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multi-Level Deep Generative Adversarial Networks for Brain Tumor Classification on magnetic Resonance Images

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Intelligent Automation & Soft Computing 2023年第4期36卷 127-143页

作者： Abdullah A.Asiri Ahmad Shaf Tariq Ali muhammad Aamir Ali Usman muhammad Irfan Hassan A.Alshamrani Khlood m.mehdar osama m.alshehri Samar m.Alqhtani Radiological Sciences Department College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia Department of Computer Science COMSATS University IslamabadSahiwal CampusSahiwal57000Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Anatomy Department Medicine CollegeNajran UniversityNajranSaudi Arabia Department of Clinical Laboratory Sciences Collage of Applied Medical ScienceNajran UniversityNajranSaudi Arabia Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia

The brain tumor is an abnormal and hysterical growth of brain tissues,and the leading cause of death affected patients *** in this technol-ogy-based arena,brain tumor images with proper labeling and acquisition still have a problem with the accurate and reliable generation of realistic images of brain tumors that are completely different from the original *** artiﬁcially created medical image data would help improve the learning ability of physicians and other computer-aided systems for the generation of augmented *** over-come the highlighted issue,a Generative Adversarial Network(GAN)deep learn-ing technique in which two neural networks compete to become more accurate in creating artiﬁcially realistic data for mRI *** GAN network contains mainly two parts known as generator and ***,a generator is the convolutional neural network,and a discriminator is the deconvolutional neural *** this research,the publicly accessible Contrast-Enhanced mag-netic Resonance Imaging(CE-mRI)dataset collected from 2005-to 2020 from different hospitals in China consists of four classes has been *** proposed method is simple and achieved an accuracy of 96%.We compare our technique results with the existing results,indicating that our proposed technique outper-forms the best results associated with the existing methods.

关键词： GAN network CE-mRI images convolutional neural network brain tumor classiﬁcation

Automated Leukemia Screening and Sub-types Classification Using Deep Learning

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Computer Systems Science & Engineering 2023年第9期46卷 3541-3558页

作者： Chaudhary Hassan Abbas Gondal muhammad Irfan Sarmad Shafique muhammad Salman Bashir mansoor Ahmed osama m.alshehri Hassan H.Almasoudi Samar m.Alqhtani mohammed m.Jalal malik A.Altayar Khalaf F.Alsharif Department of Computer Science COMSATS University Islamabad44000Pakistan Electrical Engineering Department College of EngineeringNajran UniversityNajran61441Saudi Arabia Control Automotive and Robotics LabNational Center of Robotics and Automation(NCRA HEC)MirpurPakistan Mirpur University of Science and Technology(MUST)MirpurPakistan Department of Computer Science Virtual University of PakistanLahore54000Pakistan Department of Clinical Laboratory Sciences College of Applied Medical SciencesNajran UniversityNajran61441Saudi Arabia Department of Information Systems College of Computer Science and Information SystemsNajran UniversityNajran61441Saudi Arabia Department of medical Laboratory Technology Faculty of Applied Medical SciencesUniversity of TabukTabukSaudi Arabia Department of Clinical Laboratory Sciences College of Applied Medical SciencesTaif UniversityP.O.Box 11099Taif21944Saudi Arabia

Leukemia is a kind of blood cancer that damages the cells in the blood and bone marrow of the human *** produces cancerous blood cells that disturb the human’s immune system and significantly affect bone marrow’s production ability to effectively create different types of blood cells like red blood cells(RBCs)and white blood cells(WBC),and *** can be diagnosed manually by taking a complete blood count test of the patient’s blood,from which medical professionals can investigate the signs of leukemia ***,two other methods,microscopic inspection of blood smears and bone marrow aspiration,are also utilized while examining the patient for ***,all these methods are labor-intensive,slow,inaccurate,and require a lot of human experience and *** authors have proposed automated detection systems for leukemia diagnosis to overcome these *** have deployed digital image processing and machine learning algorithms to classify the cells into normal and blast ***,these systems are more efficient,reliable,and fast than previous manual diagnosing ***,more work is required to classify leukemia-affected cells due to the complex characteristics of blood images and leukemia cells having much intra-class variability and inter-class *** this paper,we have proposed a robust automated system to diagnose leukemia and its *** have classified ALL into its sub-types based on FAB classification,i.e.,L1,L2,and L3 types with better *** have achieved 96.06%accuracy for subtypes classification,which is better when compared with the state-of-the-art methodologies.

关键词： Healthcare cancer detection deep learning convolutional neural network

motion-Based Activities monitoring through Biometric Sensors Using Genetic Algorithm

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Computers, materials & Continua 2021年第3期66卷 2525-2538页

作者： mohammed alshehri Purushottam Sharma Richa Sharma osama Alfarraj Department of Information Technology College of Computer and Information SciencesMajmaah UniversityMajmaah11952Saudi Arabia ASET Amity University NoidaNoida201301India Computer Science Department Community CollegeKing Saud UniversityRiyadhSaudi Arabia

Sensors and physical activity evaluation are quite limited for motionbased commercial *** the accelerometer of the smartwatch is utilized;walking is *** combination can perform better in terms of sensors and that can be determined by sensors on both the smartwatch and phones,i.e.,accelerometer and *** biometric efficiency,some of the diverse activities of daily routine have been evaluated,also with biometric *** result shows that using the different computing techniques in phones and watch for biometric can provide a suitable output based on the mentioned *** indicates that the high feasibility and results of continuous biometrics analysis in terms of average daily routine *** this research,the set of rules with the real-valued attributes are evolved with the use of a genetic *** the help of real value genes,the real value attributes cab be encoded,and presentation of new methods which are represents not to cares in the *** rule sets which help in maximizing the number of accurate classifications of inputs and supervise classifications are viewed as an optimization *** use of Pitt approach to the mL(machine Learning)and Genetic based system that includes a resolution mechanism among rules that are competing within the same rule sets is *** enhances the efficiency of the overall system,as shown in the research.

关键词： Genetic algorithms biometrics data mining sensors smartphone smartwatch

Self-management of Low Back Pain Using Neural Network

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Computers, materials & Continua 2021年第1期66卷 885-901页

作者： Purushottam Sharma mohammed alshehri Richa Sharma osama Alfarraj ASET Amity University Uttar PradeshNoida201301India Department of Information Technology College of Computer and Information SciencesMajmaah UniversityMajmaah11952Saudi Arabia Computer Science Department Community CollegeKing Saud UniversityRiyadhSaudi Arabia

Low back pain(LBP)is a morbid condition that has afflicted several citizens in *** has negatively impacted the European economy due to several man-days lost,with bed rest and forced inactivity being the usual LBP care and management *** models,which incorporate various regression analyses,have been executed for the investigation of this premise due to the simplicity of ***,such straight models fail to completely consider the impact of association brought about by a mix of nonlinear connections and autonomous *** this paper,we discuss a system that aids decision-making regarding the best-suited support system for LBP,allowing the individual to avail of reinforcement and improvement in its *** activities are monitored with the help of a wearable sensor that helps in their detection and their classification as those that soothe or aggravate LBP and hence,should or should not be *** system helps the patients set their own boundaries and milestones with respect to suitable *** system also does windowing and feature *** present study is an empirical and comparative analysis of the most suitable activities that patients suffering from low back pain can *** evaluation shows that the system can distinguish between nine common daily activities effectively and helps self-monitor these activities for the efficient management of LBP.

关键词： Low back pain neural networks sensor classification time series

Feature Subset Selection with Artificial Intelligence-Based Classification model for Biomedical Data

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Computers, materials & Continua 2022年第9期72卷 4267-4281页

作者： Jaber S.Alzahrani Reem m.alshehri mohammad Alamgeer Anwer mustafa Hilal Abdelwahed motwakel Ishfaq Yaseen Department of Industrial Engineering College of Engineering at AlqunfudahUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Computing and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Systems College of Science&Art at MahayilKing Khalid UniversityMahayil62529Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharj62529Saudi Arabia

Recently,medical data classification becomes a hot research topic among healthcare professionals and research communities,which assist in the disease diagnosis and decision making *** latest developments of artificial intelligence(AI)approaches paves a way for the design of effective medical data classification *** the same time,the existence of numerous features in the medical dataset poses a curse of dimensionality *** resolving the issues,this article introduces a novel feature subset selection with artificial intelligence based classification model for biomedical data(FSS-AICBD)*** FSS-AICBD technique intends to derive a useful set of features and thereby improve the classifier ***,the FSS-AICBD technique undergoes min-max normalization technique to prevent data *** addition,the information gain(IG)approach is applied for the optimal selection of feature ***,group search optimizer(GSO)with deep belief network(DBN)model is utilized for biomedical data classification where the hyperparameters of the DBN model can be optimally tuned by the GSO *** choice of IG and GSO approaches results in promising medical data classification *** experimental result analysis of the FSS-AICBD technique takes place using different benchmark healthcare *** simulation results reported the enhanced outcomes of the FSS-AICBD technique interms of several measures.

关键词： medical data classification feature selection deep learning healthcare sector artificial intelligence

Effect of rare earth(Nd^(3+))metal doping on structural,morphological,optical and magnetic traits of Zn-mg nano-ferrites

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Journal of Rare Earths 2023年第11期41卷 1763-1770,I0004页

作者： Rohit Jasrotia Nisha Kumari Ritesh Verma Suman Sachin Kumar Godara Jahangeer Ahmed Saad m.alshehri Bidhan Pandit Sanjay Kumar Himanshi Shubham Sharma Kirti Pradip K.maji School of Physics&materials Science Shoolini University of Biotechnology and Management SciencesSolanHimachal Pradesh173229India Himalayan Centre of Excellence in Nanotechnology Shoolini UniversityBajholSolanH.P173229India Department of Physics Baddi University of Emerging Science and TechnologyMakhnumajraBaddiHimachal Pradesh173205India Department of Physics Amity University HaryanaGururgram122413India Department of mathematics School of Basic and Applied SciencesMaharaja Agrasen UniversityBaddiH.P174103India Department of Apparel and Textile Technology Guru Nanak Dev UniversityAmritsar143005India Department of Chemistry College of ScienceKing Saud UniversityP.O.Box 2455Riyadh11451Saudi Arabia Department of materials Science and Engineering and Chemical Engineering Universidad Carlos III de MadridAvenida de la Universidad 3028911LeganésMadridSpain School of Advanced Chemical Sciences Shoolini University of Biotechnology and Management SciencesSolanHimachal Pradesh173229India Dept.of Polymer&Process Engineering Indian Institute of Technology RoorkeeSaharanpurUttar Pradesh247001India

Herein,we report the synthesis of Zn_(0.7)mg_(0.3)Nd_(x)Fe_(2-x)O_(4)(where,x=0,0,0,01,0,02)ferrite nanoparticles by employing the sol-gel auto-combustion *** X-ray diffraction(XRD)pattern suggests the formation of a pure cubic structure,without any impurity phase,with an Fd3m space group at room *** increasing doping amount,the crystallite size is reported as 35-41 nm,while the lattice parameters rise from 0.8381 to 0.8395 *** emission scanning electron microscopy(FESEm)images show the formation of spherical grains with agglomerated morphology in all the samples,with grain sizes ranging from 49 to 103 *** dispersive X-ray spectroscopy(EDX)and elemental mapping investigation confirm the chemical purity of all the *** transform infrared(FTIR)analysis shows the presence of two prominent peaks around 440 and 560 cm^(-1)that correspond to the octahedral and tetrahedral *** addition,the existence of five Raman active vibratio nal modes in all produced specimens again confirms the structural purity of all the *** m-H curve shows that saturation magnetization(m_(s))first increases from 14.98 to 28.22 emu/g and then decreases to 18.98emu/g with increasing doping *** is due to the A-B type super-exchange interaction for the synthesized *** variation in coercivity(H_(c))and magnetic anisotropy(K_(1))suggest the thermal stability of all the samples and can be utilized in transformers and solenoids.

关键词： magnetic nanoparticles Saturation magnetization Sol-gel auto-combustion synthesis Super-exchange interaction Cubic crystal structure Rare earths

Deep Learning Enabled microarray Gene Expression Classification for Data Science Applications

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Computers, materials & Continua 2022年第11期73卷 4277-4290页

作者： Areej A.malibari Reem m.alshehri Fahd N.Al-Wesabi Noha Negm mesfer Al Duhayyim Anwer mustafa Hilal Ishfaq Yaseen Abdelwahed motwakel 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 Department of Computer Science College of Science&Art at MahayilKing Khalid UniversitySaudi Arabia Department of Natural and Applied Sciences College of Community-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharjSaudi Arabia

In bioinformatics applications,examination of microarray data has received significant interest to diagnose *** gene expression data can be defined by a massive searching space that poses a primary challenge in the appropriate selection of *** data classification incorporates multiple disciplines such as bioinformatics,machine learning(mL),data science,and pattern *** paper designs an optimal deep neural network based microarray gene expression classification(ODNN-mGEC)model for bioinformatics *** proposed ODNN-mGEC technique performs data normalization process to normalize the data into a uniform ***,improved fruit fly optimization(IFFO)based feature selection technique is used to reduce the high dimensionality in the biomedical ***,deep neural network(DNN)model is applied for the classification of microarray gene expression data and the hyperparameter tuning of the DNN model is carried out using the Symbiotic Organisms Search(SOS)*** utilization of IFFO and SOS algorithms pave the way for accomplishing maximum gene expression classification *** examining the improved outcomes of the ODNN-mGEC technique,a wide ranging experimental analysis is made against benchmark *** extensive comparison study with recent approaches demonstrates the enhanced outcomes of the ODNN-mGEC technique in terms of different measures.

关键词： Bioinformatics data science microarray gene expression data classification deep learning metaheuristics

A Holistic,Proactive and Novel Approach for Pre,During and Post migration Validation from Subversion to Git

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Computers, materials & Continua 2021年第3期66卷 2359-2371页

作者： Vinay Singh mohammed alshehri Alok Aggarwal osama Alfarraj Purushottam Sharma K.R.Pardasani School of Computer Science University of Petroleum&Energy StudiesDehradunIndia Department of Information Technology College of Computer and Information SciencesMajmaah UniversityMajmaah11952Saudi Arabia Computer Science Department Community CollegeKing Saud UniversityRiyadhSaudi Arabia Amity School of Engineering&Technology Amity UniversityUttar PradeshNoidaIndia Department of mathematics Bioinformatics&Computer ApplicationsMaulana Azad National Institute of TechnologyBhopal462003India

Software development is getting a transition from centralized version control systems(CVCSs)like Subversion to decentralized version control systems(DVCDs)like Git due to lesser efficiency of former in terms of branching,fusion,time,space,merging,offline commits&builds and repository,*** is having a share of 77%of total VCS,followed by Subversion with a share of 13.5%.The majority of software industries are getting a migration from Subversion to *** a few migration tools are available in the software ***,these too lack in many features like lack of identifying the empty directories as premigration check,failover capabilities during migration due to network failure or disk space issue,and detailed report generation as post-migration *** this work,a holistic,proactive and novel approach has been presented for pre/during/post-migration validation from Subversion to *** scripts have been developed and executed run-time over various projects for overcoming the limitations of existing migration software tools for a Subversion to Git *** premigration,none of the available migration tools has the capability to fetch empty directories of Subversion,which results in an incomplete migration from Subversion to *** Scripts have been developed and executed for pre-migration validation and migration preparation,which overcomes the problem of incomplete *** was conducted in SRLC Software Research Lab,Chicago,*** the migration process,in case of loss of network connection or due to any other reason,if migration stops or breaks,available migration tools do not have capabilities to start over from the same point where it *** Scripts have been developed and executed to keep the migration revision history in the cache(elastic cache)to start from the same point where it was left due to connection *** post-migration,none of the available version control migration tools generate a detailed repo

关键词： Databases and information systems subversion Git version control system trunk tag translational settings author mapping

Effects of Bentonite,Hydrogel and Biochar Amendments on Soil Hydraulic Properties from Saturation to Oven Dryness

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Pedosphere 2019年第5期29卷 598-607页

作者： osama m0HAWESH Wolfgang DURNER Department of Plant Production Faculty of AgricultureMutah UniversityKarak 61710 (Jordan) Division of Environmental Science and Technology Graduate School of AgricultureKyoto UniversityKyoto 6110011 (Japan) Institute of Geoecology Technical University of BraunschweigLanger Kamp 19cBraunschweig 38106 (Germany)

Effects of hydrogel, bentonite, and biochar as soil amendments on soil hydraulic properties and improving water availability from saturation to oven dryness were investigated. Soils were mixed with hydrogel (0.10%, 0.25%, and 0.50%), bentonite (0.5%, 1.0%, and 2.5%), and biochar (1.0%, 2.5%, and 5.0%) as soil amendments (weight:weight). Three methods (extended multistep outflow (XmSO), evaporation (EVA), and WP4 dewpoint potentiometer) were used to measure soil hydraulic properties from saturation to oven dryness. The cumulative XmSO results were more uniform across all the applied pressure steps for the amended soils. The EVA exhibited a shorter linear decrease during the first evaporation stage and a lower evaporation rate during the second evaporation stage. The WP4 results also exhibited that soil amendments increased the soil water content of the amended soils at low matric potentials. The results of soil water retention curves revealed that the unamended soil retained less water at any matric potential compared to the amended soils. Soil hydraulic conductivity decreased with increasing amount of soil amendments. The saturated hydraulic conductivity was higher for the unamended soil than the soils amended w计h 2.5% bentonite, 0.50% hydrogel, and 5.0% biochar by 11, 3, and 18 times, respectively. These results suggested that soil amendments improved soil water retentivity, which confirmed the appropriateness of these soil amendments for potential use in sandy soil improvements. However, field experiments and economical perception studies should be considered for further investigation.

关键词： evaporation extended multistep outflow soil amendment soil matric potential soil moisture soil water retentivity water availability WP4 dewpoint potentiometer