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Classification of Citrus Plant Diseases Using Deep Transfer Learning

Computers, Materials & Continua 2022年第1期70卷 1401-1417页

作者： muhammad zia ur rehman Fawad Ahmed muhammad Attique Khan Usman Tariq Sajjad Shaukat Jamal Jawad Ahmad Iqtadar Hussain Department of Electrical Engineering HITEC UniversityTaxilaPakistan Department of Computer Science HITEC UniversityTaxilaPakistan College of Computer Engineering and Sciences Prince Sattam Bin Abdulaziz UniversityAl-KhrajSaudi Arabia Department of Mathematics College of ScienceKing Khalid UniversityAbhaSaudi Arabia School of Computing Edinburgh Napier UniversityUK Department of Mathematics Statisticsand PhysicsQatar UniversityDoha2713Qatar

In recent years,the field of deep learning has played an important role towards automatic detection and classification of diseases in vegetables and *** in turn has helped in improving the quality and production of vegetables and *** fruits arewell known for their taste and nutritional *** are one of the natural and well known sources of vitamin C and planted *** are several diseases which severely affect the quality and yield of citrus *** this paper,a new deep learning based technique is proposed for citrus disease *** different pre-trained deep learning models have been used in this *** increase the size of the citrus dataset used in this paper,image augmentation techniques are ***,to improve the visual quality of images,hybrid contrast stretching has been *** addition,transfer learning is used to retrain the pre-trainedmodels and the feature set is enriched by using feature *** fused feature set is optimized using a meta-heuristic algorithm,the Whale Optimization Algorithm(WOA).The selected features are used for the classification of six different diseases of citrus *** proposed technique attains a classification accuracy of 95.7%with superior results when compared with recent techniques.

关键词： Citrus plant disease classification deep learning feature fusion deep transfer learning

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An Efficient Automated Technique for Classification of Breast Cancer Using Deep Ensemble Model

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Computer Systems Science & Engineering 2023年第7期46卷 897-911页

作者： muhammad zia ur rehman Jawad Ahmad Emad Sami Jaha Abdullah Marish Ali Mohammed A.Alzain Faisal Saeed Department of Electrical Engineering HITEC UniversityTaxila47080Pakistan School of Computing Edinburgh Napier UniversityEdinburghEH105DTUK Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia DAAI Research Group Department of Computing and Data ScienceSchool of Computing and Digital TechnologyBirmingham City University15 Bartholomew RowBirminghamB55JUUK

Breast cancer is one of the leading cancers among *** has the second-highest mortality rate in women after lung *** detection,especially in the early stages,can help increase survival ***,manual diagnosis of breast cancer is a tedious and time-consuming process,and the accuracy of detection is reliant on the quality of the images and the radiologist’s ***,computer-aided medical diagnosis has recently shown promising results,leading to the need to develop an efficient system that can aid radiologists in diagnosing breast cancer in its early *** research presented in this paper is focused on the multi-class classification of breast *** deep transfer learning approach has been utilized to train the deep learning models,and a pre-processing technique has been used to improve the quality of the ultrasound *** proposed technique utilizes two deep learning models,Mobile-NetV2 and DenseNet201,for the composition of the deep ensemble *** learning models are fine-tuned along with hyperparameter tuning to achieve better ***,entropy-based feature selection is *** cancer identification using the proposed classification approach was found to attain an accuracy of 97.04%,while the sensitivity and F1 score were 96.87%and 96.76%,*** performance of the proposed model is very effective and outperforms other state-of-the-art techniques presented in the literature.

关键词： Breast cancer image enhancement ensemble model transfer learning feature selection

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Synthesis,Crystal Structure and Spectroscopic Properties of 1,2-Benzothiazine Derivatives:An Experimental and DFT Study

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Chinese Journal of Structural Chemistry 2015年第1期34卷 15-25页

作者： muhammad Nadeem Arshad TARIQ Mahmood ATHER Faroque Khan muhammad zia-ur-rehman ABDULLAH M.Asiri ISLAM Ullah Khan RIFFAT-Un-Nisa KHurSHID Ayub AZAM Mukhtar muhammad Tariq Saeed Chemistry Department Faculty of ScienceKing Abdulaziz University Centre of Excellence for Advanced Materials Research (CEAMR) King Abdulaziz University Department of Chemistry COMSATS Institute of Information TechnologyAbbottabad IRCBM COMSATS Institute of Information Technology Applied Chemistry Research Center PCSIR Laboratories ComplexFerozpur RoadLahore 54600Pakistan Materials Chemistry Laboratory Department of ChemistryGC University Department of Chemistry College of ScienceKing Faisal University Department of Chemistry University of EducationOkara CampusOkara-Pakistan

1,2-Benzothiazine derivatives methyl 3-methoxy-4-oxo-3,4-dihydro-2H-benzo[e] [1,2]thiazine-3-carboxylate 1,1-dioxide（1） and methyl 2-ethyl-3-hydroxy-4-oxo-3,4-dihydro-2Hbenzo[e][1,2]thiazine-3-carboxylate 1,1-dioxide（2） were synthesized, and characterized by spectroscopic techniques; 1H-NMR and infrared（IR） spectroscopy. Crystals of 1 and 2 were grown by slow evaporation of methanol and ethyl acetate, respectively and their crystal structures were investigated by single-crystal X-ray diffraction analysis. Geometric properties were calculated by the B3 LYP method of density functional theory（DFT） at the 6-31G＋（d） basis set to compare with the experimental data. Simulated properties were found in strong agreement with the experimental ones. Intermolecular forces have also been modeled in order to investigate the strength of packing and strong hydrogen bonding was observed in both compounds 1 and 2. Electronic properties such as Ionization Potential（IP）, Electron Affinities（EA） and coefficients of the highest occupied molecular orbital（HOMO） and the lowest unoccupied molecular orbital（LUMO） of com- pounds 1 and 2 were simulated for the first time.

关键词： 1,2-benzothiazine B3LYP/6-31+G (d) density functional theory (DFT) HUMO-LUMO crystal structures

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Foliar Application of Phosphorus Enhances Photosynthesis and Biochemical Characteristics of Maize under Drought Stress

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Phyton-International Journal of Experimental Botany 2021年第2期90卷 503-514页

作者： Zahoor Ahmad Ejaz Ahmad Waraich muhammad zia ur rehman muhammad Ashar Ayub muhammad Usman Hesham Alharby Atif Bamagoos Celaleddin Barutçular muhammad Ali Raza FatihÇiğ Ayman El Sabagh Department of Field Crops Faculty of AgricultureÇukurova UniversityAdana01330Turkey Department of Botany University of Central Punjab(UCP)Punjab Group of CollegesBahawalpur63100Pakistan Department of Agronomy University of AgricultureFaisalabad38000Pakistan Institute of Soil and Environmental Science University of AgricultureFaisalabad38000Pakistan Department of Biological Sciences Faculty of ScienceKing Abdulaziz UniversityJeddah21577Saudi Arabia College of Agronomy Sichuan Agricultural UniversityChengdu611130China Department of Field Crops Faculty of AgricultureSiirt UniversitySiirt56100Turkey Department of Agronomy Faculty of AgricultureUniversity of KafrelsheikhKafrelsheikh33516Egypt

Water is essential for the growth period of crops;however,water unavailability badly affects the growth and physiological attributes of crops,which considerably reduced the yield and yield components in ***,a pot experiment was conducted to investigate the effect of foliar phosphorus(P)on morphological,gas exchange,biochemical traits,and phosphorus use efficiency(PUE)of maize(Zea mays L.)hybrids grown under normal as well as water deficit situations at the Department of Agronomy,University of Agriculture Faisalabad,Pakistan in *** different treatments(control and P@8 kg ha^(−1))and four hybrids(Hycorn,31P41,65625,and 32B33)of maize were tested by using a randomized complete block design(RCBD)with three *** showed that the water stress caused a remarkable decline in total soluble protein(9.7%),photosynthetic rate(9.4%)and transpiration rate(13.4%),stomatal conductance(10.2%),and internal CO_(2)rate(20.4%)comparative to well-watered *** increase of 37.1%,36.8%,and 24.5%were recorded for proline,total soluble sugar,and total free amino acid,***,foliar P application minimized the negative impact of drought by improving plant growth,physio-biochemical attributes,and PUE in maize plants under water stress *** the hybrids tested,the hybrid 6525 performed better both under stress and non-stress *** outcomes confirmed that the exogenous application of P improved drought stress tolerance by modulating growth,physio-biochemical attributes,and PUE of maize hybrids.

关键词： Photosynthetic attributes biochemical characters water stress foliar P Maize

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An Automated Classification Technique for COVID-19 Using Optimized Deep Learning Features

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Computer Systems Science & Engineering 2023年第9期46卷 3799-3814页

作者： Ejaz Khan muhammad zia ur rehman Fawad Ahmed Suliman A.Alsuhibany muhammad Zulfiqar Ali Jawad Ahmad School of Engineering RMIT UniversityMelbourneAustralia Department of Electrical Engineering HITEC University Taxila47080Pakistan Department of Cyber Security Pakistan Navy Engineering CollegeNUSTKarachi 75350Pakistan Department of Computer Science College of ComputerQassim UniversityBuraydah 51452Saudi Arabia James Watt School of Engineering University of GlasgowGlasgowG128QQUK School of Computing Edinburgh Napier UniversityEdinburghEH105DTUK

In 2020,COVID-19 started spreading throughout the *** deadly infection was identified as a virus that may affect the lungs and,in severe cases,could be the cause of *** polymerase chain reaction(PCR)test is commonly used to detect this virus through the nasal passage or ***,the PCR test exposes health workers to this deadly *** limit human exposure while detecting COVID-19,image processing techniques using deep learning have been successfully *** this paper,a strategy based on deep learning is employed to classify the COVID-19 *** extract features,two deep learning models have been used,the DenseNet201 and the *** learning is used in feature extraction,and models are fine-tuned.A publicly available computerized tomography(CT)scan dataset has been used in this *** extracted features from the deep learning models are optimized using the Ant Colony Optimization *** proposed technique is validated through multiple evaluation *** classifiers have been employed to classify the optimized *** cubic support vector machine(Cubic SVM)classifier shows superiority over other commonly used classifiers and attained an accuracy of 98.72%.The proposed technique achieves state-of-the-art accuracy,a sensitivity of 98.80%,and a specificity of 96.64%.

关键词： CT scans COVID-19 classification deep learning feature optimization

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Exploiting Empirical Variance for Data Stream Classification

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Journal of Shanghai Jiaotong university(Science) 2012年第2期17卷 245-250页

作者： zia-ur rehman muhammad 李天瑞李涛 School of Information Science and Technology Southwest Jiaotong University School of Computer Science Florida International University

Classification,using the decision tree algorithm,is a widely studied problem in data *** challenge is when to split a decision node into multiple *** inequalities,that exploit variance information such as Bernstein's and Bennett's inequalities,are often substantially strict as compared with Hoeffding's bound which disregards *** machine learning algorithms for stream classification such as very fast decision tree(VFDT) learner,AdaBoost and support vector machines(SVMs),use the Hoeffding's bound as a performance *** this paper,we propose a new algorithm based on the recently proposed empirical Bernstein's bound to achieve a better probabilistic bound on the accuracy of the decision *** results on four synthetic and two real world data sets demonstrate the performance gain of our proposed technique.

关键词： Hoeffding and Bernstein’s bounds data stream classification decision tree anytime algorithm

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Gender disparities and woman-specific trends in Barrett’s esophagus in the United States:An 11-year nationwide populationbased study

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World Journal of Methodology 2025年第1期15卷 60-71页

作者： Karina Fatakhova Faisal Inayat Hassam Ali Pratik Patel Attiq ur rehman Arslan Afzal muhammad Sarfraz Shiza Sarfraz Gul Nawaz Ahtshamullah Chaudhry Rubaid Dhillon Arthur Dilibe Benjamin Glazebnik Lindsey Jones Emily Glazer Division of Gastroenterology and Hepatology Mather Hospital and Zucker School of Medicine at Hofstra UniversityPort JeffersonNY 11777United States Department of Internal Medicine Allama Iqbal Medical CollegeLahorePunjab 54550Pakistan Division of Gastroenterology and Hepatology East Carolina University Brody School of MedicineGreenvilleNC 27834United States Division of Gastroenterology and Hepatology Geisinger Wyoming Valley Medical CenterWilkes-BarrePA 18711United States Department of Internal Medicine East Carolina University Brody School of MedicineGreenvilleNC 27834United States Department of Internal Medicine St.Dominic's HospitalJacksonMS 39216United States Department of Gastroenterology Hepatologyand NutritionCleveland Clinic FoundationClevelandOH 44195United States Department of Internal Medicine Mather Hospital and Hofstra University ZuckerSchool of MedicinePort JeffersonNY 11777United States

BACKGROUND Barrett's esophagus(BE)is a known premalignant precursor to esophageal adenocarcinoma(EAC).The prevalence rates continue to rise in the United States,but many patients who are at risk of EAC are not *** practice guidelines include male gender as a predisposing factor for BE and *** population-based clinical evidence regarding female gender remains *** To study comparative trends of gender disparities in patients with BE in the United *** A nationwide retrospective study was conducted using the 2009-2019 National Inpatient Sample(NIS)*** with a primary or secondary diagnosis code of BE were *** major outcome of interest was determining the gender disparities in patients with *** analysis for respective outcomes for females was also reported to ascertain any time-based *** We identified 1204190 patients with BE for the study *** the included patients,717439(59.6%)were men and 486751(40.4%)were *** mean age was higher in women than in men(67.1±0.4 vs 66.6±0.3 years,P<0.001).The rate of BE per 100000 total NIS hospitalizations for males increased from 144.6 in 2009 to 213.4 in 2019(P<0.001).The rate for females increased from 96.8 in 2009 to 148.7 in 2019(P<0.001).There was a higher frequency of obesity among women compared to men(17.4%vs 12.6%,P<0.001).Obesity prevalence among females increased from 12.3%in 2009 to 21.9%in 2019(P<0.001).A lower prevalence of smoking was noted in women than in men(20.8%vs 35.7%,P<0.001).However,trend analysis showed an increasing prevalence of smoking among women,from 12.9%in 2009 to 30.7%in 2019(P<0.001).Additionally,there was a lower prevalence of alcohol abuse,Helicobacter pylori(***),and diabetes mellitus among females than males(P<0.001).Trend analysis showed an increasing prevalence of alcohol use disorder and a decreasing prevalence of *** and diabetes mellitus among women(P<0.001).CONCLUSION The prevalence of BE among

关键词： Barrett’s esophagus Gender disparity Epidemiological trends Esophageal adenocarcinoma Screening endoscopy Female gender Risk factors

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Electron doping induced semiconductor to metal transitions in ZrSe2 layers via copper atomic intercalation

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Nano Research 2018年第9期11卷 4914-4922页

作者： Zahir muhammad Kejun Mu Haifeng Lv Chuanqiang Wu zia ur rehman muhammad Habib Zhe Sun Xiaojun Wu Li Song National Synchrotron Radiation Laboratory CAS Center for Excellence in Nanoscience CAS Key Laboratory of Strongly-coupled Quantum Matter Physics University of Science and Technology of China Hefei 230029 China CAS Key Laboratory of Materials for Energy Conservation Synergetic Innovation Centre of Quantum Information & Quantum Physics CAS Center for Excellence in Nanoscience and Department of Material Science and Engineering University of Science and Technology of China Hefei 230026 China

Atomic intercalation in two-dimensional （2D） layered materials can be used to engineer the electronic structure at the atomic scale and generate tuneable physical and chemical properties which are quite distinct in comparison with the pristine material. Among them, electron-doped engineering induced by intercalation is an efficient route to modulate electronic states in 2D layers. Herein, we demonstrate a semiconducting to metallic phase transition in zirconium diselenide （ZrSe2） single crystals via controllable incorporation of copper （Cu） atoms. Our angle resolved photoemission spectroscopy （ARPES） measurements and first-principles density functional theory （DFT） calculations dearly revealed the emergence of conduction band dispersion at the M/L point of the Brillouin zone due to Cu-induced electron doping in ZrSe2 interlayers. Moreover, electrical measurements in ZrSe2 revealed semiconducting behavior, while the Cu-intercalated ZrSe2 exhibited a linear current-voltage curve with metallic character. The atomic intercalation approach may have high potential for realizing transparent electron-doping systems for many specific 2D-based nanoelectronic applications.

关键词： layered materials phase transition angle resolved photoemission spectroscopy electron doping

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Impact of risk management strategies on the credit risk faced by commercial banks of Balochistan

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Financial Innovation 2019年第1期5卷 761-773页

作者： zia ur rehman Noor muhammad Bilal Sarwar muhammad Asif Raz Balochistan University of Information Technology Engineering&Management Sciences QuettaPakistan

This study aims to identify risk management strategies undertaken by the commercial banks of Balochistan,Pakistan,to mitigate or eliminate credit *** findings of the study are significant as commercial banks will understand the effectiveness of various risk management strategies and may apply them for minimizing credit *** explanatory study analyses the opinions of the employees of selected commercial banks about which strategies are useful for mitigating credit *** data was collected from 250 employees of commercial banks to perform multiple regression analyses,which were used for the *** results identified four areas of impact on credit risk management(CRM):corporate governance exerts the greatest impact,followed by diversification,which plays a significant role,hedging and,finally,the bank’s Capital Adequacy *** study highlights these four risk management strategies,which are critical for commercial banks to resolve their credit risk.

关键词： Credit risk Risk management strategies Financial risk Capital adequacy ratio Hedging Corporate governance Diversification

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An Ontology-Based Framework for Semi-Automatic Schema Integration

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Journal of Computer Science & Technology 2005年第6期20卷 788-796页

作者： Zille Huma muhammad Jaffar-ur rehman Nadeem Iftikhar muhammad Ali dinnah University Islamabad Pakistan

Currently, schema integration frameworks use approaches like rule-based, machine learning, etc. This paper presents an ontology-based wrapper-mediator framework that uses both the rule-based and machine learning strategies at the same time. The proposed framework uses global and local ontologies for resolving syntactic and semantic heterogeneity, and XML for interoperability. The concepts in the candidate schemas are merged on the basis of the similarity coefficient, which is calculated using the defined rules and the prior mappings stored in the case-base.

关键词： heterogeneous databases database integration database semantics rule-based processing machine learning

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