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Fault Tolerant Optical Mark Recognition

Computers, Materials & Continua 2023年第2期74卷 3829-3847页

作者： Qamar Hafeez Waqar Aslam M.Ikramullah Lali Shafiq Ahmad mejdal alqahtani Muhammad Shafiq Department of Computer Science&IT The Islamia University of Bahawalpur63100Pakistan Department of Information Sciences The University of EducationLahore54770Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

OpticalMark Recognition(OMR)systems have been studied since *** is widely accepted as a data entry *** technology is used for surveys and multiple-choice *** to its ease of use,OMR technology has grown in popularity over the past two decades and is widely used in universities and colleges to automatically grade and grade student responses to *** accuracy of OMR systems is very important due to the environment inwhich they are *** relies on pixel projection or Hough transform to determine the exact answer in the *** techniques rely on majority voting to approximate a predetermined *** performance of these systems depends on precise input from dedicated *** and scanning OMR tables introduces artifacts that make table processing *** observation is a fundamental limitation of traditional pixel projection and Hough transform *** on the type of artifact introduced,accuracy is affected *** classified the types of errors and their frequency according to the artifacts in the OMR *** a major contribution,we propose an improved algorithm that fixes errors due to *** proposal is based on the Hough transform for improving the accuracy of bias correction mechanisms in OMR *** a minor contribution,our proposal also improves the accuracy of detecting markers in OMR *** results show an improvement in accuracy over existing algorithms in each of the identified *** improvement increases confidence in OMR document processing and increases efficiency when using automated OMR document processing.

关键词： Optical mark recognition fault recognition marking system

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Intelligent Systems and Photovoltaic Cells Empowered Topologically by Sudoku Networks

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Computers, Materials & Continua 2023年第2期74卷 4221-4238页

作者： Khalid Hamid Muhammad Waseem Iqbal MUsman Ashraf Akber Abid Gardezi Shafiq Ahmad mejdal alqahtani Muhammad Shafiq Department of Computer Science Superior UniversityLahore54000Pakistan Department of Software Engineering Superior UniversityLahore54000Pakistan Department of Computer Science GC Women UniversitySialkot51310Pakistan Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

A graph invariant is a number that can be easily and uniquely calculated through a ***,part of mathematical graph invariants has been portrayed and utilized for relationship ***,no reliable appraisal has been embraced to pick,how much these invariants are associated with a network graph in interconnection networks of various fields of computer science,physics,and *** this paper,the study talks about sudoku networks will be networks of fractal nature having some applications in computer science like sudoku puzzle game,intelligent systems,Local area network(LAN)development and parallel processors interconnections,music composition creation,physics like power generation interconnections,Photovoltaic(PV)cells and chemistry,synthesis of chemical *** networks are generally utilized in disorder,fractals,recursive groupings,and complex *** outcomes are the normal speculations of currently accessible outcomes for specific classes of such kinds of networks of two unmistakable sorts with two invariants K-banhatti sombor(KBSO)invariants,Irregularity sombor(ISO)index,Contraharmonic-quadratic invariants(CQIs)and dharwad invariants with their reduced *** study solved the Sudoku network used in mentioned systems to improve the performance and find irregularities present in *** calculated outcomes can be utilized for the modeling,scalability,introduction of new architectures of sudoku puzzle games,intelligent systems,PV cells,interconnection networks,chemical compounds,and extremely huge scope in very large-scale integrated circuits(VLSI)of processors.

关键词： Sudoku dharwad KBSO indices CQIs network graph intelligent system photovoltaic cells

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Detecting Android Botnet Applications Using Convolution Neural Network

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Computers, Materials & Continua 2023年第11期77卷 2123-2135页

作者： Mamona Arshad Ahmad Karim Salman Naseer Shafiq Ahmad mejdal alqahtani Akber Abid Gardezi Muhammad Shafiq Jin-Ghoo Choi Department of Information Technology Bahauddin Zakariya UniversityMultan60000Pakistan Department of Information Technology University of the Punjab Gujranwala CampusGujranwala52250Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

The exponential growth in the development of smartphones and handheld devices is permeated due to everyday activities i.e.,games applications,entertainment,online banking,social network sites,etc.,and also allow the end users to perform a variety of *** of activities,mobile devices attract cybercriminals to initiate an attack over a diverse range of malicious activities such as theft of unauthorized information,phishing,spamming,Distributed Denial of Services(DDoS),and malware *** applications are a type of harmful attack that can be used to launch malicious activities and has become a significant threat in the research area.A botnet is a collection of infected devices that are managed by a botmaster and communicate with each other via a command server in order to carry out malicious *** the rise in malicious attacks,detecting botnet applications has become more ***,it is essential to investigate mobile botnet attacks to uncover the security issues in severe financial and ethical damages caused by a massive coordinated command *** state of the art,various solutions were provided for the detection of botnet applications,but in general,the researchers suffer various techniques of machine learning-based methods with static features which are usually ineffective when obfuscation techniques are used for the detection of botnet *** this paper,we propose an approach by exploring the concept of a deep learning-based method and present a well-defined Convolutional Neural Network(CNN)*** the visualization approach,we obtain the colored images through byte code files of applications and perform an *** analysis of the results of an experiment,we differentiate the performance of the model from other existing research ***,our method outperforms with 94.34%accuracy,92.9%of precision,and 92%of recall.

关键词： CNN botnet applications machine learning image processing

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Impediments of Cognitive System Engineering in Machine-Human Modeling

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Computers, Materials & Continua 2023年第3期74卷 6689-6701页

作者： Fayaz Ahmad Fayaz Arun Malik Isha Batra Akber Abid Gardezi Syed Immamul Ansarullah Shafiq Ahmad mejdal alqahtani Muhammad Shafiq National Institute of Electronics and Information Technology(NIELIT) J&K191132India Department of Computer Science&Engineering Lovely Professional University(LPU)Punjab144402India Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Department of Computer Science Govt.Degree College Sumbal Kashmir193501India Industrial Engineering Department College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

A comprehensive understanding of human intelligence is still an ongoing process,i.e.,human and information security are not yet perfectly *** understanding cognitive processes,designers can design humanized cognitive information systems(CIS).The need for this research is justified because today’s business decision makers are faced with questions they cannot answer in a given amount of time without the use of cognitive information *** researchers aim to better strengthen cognitive information systems with more pronounced cognitive thresholds by demonstrating the resilience of cognitive resonant frequencies to reveal possible responses to improve the efficiency of human-computer interaction(HCI).Apractice-oriented research approach included research analysis and a review of existing articles to pursue a comparative research model;thereafter,amodel development paradigm was used to observe and monitor the progression of CIS during *** scope of our research provides a broader perspective on how different disciplines affect HCI and how human cognitive models can be enhanced to enrich *** have identified a significant gap in the current literature on mental processing resulting from a wide range of theory and practice.

关键词： Cognitive-IoT human-computer interaction decision making

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Regulatory Genes Through Robust-SNR for Binary Classification Within Functional Genomics Experiments

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Computers, Materials & Continua 2023年第2期74卷 3663-3677页

作者： Muhammad Hamraz Dost Muhammad Khan Naz Gul Amjad Ali Zardad Khan Shafiq Ahmad mejdal alqahtani Akber Abid Gardezi Muhammad Shafiq Department of Statistics Abdul Wali Khan UniversityMardan23200Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityP.O.Box 800Riyadh11421Saudi Arabia Department of Computer Science COMSATS University IslamabadIslamabad45550Pakistan Department of Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

The current study proposes a novel technique for feature selection by inculcating robustness in the conventional Signal to noise Ratio(SNR).The proposed method utilizes the robust measures of location i.e.,the“Median”as well as the measures of variation i.e.,“Median absolute deviation(MAD)and Interquartile range(IQR)”in the *** this way,two independent robust signal-to-noise ratios have been *** proposed method selects the most informative genes/features by combining the minimum subset of genes or features obtained via the greedy search approach with top-ranked genes selected through the robust signal-to-noise ratio(RSNR).The results obtained via the proposed method are compared with wellknown gene/feature selection methods on the basis of performance metric i.e.,classification error rate.A total of 5 gene expression datasets have been used in this *** subsets of informative genes are selected by the proposed and all the other methods included in the study,and their efficacy in terms of classification is investigated by using the classifier models such as support vector machine(SVM),Random forest(RF)and k-nearest neighbors(k-NN).The results of the analysis reveal that the proposed method(RSNR)produces minimum error rates than all the other competing feature selection methods in majority of the *** further assessment of the method,a detailed simulation study is also conducted.

关键词： Median absolute deviation(MAD) classification feature selection high dimensional gene expression datasets signal to noise ratio

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