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Intelligent Forecasting Model of COVID-19 Novel Coronavirus Outbreak Empowered with Deep Extreme Learning Machine

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Computers, Materials & Continua 2020年第9期64卷 1329-1342页

作者： Muhammad Adnan k.an Sagheer Abbas khalid masood k.an Mohammed AAl Ghamdi Abdur Rehman Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan Department of Computer Science National College of Business Administration&EconomicsLahore54000Pakistan Department of Computer Science Umm Al-Qura UniversityMakkah23500Saudi Arabia

An epidemic is a quick.and widespread disease that threatens many lives and damages the *** epidemic lifetime should be accurate so that timely and remedial steps are *** include the closing of borders schools,suspension of community and commuting *** forecast of an outbreak effectively is a very necessary but difficult task.A predictive model that provides the best possible forecast is a great challenge for machine learning with only a few samples of training *** work proposes and examines a prediction model based on a deep extreme learning machine(DELM).This methodology is used to carry out an experiment based on the recent Wuhan coronavirus *** optimized prediction model that has been developed,namely DELM,is demonstrated to be able to make a prediction that is fairly *** results show that the new methodology is useful in developing an appropriate forecast when the samples are far from abundant during the critical period of the *** the investigation,it is shown that the proposed approach has the highest accuracy rate of 97.59%with 70%of training,30%of test and *** results validate the prediction effectiveness of the proposed scheme.

关键词： Coronavirus nCoV DELM Mis rate SERS-CoV WHO COVID-19

Social Distancing and Isolation Management Using Machine-to-Machine Technologies to Prevent Pandemics

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Computers, Materials & Continua 2021年第6期67卷 3545-3562页

作者： Muhammad Saad Maaz Bin Ahmad Muhammad Asif khalid masood Mohammad A.Al Ghamdi College of Computing and Information Sciences PAF KIETKarachiPakistan Department of Computer Science Lahore Garrison UniversityLahorePakistan Department of Computer Science Umm Al-Qura UniversityMakkah CitySaudi Arabia

Social distancing and self-isolation management are crucial preventive measures that can save millions of lives during challenging pandemics of diseases such as the Spanish u,swine u,and coronavirus disease 2019(COVID-19).This study describes the comprehensive and effective implementation of the Industrial Internet of Things and machine-to-machine technologies for social distancing and smart self-isolation *** technologies can help prevent outbreaks of any disease that can disperse widely and develop into a ***,a smart wristband is proposed that incorporates Bluetooth beacon technology to facilitate the tracing and tracking of Bluetooth Low Energy beacon packets for smart contact ***,the connectivity of the device with Android or iOS applications using long-term evolution technology is realized to achieve ***,mathematical formulations are proposed to measure the distance between coordinates in order to detect geo-fencing *** formulations are specically designed for the virtual circular and polygonal boundaries used to restrict suspected or infected persons from trespassing in predetermined areas,e.g.,at home,in a hospital,or in an isolation *** proposed framework outperforms existing solutions,since it is implemented on a wider scale,provides a range of functionalities,and is cost-effective.

关键词： Coronavirus disease 2019 pandemic machine-to-machine industrial internet of things social distance geo-fencing

Intelligent Decision Support System for COVID-19 Empowered with Deep Learning

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Computers, Materials & Continua 2021年第2期66卷 1719-1732页

作者： Shahan Yamin Siddiqui Sagheer Abbas Muhammad Adnan k.an Iftikhar Naseer Tehreem masood khalid masood k.an Mohammed A.Al Ghamdi Sultan H.Almotiri School of Computer Science NCBA&ELahore54000Pakistan School of Computer Science Minhaj University LahoreLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54792Pakistan Department of Computer Science&Information Technology Superior UniversityLahore54000Pakistan Computer Science Department Umm Al-Qura UniversityMakkah City715Saudi Arabia

The prompt spread of Coronavirus(COVID-19)subsequently adorns a big threat to the people around the *** evolving and the perpetually diagnosis of coronavirus has become a critical challenge for the healthcare *** increase of COVID-19 has rendered the necessity to detect the people who are more likely to get ***,the testing kits for COVID-19 are not available to deal it with required proficiency,along with-it countries have been widely hit by the COVID-19 *** keep in view the need of hour asks for an automatic diagnosis system for early detection of *** would be a feather in the cap if the early diagnosis of COVID-19 could reveal that how it has been affecting the masses *** to the apparent clinical research,it has unleashed that most of the COVID-19 cases are more likely to fall for a lung *** abrupt changes do require a solution so the technology is out there to pace up,Chest X-ray and Computer tomography(CT)scan images could significantly identify the preliminaries of COVID-19 like lungs *** scan and X-ray images could flourish the cause of detecting at an early stage and it has proved to be helpful to radiologists and the medical *** unbearable circumstances compel us to flatten the curve of the sufferers so a need to develop is obvious,a quick.and highly responsive automatic system based on Artificial Intelligence(AI)is always there to aid against the masses to be prone to *** proposed Intelligent decision support system for COVID-19 empowered with deep learning(ID2S-COVID19-DL)study suggests Deep learning(DL)based Convolutional neural network(CNN)approaches for effective and accurate detection to the maximum extent it could be,detection of coronavirus is assisted by using X-ray and CT-scan *** primary experimental results here have depicted the maximum accuracy for training and is around 98.11 percent and for validation it comes out to be approxim

关键词： COVID-19 deep learning convolutional neural network CT-scan X-ray decision support system ID2S-COVID19-DL

Identification of Anomaly Scenes in Videos Using Graph Neural Networks

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Computers, Materials & Continua 2023年第3期74卷 5417-5430页

作者： khalid masood Mahmoud M.Al-Sakhnini Waqas Nawaz Tauqeer Faiz Abdul Salam Mohammad Hamza kashif Department of Software Engineering Lahore Garrison UniversityLahore54000Pakistan School of Business Skyline University CollegeSharjahUAE Al-Madinah International University–Faculty of Computer and Information Technology Kuala LumpurMalaysia College of Computer and Information Systems Islamic University of MadinahMadinahKingdom of Saudi Arabia School of IT Skyline University CollegeSharjahUAE Faculty of Engineering Computing and Science(FECS)-Swinburne University of TechnologySarawak Department of General Education Skyline University CollegeUniversity City of SharjahUAE Department of Computer Science Lahore Garrison UniversityLahore54000Pakistan

Generally,conventional methods for anomaly detection rely on clustering,proximity,or *** themassive growth in surveillance videos,outliers or anomalies find ingenious ways to obscure themselves in the network.and make conventional techniques *** research explores the structure of Graph neural networks(GNNs)that generalize deep learning frameworks to graph-structured *** node in the graph structure is labeled and anomalies,represented by unlabeled nodes,are predicted by performing random walks on the node-based graph *** to their strong learning abilities,GNNs gained popularity in various domains such as natural language processing,social network.analytics and *** detection is a challenging task in computer vision but the proposed algorithm using GNNs efficiently performs the identification of *** Graph-based deep learning networks are designed to predict unknown objects and *** our case,they detect unusual objects in the form of malicious *** edges between nodes represent a relationship of nodes among each *** case of anomaly,such as the bike rider in Pedestrians data,the rider node has a negative value for the edge and it is identified as an *** encoding and decoding layers are crucial for determining how statistical measurements affect anomaly identification and for correcting the graph path to the best possible *** show that the proposed framework is a step ahead of the traditional approaches in detecting unusual activities,which shows a huge potential in automatically monitoring surveillance *** autonomous monitoring of CCTV,crime control and damage or destruction by a group of people or crowd can be identified and alarms may be triggered in unusual activities in streets or public *** suggested GNN model improves accuracy by 4%for the Pedestrian 2 dataset and 12%for the Pedestrian 1 dataset compared to a few state-of the-art techniq

关键词： Graph neural network deep learning anomaly detection auto encoders

Enhance Intrusion Detection in Computer Networks Based on Deep Extreme Learning Machine

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Computers, Materials & Continua 2021年第1期66卷 467-480页

作者： Muhammad Adnan k.an Abdur Rehman khalid masood k.an Mohammed A.Al Ghamdi Sultan H.Almotiri Department of Computer Science Lahore Garrison UniversityLahore54792Pakistan School of Computer Science NCBA&ELahore54000Pakistan Computer Science Department Umm Al-Qura UniversityMakkah City715Saudi Arabia

Networks provide a significant function in everyday life,and cybersecurity therefore developed a critical field of *** Intrusion detection system(IDS)becoming an essential information protection strategy that tracks the situation of the software and hardware operating on the *** advancements of growth,current intrusion detection systems also experience difficulties in enhancing detection precision,growing false alarm levels and identifying suspicious *** order to address above mentioned issues,several researchers concentrated on designing intrusion detection systems that rely on machine learning *** learning models will accurately identify the underlying variations among regular information and irregular information with incredible *** intelligence,particularly machine learning methods can be used to develop an intelligent intrusion detection *** in this article in order to achieve this objective,we propose an intrusion detection system focused on a Deep extreme learning machine(DELM)which first establishes the assessment of safety features that lead to their prominence and then constructs an adaptive intrusion detection system focusing on the important *** the moment,we researched the viability of our suggested DELMbased intrusion detection system by conducting dataset assessments and evaluating the performance factors to validate the system *** experimental results illustrate that the suggested framework outclasses traditional *** fact,the suggested framework is not only of interest to scientific research but also of functional importance.

关键词： Intrusion detection system DELM network security machine learning

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MEMBERSHIP PROSPECTS

Beijing Review 2018年第23期61卷 18-19页

作者： khalid, masood

Last June,Pakistan officially joined the Shanghai Cooperation Organization(SCO).As a new member of the SCO,what kind of role will Pakistan play and what are the views in the country on the future prospects of the organization?Before the 18th SCO Summit to be held on June 9-10 in Qingdao,east China’s Shandong Province,Pakistani Ambassador to China masood khalid shared his insight on these questions in an exclusive interview with Beijing *** edited excerpt of the interview follows:

关键词：会员巴基斯坦合作组织 SCO 山东省

Marker-Based and Marker-Less Motion Capturing Video Data: Person and Activity Identification Comparison Based on Machine Learning Approaches

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Computers, Materials & Continua 2021年第2期66卷 1269-1282页

作者： Syeda Binish Zahra Muhammad Adnan k.an Sagheer Abbas khalid masood k.an Mohammed A.Al-Ghamdi Sultan H.Almotiri School of Computer Science National College for Business Administration and EconomicsLahore54000Pakistan Department of Computer Science Lahore Garrison UniversityLahore54792Pakistan Computer Science Department Umm Al-Qura UniversityMakkah CitySaudi Arabia

Biomechanics is the study of physiological properties of data and the measurement of human *** normal conditions,behavioural properties in stable form are created using various inputs of subconscious/conscious human activities such as speech style,body movements in walking patterns,writing style and voice *** cannot perform any change in these inputs that make results reliable and increase the *** aim of our study is to perform a comparative analysis between the marker-based motion capturing system(MBMCS)and the marker-less motion capturing system(MLMCS)using the lower body joint angles of human gait *** both the MLMCS and MBMCS,we collected trajectories of all the participants and performed joint angle computation to identify a person and recognize an activity(walk.and running).Using five state of the art machine learning algorithms,we obtained 44.6%and 64.3%accuracy in person identification using MBMCS and MLMCS respectively with an ensemble algorithm(two angles as features).In the second set of experiments,we used six machine learning algorithms to obtain 65.9%accuracy with the k-nearest neighbor(kNN)algorithm(two angles as features)and 74.6%accuracy with an ensemble ***,by increasing features(6 angles),we obtained higher accuracy of 99.3%in MBMCS for person recognition and 98.1%accuracy in MBMCS for activity recognition using the kNN *** is computationally expensive and if we redesign the model of OpenPose with more body joint points and employ more features,MLMCS(low-cost system)can be an effective approach for video data analysis in a person identification and activity recognition process.

关键词： Marker-based motion capturing system marker-less motion capturing system support vector machine k-nearest neighbor

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Memories of China

China News Release 2023年第10期 59-63页

作者： masood khalid 不详

It is difficult to encapsulate in a few pages the experience of six and a half years of stay in a country,especially with which one has a deep,historical and multidimensional *** aspect of this relationship would perh... 详细信息

关键词： relationship. perhaps historical

Effect of Zn doping on electronic structure and optical properties zincblende GaN(A DFT+U insight)

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Communications in Theoretical Physics 2021年第3期73卷 139-147页

作者： Muhammad Junaid Iqbal k.an Zarfishan kanwal masood Yousaf Hamid Ullah Javed Ahmad Abid Latif Yong-Han Shin Ata Ur Rahman khalid Laboratory of Theoretical and Experimental Physics Department of PhysicsBahauddin Zakariya UniversityMultan(60800)Pakistan Department of Civil Engineering Faculty of Engineering and TechnologyBahauddin Zakariya UniversityMultan60800Pakistan Department of Physics Division of Science and TechnologyUniversity of EducationTownshipLahore54770Pakistan Multiscale Materials Modelling Laboratory Department of PhysicsUniversity of UlsanUlsan44610Republic of Korea

The development of new materials,having exceptional properties in comparison to existing materials is highly required for bringing advancement in electronic and optoelectronic *** this fact,we investigated structural,electronic,and optical properties of zincblende GaN doped with selected Zn concentrations(6.25%,12.50%,and 18.70%),using the first-principle calculations based on density functional theory with GGA+*** conducted the entire study using the WIEN2k *** this study,we calculated various significant parametric quantities such as cohesive energies,formation energies,bulk moduli,and lattice constants along with the study of optical and electronic properties by substituting Ga atoms with Zn atoms in 1×2×2 *** structural stability is confirmed by studying the phonon dispersion curves which suggest that Zn:GaN material is stable against the 6.25%and 18.70%Zn concentrations while for 12.50%,it shows *** Hubbard values U=0,2,4,6 eV were added to GGA and the electronic properties were improved with the U=6 *** absorption was blue shifted while the refractive index and dielectric constant were increased with increasing the Zn *** properties are enhanced due to the prime contribution of cations(Zn)3ri *** optical and electronic properties are further discussed in detail in the entire study.

关键词： density functional theory(DFT) optoelectronics Ⅲ-Ⅴsemiconductors optical properties electronic properties structural properties