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Two-dimensional investigation of characteristic parameters and their gradients for the self-generated electric and magnetic fields of laser-induced zirconium plasma

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Plasma Science and Technology 2024年第5期26卷 138-155页

作者： Tayyaba SAJID Shazia BASHIR Mahreen AKRAM Maira RAZZAQ khaliq MAHMOOD Centre for Advanced Studies in Physics Institute of PhysicsGovernment College University LahoreLahore 54000Pakistan Department of Physics Institute of PhysicsGovernment College University LahoreLahore 54000Pakistan

Two-dimensional diagnosis of laser-induced zirconium(Zr)plasma has been experimentally performed using the time-of-flight method by employing Faraday cups in addition to electric and magnetic *** characteristic parameters of laser-induced Zr plasma have been evaluated as a function of different laser irradiances ranging from 4.5 to 11.7 GW cm-2 at different axial positions of 1–4 cm with a fixed radial distance of 2 cm.A well-supporting correlation between the plume parameters and the laser-plasma-produced spontaneous electric and magnetic(E and B)fields was *** measurements of the characteristic parameters and spontaneously induced fields were observed to have an increasing trend with the increasing laser ***,when increasing the spatial distance in both the axial and radial directions,the plasma parameters(electron/ion number density,temperature and kinetic energy)did not show either continuously increasing or decreasing trends due to various kinetic and dynamic processes during the spatial evolution of the ***,the E and B fields were observed to be always diffusing away from the *** radial component of electron number densities remained higher than the axial number density component,whereas the axial ion number density at all laser irradiances and axial distances remained higher than the radial ion number *** higher axial self-generated electric field(SGEF)values than radial SGEF values are correlated with the effective charge-separation mechanism of electrons and *** generation of a self-generated magnetic field is observed dominantly in the radial direction at increasing laser irradiance as compared to the axial one due to the deflection of fast-moving electrons and the persistence of two-electron temperature on the radial axis.

关键词： Faraday cup axial and radial expansion space-charge effect laser-induced zirconium plasma two-electron temperature distribution self-generated electric and magnetic fields

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Enhanced Topic-Aware Summarization Using Statistical Graph Neural Networks

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Computers, Materials & Continua 2024年第8期80卷 3221-3242页

作者： Ayesha khaliq Salman Afsar Awan Fahad Ahmad Muhammad Azam Zia Muhammad Zafar Iqbal Department of Computer Science University of Agriculture FaisalabadFaisalabadPunjab37300Pakistan School of Computing Faculty of TechnologyUniversity of PortsmouthSouthseaPortsmouthPO12UPUK Department of Mathematics and Statistics University of Agriculture FaisalabadFaisalabadPunjab37300Pakistan

The rapid expansion of online content and big data has precipitated an urgent need for efficient summarization techniques to swiftly comprehend vast textual documents without compromising their original *** approaches in Extractive Text Summarization(ETS)leverage the modeling of inter-sentence relationships,a task of paramount importance in producing coherent *** study introduces an innovative model that integrates Graph Attention Networks(GATs)with Transformer-based Bidirectional Encoder Representa-tions from Transformers(BERT)and Latent Dirichlet Allocation(LDA),further enhanced by Term Frequency-Inverse Document Frequency(TF-IDF)values,to improve sentence selection by capturing comprehensive topical *** approach constructs a graph with nodes representing sentences,words,and topics,thereby elevating the interconnectivity and enabling a more refined understanding of text *** model is stretched to Multi-Document Summarization(MDS)from Single-Document Summarization,offering significant improvements over existing models such as THGS-GMM and Topic-GraphSum,as demonstrated by empirical evaluations on benchmark news datasets like Cable News Network(CNN)/Daily Mail(DM)and *** results consistently demonstrate superior performance,showcasing the model’s robustness in handling complex summarization tasks across single and multi-document *** research not only advances the integration of BERT and LDA within a GATs but also emphasizes our model’s capacity to effectively manage global information and adapt to diverse summarization challenges.

关键词： Summarization graph attention network bidirectional encoder representations from transformers Latent Dirichlet Allocation term frequency-inverse document frequency

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Autologous hematopoietic stem cell transplantation conditioning regimens and chimeric antigen receptor T cell therapy in various diseases

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World Journal of Transplantation 2024年第1期14卷 32-41页

作者： Shahzaib Maqbool Maryam Farhan Baloch Muhammad Abdul khaliq Khan Azeem Khalid Kiran Naimat Department of Medicine Holy Family HospitalRawalpindi 46000Pakistan Department of Community Medicine Allama Iqbal Medical CollegeLahore 45000Pakistan Department of Community Dentistry Baqai Medical UniversityKarachi 43000Pakistan Department of Medicine Allama lqbal Medical CollegeLahore 45000Pakistan Department of MedicineLiaquat University of Medical and Health Sciences Karachi 43000Pakistan

Conditioning regimens employed in autologous stem cell transplantation have been proven useful in various hematological disorders and underlying malignancies;however,despite being efficacious in various instances,negative consequences have also been *** conditioning regimens were extracted from various literature searches from databases like PubMed,Google scholar,EMBASE,and *** regimens for each disease were compared by using various end points such as overall survival(OS),progression free survival(PFS),and leukemia free survival(LFS).Variables were presented on graphs and analyzed to conclude a more efficacious conditioning *** multiple myeloma,the most effective regimen was high dose melphalan(MEL)given at a dose of 200/mg/*** comparative results of acute myeloid leukemia were presented and the regimens that proved to be at an admirable position were busulfan(BU)+MEL regarding OS and BU+VP16 regarding *** case of acute lymphoblastic leukemia(ALL),BU,fludarabine,and etoposide(BuFluVP)conferred good disease control not only with a paramount improvement in survival rate but also low risk of ***,for ALL,chimeric antigen receptor(CAR)T cell therapy was preferred in the context of better OS and *** respect to Hodgkin’s lymphoma,mitoxantrone(MITO)/MEL overtook carmustine,VP16,cytarabine,and MEL in view of PFS and vice versa regarding ***-Hodgkin’s lymphoma patients were administered MITO(60 mg/m2)and MEL(180 mg/m2)which showed promising ***,amyloidosis was considered,and the regimen that proved to be competent was MEL 200(200 mg/m2).This review article demonstrates a comparison between various conditioning regimens employed in different diseases.

关键词： Conditioning regimens Multiple myeloma Lymphoma Hodgkin Non-Hodgkin Acute leukemia

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Decoding degeneration:the implementation of machine learning for clinical detection of neurodegenerative disorders

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Neural Regeneration Research 2023年第6期18卷 1235-1242页

作者： Fariha khaliq Jane Oberhauser Debia Wakhloo Sameehan Mahajani Department of Biomedical Engineering and Sciences(BMES) National University of Science and TechnologyIslamabadPakistan Department of Neuropathology School of MedicineStanford UniversityStanfordCAUSA

Machine learning represents a growing subfield of artificial intelligence with much promise in the diagnosis,treatment,and tracking of complex conditions,including neurodegenerative disorders such as Alzheimer’s and Parkinson’s *** no definitive methods of diagnosis or treatment exist for either disease,researchers have implemented machine learning algorithms with neuroimaging and motion-tracking technology to analyze pathologically relevant symptoms and *** learning algorithms such as neural networks and complex combined architectures have proven capable of tracking disease-linked changes in brain structure and physiology as well as patient motor and cognitive symptoms and responses to ***,such techniques require further development aimed at improving transparency,adaptability,and *** this review,we provide an overview of existing neuroimaging technologies and supervised and unsupervised machine learning techniques with their current applications in the context of Alzheimer’s and Parkinson’s diseases.

关键词： Alzheimer’s disease clinical detection deep learning machine learning neurodegenerative disorders neuroimaging Parkinson’s disease

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A Three-Dimensional Real-Time Gait-Based Age Detection System Using Machine Learning

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Computers, Materials & Continua 2023年第4期75卷 165-182页

作者： Muhammad Azhar Sehat Ullah Khalil Ullah Habib Shah Abdallah Namoun khaliq Ur Rahman Department of Computer Science&IT University of MalakandChakdara18800Pakistan Department of Software Engineering University of MalakandChakdara18800Pakistan College of Computer Science King Khalid UniversityAbha62529Saudi Arabia Faculty of Computer and Information Systems Islamic University of MadinahMadinah42351Saudi Arabia Department of Statistics Abdul Wali Khan UniversityMardan23200Pakistan

Human biometric analysis has gotten much attention due to itswidespread use in different research areas, such as security, surveillance,health, human identification, and classification. Human gait is one of the keyhuman traits that can identify and classify humans based on their age, gender,and ethnicity. Different approaches have been proposed for the estimation ofhuman age based on gait so far. However, challenges are there, for which anefficient, low-cost technique or algorithm is needed. In this paper, we proposea three-dimensional real-time gait-based age detection system using a machinelearning approach. The proposed system consists of training and testingphases. The proposed training phase consists of gait features extraction usingthe Microsoft Kinect (MS Kinect) controller, dataset generation based onjoints’ position, pre-processing of gait features, feature selection by calculatingthe Standard error and Standard deviation of the arithmetic mean and bestmodel selection using R2 and adjusted R2 techniques. T-test and ANOVAtechniques show that nine joints (right shoulder, right elbow, right hand, leftknee, right knee, right ankle, left ankle, left, and right foot) are statisticallysignificant at a 5% level of significance for age estimation. The proposedtesting phase correctly predicts the age of a walking person using the resultsobtained from the training phase. The proposed approach is evaluated on thedata that is experimentally recorded from the user in a real-time *** (50) volunteers of different ages participated in the experimental *** the limited features, the proposed method estimates the age with 98.0%accuracy on experimental images acquired in real-time via a classical generallinear regression model.

关键词： Age estimation gait biometrics classical linear regression model

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Convolutional Neural Network-Based Classificationof Multiple Retinal Diseases Using Fundus Images

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Intelligent Automation & Soft Computing 2023年第6期36卷 2607-2622页

作者： Aqsa Aslam Saima Farhan Momina Abdul khaliq Fatima Anjum Ayesha Afzaal Faria Kanwal Lahore College for Women University Lahore54000Pakistan

Use of deep learning algorithms for the investigation and analysis of medical images has emerged as a powerful *** increase in retinal dis-eases is alarming as it may lead to permanent blindness if left ***-tion of the diagnosis process of retinal diseases not only assists ophthalmologists in correct decision-making but saves time *** researchers have worked on automated retinal disease classification but restricted either to hand-crafted fea-ture selection or binary *** paper presents a deep learning-based approach for the automated classification of multiple retinal diseases using fundus *** this research,the data has been collected and combined from three distinct *** images are preprocessed for enhancing the *** layers of the convolutional neural network(CNN)are used for the automated feature extraction and classification of 20 retinal *** is observed that the results are reliant on the number of *** binary classification(healthy ***),up to 100%accuracy has been *** 16 classes are used(treating stages of a disease as a single class),93.3%accuracy,92%sensitivity and 93%specificity have been obtained *** 20 classes(treating stages of the disease as separate classes),the accuracy,sensitivity and specificity have dropped to 92.4%,92%and 92%respectively.

关键词： Classification convolutional neural network fundus images medical image diagnosis retinal diseases

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Optical dromions for complex Ginzburg Landau model with nonlinear media

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Applied Mathematics(A Journal of Chinese Universities) 2023年第1期38卷 111-125页

作者： Syed T.R.Rizvi Aly R.Seadawy Muhammad Younis S.O.Abbas Abdul khaliq Department of Mathematics COMSATS University IslamabadLahore CampusPakistan Mathematics Department Faculty of ScienceTaibah UniversityAl-Madinah Al-Munawarah 41411Kingdom of Saudi Arabia Punjab University College of Information Technology University of the PunjabLahore Pakistan Mathematics Department Riphah Institute of Computing and Applied SciencesRiphah International UniversityLahorePakistan

This manuscript studies the optical dromions with beta derivative(BD)applied to the Complex Ginzburg Landau equation(CGLE)with Kerr law,parabolic law,cubic quintic septic law and quadratic cubic *** obtain bright dromians by using the sine-cosine method(SCM).We will also obtain domain walls with the assistance of Bernoulli equation approach(BEA).Constraint conditions are also listed.

关键词： CGLE optical dromians non-Kerr laws

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Indirect Vector Control of Linear Induction Motors Using Space Vector Pulse Width Modulation

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Computers, Materials & Continua 2023年第3期74卷 6263-6287页

作者： arjm.nd khaliq Syed Abdul Rahman Kashif Fahad Ahmad Muhammad Anwar Qaisar Shaheen Rizwan Akhtar Muhammad Arif Shah Abdelzahir Abdelmaboud Electrical Engineering Department University of Engineering and TechnologyLahore54700Pakistan Department of Basic Sciences Deanship of Common First YearJouf UniversitySakakaAljouf72341Saudi Arabia Department of Information Science Division of Science and TechnologyUniversity of EducationLahore54000Pakistan Department of Computer Science and Information Technology The Islamia University of BahawalpurRahim Yar Khan Sub CampusPakistan Department of IT and Computer Science Pak-Austria Fachhochschule Institute of Applied Sciences and TechnologyHaripurPakistan Department of Information Systems King Khalid UniversityMuhayel Aseer61913Saudi Arabia

Vector control schemes have recently been used to drive linear induction motors(LIM)in high-performance *** trend promotes the development of precise and efficient control schemes for individual *** research aims to present a novel framework for speed and thrust force control of LIM using space vector pulse width modulation(SVPWM)*** framework under consideration is developed in four *** begin,MATLAB Simulink was used to develop a detailed mathematical and electromechanical *** research presents a modified SVPWM inverter control *** tuning the proportional-integral(PI)controller with a transfer function,optimized values for the PI controller are *** the subsystems mentioned above are integrated to create a robust simulation of the LIM’s precise speed and thrust force control *** reference speed values were chosen to evaluate the performance of the respective system,and the developed system’s response was verified using various data *** the low-speed range,a reference value of 10m/s is used,while a reference value of 100 m/s is used for the high-speed *** speed output response indicates that themotor reached reference speed in amatter of seconds,as the delay time is between 8 and 10 *** maximum amplitude of thrust achieved is less than 400N,demonstrating the controller’s capability to control a high-speed LIM with minimal thrust *** to the controlled speed range,the developed system is highly recommended for low-speed and high-speed and heavy-duty traction applications.

关键词： Space vector pulse width modulation linear induction motor proportional-integral controller indirect vector control electromechanical dynamic modeling

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Investigation of secondary phases and tensile strength of nitrogen-containing Alloy 718 weldment

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International Journal of Minerals,Metallurgy and Materials 2020年第9期27卷 1259-1268页

作者： Behrooz Nabavi Massoud Goodarzi Abdul khaliq Khan School of Metallurgy and Materials Engineering Iran University of Science and TechnologyTehran ***Iran Department of Mechanical Engineering Manitoba Institute for MaterialsUniversity of ManitobaWinnipeg R3T 2N2Canada

The influence of nitrogen content on the precipitation of secondary phases and the tensile strength of Alloy 718 during gas tungstenarc welding was investigated. Various types of precipitates were characterized using scanning electron microscopy and transmission electronmicroscopy. The results showed that in the fusion zone, the volume fraction of Nb-rich phases such as Laves, (Nb,Ti)C, and δ phases, as wellas Ti-rich phases such as (Ti,Nb)CN and (Ti,Nb)N, increased with increase in the nitrogen content due to the microsegregation of Nb and Tiwithin interdendritic areas. Nitrogen was also found to decrease the size of γ′′ particles within γ dendrites. For precipitates in the partiallymelted zone, constitutional liquation was observed for both (Nb,Ti)C and (Ti,Nb)N particles. Based on the results of tensile tests, the weld containing0.015wt% nitrogen exhibited the highest ultimate tensile strength (UTS), whereas more addition of nitrogen led to a decrease in both theUTS and yield strength due to the increased content of brittle Laves phases and decreased size of γ′′.

关键词： nitrogen secondary phases gas tungsten arc welding tensile strength Alloy 718

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SDN-based intrusion detection system for IoT using deep learning classifier (IDSIoT-SDL)

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CAAI Transactions on Intelligence Technology 2021年第3期6卷 281-290页

作者： Azka Wani Revathi S Rubeena khaliq Department of Computer Applications Crescent B S Abdur Rahman Institute of Science and TechnologyChennaiIndia Department of Computer Science and Engineering Crescent B S Abdur Rahman Institute of Science and TechnologyChennaiIndia Department of Mathematics Crescent B S Abdur Rahman Institute of Science and TechnologyChennaiIndia

The participation of ordinary devices in networking has created a world of connected devices *** Internet of Things(IoT)includes heterogeneous devices from every *** are no definite protocols or standards for IoT communication,and most of the IoT devices have limited *** a complete security measure for such devices is a challenging task,yet *** lightweight security solutions have surfaced lately for *** lightweight security protocols are unable to provide an optimum protection against prevailing powerful threats in cyber *** is also hard to deploy any traditional security protocol on resource-constrained IoT ***-defined networking introduces a centralized control in computer *** has a programmable approach towards networking that decouples control and data *** SDN-based intrusion detection system is proposed which uses deep learning classifier for detection of anomalies in *** proposed intrusion detection system does not burden the IoT devices with security *** proposed work is executed on the simulated *** results of the simulation test are evaluated using various matrices and compared with other relevant methods.

关键词： IoT classifier system

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