory for Protected Horticulture Weifang University of Science and TechnologyShouguang262700China Telecommunications Group Department of Electrical and Electronic EngineeringShiraz University of TechnologyShirazIran

The packet classification is a fundamental process in provisioning security and quality of service for many intelligent network-embedded systems running in the Internet of Things(IoT).In recent years,researchers have tried to develop hardware-based solutions for the classification of Internet *** to higher throughput and shorter delays,these solutions are considered as a major key to improving the quality of *** of these efforts have attempted to implement a software algorithm on the FPGA to reduce the processing time and enhance the *** proposed architectures,however,cannot reach a compromise among power consumption,memory usage,and throughput *** view of this,the architecture proposed in this paper contains a pipelinebased micro-core that is used in network processors to classify *** this end,three architectures have been implemented using the proposed *** first architecture performs parallel classification based on header *** second one classifies packets in a serial *** last architecture is the pipeline-based classifier,which can increase performance by nine *** proposed architectures have been implemented on an FPGA *** results are indicative of a reduction in memory usage as well as an increase in speedup and *** architecture has a power consumption of is 1.294w,and its throughput with a frequency of 233 MHz exceeds 147 Gbps.

关键词： Efficiency Intelligent flow processing IoT Packet classification Pipeline

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Introducing a new rock abrasivity index using a scaled down disc cutter

Rock Mechanics Bulletin

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rock Mechanics Bulletin 2024年第3期3卷 24-37页

作者： Maziar Moradi mohammad Hossein khosravi Jafar Khademi Hamidi Department of Civil and Environmental Engineering University of StrathclydeGlasgowG11XQUK Department of Mining Engineering Faculty of EngineeringUniversity of BirjandBirjand ***Iran

rock abrasivity influences wear of cutting tools and consequently,performance of mechanized tunneling *** methods have been proposed to evaluate rock abrasivity in recent decades,each one has its own *** this paper,a new method is introduced to estimate wear of disc cutters based on rock cutting tests using scaled down discs(i.e.54 and 72 mm diameter).The discs are made of H13 steel,which is a common steel type in producing real-scale discs,with hardness of 32 and 54 *** small-scale linear rock cutting machine and a new abrasion test apparatus,namely University of Tehran abrasivity test machine,are utilized to perform the *** width of the worn discs is monitored and presented as the function of the accumulated test run to classify the rock *** tests show that by increasing the uniaxial compressive strength(UCS)of the rock samples,wear rate is doubled gradually that reveals the sensitivity of the test procedure to the main pa-rameters affecting the abrasivity of hard *** the rocks with the highest UCS,the normal wear stops after performing 5 to 10 rounds of the tests,and then,deformation of the disc tip is *** abrasivity indices are defined based on the abrasivity tests results and their correlations with Cerchar Abrasivity Index(CAI)and UCS are *** of the established correlations in this study with previous investigations dem-onstrates the sensitivity of the indices to the parameters affecting wear of the disc cutters and repeatability of the outputs obtained from abrasivity tests using scaled down *** of this study can be used to enhance the accuracy of rock abrasivity classifications.

关键词： Mechanized tunneling rock cutting rock abrasivity classification University of Tehran abrasivity test Wear

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A machine learning-guided design and manufacturing of wearable nanofibrous acoustic energy harvesters

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Nano research 2024年第10期17卷 9181-9192页

作者： Negar Hosseinzadeh Kouchehbaghi Maryam Yousefzadeh Aliakbar Gharehaghaji Safoora khosravi Danial Khorsandi reihaneh Haghniaz Ke Cao Mehmet r.Dokmeci mohammad rostami Ali Khademhosseini Yangzhi Zhu Terasaki Institute for Biomedical Innovation Los AngelesCA 91367USA Department of Textile Engineering Amirkabir University of Technology(Tehran Polytechnic)Hafez Avenue*** TehranIran Department of Electrical and Computer Engineering University of British ColumbiaVancouverBC V6T1Z4Canada Chemical Sciences Division Oak Ridge National LaboratoryOak RidgeTN 37831USA Department of Computer Science University of Southern CaliforniaLos AngelesCA 90007USA

Nanofibrous acoustic energy harvesters(NAEHs)have emerged as promising wearable platforms for efficient noise-to-electricity conversion in distributed power energy systems and wearable sound amplifiers for assistive listening ***,their reallife efficacy is hampered by low power output,particularly in the low-frequency range(roduces a novel approach to enhance the performance of NAEHs by applying machine learning(ML)techniques to guide the synthesis of electrospun polyvinylidene fluoride(PVDF)/polyurethane(PU)nanofibers,optimizing their application in wearable *** use a feed-forward neural network along with solving an optimization problem to find the optimal input values of the electrospinning(applied voltage,nozzle-collector distance,electrospinning time,and drum rotation speed)to generate maximum output performance(acoustic-to-electricity conversion efficiency).We first prepared a dataset to train the network to predict the output power given the input variables with high *** introducing the neural network,we fix the network and then solve an optimization problem using a genetic algorithm to search for the input values that lead to the maximum energy harvesting *** ML-guided wearable PVDF/PU NAEH platform can deliver a maximal acoustoelectric power density output of 829μW/cm^(3) within the surrounding noise *** addition,our system can function stably in a broad frequency(0.1-2 kHz)with a high energy conversion efficiency of 66%.Sound recognition analysis reveals a robust correlation exceeding 0.85 among lexically akin terms with varying sound intensities,contrasting with a diminished correlation below 0.27 for words with disparate semantic ***,this work provides a previously unexplored route to utilize ML in advancing wearable NAEHs with excellent practicability.

关键词： wearable electronics acoustic energy harvester machine learning piezoelectric nanogenerator electrospun nanofiber

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Black radish root extract alleviates sodium valproate-induced liver damage via inhibiting mitochondrial membrane potential collapse and oxidative stress in mice

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Asian Pacific Journal of Tropical Biomedicine 2024年第7期14卷 298-306页

作者： mohammad Hadi Zarei Sami Akbulut Maryam Zafari Elham Saghaei Zahra Lorigooini Hossein AminiKhoei Somaye khosravi Elham Bijad Medical Plants research Center Basic Health Sciences InstituteShahrekord University of Medical SciencesShahrekordIran Department of Liver Transplant Institute and Biostatistics Inonu University Faculty of Medicine44280MalatyaTurkey Student research Committee Shahrekord University of Medical SciencesShahrekordIran Physiology and Pharmacology Department School of MedicineShahrekord University of Medical SciencesShahrekordIran Department of Anatomical Sciences School of MedicineShahrekord University of Medical SciencesShahrekordIran

Objective:To explore the effect of black radish(raphanus sativus *** niger)root extract on liver enzymes,oxidative stress,and histopathological alterations in mice with sodium valproate-induced ***:Thirty-two mice were divided into four groups:the control group received drinking water by gavage,the second group was administered with 100 mg/kg of sodium valproate,the third group received 300 mg/kg of black radish root extract,and the fourth group was given both sodium valproate(100 mg/kg)and black radish root extract(300 mg/kg).After 28 days,the mice were euthanized,and serum levels of aspartate aminotransferase(AST),alanine aminotransferase(ALT),and alkaline phosphatase(ALP),along with liver malondialdehyde(MDA),reactive oxygen species(rOS),mitochondrial parameters,tumor necrosis factor-alpha(TNF-α)gene expression,and histopathological changes were ***:Sodium valproate caused hepatic damage in mice,characterized by elevated serum levels of liver enzymes,increased MDA and rOS levels and TNF-αgene expression,as well as histopathological *** black radish root extract significantly alleviated sodium valproate-caused hepatic injury by decreasing the serum levels of ALT and AST,MDA,rOS,TNF-αgene expression,as well as mitochondrial impairment,but did not have a significant effect on sodium valproate-induced histopathological ***:The black radish root extract demonstrates protective effects against sodium valproate-induced liver injury,possibly through mitigating oxidative stress,mitochondrial impairment,and inflammatory mediator expression.

关键词： Black radish raphanus sativus Sodium valproate Hepatotoxicity Oxidative stress Anti-inflammation

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Niosome-encapsulated auraptene reduced the mrNA expression of VEGF-A and PDGFs genes in human retinaderived rPE cell line

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International Journal of Ophthalmology(English edition) 2024年第6期17卷 1028-1035页

作者： Akram Vahidi Teymoor.khosravi Farzad Dastaviz Mehdi Sheikh Arabi Ayyoob khosravi Morteza Oladnabi Student research Committee Golestan University of Medical SciencesGorgan ***Iran Department of Medical Nanotechnology Faculty of Advanced Medical TechnologiesGolestan University of Medical SciencesGorgan ***Iran Stem Cell research Center Golestan University of Medical SciencesGorgan ***Iran Department of Molecular Medicine Faculty of Advanced Medical TechnologiesGolestan University of Medical SciencesGorgan ***Iran Gorgan Congenital Malformations research Center Golestan University of Medical SciencesGorgan ***Iran

AIM:To evaluate the effect of auraptene(AUr)treatment in forms of free and encapsulated in niosome nanoparticles by investigating the mrNA expression level of vascular endothelium growth factor(VEGF)-A and platelet-derived growth factors(PDGFs)in human retinal pigment epithelium(rPE)cell ***:Niosome nanocarriers were produced using two surfactants Span 60 and Tween *** cell line was treated with both free AUr and *** dosage of treatments was calculated using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide(MTT)*** of VEGF-A and PDGF-A,PDGF-B,PDGF-C,PDGF-D genes was measured after total rNA extraction and cDNA synthesis,using real-time polymerase chain reaction(rT-PCr).rESULTS:The highest entrapment efficiency(EE)was achieved by Span 60:cholesterol(1:1)with 64.3%.The half maximal inhibitory concentration(IC50)of free and niosome-encapsulated AUr were 38.5 and 27.78µg/mL,*** study revealed that niosomal AUr had more gradual delivery to the ***-PCr results showed reduced expression levels of VEGF-A,PDGF-A,PDGF-B,PDGF-C,and PDGF-D after treatment with both free and niosomal ***:Niosomal formulation of Span 60:cholesterol(1:1)is an effective drug delivery approach to transfer AUr to rPE ***-A,PDGF-A,PDGF-B,PDGF-C,and PDGF-D are four angiogenic factors,inhibiting which by niosomal AUr may be effective in age-related macular degeneration.

关键词： auraptene niosome age-related macular degeneration angiogenesis nanocarrier

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Impact of umbelliprenin-containing niosome nanoparticles on VEGF-A and CTGF genes expression in retinal pigment epithelium cells

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International Journal of Ophthalmology(English edition) 2024年第1期17卷 7-15页

作者： Farzad Dastaviz Akram Vahidi Teymoor.khosravi Ayyoob khosravi Mehdi Sheikh Arabi Abouzar Bagheri Mohsen rashidi Morteza Oladnabi Stem Cell research Center Golestan University of Medical SciencesGorgan ***Iran Department of Medical Genetics School of Advanced Technologies in MedicineGolestan University of Medical SciencesGorgan ***Iran Student research Committee Golestan University of Medical SciencesGorgan ***Iran Department of Molecular Medicine Faculty of Advanced Medical TechnologiesGolestan University of Medical SciencesGorgan ***Iran Department of Medical Nanotechnology Faculty of Advanced Medical TechnologiesGolestan University of Medical SciencesGorgan ***Iran Department of Clinical Biochemistry and Genetics Faculty of MedicineMazandaran University of Medical SciencesSari ***Iran Department Pharmacology Faculty of MedicineMazandaran University of Medical SciencesSari ***Iran Gorgan Congenital Malformations research Center Golestan University of Medical SciencesGorgan ***Iran

AIM:To investigate the impact of niosome nanoparticles carrying umbelliprenin(UMB),an anti-angiogenic and anti-inflammatory plant compound,on the expression of vascular endothelial growth factor(VEGF-A)and connective tissue growth factor(CTGF)genes in a human retinal pigment epithelium(rPE)-like retina-derived cell ***:UMB-containing niosomes were created,optimized,and ***-like cells were treated with free UMB and UMB-containing *** IC_(50)values of the treatments were determined using an MTT *** expression of VEGF-A and CTGF was evaluated using real-time polymerase chain reaction after rNA extraction and cDNA ***’characteristics,including drug entrapment efficiency,size,dispersion index,and zeta potential were *** UMB had an IC_(50)of 96.2μg/mL,while UMB-containing niosomes had an IC_(50)of 25μg/***:Treatment with UMB-containing niosomes and free UMB resulted in a significant reduction in VEGF-A expression compared to control cells(P=0.001).Additionally,UMB-containing niosomes demonstrated a significant reduction in CTGF expression compared to control cells(P=0.05).However,there was no significant reduction in the expression of both genes in cells treated with free ***:Both free UMB and niosome-encapsulated UMB inhibits VEGF-A and CTGF genes ***,the latter demonstrates significantly greater efficacy,potentially due to the lower UMB dosage and gradual *** findings have implications for anti-angiogenesis therapeutic approaches targeting age-related macular degeneration.

关键词： umbelliprenin niosome age-related macular degeneration vascular endothelial growth factor-A connective tissue growth factor

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