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Deep Learning-Based Mask Identification System Using ResNet Transfer Learning Architecture

Computer Systems Science & Engineering 2024年第2期48卷 341-362页

作者： arpit jain Nageswara Rao Moparthi A.Swathi Yogesh Kumar Sharma Nitin mittal Ahmed Alhussen Zamil S.Alzamil MohdAnul Haq Department of Computer Science and Engineering KoneruLakshmaiah Education FoundationVaddeswaram522302India Department of Computer Science and Engineering Sreyas Institute of Engineering and TechnologyHyderabad500068India University Centre for Research and Development Chandigarh UniversityMohali140413India Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl-Majmaah11952Saudi Arabia

Recently,the coronavirus disease 2019 has shown excellent attention in the global community regarding health and the *** Health Organization(WHO)and many others advised controlling Corona Virus Disease in *** limited treatment resources,medical resources,and unawareness of immunity is an essential horizon to *** all resources,wearing a mask is the primary non-pharmaceutical intervention to stop the spreading of the virus caused by Severe Acute Respiratory Syndrome Coronavirus 2(SARS-CoV-2)*** countries made masks mandatory to prevent *** such enforcement,automatic and effective face detection systems are *** study presents a face mask identification approach for static photos and real-time movies that distinguishes between images with and without *** contribute to society,we worked on mask detection of an individual to adhere to the rule and provide awareness to the public or *** paper aims to get detection accuracy using transfer learning from Residual Neural Network 50(ResNet-50)architecture and works on detection *** experiment is tested with other popular pre-trained models such as Deep Convolutional Neural Networks(AlexNet),Residual Neural Networks(ResNet),and Visual Geometry Group Networks(VGG-Net)advanced *** proposed system generates an accuracy of 98.4%when modeled using Residual Neural Network 50(ResNet-50).Also,the precision and recall values are proved as better when compared to the existing *** outstanding work also can be used in video surveillance applications.

关键词： Transfer learning depth analysis convolutional neural networks(CNN) COVID-19

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Liquefaction proneness of stratified sand-silt layers based on cyclic triaxial tests

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Journal of Rock Mechanics and Geotechnical Engineering 2023年第7期15卷 1826-1845页

作者： arpit jain.satyendra mittal Sanjay Kumar Shukla Department of Civil Engineering Indian Institute of TechnologyRoorkeeUttarakhandIndia School of Engineering Edith Cowan UniversityJoondalupPerthAustralia Department of Civil Engineering Indian Institute of Technology MadrasChennaiIndia Department of Civil Engineering BIT SindriIndia

Most studies on liquefaction have addressed homogeneous soil strata using sand or sand with fine content without considering soil *** this study,cyclic triaxial tests were conducted on the stratified sand specimens embedded with the silt layers to investigate the liquefaction failures and void-redistribution at confining stress of 100 kPa under stress-controlled *** loosening of underlying sand mass and hindrance to pore-water flow caused localized bulging at the sand-silt *** is observed that at a silt thickness of 0.2H(H is the height of the specimen),nearly 187 load cycles were required to attain liquefaction,which was the highest among all the silt thicknesses with a single silt ***,0.2H is assumed as the optimum silt thickness(t_(opt)).The silt was placed at the top,middle and bottom of the specimen to understand the effect of silt layer *** to the increase in depth of the silt layer from the top position(capped soil state)to the bottom,the cycles to reach liquefaction(N_(cyc,L))increased 2.18 ***,when the number of silt layers increased from single to triple,there was an increase of about 880%in N_(cyc,L).The micro-characterization analysis of the soil specimens indicated silty materials transported in upper sections of the specimen due to the dissipated pore *** main parameters,including thickness(t),location(z),cyclic stress ratio(CSR),number of silt layers(n)and modified relative density(D_(r,m)),performed significantly in governing the lique-faction *** this,a multilinear regression model is developed based on critical parameters for prediction of N_(cyc,L).Furthermore,the developed constitutive model has been validated using the data from the present study and earlier findings.

关键词： Cyclic triaxial tests Soil stratification Soil liquefaction Regression model

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Image smog restoration using oblique gradient profile prior and energy minimization

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Frontiers of Computer Science 2021年第6期15卷 147-153页

作者： Ashok KUMAR arpit jain College of Computing Science and Information Technogy TeerthankerMahaveer UniversityMoradabad 244001India

Removing the smog from digital images is a challenging pre-processing tool in various imaging ***,many smog removal(i.e.,desmogging)models are proposed so far to remove the effect of smog from *** desmogging models are based upon a physical model,it means it requires efficient estimation of transmission map and atmospheric veil from a single smoggy ***,many prior based restoration models are proposed in the literature to estimate the transmission map and an atmospheric ***,these models utilized computationally extensive minimization of an energy ***,the existing restoration models suffer from various issues such as distortion of texture,edges,and ***,in this paper,a convolutional neural network(CNN)is used to estimate the physical attributes of smoggy *** gradient channel prior(OGCP)is utilized to restore the smoggy ***,a dataset of smoggy and sunny images are ***,we have trained CNN to estimate the smog gradient from smoggy ***,based upon the computed smog gradient,OGCP is utilized to restore the still smoggy *** analyses reveal that the proposed CNN-OGCP based desmogging model outperforms the existing desmogging models in terms of various performance metrics.

关键词： convolutional neural networks desmogging smog oblique gradient channel prior

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Multilayer Neural Network Based Speech Emotion Recognition for Smart Assistance

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Computers, Materials & Continua 2023年第1期74卷 1523-1540页

作者： Sandeep Kumar MohdAnul Haq arpit jain C.Andy Jason Nageswara Rao Moparthi Nitin mittal Zamil S.Alzamil Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaramAP522502India Department of Computer Science College of Computer and Information SciencesMajmaah University11952Al-MajmaahSaudi Arabia Department of Computer Science and Engineering Teerthanker Mahaveer UniversityMoradabadUttar Pradesh244001India Department of Electronics and Communication Engineering Sreyas Institute of Engineering and TechnologyHyderabad500068India University Centre for Research and Development Chandigarh UniversityMohali140413PunjabIndia

Day by day,biometric-based systems play a vital role in our daily *** paper proposed an intelligent assistant intended to identify emotions via voice message.A biometric system has been developed to detect human emotions based on voice recognition and control a few electronic peripherals for alert *** proposed smart assistant aims to provide a support to the people through buzzer and light emitting diodes(LED)alert signals and it also keep track of the places like households,hospitals and remote areas,*** proposed approach is able to detect seven emotions:worry,surprise,neutral,sadness,happiness,hate and *** key elements for the implementation of speech emotion recognition are voice processing,and once the emotion is recognized,the machine interface automatically detects the actions by buzzer and *** proposed system is trained and tested on various benchmark datasets,i.e.,Ryerson Audio-Visual Database of Emotional Speech and Song(RAVDESS)database,Acoustic-Phonetic Continuous Speech Corpus(TIMIT)database,Emotional Speech database(Emo-DB)database and evaluated based on various parameters,i.e.,accuracy,error rate,and *** comparing with existing technologies,the proposed algorithm gave a better error rate and less *** rate and time is decreased by 19.79%,5.13 *** the RAVDEES dataset,15.77%,0.01 s for the Emo-DB dataset and 14.88%,3.62 for the TIMIT *** proposed model shows better accuracy of 81.02%for the RAVDEES dataset,84.23%for the TIMIT dataset and 85.12%for the Emo-DB dataset compared to Gaussian Mixture Modeling(GMM)and Support Vector Machine(SVM)Model.

关键词： Speech emotion recognition classifier implementation feature extraction and selection smart assistance

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Performance Analysis of AODV Routing forWireless Sensor Network in FPGA Hardware

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Computer Systems Science & Engineering 2022年第3期40卷 1073-1084页

作者： Namit Gupta Kunwar Singh Vaisla arpit jain Adesh Kumar Rajeev Kumar Department of Computer Science&Engineering Uttarakhand Technical UniversityDehradun248007India Department of Computer Science B T Kumaon Institute of Technology DwarahatIndia Faculty of Engineering&CS Teerthanker Mahaveer UniversityMoradabadIndia Department of Electrical&Electronics Engineering School of EngineeringUniversity of Petroleum and Energy StudiesDehradun248007India

Wireless sensor network(WSN)is a group of interconnected sensor nodes that work wirelessly to capture the information of *** routing of the network is a challenging *** routing of WSN is classified as proactive,reactive,and *** on-demand distance vector(AODV)routing is an example of reactive routing based on the demand route formations among different nodes in the *** research article emphasizes the design and simulation of the AODV routing hardware chip using very-high-speed integrated circuit hardware description language(VHDL)programming in Xilinx integrated synthesis environment(ISE)14.7 *** performance of the chip is studied based on the field-programmable gate array(FPGA)hardware parameters such as slices,lookup table(LUTs),input/output block(IOB),flipflops,and memory for the different configurations of the network(N=10,20….100).The delay and frequency are also estimated on the Virtex-5 *** performance of the WSN with AODV routing is also analyzed based on the packet delivery ratio,throughput,delay,and control *** simulation test cases verified the 8-bit,64-bit,and 128-bit data communication within the nodes.

关键词： Wireless sensor network FPGA synthesis AODVrouting simulation and synthesis VHDL simulation

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Design and Simulation of Ring Network-on-Chip for Different Configured Nodes

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Computers, Materials & Continua 2022年第5期71卷 4085-4100页

作者： arpit jain Rakesh Kumar Dwivedi Hammam Alshazly Adesh Kumar Sami Bourouis Manjit Kaur Faculty of Engineering&Computer Sciences Teerthanker Mahaveer UniversityMoradabadUttar Pradesh244001India Faculty of Computers and Information South Valley UniversityQena83523Egypt Department of Electrical and Electronics Engineering School of EngineeringUniversity of Petroleum and Energy StudiesDehradun248007India Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia School of Engineering and Applied Sciences Bennett UniversityGreater Noida201310India

The network-on-chip(NoC)technology is frequently referred to as a front-end solution to a back-end *** physical substructure that transfers data on the chip and ensures the quality of service begins to collapse when the size of semiconductor transistor dimensions shrinks and growing numbers of intellectual property(IP)blocks working together are integrated into a *** system on chip(SoC)architecture of today is so complex that not utilizing the crossbar and traditional hierarchical bus *** connectivity reduces the amount of hardware required for routing and functions,allowing SoCs with NoC interconnect fabrics to operate at higher ***(Octagons)is a direct NoC that is specifically used to solve the scalability problem by expanding each node in the shape of an *** paper discusses the ring NoC design concept and its simulation in Xilinx ISE 14.7,as well as the communication of functional *** the field-programmable gate array(FPGA)synthesis,the performance of NoC is evaluated in terms of hardware and timing *** design allows 64 to 256 node communication in a single chip with‘N’bit data transfer in the ring *** performance of the NoC is evaluated with variable nodes from 2 to 256 in Digilent manufactured Virtex-5 FPGA hardware.

关键词： Ring NoC FPGA synthesis nodes communication SoC design integrated synthesis environment

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Higher Plant Proteins of Cyanobacterial Origin:Are They or Are They Not Preferentially Targeted to Chloroplasts?

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Molecular Plant 2014年第12期7卷 1797-1800页

作者： Roman G.Bayer Tina Kostler, arpit jain Simon Stael Ingo Ebersberger Markus Teige Department of Biochemistry and Cell Biology MFPLUniversity of ViennaDr Bohr Gasse 9A-1030 ViennaAustria CIBIV—Center for Integrative Bioinformatics Vienna MFPLDr.Bohr Gasse 9A-1030 ViennaAustria Department for Applied Bioinformatics Institute for Cell Biology and NeuroscienceGoethe UniversityMax-von-Laue Str.13D-60438 FrankfurtGermany VIB Department of Plant Systems Biology Ghent UniversityTechnologiepark 9279052 GentBelgium Department of Ecogenomics and Systems Biology University of ViennaAlthanstr 14A-1090 ViennaAustria Department of Applied Genetics and Cell Biology University of Natural Resources and Life SciencesMuthgasse 18A-1190 ViennaAustria

Dear Editor, What does the evolutionary origin of a plant protein tell about its subcellular localization？ Naively thinking, one would assume that plant proteins that were originally encoded in the endosymbiont genome are targeted to the chloroplast. However, published data seem to support only a loose link between evolutionary origin and subcel- lular localization. About half of the Arabidopsis proteins with a detectable cyanobacterial ortholog are targeted to subcellular compartments other than the chloroplast （Martin et al., 2002）. H

关键词： Plant protein The origin of evolution chloroplast

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Co-relation of SARS-CoV-2 related 30-d mortality with HRCT score and RT-PCR Ct value-based viral load in patients with solid malignancy

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World Journal of Clinical Oncology 2022年第5期13卷 339-351页

作者： Satya Narayan Vineet Talwar Varun Goel Krushna Chaudhary Anurag Sharma Pallavi Redhu Satyajeet Soni arpit jain Department of Medical Oncology Rajiv Gandhi Cancer Institute and Research CentreNew Delhi 110085India Department of Research Rajiv Gandhi Cancer Institute and Research CentreNew Delhi 110085India

BACKGROUND Coronavirus disease 2019(COVID-19)patients with malignancy are published worldwide but are lacking in data from *** To characterize COVID-19 related mortality outcomes within 30 d of diagnosis with HRCT score and RT-PCR Ct value-based viral load in various solid *** Patients included in this study were with an active or previous malignancy and with confirmed severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)infection from the institute *** collected data on demographic details,baseline clinical conditions,medications,cancer diagnosis,treatment and the COVID-19 disease *** primary endpoint was the association between the mortality outcome and the potential prognostic variables,specially,HRCT score,RT-PCR Ct value-based viral load,*** logistic regression analyses treatment received in 30 *** Out of 131 patients,123 met inclusion criteria for our *** median age was 57 years(interquartile range=19-82)while 7(5.7%)were aged 75 years or *** most prevalent malignancies were of GUT origin 49(39.8%),hepatopancreatobiliary(HPB)40(32.5%).109(88.6%)patients were on active anticancer treatment,115(93.5%)had active(measurable)*** analysis on May 20,2021,26(21.1%)patients had *** logistic regression analysis,independent factors associated with an increased 30-d mortality were in patients with the symptomatic *** in the last 4 wk,number of comorbidities(≥2 vs none:3.43,1.08-8.56).The univariate analysis showed that the risk of death was significantly associated with the HRCT score:for moderate(8-15)[odds ratio(OR):3.44;95%confidence interval(CI):1.3-9.12;P=0.0132],severe(>15)(OR:7.44;95%CI:1.58-35.1;P=0.0112).CONCLUSION To the best of our knowledge,this is the first study from India reporting the association of HRCT score and RT-PCR Ct value-based 30-d mortality outcomes in SARS-CoV-2 infected cancer patients.

关键词： SARS-CoV-2 COVID-19 Cancer HRCT Viral load

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