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Fruit Image Classification Using Deep Learning

Computers, Materials & Continua 2022年第6期71卷 5135-5150页

作者： harmandeep singh gill Osamah Ibrahim Khalaf Youseef Alotaibi Saleh Alghamdi Fawaz Alassery Department of Computer Science Guru Arjan Dev Khalsa College Chohla Sahib143408PunjabIndia Al-Nahrain University Al-Nahrain Nano-Renewable Energy Research CenterBaghdad964Iraq Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Engineering College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

Fruit classification is found to be one of the rising fields in computer and machine *** deep learning-based procedures worked out so far to classify images may have some ill-posed *** performance of the classification scheme depends on the range of captured images,the volume of features,types of characters,choice of features from extracted features,and type of classifiers *** paper aims to propose a novel deep learning approach consisting of Convolution Neural Network(CNN),Recurrent Neural Network(RNN),and Long Short-TermMemory(LSTM)application to classify the fruit *** accuracy depends on the extracted and selected optimal *** learning applications CNN,RNN,and LSTM were collectively involved to classify the *** is used to extract the image *** is used to select the extracted optimal features and LSTM is used to classify the fruits based on extracted and selected images features by CNN and *** study shows the supremacy of proposed over existing Support Vector Machine(SVM),Feed-forwardNeural Network(FFNN),and Adaptive Neuro-Fuzzy Inference System(ANFIS)competitive techniques for fruit images *** accuracy rate of the proposed approach is quite better than the SVM,FFNN,and ANFIS *** has been concluded that the proposed technique outperforms existing schemes.

关键词： Image classification feature extraction type-II fuzzy logic integrator generator deep learning

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Design of a Lightweight Compressed Video Stream-Based Patient Activity Monitoring System

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Computers, Materials & Continua 2024年第1期78卷 1253-1274页

作者： Sangeeta Yadav Preeti Gulia Nasib singh gill Piyush Kumar Shukla Arfat Ahmad Khan Sultan Alharby Ahmed Alhussen Mohd Anul Haq Department of Computer Science&Applications Maharshi Dayanand UniversityRohtak124001India University Institute of Technology Rajiv Gandhi Proudyogiki VishwavidyalayaBhopal462033India Department of Computer Science College of ComputingKhon Kaen UniversityKhon Kaen40002Thailand Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl Majmaah11952Kingdom of Saudi Arabia Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityAl Majmaah11952Kingdom of Saudi Arabia

Inpatient falls from beds in hospitals are a common *** falls may result in severe *** problem can be addressed by continuous monitoring of patients using *** advancements in deep learning-based video analytics have made this task of fall detection more effective and *** with fall detection,monitoring of different activities of the patients is also of significant concern to assess the improvement in their *** computation-intensive models are required to monitor every action of the patient *** requirement limits the applicability of such ***,to keep the model lightweight,the already designed fall detection networks can be extended to monitor the general activities of the patients along with the fall *** by the same notion,we propose a novel,lightweight,and efficient patient activity monitoring system that broadly classifies the patients’activities into fall,activity,and rest classes based on their *** whole network comprises three sub-networks,namely a Convolutional Neural Networks(CNN)based video compression network,a Lightweight Pose Network(LPN)and a Residual Network(ResNet)Mixer block-based activity recognition *** compression network compresses the video streams using deep learning networks for efficient storage and retrieval;after that,LPN estimates human ***,the activity recognition network classifies the patients’activities based on their *** proposed system shows an overall accuracy of approx.99.7% over a standard dataset with 99.63% fall detection accuracy and efficiently monitors different events,which may help monitor the falls and improve the inpatients’health.

关键词： Fall detection activity recognition human pose estimation accuracy

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Comparative analysis of proficiencies of various textures and geometric features in breast mass classification using k-nearest neighbor

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Visual Computing for Industry,Biomedicine,and Art 2022年第1期5卷 25-43页

作者： harmandeep singh Vipul Sharma Damanpreet singh Department of Computer Science and Engineering IKG Punjab Technical UniversityJalandharPunjab 144603India Department of Computer Science and Engineering Sant Longowal Institute of Engineering and TechnologySangrurPunjab 148106India

This paper introduces a comparative analysis of the proficiencies of various textures and geometric features in the diagnosis of breast masses on *** improved machine learning-based framework was developed for this *** proposed system was tested using 106 full field digital mammography images from the INbreast dataset,containing a total of 115 breast mass *** proficiencies of individual and various combinations of computed textures and geometric features were investigated by evaluating their contributions towards attaining higher classification *** state-of-the-art filter-based feature selection algorithms(Relief-F,Pearson correlation coefficient,neighborhood component analysis,and term variance)were employed to select the top 20 most discriminative *** Relief-F algorithm outperformed other feature selection algorithms in terms of classification results by reporting 85.2%accuracy,82.0%sensitivity,and 88.0%specificity.A set of nine most discriminative features were then selected,out of the earlier mentioned 20 features obtained using Relief-F,as a result of further *** classification performances of six state-of-the-art machine learning classifiers,namely k-nearest neighbor(k-NN),support vector machine,decision tree,Naive Bayes,random forest,and ensemble tree,were investigated,and the obtained results revealed that the best classification results(accuracy=90.4%,sensitivity=92.0%,specificity=88.0%)were obtained for the k-NN classifier with the number of neighbors having k=5 and squared inverse distance *** key findings include the identification of the nine most discriminative features,that is,FD26(Fourier Descriptor),Euler number,solidity,mean,FD14,FD13,periodicity,skewness,and contrast out of a pool of 125 texture and geometric *** proposed results revealed that the selected nine features can be used for the classification of breast masses in mammograms.

关键词： Mammography Breast cancer Machine learning Classification

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Exploring influential factors and endogeneity of traffic flow of different lanes on urban freeways using Bayesian multivariate spatial models

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Journal of Traffic and Transportation Engineering(English Edition) 2023年第1期10卷 104-115页

作者： Yongping Zhang Gurdiljot singh gill Wen Cheng Paulina Reina Mankirat singh Department of Civil Engineering California State Polytechnic UniversityPomonaCA 91768USA Department of Civil and Environmental Engineering California State UniversityFullertonCA 91768USA

The traffic flow pertinent modelling is essential for distinct strategy ***,the present literature illustrated some needed improvements for such models,especially those related to lane-specific *** such context,this study aims to bridge the research gap by generating regression models to investigate influential factors for traffic flow based on the data collected from one multilane *** the Full Bayesian specification,the hierarchical models were built by accounting for three types of random effects:the structured and unstructured spatial effects,and the one addressing the multivariate heterogeneity across multiple *** endogenous relationship of traffic flow of adjacent lanes was also explored by utilizing the capability of multivariate correlation structure for simultaneous estimation of lane *** model estimates revealed the presence of endogeneity with statistical significance for the flow of neighbouring lanes for both directions of *** impact of flow was not only limited to the adjacent lanes but also to non-adjacent *** multivariate specification also confirmed interdependency for lane *** to conventional approaches,the more accurate model estimation in the study indicates the advantage of incorporating the various correlation structures in the models.

关键词： Spatial interdependency Structured and unstructured random effects Multivariate specification Endogeneity Traffic flow

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Comparative efficacy and safety of adenosine and regadenoson for assessment of fractional flow reserve:A systematic review and meta-analysis

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World Journal of Cardiology 2022年第5期14卷 319-328页

作者： Gauravpal singh gill Akshaya Gadre Arun Kanmanthareddy Cardiovascular Medicine Creighton University School of MedicineOmahaNE 68124United States Internal Medicine Western Michigan University Homer Stryker MD School of MedicineKalamazooMI 49007United States

BACKGROUND Adenosine is a coronary hyperemic agent used to measure invasive fractional flow reserve(FFR)of intermediate severity coronary *** To compare FFR assessment using adenosine with an alternate hyperemic agent,*** PubMed,Google Scholar,CINAHL and Cochrane databases were queried for studies comparing adenosine and regadenoson for assessment of *** on FFR,correlation coefficient and adverse events from the selected studies were extracted and analyzed by means of random effects *** tailed P-value less than 0.05 was considered *** was assessed using I2 *** Five studies with 248 patients were included in the final *** included patients and coronary lesions underwent FFR assessment using both adenosine and *** was no significant mean difference between FFR measurement by the two agents[odds ratio(OR)=-0.00;95%confidence interval(CI):(-0.02)-0.01,P=0.88].The cumulative correlation coefficient was 0.98(0.96-0.99,P<0.01).Three of five studies reported time to FFR with cumulative results favoring regadenoson(mean difference 34.31 s;25.14-43.48 s,P<0.01).Risk of adverse events was higher with adenosine compared to regadenoson(OR=2.39;95%CI:1.22-4.67,P=0.01),which most commonly included bradycardia and *** majority of the adverse events associated with both agents were *** The performance of regadenoson in inducing maximal hyperemia was comparable to that of *** was excellent correlation between the FFR measurements by both the *** use of adenosine,was however associated with higher risk of adverse events and longer time to FFR compared to regadenoson.

关键词： Adenosine Regadenoson Fractional flow reserve Meta-analysis

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Molecular imaging as a tool for evaluation of COVID-19 sequelae-A review of literature

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World Journal of Radiology 2022年第7期14卷 194-208页

作者： Kunal R Chandekar Swayamjeet Satapathy harmandeep singh Anish Bhattacharya Department of Nuclear Medicine Post Graduate Institute of Medical Education and ResearchChandigarh 160012India

Coronavirus disease 2019(COVID-19)is caused by the novel viral pathogen,severe acute respiratory syndrome coronavirus 2(SARS-CoV-2).COVID-19 primarily involves the *** acid testing based on reverse-transcription polymerase chain reaction of respiratory samples is the current gold standard for the diagnosis of SARS-CoV-2 *** modalities have an established role in triaging,diagnosis,evaluation of disease severity,monitoring disease progression,extra-pulmonary involvement,and *** our understanding of the disease improves,there has been substantial evidence to highlight its potential for multi-systemic involvement and development of longterm *** imaging techniques are highly sensitive,allowing noninvasive visualization of physiological or pathological processes at a cellular or molecular level with potential for detection of functional changes earlier than conventional radiological *** purpose of this review article is to highlight the evolving role of molecular imaging in evaluation of COVID-19 *** not ideal for diagnosis,the various modalities of molecular imaging play an important role in assessing pulmonary and extra-pulmonary sequelae of *** imaging using single photon emission computed tomography fused with computed tomography(CT)can be utilized as a first-line imaging modality for COVID-19 related pulmonary embolism.^(18)F-fluorodeoxyglucose positron emission tomography(PET)/CT is a sensitive tool to detect multi-systemic inflammation,including myocardial and vascular *** in conjunction with magnetic resonance imaging helps in better characterization of neurological sequelae of *** the fact that the majority of published literature is retrospective in nature with limited sample sizes,it is clear that molecular imaging provides additional valuable information(complimentary to anatomical imaging)with semi-quantitative or quantitative parameters to define

关键词： Molecular imaging Nuclear medicine Functional imaging COVID-19 SARS-CoV-2 Sequelae

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Optimization of CMOS Repeater Driven Interconnect RC Line Using Genetic Algorithm

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Journal of Shanghai Jiaotong university(Science) 2017年第2期22卷 167-172页

作者： KAUR Jasmeet gill Sandeep singh KAUR Navneet Department of Electronics and Communication Engineering Guru Nanak Dev Engineering CollegeLudhiana 141006India

In this work, optimization of complementary metal oxide semiconductor(CMOS) repeater driven interconnect resistive-capacitive(RC) line is carried out using genetic algorithm(GA). This work is aimed at powerdelay-product(PDP) minimization of RC interconnect at 180 nm technology node. The algorithm simultaneously optimizes the values of supply voltage, number of repeaters and repeater width for delay and PDP *** accuracy of results obtained is verified by simulations from Cadence virtuoso tool. For delay minimization,comparison of GA results with previous results of the literature shows an improvement of 44.4% in the value of the optimal number of repeaters required. This improvement is obtained by increasing the repeater size, which also increases power dissipation, so a tradeoff has also been achieved in terms of PDP minimization. The comparison of PDP results obtained in this work, with the results at 70, 100, and 130 nm technologies from literature shows improvement in optimal number of repeaters required. The results of algorithm and simulations are in good agreement and demonstrate the validity of proposed algorithm.

关键词： complementary metal oxide semiconductor(CMOS) genetic algorithm interconnects optimal power-delay-product repeater

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Apatite formation and weight loss study in EDMed perforated AZ31 Mg-alloy

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Journal of Magnesium and Alloys 2017年第3期5卷 362-367页

作者： Randeep singh gill Kamal Kumar Uma Batra Department of Mechanical Engineering PEC University of TechnologyChandigarh 160012India Department of Materials and Metallurgy Engineering PEC University of TechnologyChandigarh 160012India

Porous structures are highly preferred for bone regeneration and high tissue *** present work,electrical discharge drilling(EDD),a thermal erosion process was used to produce through holes in Mg-alloys to fabricate perforated structure similar to open cell porous structure in extruded *** formation and weight loss study was conducted for 7 days,14 days and 21 days after immersion tests in SBF *** perforated structure in AZ31 with 26 through micro-holes provides 72%increase in surface area but with marginally 4%higher weight loss as compare to non-perforated *** perforated and non-perforated samples of Mg-alloy,it was well observed that perforated structure forms high volume of apatite as compared to non-perforated *** electron microscopic(SEM)study revealed that in perforated structure,drilled holes retain their circularity after 21 days of immersion test and distinct corrosion phenomenon occur at localized sites.

关键词： Mg-alloys AZ31 Perforated structure Electrical discharge drilling Apatite formation Weight loss

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Water-Extractable Carbon Pools and Microbial Biomass Carbon in Sodic Water-Irrigated Soils Amended with Gypsum and Organic Manures

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Pedosphere 2013年第1期23卷 88-97页

作者： O.P.CHOUDHARY J.K.gill BIJAY-singh Department of Soil Science Punjab Agricultural University School of Earth and Environment University of Western Australia

Microbial biomass carbon (MBC), a small fraction of soil organic matter, has a rapid turnover rate and is a reservoir of labile nutrients. The water-extractable carbon pools provide a fairly good estimate of labile C present in soil and can be easily quantified. Changes in soil MBC and water-extractable organic carbon pools were studied in a 14-year long-term experiment in plots of rice-wheat rotation irrigated with canal water (CW), sodic water (SW, 10-12.5 mmol c L-1 residual sodium carbonate), and SW amended with gypsum with or without application of organic amendments including farmyard manure (FYM), green manure (GM), and wheat straw (WS). Irrigation with SW increased soil exchangeable sodium percentage by more than 13 times compared to irrigation with CW. Sodic water irrigation significantly decreased hot water-extractable organic carbon (HWOC) from 330 to 286 mg kg-1 soil and cold water-extractable organic carbon (CWOC) from 53 to 22 mg kg-1 soil in the top 0-7.5 cm soil layer. In the lower soil layer (7.5-15 cm), reduction in HWOC was not significant. Application of gypsum alone resulted in a decrease in HWOC in the SW plots, whereas an increase was recorded in the SW plots with application of both gypsum and organic amendments in both the soil layers. Nevertheless, application of gypsum and organic amendments increased the mean CWOC as compared with application of gypsum alone. CWOC was significantly correlated with MBC but did not truly reflect the changes in MBC in the treatments with gypsum and organic amendments applied. For the treatments without organic amendments, HWOC was negatively correlated with MBC (r = 0.57*) in the 0-7.5 cm soil layer, whereas for the treatments with organic amendments, both were positively correlated. Irrigation with SW significantly reduced the rice yield by 3 t ha-1 and the yield of rice and wheat by 5 t ha-1 as compared to irrigation with canal water. Application of amendments significantly increased rice and wheat yields.

关键词：土壤有机质微生物量碳热水提取有机碳库灌溉石膏水库碱化

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Efficient Clustering and Simulated Annealing Approach for Circuit Partitioning

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Journal of Shanghai Jiaotong university(Science) 2011年第6期16卷 708-712页

作者： SANDEEP singh gill RAJEEVAN Chandel ASHWANI Kumar Chandel Department of Electronics and Communication Engineering Guru Nanak Dev Engineering College National Institute of Technology

Circuit net list bipartitioning using simulated annealing technique has been proposed in the *** method converges asymptotically and probabilistically to global *** circuit net list is partitioned into two partitions such that the number of interconnections between the partitions is *** proposed method begins with an innovative clustering technique to obtain a good initial *** obtained show the versatility of the proposed method in solving non polynomial hard problems of circuit net list partitioning and show an improvement over those available in literature.

关键词： cut size non polynomial hard partitioning simulated annealing interconnections very large scale integration(VLSI) design

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