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

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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 economy.World Health Organization(WHO)and many others advised controlling Corona Virus Disease in 2019.The limited treatment resources,medical resources,and unawareness of immunity is an essential horizon to unfold.Among 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)droplets.All countries made masks mandatory to prevent infection.For such enforcement,automatic and effective face detection systems are crucial.This study presents a face mask identification approach for static photos and real-time movies that distinguishes between images with and without masks.To contribute to society,we worked on mask detection of an individual to adhere to the rule and provide awareness to the public or organization.The paper aims to get detection accuracy using transfer learning from Residual Neural Network 50(ResNet-50)architecture and works on detection localization.The 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 architecture.The 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 models.This outstanding work also can be used in video surveillance applications.

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

Improvement of phosphorus uptake,phosphorus use efficiency,and grain yield of upland rice(Oryza sativa L.)in response to phosphate-solubilizing bacteria blended with phosphorus fertilizer

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Pedosphere 2022年第5期32卷 752-763页

作者： Pratibha RAWAT Anita sharma Deepti SHANKHDHAR Shailesh chandra SHANKHDHAR Department of Plant Physiology College of Basic Sciences&HumanitiesGovind Ballabh Pant University of Agriculture&TechnologyPantnagar-263145(India) Department of Microbiology College of Basic Sciences&HumanitiesGovind Ballabh Pant University of Agriculture&TechnologyPantnagar-263145(India)

Phosphorus(P)limitation in soil is a major concern for crop productivity.However,the use of chemical fertilizer is hazardous to the environment and costly.Therefore,the use of phosphate-solubilizing bacteria(PSB)is an eco-friendly approach for a sustainable agricultural system.In the present study,a field trial was conducted for two consecutive years to study the effects of three PSB strains isolated,Bacillus licheniformis,Pantoea dispersa,and Staphylococcus sp.,with different P fertilizer rates on P uptake,P use efficiency(PUE),and grain yield of rice.The activities of soil enzymes were also studied in relation to PSB treatments.Comparative analysis of the yield and biochemical parameters revealed that inoculation of PSB consortium could reduce almost 50%of the recommended P dose in rice cultivation.Three PSB strains in combination with 50%P dose was most effective and showed the highest increases in P uptake and PUE as compared to the uninoculated control.Moreover,the PSB consortium combined with 50%P dose contributed to 50.58%and35.64%yield increases compared to the uninoculated control for 2018 and 2019,respectively.Significant increases in the activities of soil dehydrogenase,alkaline phosphatase,and acid phosphatase were also recorded under PSB treatment.

关键词： bacterial inoculation enzyme activity phosphate solubilization index recommended P dose soil dehydrogenase soil phosphatase

An Acoustic Analysis of Fluctuations for Inter-and Intra-Speaker Variability in Speech Sounds

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Journal of Forensic Science and Medicine 2023年第1期9卷 38-43页

作者： Jasdeep Kaur Kailash chandra Juglan Kush sharma Vishal sharma Department of Physics School of Chemical Engineering and Physical Sciences Lovely Professional UniversityPhagwaraPunjab Data Manager School of Community Medicine and Public HealthPostgraduate Institute of Medical Education and ResearchChandigarh Institute of Forensic Science and Criminology Panjab UniversityChandigarhIndia

Background:Variation in the speech of speakers is a crucial issue for the forensic system.The main reason behind incorrect speaker identification is greater intra-speaker fluctuation.In the forensic state of play,a lot of research has been carried out on speaker identification.However inter variations and intra fluctuations in speakers for the Punjabi language is still a grey area.Aims and Objectives:Our aim is to study acoustic analysis of fluctuations for inter and intra speaker variability in speech sounds.In our study,we will consider Punjabi vowel with consonants.The Statistical methods will be applied to analyze the data;firstly,the Shapiro-Wilk test will be checked for normality and then Levene’s Test to assess the equality of variances.Materials and Method:Five vowels were selected with different consonants.They were combined to make meaningful words.Then these meaningful words were embedded in sentences.Ten speakers participated voluntarily.All are students of A.S College at Khanna in Punjab.The individuals were aged between 20-22 years with no hearing or speech disorder.The voice samples were recorded with help of good quality microphone and by Goldwave software in the sound proof lab.Samples were introduced directly into PRAAT software by the use of a Sony microphone and with sampling rate of 44100 Hz frequency.Acoustic Analysis has been done with help of Goldwave software in form of spectrograms.Results and Conclusion:Each formant shows a different value for inter variations and inter speaker fluctuations.F1 and F2 shows lesser speaker variation than the high-frequency region in F3 and F4,so we can say that in comparison with the lower part,high-frequency regions are more valuable.The assumptions for TWO-WAY ANOVA is violated and hence,we have used the non-parametric Friedman Test and performed its Post hoc analysis.From Posthoc analysis,we can say that F1 and F2(p>0.05)and F2 and F3(p>0.05)gave the same type of results.Hence,from the results of these statistical tests,we can conclude that F1 is recom

关键词： Forensic voice identification Friedman test intervariations and intrafluctuations Punjabi

Feature-based augmentation and classification for tabular data

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CAAI Transactions on Intelligence Technology 2022年第3期7卷 481-491页

作者： Balachander Sathianarayanan yogesh chandra Singh Samant Prahalad S.Conjeepuram Guruprasad Varshin B.Hariharan Nirmala Devi Manickam Amrita School of Engineering Amrita Vishwa VidyapeethamCoimbatoreIndia

Generating synthetic samples for a tabular data is a strenuous task.Most of the time,the columns(features)in the dataset may not follow an ideal distribution function.The objective of the proposed algorithm,Histogram Augmentation Technique(HAT),is to generate a dataset whose distribution is similar to that of the original dataset.This augmentation is achieved based on individual columns,where separate algorithms are designed for continuous and discrete columns.Humans also use features of an object for interpretation.When humans make a judgement,they notice prominent features and characterise the perceived object.However,conventional Machine Learning classifiers are designed and trained on the basis of samples.Taking the features as the basis for classification,Feature Importance Classifier(FIC)has been attempted in this work.FIC treats every feature independent of each other,and ranks the features based on its dependence with the classified label.It has been found that the FIC has the highest accuracy and has improved the accuracy by 5.54%on average,when it's compared to other classifiers.The suggested algorithms have been experimented on five datasets and compared with two augmentation algorithms and four state-of-the-art ML classification algorithms.

关键词： function classifier columns

Assessment of reproductive health service utilization in urban slums: Evidence from Western Rajasthan

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Asian pacific Journal of Reproduction 2023年第2期12卷 52-57页

作者： Jyoti sharma Nitin Kumar Joshi yogesh Kumar Jain Kuldeep Singh Pankaj Bhardwaj School of Public Health All India Institute of Medical SciencesJodhpurIndia Department of Community Medicine and Family Medicine and School of Public Health All India Institute of Medical SciencesJodhpurIndia

Objective:To assess the utilization of reproductive health services in urban slum of Jodhpur city,India.Methods:A community based cross-sectional study was conducted in an urban slums of Jodhpur city amongst 300 married women of reproductive age between March and June 2021.Semi-structured questionnaire was used to gather demographic data and information about utilization of antenatal care(ANC)services,delivery and post-partum services.Results:The majority of females were aged less than 25 years(n=195;65.0%),married after 18 years(n=240;80%),living in extended families(n=265;88.3%)and with monthly family income less than 10000 rupees(n=182;60.7%).Statistically significant associations were found between≥4 ANC visits and educational level of secondary and above(OR 2.47,95%CI 1.03–6.28;P=0.04),older age(OR 15.70,95%CI 14.87–16.54 for women aged 26-35 years,OR 16.14,95%CI 12.12–20.01 for women aged≥36 years;P<0.01),and backward and general castes(OR 15.91,95%CI 13.57–17.85 for backward caste and OR 8.11,95%CI 8.07–8.26 for general category of caste;P<0.01).Seven percent of females had undergone parturition.Older age was associated with higher risks of postpartum complications(OR 1.06,95%CI 1.01–1.57 for women aged 26-35 years,OR 3.56,95%CI 1.29–4.69 for women aged≥36 years;P<0.01).In addition,risks of postpartum complications were associated with backward and general castes(OR 1.69,95%CI 1.34–2.13 for backward classes and OR 5.01,95%CI 4.29–5.31 for general category castes;P<0.01),and more than 4 ANC visits(OR 0.20,95%CI 0.09–0.34;P<0.01).Conclusions:More frequent ANC visits are associated with a lower risk of postpartum complications.Furthermore,a high utilization of reproductive health services represents good implementation of reproductive and child health programme at the peripheral level resulting in a stark rise in maternal health indicators in the state of Rajasthan.

关键词： Female Pregnancy Maternal health Maternal health services Prenatal care Postpartum period Facilities and services utilization Health services accessibility

Hybrid Whale Optimization Algorithm for Resource Optimization in Cloud E-Healthcare Applications

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Computers, Materials & Continua 2022年第6期71卷 5659-5676页

作者： Punit Gupta Sanjit Bhagat Dinesh Kumar Saini Ashish Kumar Mohammad Alahmadi Prakash chandra sharma School of Computing&Information Technology Manipal University JaipurJaipur303007India School of Basic Sciences Manipal University JaipurJaipur303007India Department of Software Engineering College of Computer Science and EngineeringUniversity of JeddahJeddah23218Saudi Arabia

In the next generation of computing environment e-health care services depend on cloud services.The Cloud computing environment provides a real-time computing environment for e-health care applications.But these services generate a huge number of computational tasks,real-time computing and comes with a deadline,so conventional cloud optimizationmodels cannot fulfil the task in the least time and within the deadline.To overcome this issue many resource optimization meta-heuristic models are been proposed but these models cannot find a global best solution to complete the task in the least time and manage utilization with the least simulation time.In order to overcome existing issues,an artificial neural-inspired whale optimization is proposed to provide a reliable solution for healthcare applications.In this work,two models are proposed one for reliability estimation and the other is based on whale optimization technique and neural network-based binary classifier.The predictive model enhances the quality of service using performance metrics,makespan,least average task completion time,resource usages cost and utilization of the system.Fromresults as compared to existing algorithms the proposedANN-WHOalgorithms prove to improve the average start time by 29.3%,average finish time by 29.5%and utilization by 11%.

关键词： Cloud computing whale optimization health care resource optimization

Long-term photometric study of a faint W UMa binary in the direction of M31

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Research in Astronomy and Astrophysics 2017年第11期17卷 59-70页

作者： yogesh chandra Joshi Rukmini Jagirdar Aryabhatta Research Institute of Observational Sciences Manora Peak Nainital 263002 India Center for Advanced Study in Astronomy Osmania University 500007 India

We carry out a re-analysis of the photometric data in Rclc bands which were taken during the Nainital Microlensing Survey from 1998 to 2002 with the aim to detect gravitational microlensing events in the direction of M31. Here, we do photometric analysis of a faint W UMa binary CSS_JO04259.3＋410629 identified in the target field. The orbital period of this star is found to be 0.266402±0.000018 d. The photometric mass ratio, q, is found to be 0.28±0.01. The photometric light curves are investigated using the Wilson-Devinney （WD） code and absolute parameters are determined using empirical relations which provide masses and radii of the binary as M1 = 1.19±0.09M⊙, M2 = 0.33±0.02M⊙ and R1 = 1.02±0.04R⊙, R2 = 0.58±0.08Re respectively based on Rc band data. Quite similar values are found by analyzing/c band data. From the photometric light curve examination, the star is understood to be a low mass-ratio overcontact binary of A-subtype with a high fill-out factor of about 47%. The binary system is found to be located approximately at a distance of 2.64±0.03 kpc having a separation of 2.01 ±0.05 Re between the two components.

关键词： methods： observational -- techniques： photometric -- binaries： eclipsing -- stars： funda- mental parameters

Photometric studies of two W UMa type variables in the field of distant open cluster NGC 6866

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Research in Astronomy and Astrophysics 2016年第4期16卷 87-96页

作者： yogesh chandra Joshi Rukmini Jagirdar Santosh Joshi Aryabhatta Research Institute of Observational Sciences Manora PeakNainital 263002India Center for Advanced Study in Astronomy Osmania UniversityHyderabad 500007India

We present photometric analysis of the two W UMa type binaries identified in the field of distant open star cluster NGC 6866. Although these systems, namely ID487 and ID494, were reported by Joshi et al., a detailed study of these stars has not been carried out before. The orbital periods of these stars are found to be 0.415110±0.000001 day and 0.366709±0.000004 day, respectively. Based on the photometric and infrared colors, we find their respective spectral types to be K0 and K3. The photometric light vari- ations of both stars show the O＇Connell effect which can be explained by employing a dark spot on the secondary components. The V and I band light curves are analyzed using the Wilson-Devinney （WD） code and relations given by Gazeas which yield radii and masses for the binary components of star ID487 of R1 = 1.24 ± 0.01R,R2 = 1.11 4- 0.02Re, and M1 = 1.24 ± 0.02Me, M2 = 0.96 ±0.05Me and for star ID494 of R1 = 1.22 ± 0.02Re, R2 = 0.81 4- 0.01 Re, and M1 = 1.20 4- 0.06 Me, M2 = 0.47 4- 0.01 Me.

关键词： methods： observational -- techniques： photometric -- binaries： eclipsing -- stars： fundamen-tal parameters

Low-cost high entropy alloy(HEA)for high-efficiency oxygen evolution reaction(OER)

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Nano Research 2022年第6期15卷 4799-4806页

作者： Lalita sharma Nirmal Kumar Katiyar Arko Parui Rakesh Das Ritesh Kumar chandra Sekhar Tiwary Abhisek K.Singh Aditi Halder Krishanu Biswas School of Basic Sciences Advanced Materials Research Centre(AMRC)Indian Institute of Technology Mandi(H.P)KamandMandi 175005India Department of Materials Science and Engineering Indian Institute of Technology KanpurKanpur 208016India School of Engineering London South Bank UniversityLondonSE10 AAUK Materials Research Centre Indian Institute of ScienceBangalore 560012India Metallurgical and Materials Engineering Indian Institute of Technology KharagpurKharagpur 382355India

Oxygen evolution reaction(OER)is the key step involved both in water splitting devices and rechargeable metal-air batteries,and hence,there is an urgent need for a stable and low-cost material for efficient OER.In the present investigation,Co-Fe-Ga-NiZn(CFGNZ)high entropy alloy(HEA)has been utilized as a low-cost electrocatalyst for OER.Herein,after cyclic voltammetry activation,CFGNZ-nanoparticles(NPs)are covered with oxidized surface and form high entropy(oxy)hydroxides(HEOs),exhibiting a low overpotential of 370 mV to achieve a current density of 10 mA/cm^(2)with a small Tafel slope of 71 mV/dec.CFGNZ alloy has higher electrochemical stability in comparison to state-of-the art RuO2 electrocatalyst as no degradation has been observed up to 10 h of chronoamperometry.Transmission electron microscopy(TEM)studies after 10 h of long-term chronoamperometry test showed no change in the crystal structure,which confirmed the high stability of CFGNZ.The density functional theory(DFT)based calculations show that the closeness of d(p)-band centers to the Fermi level(EF)plays a major role in determining active sites.This work highlights the tremendous potential of CFGNZ HEA for OER,which is the primary reaction involved in water splitting.

关键词： high entropy alloy cyclic voltammetry activation oxygen evolution reaction electrocatalyst nanocrystalline catalyst