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Network Quality Assessment in Heterogeneous Wireless Settings: An Optimization Approach

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Computers, Materials & Continua 2022年第4期71卷 439-455页

作者： Sultan H.almotiri mohammed a.al ghamdi Computer Science Department College of Computer and Information ScienceUmm AlQura UniversityMakkahKingdom of Saudi Arabia

The identification of an effective network which can efficiently meet the service requirements of the target,while maintaining ultimate performance at an increased level is significant and challenging in a fully interconnected wireless *** wrong selection can contribute to unwanted situations like frustrated users,slow service,traffic congestion issues,missed and/or interrupted calls,and wastefulness of precious network *** schemes estimate the handoff need and cause the network screening process by a single *** strategies are not effective enough because traffic characteristics,user expectations,network terminology and other essential device metrics are not taken into *** article describes an intelligent computing technique based on Multiple-Criteria Decision-Making(MCDM)approach developed based on integrated Fuzzy AHP-TOPSIS which ensures flexible usability and maximizes the experience of end-users in miscellaneous wireless *** different components the handover need is assessed and the desired network is ***,fuzzy sets provide effective solutions to address decision making problems where experts counter uncertainty to make a *** proposed research endeavor will support designers and developers to identify,select and prioritize best attributes for ensuring flexible usability in miscellaneous wireless *** results of this research endeavor depict that this proposed computational procedure would be the most conversant mechanism for determining the usability and experience of end-users.

关键词： Wireless sensor networks fuzzy logic AHP-TOPSIS miscellaneous network intelligent computing techniques

A Systematic Literature Review of Deep Learning algorithms for Segmentation of the COVID-19 Infection

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Computers, Materials & Continua 2023年第6期75卷 5717-5742页

作者： Shroog alshomrani Muhammad Arif mohammed a.al ghamdi Department of Computer Science College of Computer and Information SciencesUmm AlQura UniversityMakkah24231Saudi Arabia

Coronavirus has infected more than 753 million people,ranging in severity from one person to another,where more than six million infected people died ***-aided diagnostic(CAD)with artificial intelligence(AI)showed outstanding performance in effectively diagnosing this virus in *** tomography is a complementary diagnostic tool to clarify the damage of COVID-19 in the lungs even before symptoms appear in *** paper conducts a systematic literature review of deep learning methods for classifying the segmentation of COVID-19 infection in the *** used the methodology of systematic reviews and meta-a.alyses(PRISMA)flow *** research aims to systematically a.alyze the supervised deep learning methods,open resource datasets,data augmentation methods,and loss functions used for various segment shapes of COVID-19 infection from computerized tomography(CT)chest *** have selected 56 primary studies relevant to the topic of the *** have compared different aspects of the algorithms used to segment infected areas in the CT *** to deep learning in the segmentation of infected areas still need to be developed to predict smaller regions of infection at the beginning of their appearance.

关键词： COVID-19 segmentation chest CT images deep learning systematic review 2D and 3D supervised deep learning

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 Khan Abdur Rehman Khalid Masood Khan 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

An Efficient Mechanism for Product Data Extraction from E-Commerce Websites

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Computers, Materials & Continua 2020年第12期65卷 2639-2663页

作者： Malik Javed Akhtar Zahur Ahmad Rashid Amin Sultan H.almotiri mohammed a.al ghamdi Hamza.aldabbas University of Engineering and Technology TaxilaPakistan Computer Science Department Umm Al-Qura UniversityMakkah CitySaudi Arabia al-Balqa Applied University Al-SaltJordan

A large amount of data is present on the web which can be used for useful purposes like a product recommendation,price comparison and demand forecasting for a particular *** are designed for human understanding and not for ***,to make data machine-readable,it requires techniques to grab data from web *** have addressed the problem using two approaches,i.e.,knowledge engineering and machine *** of the art knowledge engineering approaches use the structure of documents,visual cues,clustering of attributes of data records and text processing techniques to identify data records on a web *** learning approaches use annotated pages to learn *** rules are used to extract data from unseen web *** structure of web documents is continuously ***,new techniques are needed to handle the emerging requirements of web data *** this paper,we have presented a novel,simple and efficient technique to extract data from web pages using visual styles and structure of *** proposed technique detects Rich Data Region(RDR)using query and correlative words of the *** is then divided into data records using style *** elements are removed using a Common Tag Sequence(CTS)and formatting *** system is implemented using JAVA and runs on the dataset of real-world working *** effectiveness of results is evaluated using precision,recall,and F-measure and compared with five existing systems.A comparison of the proposed technique to existing systems has shown encouraging results.

关键词： Document object model rich data region common tag sequence web data extraction deep web mining

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 Khan Sagheer Abbas Khalid Masood Khan 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 a.alysis 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 a.alysis 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

a.alysis of the Smart Player’s Impact on the Success of a Team Empowered with Machine Lea.alysis of the Smart Player’s Impact on the Success of a Team Empowered with Machine Learningarning

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Computers, Materials & Continua 2021年第1期66卷 691-706页

作者： Muhammad Adnan Khan Mubashar Habib Shazia Saqib Tahir alyas Khalid Masood Khan mohammed a.al ghamdi Sultan H.almotiri Lahore Garrison University Lahore54792Pakistan Computer Science Department Umm Al-Qura UniversityMakkah City715Saudi Arabia

The innovation and development in data science have an impact in all trades of *** commercialization of sport has encouraged players,coaches,and other concerns to use technology to be in better position than r their *** the past,the focus was on improved training techniques for better physical *** days,sports a.alytics identify the patterns in the performance and highlight strengths and weaknesses of potential *** a.alytics not only predict the performance of players in the near future but it also performs predictive modeling for a particular behavior of a player in the *** impact of a smart player on the success of a team is always a big question mark before the start of a *** fans always want to know performance a.alysis of these superstar players and they always are interested to get to know more about their favorite player and they always have high hopes from their favorite *** learning(ML)based techniques help in predicting the performance of an individual player as well as for the whole *** statistics are very vital and useful for management,fans,and expert *** our proposed framework,the adaptive back propagation neural network(ABPNN)model is used for the prediction of a player’s *** data is collected from football websites,and the results are stored in the cloud for fast fetching of *** can be retrieved anywhere in the world through cloud *** results are computed with 94%accuracy and the performance of the smart player is formulated for the success of a team.

关键词： Machine learning adaptive feed forwarded neural network adaptive back propagation neural network cloud computing fetching

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 Khan Iftikhar Naseer Tehreem Masood Khalid Masood Khan 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

Intelligent Software-Defined Network for Cognitive Routing Optimization Using Deep Extreme Learning Machine Approach

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Computers, Materials & Continua 2021年第4期67卷 1269-1285页

作者： Fahd alhaidari Sultan H.almotiri mohammed a.al ghamdi Muhammad Adnan Khan Abdur Rehman Sagheer Abbas Khalid Masood Khan Atta-ur-Rahman Department of Computer Information System College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia Department of Computer Science Umm Al-Qura UniversityMakkah City715Saudi Arabia Department of Computer Science Lahore Garrison UniversityLahore54792Pakistan School of Computer Science NCBA&ELahore54000Pakistan Department of Computer Science College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia

In recent years,the infrastructure,instruments,and resources of network systems are becoming more complex and heterogeneous,with the rapid development of current internet and mobile communication *** order to efficaciously prepare,control,hold and optimize networking systems,greater intelligence needs to be ***,due to the inherently dispensed characteristic of conventional networks,Machine Learning(ML)techniques are hard to implement and deployed to govern and operate ***-Defined Networking(SDN)brings us new possibilities to offer intelligence in the ***’s characteristics(e.g.,logically centralized control,global network view,software-based site visitor a.alysis,and dynamic updating of forwarding rules)make it simpler to apply machine learning *** perspectives of fiber-optic communications including fiber nonlinearity coverage,optical performance checking,cognitive shortcoming detection/anticipation,and arranging and improvement of softwaredefined networks are examined in Machine Learning(ML)*** research paper has presented an imaginative framework concept called Intelligent Software Defined Network(ISDN)for Cognitive Routing Optimization(CRO)using Deep Extreme Learning Machine(DELM)approach(ISDN-CRO-DELM)in light of the new challenges in the development and operation of communication systems,and capturing motivation from how living creatures deal with difficulty and *** proposed methodology develops around the planned applications of progressive DELM methods and,specifically,probabilistic generative models for framework wide learning,demonstrating,improvement,and information ***,ISDN-CRO-DELM,suggest to integrate this learning framework with the ISDN for CRO and reconfiguration approaches at the system *** 2019a is used for DELM simulation and superior results show the effectiveness of the proposed framework.

关键词： SDN DELM machine learning cognition

Forecast the Influenza Pandemic Using Machine Learning

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Computers, Materials & Continua 2021年第1期66卷 331-340页

作者： Muhammad Adnan Khan Wajhe Ul Husnain Abidi mohammed a.al ghamdi Sultan H.almotiri Shazia Saqib Tahir alyas Khalid Masood Khan Nasir Mahmood Department of Computer Science Lahore Garrison UniversityLahore54792Pakistan Systems Limited Lahore54792Pakistan Computer Science Department Umm Al-Qura UniversityMakkah City715Saudi Arabia Department of Computer Science University of Engineering and TechnologyLahore54000Pakistan

Forecasting future outbreaks can help in minimizing their *** is a disease primarily found in animals but transferred to humans through *** 1918,influenza became a pandemic and spread rapidly all over the world becoming the cause behind killing one-third of the human population and killing one-fourth of the pig ***,that influenza became a pandemic several times on a local and global *** 2009,influenza‘A’subtype H1N1 again took many human *** disease spread like in a pandemic *** paper proposes a forecasting modeling system for the influenza pandemic using a feed-forward propagation neural network(MSDII-FFNN).This model helps us predict the outbreak,and determines which type of influenza becomes a pandemic,as well as which geographical area is *** collection for the model is done by using IoT *** model is divided into 2 phases:The training phase and the validation phase,both being connected through the *** the training phase,the model is trained using FFNN and is updated on the *** the validation phase,whenever the input is submitted through the IoT devices,the system model is updated through the cloud and predicts the pandemic *** our dataset,the data is divided into an 85%training ratio and a 15%validation *** applying the proposed model to our dataset,the predicted output precision is 90%.

关键词： Influenza pandemic machine learning prediction influenza influenza pandemic prediction forecast pandemic influenza