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A Hybrid Deep Fused Learning Approach to Segregate Infectious Diseases

Computers, Materials & Continua 2023年第2期74卷 4239-4259页

作者： jawad Rasheed Shtwai Alsubai Department of Software Engineering Nisantasi UniversityIstanbul34398Turkey Dapartment of Computer Science College of Computer Engineering and Sciences in Al-KharjPrince Sattam Bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942Saudi Arabia

Humankind is facing another deadliest pandemic of all times in history,caused by *** from this challenging pandemic,World Health Organization(WHO)considers tuberculosis(TB)as a preeminent infectious disease due to its high infection ***,both TB and COVID-19 severely affect the lungs,thus hardening the job of medical practitioners who can often misidentify these diseases in the current ***,the time of need calls for an immediate and meticulous automatic diagnostic tool that can accurately discriminate both *** one of the preliminary smart health systems that examine three clinical states(COVID-19,TB,and normal cases),this study proposes an amalgam of image filtering,data-augmentation technique,transfer learning-based approach,and advanced deep-learning classifiers to effectively segregate these *** first employed a generative adversarial network(GAN)and Crimmins speckle removal filter on X-ray images to overcome the issue of limited data and *** pre-processed image is then converted into red,green,and blue(RGB)and Commission Internationale de l’Elcairage(CIE)color spaces from which deep fused features are formed by extracting relevant features using DenseNet121 and *** feature extractor extracts 1000 most useful features which are then fused and finally fed to two variants of recurrent neural network(RNN)classifiers for precise discrimination of threeclinical *** analysis showed that the proposed Bi-directional long-short-term-memory(Bi-LSTM)model dominated the long-short-termmemory(LSTM)network by attaining an overall accuracy of 98.22%for the three-class classification task,whereas LSTM hardly achieved 94.22%accuracy on the test dataset.

关键词： Computer-aided diagnosis decision support system deep transfer learning deep fused features tuberculosis COVID-19

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Prevalence of post-traumatic stress disorder and depressive symptoms among civilians residing in armed conflict-affected regions:a systematic review and meta-analysis

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General Psychiatry 2024年第3期37卷 324-334页

作者： Syed Hassan Ahmed Aabia Zakai Maha Zahi muhammad Youshay jawad Rui Fu Michael Chaiton Dow University of Health Sciences KarachiPakistan Department of Psychiatry and Behavioral Health Penn State College of MedicineHersheyPennsylvaniaUSA Dalla Lana School of Public Health University of TorontoTorontoOntarioCanada institute of Mental Health Policy Research The Center of Addiction and Mental HealthTorontoOntarioCanada

Background Globally,populations afflicted by armed conflict are known to have high rates of mental health *** This meta-analysis aims to estimate the prevalence of post-traumatic stress disorder(PTSD)and depressive symptoms among civilians residing in armed conflictaffected *** This meta-analysis was conducted in accordance with the Preferred Reporting Items forSystematic Reviews and Meta-Analyses.A literature search employing MEDLINE(R),Embase Classic+Embase,APA PsyclNFO,Ovid Healthstar,Journal@Ovid Full Text,Cochrane,PTSDpubs and CINAHL was conducted from inception until 19 March 2024 to identify relevant *** assessment was performed using the Joanna Briggs Institute Critical Appraisal Checklist for Prevalence Studies,and a Comprehensive Meta-Analysiswas usedto conduct the statistical *** The search yielded 38595 articles,of which 57 were considered eligible for *** included studies comprised data from 64596 *** estimated a prevalence of 23.70%(95%CI 19.50%to28.40%)forPTSD symptomsand 25.60%(95%Cl 20.70%to 31.10%)for depressive features among war-afflicted *** subgroup analysis based on time since the war and the country's economic status revealed the highest prevalence for both PTSD and depressive symptoms was present during the years of war and in low/*** The results of this study provide conclusive evidence of the detrimental impacts of armed conflict on mental health ***,it is crucial to emphasise the significance of both physical and mental health in the aftermath of war and take appropriate humanistic measures to overcome challenges in the management of psychiatric illnesses.

关键词： analysis stress armed

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Improving Quantitative and Qualitative Characteristics of Wheat (Triticum aestivum L.) through Nitrogen Application under Semiarid Conditions

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Phyton-International Journal of Experimental Botany 2023年第4期92卷 1001-1017页

作者： muhammad Rafiq muhammad Saqib Husnain jawad Talha Javed Sadam Hussain muhammad Arif Baber Ali muhammad Sultan Ali Bazmi Ghulam Abbas Marjan Aziz Mohammad Khalid Al-Sadoon Aneela Gulnaz Sobhi F.Lamlom muhammad Azeem Sabir Jameel Akhtar Agronomic Research Institute Ayub Agricultural Research InstituteFaisalabad38850Pakistan Depertment of Agronomy University of AgricultureFaisalabad38040Pakistan Department of Agronomy Northwest A&F UniversityYangling712100China Department of Plant Sciences Quaid-i-Azam UniversityIslamabad45320Pakistan Fodder Research Institute Sargodha Sargodha40100Pakistan Department of Agricultural Engineering Barani Agricultural Research InstituteChakwal48800Pakistan Department of Zoology College of ScienceKing Saud UniversityRiyadh11451Saudi Arabia Department of Biotechnology Yeungnam UniversityGyeongbuk38641Korea Plant Production Department Faculty of Agriculture Saba BashaAlexandria UniversityAlexandria21531Egypt Department of Forestry Range and Wildlife ManagementThe Islamia University of BahawalpurBahawalpur63100Pakistan

Nitrogen(N),the building block of plant proteins and enzymes,is an essential macronutrient for plant functions.A field experiment was conducted to investigate the impact of different N application rates(28,57,85,114,142,171,and 200 kg ha^(−1))on the performance of spring wheat(***-2016)during the 2017–2018 and 2018–2019 growing seasons.A control without N application was kept for *** years mean data showed optimum seed yield(5,461.3 kg ha^(−1))for N-application at 142 kg ha^(−1) whereas application of lower and higher rates of N did not result in significant and economically higher seed yield.A higher seed yield was obtained in the 2017–2018(5,595 kg ha^(−1))than in the 2018–2019(5,328 kg ha^(−1))growing seasons under an N application of 142 kg ha^(−1).It was attributed to the greater number of growing degree days in the first(1,942.35°C days)than in the second year(1,813.75°C).Higher rates of N(171 and 200 kg ha^(−1))than 142 kg ha^(−1) produced more number of tillers(i.e.,948,300 and 666,650 ha^(−1),respectively).However,this increase did not contribute in achieving higher *** of 142,171,and 200 kg ha^(−1) resulted in 14.15%,15.0%and 15.35%grain protein concentrations in comparison to 13.15%with the application of 114 kg ha^(−1).It is concluded that the application of N at 142 kg ha^(−1) could be beneficial for attaining higher grain yields and protein concentrations of wheat cultivar Ujala-2016.

关键词： Economical yield growing degree days nitrogen Ujala-2016 wheat

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可编程式自组装生长多色有机微米阵列（英文）

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Science China Materials 2025年

作者：张秋仪黄淇李建平岳晓飞盛晨旭 Husnain jawad 周治国宋子洋解凤贤丛春晓仇志军胡来归刘冉 Center of Micro Nano System School of Information Science and Technology Fudan University Institute for Electric Light Sources School of Information Science and Technology Fudan University College of Chemistry and Materials Science Shanghai Frontiers Science Center of Biomimetic Catalysis Shanghai Normal University Shanghai Key Lab of Chemical Assessment and Sustainability School of Chemical Science and Engineering Tongji University

具有不同像素类型的高分辨率有机阵列在各种领域中有着重要的应用前景,如全彩显示和光子晶体.通过传统工艺很难一步就制备出这类阵列(如高分辨率多色图案).在本工作中,我们提出了一种自下而上的溶液法,结合相变材料(特别是聚集诱导发光...

具有不同像素类型的高分辨率有机阵列在各种领域中有着重要的应用前景,如全彩显示和光子晶体.通过传统工艺很难一步就制备出这类阵列(如高分辨率多色图案).在本工作中,我们提出了一种自下而上的溶液法,结合相变材料(特别是聚集诱导发光材料).通过自组装过程,直接制备出了具有不同相或颜色的可编程微米级有机图案.值得注意的是,通过调整事先预定义的成核位点尺寸,实现了对成核和结晶物质的量的控制.这种精确调控可导致每个像素呈现不同的相和颜色.因此,直接实现了无需转移的具有多种颜色像素的高分辨率有机微米阵列,这为利用相变材料进行无需转移的多功能微图案生长开辟了道路,在高分辨率全彩成像/显示、光子晶体、信息存储、加密等领域有着巨大的潜力.

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Reconstruction of Scalar Field Dark Energy Models in Kaluza-Klein Universe

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Communications in Theoretical Physics 2013年第8期60卷 183-188页

作者： M.Sharif Abdul jawad Department of Mathematics University of the PunjabQuaid-e-Azam CampusLahore-54590Pakistan

This paper is devoted to study the modified holographic dark energy model by taking its different aspects in the t/at Kaiuza-Klein universe. We construct the equation of state parameter which evolutes the universe from quintessence region towards the vacuum. It is found that the modified holographic model exhibits instability against small perturbations in the early epoch of the universe but becomes stable in the later times. We also develop its correspondence with some scalar field dark energy models. It is interesting to mention here that ail the results are consistent with the present observations.

关键词： Kaluza-Klein cosmology modified holographic dark energy scalar field models

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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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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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Nitrogen(N) metabolism related enzyme activities,cell uitrastructure and nutrient contents as affected by N level and barley genotype

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Journal of Integrative Agriculture 2017年第1期16卷 190-198页

作者： jawad Munawar Shah Syed Asad Hussain Bukhari ZENG Jian-bin QUAN Xiao-yan Essa Ali Noor muhammad ZHANG Guo-ping Department of Agronomy Zijingang Campus Zhejiang University Hangzhou 310058 P.R. China

Development of the new crop cultivars with high yield under low nitrogen （N） input is a fundamental approach to enhance agricultural sustainability, which is dependent on the exploitation of the elite germplasm. In the present study, four barley genotypes （two Tibetan wild and two cultivated）, differing in N use efficiency （NUE）, were characterized for their physiolog- ical and biochemical responses to different N levels. Higher N levels significantly increased the contents of other essential nutrients （P, K, Ca, Fe, Cu and Mn）, and the increase was more obvious for the N-efficient genotypes （ZD9 and XZ149）. The observation of ultrastructure showed that chloroplast structure was severely damaged under low nitrogen, and the two high N efficient genotypes were relatively less affected. The activities of the five N metabolism related enzymes, i.e., nitrate reductase （NR）, glutamine sy＇nthetase （GS）, nitrite reductase （NiR）, glutamate synthase （GOGAT） and glutamate dehydrogenase （GDH） all showed the substantial increase with the increased N level in the culture medium. However the increased extent differed among the four genotypes, with the two N efficient genotypes showing more increase in com- parison with the other two genotypes with relative N inefficiency （HXRL and XZ56）. The current findings showed that a huge difference exists in low N tolerance among barley genotypes, and improvement of some physiological traits （such as enzymes） could be helpful for increasing N utilization efficiency.

关键词： barley enzyme genotype nitrogen ultrastructure

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Nonlinear Axisymmetric Deformation Model for Structures of Revolution

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Advances in Applied Mathematics and Mechanics 2011年第4期3卷 420-447页

作者： Ayman Mourad jawad Zaarour Department of Mathematics Lebanese UniversityHadathLebanon Jean Kutzman Laboratory Joseph Fourier UniversityGrenobleFrance

An axisymmetric formulation for modeling three-dimensional deformation of structures of revolution is *** axisymmetric deformation model is described using the cylindrical coordinate *** displacement effects and material nonlinearities and anisotropy are accommodated by the *** derivation of the formulation is given,and an example is presented to demonstrate the capabilities and efficiency of the technique compared to the full three-dimensional model.

关键词： Modeling axisymmetry nonlinear elasiticity large deformations numerical simulations

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Winding Function Model-based Performance Evaluation of a PM Transverse Flux Generator for Applications in Direct-drive Systems

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CES Transactions on Electrical Machines and Systems 2024年第2期8卷 216-226页

作者： Mehrage Ghods jawad Faiz Ali A Pourmoosa IEEE School of Electrical and Computer Engineering College of Engineeringthe University of Tehran

The magnetic flux in a permanent magnet transverse flux generator(PMTFG) is three-dimensional(3D), therefore, its efficacy is evaluated using 3D magnetic field analysis. Although the 3D finite-element method(FEM) is highly accurate and reliable for machine simulation, it requires a long computation time, which is crucial when it is to be used in an iterative optimization process. Therefore, an alternative to 3DFEM is required as a rapid and accurate analytical technique. This paper presents an analytical model for PMTFG analysis using winding function method. To obtain the air gap MMF distribution, the excitation magneto-motive force(MMF) and the turn function are determined based on certain assumptions. The magnetizing inductance, flux density, and back-electro-magnetomotive force of the winding are then determined. To assess the accuracy of the proposed method, the analytically calculated parameters of the generator are compared to those obtained by a 3D-FEM. The presented method requires significantly shorter computation time than the 3D-FEM with comparable accuracy.

关键词： Index Terms—Permanent magnet transverse flux generator Winding function 3D-FEM Cogging torque Prototyping

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