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Masked Face Recognition Using MobileNet V2 with Transfer Learning

Computer Systems Science & Engineering 2023年第4期45卷 293-309页

作者： Ratnesh kumar Shukla arvind kumar tiwari Department of Computer Science&Engineering Dr.APJ Abdul Kalam Technical UniversityLucknow226021India Department of Computer Science&Engineering KNITSultanpur228118Uttar PradeshIndia

Corona virus(COVID-19)is once in a life time calamity that has resulted in thousands of deaths and security *** are using face masks on a regular basis to protect themselves and to help reduce corona virus *** the on-going coronavirus outbreak,one of the major priorities for researchers is to discover effective *** important parts of the face are obscured,face identification and verification becomes exceedingly *** suggested method is a transfer learning using MobileNet V2 based technology that uses deep feature such as feature extraction and deep learning model,to identify the problem of face masked *** the first stage,we are applying face mask detector to identify the face ***,the proposed approach is applying to the datasets from Canadian Institute for Advanced Research10(CIFAR10),Modified National Institute of Standards and Technology Database(MNIST),Real World Masked Face Recognition Database(RMFRD),and Stimulated Masked Face Recognition Database(SMFRD).The proposed model is achieving recognition accuracy 99.82%with proposed *** article employs the four pre-programmed models VGG16,VGG19,ResNet50 and *** extract the deep features of faces with VGG16 is achieving 99.30%accuracy,VGG19 is achieving 99.54%accuracy,ResNet50 is achieving 78.70%accuracy and ResNet101 is achieving 98.64%accuracy with own *** comparative analysis shows,that our proposed model performs better result in all four previous existing *** fundamental contribution of this study is to monitor with face mask and without face mask to decreases the pace of corona virus and to detect persons using wearing face masks.

关键词： Convolutional Neural Network(CNN) deep learning face recognition system COVID-19 dataset and machine learning based models

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Prediction of Alzheimer’s Using Random Forest with Radiomic Features

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Computer Systems Science & Engineering 2023年第4期45卷 513-530页

作者： Anuj Singh Raman kumar arvind kumar tiwari KNIT Sultanpur Sultanpur228118India

Alzheimer’s disease is a non-reversible,non-curable,and progressive neurological disorder that induces the shrinkage and death of a specific neuronal population associated with memory formation and *** is a frequently occurring mental illness that occurs in about 60%–80%of cases of *** is usually observed between people in the age group of 60 years and *** upon the severity of symptoms the patients can be categorized in Cognitive Normal(CN),Mild Cognitive Impairment(MCI)and Alzheimer’s Disease(AD).Alzheimer’s disease is the last phase of the disease where the brain is severely damaged,and the patients are not able to live on their *** is an approach to extracting a huge number of features from medical images with the help of data characterization ***,105 number of radiomic features are extracted and used to predict the alzhimer’*** paper uses Support Vector Machine,K-Nearest Neighbour,Gaussian Naïve Bayes,eXtreme Gradient Boosting(XGBoost)and Random Forest to predict Alzheimer’s *** proposed random forest-based approach with the Radiomic features achieved an accuracy of 85%.This proposed approach also achieved 88%accuracy,88%recall,88%precision and 87%F1-score for AD ***,it achieved 72%accuracy,73%recall,72%precisionand 71%F1-score for AD *** and it achieved 69%accuracy,69%recall,68%precision and 69%F1-score for MCI *** comparative analysis shows that the proposed approach performs better than others approaches.

关键词： Alzheimer’s disease radiomic features cognitive normal support vector machine mild cognitive impairment extreme gradient boosting random forest

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Improvements in Weather Forecasting Technique Using Cognitive Internet of Things

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Computer Systems Science & Engineering 2023年第9期46卷 3767-3782页

作者： Kaushlendra Yadav Anuj Singh arvind kumar tiwari KNIT Sultanpur Sultanpur228118India

Forecasting the weather is a challenging task for human beings because of the unpredictable nature of the ***,effective forecasting is vital for the general growth of a country due to the significance of weather forecasting in science and *** primary motivation behind this work is to achieve a higher level of forecasting accuracy to avoid any ***,most weather forecasting work is based on initially observed numerical weather data that cannot fully cover the changing essence of the *** this work,sensors are used to collect real-time data for a particular location to capture the varying nature of the *** solution can give the anticipated results with the least amount of human engagement by combining human intelligence and machine learning with the help of the cognitive Internet of *** Authors identified weatherrelated parameters such as temperature,humidity,wind speed,and rainfall and then applied cognitive data collection methods to train and validate their *** addition,the Authors have examined the efficacy of various machine learning algorithms by using them on both data sets i.e.,pre-recorded metrological data sets and live sensor data sets collected from multiple *** Authors noticed that the results were superior on the sensor *** Authors developed ensemble learning model using stacked method that achieved 99.25%accuracy,99%recall,99%precision,and 99%F1-score for Sensor *** also achieved 85%accuracy,86%recall,85%precision,and 86%F1 score for Australian rainfall data.

关键词： Internet of Things machine learning weather forecast cognitive computing predictors

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Intricacies during pregnancy with gestational diabetes mellitus

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World Journal of Clinical Cases 2025年第1期13卷 62-64页

作者： Richa Rattan Rimesh Pal Parul Chawla Gupta arvind kumar Morya Ripunjay Prasad Department of Endocrinology Post Graduate Institute of Medical Education and ResearchChandigarh 160012India Department of Ophthalmology Post Graduate Institute of Medical Education and ResearchChandigarh 160012PunjabIndia Department of Ophthalmology All India Institute of Medical SciencesHyderabad 508126TelanganaIndia Department of Ophthalmology RP Eye InstituteDelhi 110001India

The study by Cao et al aimed to identify early second-trimester biomarkers that could predict gestational diabetes mellitus(GDM)development using advanced proteomic techniques,such as Isobaric tags for relative and absolute quantitation isobaric tags for relative and absolute quantitation and liquid chromatography-mass spectrometry liquid chromatography-mass *** analysis revealed 47 differentially expressed proteins in the GDM group,with retinol-binding protein 4 and angiopoietin-like 8 showing significantly elevated serum levels compared to *** these findings are promising,the study is limited by its small sample size(n=4 per group)and lacks essential details on the reproducibility and reliability of the protein quantification methods ***,the absence of experimental validation weakens the interpretation of the protein-protein interaction network identified through bioinformatics *** study's focus on second-trimester biomarkers raises concerns about whether this is a sufficiently early period to implement preventive interventions for *** GDM risk during the first trimester or pre-conceptional period may offer more clinical *** its limitations,the study presents valuable insights into potential GDM biomarkers,but larger,well-validated studies are needed to establish their predictive utility and generalizability.

关键词： Gestational diabetes mellitus Biomarkers Differentially expressed proteins Retinol-binding protein 4 Angiopoietin-like 8 Proteomics Lifestyle interventions Early prediction

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A nonautonomous mat hematical model to assess the impact of algae on the abatement of atmospheric carbon dioxide

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International Journal of Biomathematics 2021年第7期14卷 227-264页

作者： Pankaj kumar tiwari Rajesh kumar Singh Debaldev Jana Yun Kang arvind kumar Misra Department of Basic Science and Humanities Indian Institute of Information Technology Bhagalpur 813210 India Government Shahid Kedamath P.G.College Mauganj Rewa 486331India Department of Mathematics&SRM Research Institute SRM Institute of Science and Technology Kattankulathur 603203 Tamil NaduIndia Science and Mathematics Faculty Arizona State University Mesa AZ 85212USA Department of Mathematics Institute of Science Banaras Hindu UniversityVaranasi 221005India

The world's oceans have played an important role in sequestering atmospheric carbon dioxide through solubility and the action of *** of atmospheric carbon dioxide by photoautotrophic algal cultures has the potential to diminish the release of carbon dioxide into the atmosphere,thereby helping to alleviate the trend toward global *** work investigates the role of algae in controlling the level of atmospheric carbon *** Rank Correlation Coefficients(PRCCs)technique is used to address how the concentration of atmospheric carbon dioxide is affected by changes in a specific parameter disregarding the uncertainty over the rest of the model *** related to algal growth are shown to significantly reduce the level of atmospheric CO_(2).Further,we explore the dynamics of nonautonomous system by incorporating the seasonal variations of sonic ecologically important model *** nonautonomous system exhibits globally attractive positive periodic solution,and also the appearance of double periodic solution is ***,by letting the seasonally forced parameters as almost periodic functions of time,we show almost periodic behavior of the *** findings suggest that the policy makers should focus on continuous addition of nutrients in the ocean to accelerate the algal growth thereby reducing the level of carbon dioxide in the atmosphere.

关键词： Mathematical model algae atmospheric CO2 sensitivity analysis:seasonality periodic solution

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ηmesons in hot magnetized nuclear matter

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Chinese Physics C 2022年第2期46卷 160-177页

作者： Rajesh kumar arvind kumar Department of Physics Dr.B R Ambedkar National Institute of Technology JalandharJalandhar-144011PunjabIndia

ηN interactions are investigated in hot magnetized asymmetric nuclear matter using the chiral SU(3)model and chiral perturbation theory(ChPT).In the chiral modcl,thc in-medium properties of η-mesons are calcu-lated using medium modified scalar densities under the influence of an extermal magnetic ***,in a com-bined chiral model and ChPT approach,off-shell contributions of the ηN interactions are evaluated from the ChPTeffective ηN Lagrangian,and the in-medium effect of scalar densities are incorporated from the chiral SU(3)*** find that the magnetic field has a significant effect on the in-medium mass and optical potential of η mesons,andwe observe a deeper mass-shift in the combined chiral model and ChPT approach than in the solo chiral SU(3)*** both approaches,no additional mass-shift is observed due to the uncharged nature of η mesons in the presenceof a magnetic field.

关键词： hadron physics ηinteractions in-medium mesons

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Charmonia and bottomonia in asymmetric magnetized hot nuclear matter

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Chinese Physics C 2019年第12期43卷 141-158页

作者： Rajesh kumar arvind kumar Department of Physics Dr.B R Ambedkar National Institute of Technology Jalandhar

We investigate the mass-shift of P-wave charmonium(χc0,χc1),and S and P-wave bottomonium(ηb,■,χb0,andχb1)states in magnetized hot asymmetric nuclear matter using the unification of QCD sum rules(QCDSR)and the chiral S U(3)*** QCDSR,we use two approaches,i.e.,the moment sum rule and the Borel sum *** magnetic field induced scalar gluon condensateand the twist-2 gluon operatorcalculated in the chiral S U(3)model are utilised in QCD sum rules to calculate the in-medium mass-shift of the above *** attractive mass-shift of these mesons is observed,which is more sensitive to magnetic field in the high density regime for charmonium,however less so for *** results may be helpful to understand the decay of higher quarkonium states to the lower quarkonium states in asymmetric heavy ion collision experiments.

关键词： heavy mesons hot and dense matter finite magnetic field QCD sum rules chiral model

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Reliability assessment of deep excavations in spatially random cohesion weakening friction strengthening massive rocks:Application to nuclear repositories

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Underground Space 2023年第6期13卷 48-73页

作者： Akshay kumar Gaurav tiwari Department of Civil Engineering Indian Institute of Technology KanpurKanpurUttar Pradesh 208016India

An augmented methodology is developed to estimate the reliability of deep excavations along spatially variable massive rock masses using the cohesion weakening friction strengthening(CWFS)*** parameters of the CWFS model were initially identified using Sobol’s global sensitivity analysis based on their influence on the displacements and excavation damage zone around *** probability of failure was estimated by performing Mont–Carlo Simulations on random finite difference models of excavations generated via MATLAB-FLAC2D coupling,considering the spatial variation of these sensitive *** variation was modeled by generating anisotropic random fields of sensitive CWFS parameters via the recently developed Fourier series method and updated correlations suggested by Walton(2019).The proposed methodology was demonstrated for a proposed deep nuclear waste repository to be located in *** from the developed methodology were systematically compared with those of traditional reliability(ignoring spatial variation)and deterministic methods(ignoring uncertainty).Although the developed methodology was computationally complex,it was judged to be the most realistic due to the realistic consideration of heterogeneous distributions of rock *** methodologies underestimate/overestimate the excavation performance due to negligence of uncertainty and spatial ***,a parametric analysis was performed using developed methodology by varying the initial friction angle,scale of fluctuations(SOFs)and dilation *** effect of initial friction angle was observed to be more pronounced on the probability of failures as compared to SOFs and dilation *** observations were made related to the excavation damage zone(EDZ)development quantified using yield area ratio.

关键词： Deep excavations Brittle failures CWFS model Sobol’s sensitivity Moving least square response surface Fourier series random field

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Thermodynamic properties and phase diagram of quark matter within non-extensive Polyakov chiral SU(3)quark mean field model

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Chinese Physics C 2024年第5期48卷 60-71页

作者： Dhananjay Singh arvind kumar Department of Physics Dr.B R Ambedkar National Institute of Technology JalandharJalandhar–144008PunjabIndia

In the present study,we applied Tsallis non-extensive statistics to investigate the thermodynamic properties and phase diagram of quark matter in the Polyakov chiral SU(3)quark mean field *** this model,the properties of the quark matter were modified through the scalar fieldsσ,ζ,δ,χ,vector fieldsω,ρ,ϕ,and Polyakov fieldsΦandΦ¯at finite temperature and chemical ***-extensive effects were introduced through a dimensionless parameter q,and the results were compared to those of the extensive case(q→1).In the non-extensive case,the exponential in the Fermi-Dirac(FD)function was modified to a q-exponential *** influence of the q parameter on the thermodynamic properties,pressure,energy,and entropy density,as well as trace anomaly,was *** speed of sound and specific heat with non-extensive effects were also ***,the effect of non-extensivity on the deconfinement phase transition as well as the chiral phase transition of u,d,and s quarks was *** found that the critical end point(CEP),which defines the point in the(T−μ)phase diagram where the order of the phase transition changes,shifts to a lower value of temperature,TCEP,and a higher value of chemical potential,μCEP,as the non-extensivity is increased,that is,q>1.

关键词： quark matter quark mean field model QCD phase diagram non-extensive statistics

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Nonlinear analysis of traffic jams in an anisotropic continuum model

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Chinese Physics B 2010年第11期19卷 156-164页

作者： arvind kumar Gupta Sapna Sharma Department of Mathematics IIT Ropar-140001India Mathematics Group Birla Institute of Technology and SciencePilani-333031India

This paper presents our study of the nonlinear stability of a new anisotropic continuum traffic flow model in which the dimensionless parameter or anisotropic factor controls the non-isotropic character and diffusive influence. In order to establish traff^c flow stability criterion or to know the critical parameters that lead, on one hand, to a stable response to perturbations or disturbances or, on the other hand, to an unstable response and therefore to a possible congestion, a nonlinear stability criterion is derived by using a wavefront expansion technique. The stability criterion is illustrated by numerical results using the finite difference method for two different values of anisotropic parameter. It is also been observed that the newly derived stability results are consistent with previously reported results obtained using approximate linearisation methods. Moreover, the stability criterion derived in this paper can provide more refined information from the perspective of the capability to reproduce nonlinear traffic flow behaviors observed in real traffic than previously established methodologies.

关键词： traffic flow non-linear stability wavefront method

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