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Unweighted Voting Method to Detect Sinkhole Attack in RPL-Based Internet of Things Networks

Computers, Materials & Continua 2023年第10期77卷 491-515页

作者： Shadi Al-Sarawi Mohammed Anbar Basim ahmad Alabsi mohammad Adnan Aladaileh Shaza Dawood Ahmed Rihan National Advanced IPv6 Centre(NAv6) University Sains MalaysiaGelugorPenang11800Malaysia Applied College Najran UniversityKing Abdulaziz StreetP.O.Box 1988NajranSaudi Arabia Cybersecurity Department School of Information TechnologyAmerican University of Madaba(AUM)Amman11821Jordan

The Internet of Things(IoT)consists of interconnected smart devices communicating and collecting *** Routing Protocol for Low-Power and Lossy Networks(RPL)is the standard protocol for Internet Protocol Version 6(IPv6)in the ***,RPL is vulnerable to various attacks,including the sinkhole attack,which disrupts the network by manipulating routing *** paper proposes the Unweighted Voting Method(UVM)for sinkhole node identification,utilizing three key behavioral indicators:DODAG Information Object(DIO)Transaction Frequency,Rank Harmony,and Power *** indicators have been carefully selected based on their contribution to sinkhole attack detection and other relevant features used in previous *** UVM method employs an unweighted voting mechanism,where each voter or rule holds equal weight in detecting the presence of a sinkhole attack based on the proposed *** effectiveness of the UVM method is evaluated using the COOJA simulator and compared with existing ***,the proposed approach fulfills power consumption requirements for constrained nodes without increasing consumption due to the deployment *** terms of detection accuracy,simulation results demonstrate a high detection rate ranging from 90%to 100%,with a low false-positive rate of 0%to 0.2%.Consequently,the proposed approach surpasses Ensemble Learning Intrusion Detection Systems by leveraging three indicators and three supporting rules.

关键词： Internet of Things IPv6 over low power wireless personal area networks Routing Protocol for Low-Power and Lossy Networks Internet Protocol Version 6 distributed denial of service wireless sensor networks

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Improved Reptile Search Algorithm by Salp Swarm Algorithm for Medical Image Segmentation

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Journal of Bionic Engineering 2023年第4期20卷 1766-1790页

作者： Laith Abualigah Mahmoud Habash Essam Said Hanandeh ahmad MohdAziz Hussein mohammad Al Shinwan Raed Abu Zitar Heming Jia Computer Science Department Prince Hussein Bin Abdullah Faculty for Information TechnologyAl Al-Bayt UniversityMafraq25113Jordan Hourani Center for Applied Scientific Research Al-Ahliyya Amman UniversityAmman19328Jordan Faculty of Information Technology Middle East UniversityAmman11831Jordan Applied Science Research Center Applied Science Private UniversityAmman11931Jordan School of Computer Sciences Universiti Sains Malaysia11800Pulau PinangMalaysia Amman Arab University AmmanJordan Department of Computer Information System Zarqa UniversityP.O.Box 13132ZarqaJordan Deanship of E-Learning and Distance Education Umm Al-Qura UniversityMakkah21955Saudi Arabia Faculty of Information Technology Applied Science Private UniversityAmman11931Jordan Sorbonne Center of Artificial Intelligence Sorbonne University-Abu DhabiAbu DhabiUnited Arab Emirates School of Information Engineering Sanming UniversitySanming365004China

This study proposes a novel nature-inspired meta-heuristic optimizer based on the Reptile Search Algorithm combed with Salp Swarm Algorithm for image segmentation using gray-scale multi-level thresholding,called *** proposed method introduces a better search space to find the optimal solution at each ***,we proposed RSA-SSA to avoid the searching problem in the same area and determine the optimal multi-level *** obtained solutions by the proposed method are represented using the image *** proposed RSA-SSA employed Otsu’s variance class function to get the best threshold values at each *** performance measure for the proposed method is valid by detecting fitness function,structural similarity index,peak signal-to-noise ratio,and Friedman ranking *** benchmark images of COVID-19 validate the performance of the proposed *** results showed that the proposed RSA-SSA outperformed other metaheuristics optimization algorithms published in the literature.

关键词： Bioinspired Reptile Search Algorithm Salp Swarm Algorithm Multi-level thresholding Image segmentation Meta-heuristic algorithm

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Exploiting Human Pose and Scene Information for Interaction Detection

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Computers, Materials & Continua 2023年第3期74卷 5853-5870页

作者： Manahil Waheed Samia Allaoua Chelloug mohammad Shorfuzzaman Abdulmajeed Alsufyani ahmad Jalal Khaled Alnowaiser Jeongmin Park Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Engineering College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Computer Engineering Korea Polytechnic UniversitySiheung-siGyeonggi-do237Korea

Identifying human actions and interactions finds its use in manyareas, such as security, surveillance, assisted living, patient monitoring, rehabilitation,sports, and e-learning. This wide range of applications has attractedmany researchers to this field. Inspired by the existing recognition systems,this paper proposes a new and efficient human-object interaction recognition(HOIR) model which is based on modeling human pose and scene featureinformation. There are different aspects involved in an interaction, includingthe humans, the objects, the various body parts of the human, and the backgroundscene. Themain objectives of this research include critically examiningthe importance of all these elements in determining the interaction, estimatinghuman pose through image foresting transform (IFT), and detecting the performedinteractions based on an optimizedmulti-feature vector. The proposedmethodology has six main phases. The first phase involves preprocessing theimages. During preprocessing stages, the videos are converted into imageframes. Then their contrast is adjusted, and noise is removed. In the secondphase, the human-object pair is detected and extracted from each image *** third phase involves the identification of key body parts of the detectedhumans using IFT. The fourth phase relates to three different kinds of featureextraction techniques. Then these features are combined and optimized duringthe fifth phase. The optimized vector is used to classify the interactions in thelast phase. TheMSRDaily Activity 3D dataset has been used to test this modeland to prove its efficiency. The proposed system obtains an average accuracyof 91.7% on this dataset.

关键词： Artificial intelligence daily activities human interactions human pose information image foresting transform scene feature information

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Joint Channel and Multi-User Detection Empowered with Machine Learning

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Computers, Materials & Continua 2022年第1期70卷 109-121页

作者： mohammad Sh.Daoud Areej Fatima Waseem ahmad Khan Muhammad Adnan Khan Sagheer Abbas Baha Ihnaini Munir ahmad Muhammad Sheraz Javeid Shabib Aftab College of Engineering Al Ain UniversityAbu Dhabi112612UAE Department of Computer Science Lahore Garrison UniversityLahore54792Pakistan School of Computer Science National College of Business Administration and EconomicsLahore54000Pakistan Riphah School of Computing and Innovation Faculty of ComputingRiphah International UniversityLahore54000Pakistan Pattern Recognition and Machine Learning Lab Department of Software EngineeringGachon UniversitySeongnam13557South Korea Department of Computer Science College of Science and TechnologyWenzhou Kean University325060USA Department of Computer Science Hameeda Rasheed Institute of Science and TechnologyMultan66000Pakistan

The numbers of multimedia applications and their users increase with each passing *** multi-carrier systems have been developed along with varying techniques of space-time coding to address the demand of the future generation of network *** this article,a fuzzy logic empowered adaptive backpropagation neural network(FLeABPNN)algorithm is proposed for joint channel and multi-user detection(CMD).FLeABPNN has two *** first stage estimates the channel parameters,and the second performsmulti-user *** proposed approach capitalizes on a neuro-fuzzy hybrid systemthat combines the competencies of both fuzzy logic and neural *** study analyzes the results of using FLeABPNN based on a multiple-input andmultiple-output(MIMO)receiver with conventional partial oppositemutant particle swarmoptimization(POMPSO),total-OMPSO(TOMPSO),fuzzy logic empowered POMPSO(FL-POMPSO),and FL-TOMPSO-based MIMO *** FLeABPNN-based receiver renders better results than other techniques in terms of minimum mean square error,minimum mean channel error,and bit error rate.

关键词： Channel and multi-user detection minimum mean square error multiple-input and multiple-output minimum mean channel error bit error rate

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Data Mining with Comprehensive Oppositional Based Learning for Rainfall Prediction

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Computers, Materials & Continua 2023年第2期74卷 2725-2738页

作者： mohammad Alamgeer Amal Al-Rasheed ahmad Alhindi Manar Ahmed Hamza Abdelwahed Motwakel Mohamed I.Eldesouki Department of Information Systems College of Science&Art at MahayilKing Khalid UniversityAbha62529Saudi Arabia Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Science College of Computing and Information SystemMecca24382Saudi Arabia Department of Computer and Self Development Preparatory Year DeanshipPrince Sattam bin Abdulaziz UniversityAlKharj16278Saudi Arabia Department of Information System College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAlKharj16278Saudi Arabia

Data mining process involves a number of steps fromdata collection to visualization to identify useful data from massive data *** same time,the recent advances of machine learning(ML)and deep learning(DL)models can be utilized for effectual rainfall *** this motivation,this article develops a novel comprehensive oppositionalmoth flame optimization with deep learning for rainfall prediction(COMFO-DLRP)*** proposed CMFO-DLRP model mainly intends to predict the rainfall and thereby determine the environmental ***,data pre-processing and correlation matrix(CM)based feature selection processes are carried *** addition,deep belief network(DBN)model is applied for the effective prediction of rainfall ***,COMFO algorithm was derived by integrating the concepts of comprehensive oppositional based learning(COBL)with traditional MFO ***,the COMFO algorithm is employed for the optimal hyperparameter selection of the DBN *** demonstrating the improved outcomes of the COMFO-DLRP approach,a sequence of simulations were carried out and the outcomes are assessed under distinct *** simulation outcome highlighted the enhanced outcomes of the COMFO-DLRP method on the other techniques.

关键词： Data mining rainfall prediction deep learning correlation matrix hyperparameter tuning metaheuristics

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Real Objects Understanding Using 3D Haptic Virtual Reality for E-Learning Education

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Computers, Materials & Continua 2023年第1期74卷 1607-1624页

作者： Samia Allaoua Chelloug Hamid Ashfaq Suliman A.Alsuhibany mohammad Shorfuzzaman Abdulmajeed Alsufyani ahmad Jalal Jeongmin Park Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Engineering Korea Polytechnic UniversitySiheung-siGyeonggi-do237Korea

In the past two decades,there has been a lot of work on computer vision technology that incorporates many tasks which implement basic filtering to image *** research areas of this field include object detection and object ***,wireless communication technologies are presently adopted and they have impacted the way of education that has been *** are different phases of changes in the traditional *** of three-dimensional(3D)from two-dimensional(2D)image is one of the demanding *** human can easily perceive but making 3D using software will take time ***,the blackboard has been replaced by projectors and other digital screens so such that people can understand the concept better through ***,the computer labs in schools are now more common than ***,online classes have become a ***,transferring to online education or e-learning is not without ***,we propose a method for improving the efficiency of *** proposed system consists of twoand-a-half dimensional(2.5D)features extraction using machine learning and image ***,these features are utilized to generate 3D mesh using ellipsoidal deformation *** that,3D bounding box estimation is *** results show that there is a need to move to 3D virtual reality(VR)with haptic sensors in the field of e-learning for a better understanding of real-world ***,people will have more information as compared to the traditional or simple online education *** compare our result with the ShapeNet dataset to check the accuracy of our proposed *** proposed system achieved an accuracy of 90.77%on plane class,85.72%on chair class,and car class have 72.14%.Mean accuracy of our method is 70.89%.

关键词： Artificial intelligence e-learning online education system computer vision virtual reality 3D haptic

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Traffic Priority-Aware Medical Data Dissemination Scheme for IoT Based WBASN Healthcare Applications

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Computers, Materials & Continua 2022年第6期71卷 4443-4456页

作者： Muhammad Anwar Farhan Masud Rizwan Aslam Butt Sevia Mahdaliza Idrus mohammad Nazir ahmad Mohd Yazid Bajuri Department of Computer Science NFC Institute of Engineering and Fertilizer ResearchFaisalabadPakistan Department of Statistics and Computer Science Faculty of Life Sciences Business ManagementUniversity of Veterinary and Animal SciencesLahorePakistan Department of Electronics Engineering NED University of Engineering and TechnologyKarachiPakistan School of Electrical Engineering Universiti Teknologi MalaysiaJohor BahruMalaysia Institute of IR4.0 Universiti Kebangsaan MalaysiaBangiSelangorMalaysia Department of Orthopedics and Traumatology Faculty of MedicineUniversiti Kebangsaan MalaysiaKuala LumpurMalaysia

Wireless Body Area Sensor Network(WBASN)is an automated system for remote health monitoring of *** under umbrella of Internet of Things(IoT)is comprised of small Biomedical Sensor Nodes(BSNs)that can communicate with each other without human *** BSNs can be placed on human body or inside the skin of the patients to regularly monitor their vital *** BSNs generate critical data as it is related to patient’s *** data traffic can be classified as Sensitive Data(SD)and Non-sensitive Data(ND)packets based on the value of vital *** data packets have different priority to *** ND packets may tolerate some delay or packet loss whereas,the SD packets required to be delivered on time with minimized packet loss otherwise it can be life threating to the *** this research,we propose a Traffic Priority-aware Medical Data Dissemination(TPMD2)scheme forWBASN to deliver the data packets according to their priority based on the sensitivity of the *** assessment of the proposed scheme is carried out in various *** simulation results of the TPMD2 scheme indicate a significant improvement in packets delivery,transmission delay and energy efficiency in comparison with the existing schemes.

关键词： WBANS wearable technology priority routing eHealth applications remote health monitoring

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Hybrid Computational Modeling for Web Application Security Assessment

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Computers, Materials & Continua 2022年第1期70卷 469-489页

作者： Adil Hussain Seh Jehad F.Al-Amri ahmad F.Subahi Md Tarique Jamal Ansari Rajeev Kumar mohammad Ubaidullah Bokhari Raees ahmad Khan Department of Information Technology Babasaheb Bhimrao Ambedkar UniversityLucknow226025Uttar PradeshIndia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science University College of Al JamoumUmm Al Qura UniversityMakkah21421Saudi Arabia Department of Computer Applications Shri Ramswaroop Memorial UniversityBarabanki225003Uttar PradeshIndia Department of Computer Science Aligarh Muslim UniversityAligarh202002Uttar PradeshIndia

Transformation from conventional business management systems to smart digital systems is a recurrent trend in the current *** has led to digital revolution,and in this context,the hardwired technologies in the software industry play a significant role However,from the beginning,software security remains a serious issue for all levels of *** vulnerabilities lead to intrusions that cause data breaches and result in disclosure of sensitive data,compromising the organizations’reputation that translates into,financial losses as *** of the data breaches are financially motivated,especially in the healthcare *** cyber invaders continuously penetrate the E-Health data because of the high cost of the data on the dark ***,security assessment of healthcare web-based applications demands immediate intervention mechanisms to weed out the threats of *** aim of this work is to provide efficient and effective healthcare web application security *** study has worked with the hybrid computational model of Multi-Criteria Decision Making(MCDM)based on Analytical Hierarchy Process(AHP)and Technique for Order of Preference by Similarity to Ideal-Solutions(TOPSIS)under the Hesitant Fuzzy(HF)*** fuzzy sets provide effective solutions to address decision making problems where experts counter hesitation to make a *** proposed research endeavor will support designers and developers in identifying,selecting and prioritizing the best security attributes for web applications’*** empirical analysis concludes that Robustness got highest priority amongst the assessed security attributes set followed by Encryption,Authentication,Limit Access,Revoke Access,Data Validation,and Maintain Audit *** results of this research endeavor depict that this proposed computational procedure would be the most conversant mechanism for determining the web application *** study also establishes g

关键词： Healthcare web application security assessment hesitant fuzzy sets AHP-TOPSIS

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A Framework for Securing Saudi Arabian Hospital Industry: Vision-2030 Perspective

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Intelligent Automation & Soft Computing 2023年第6期36卷 2773-2786页

作者： Hosam Alhakami Abdullah Baz mohammad Al-shareef Rajeev Kumar Alka Agrawal Raees ahmad Khan Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955SaudiArabia Department of Computer Engineering College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Security Forces Hospital Makkah21955Saudi Arabia Department of Computer Science and Engineering Babu Banarasi Das UniversityLucknow226028Uttar PradeshIndia Department of Information Technology Babasaheb Bhimrao Ambedkar UniversityLucknow226025Uttar PradeshIndia

Recent transformation of Saudi Arabian healthcare sector into a reven-ue producing one has signaled several advancements in healthcare in the *** healthcare management into Smart hospital systems is one of *** hospital management systems which are breach-proof only can be termed as effective smart hospital *** the perspective of Saudi Vision-2030,many practitioners are trying to achieve a cost-effective hospital management sys-tem by using smart *** this row,the proposed framework posits the main objectives for creating smart hospital management systems that can only be acknowledged by managing the security of healthcare data and medical ***,the proposed framework will also be helpful in gaining satisfactory rev-enue from the healthcare sector by reducing the cost and time involved in mana-ging the smart hospital *** framework is based on a hybrid approach of three key methods which include:employing the Internet of Medical Things(IoMT)and blockchain methodologies for maintaining the security and privacy of healthcare data and medical practices,and using big data analytics methodol-ogy for raising the funds and revenue by managing the bulk volume of healthcare ***,the framework will also be helpful for both the patients and the doctors,thus enabling the Kingdom of Saudi Arabia(KSA)to meet its goals of Vision-2030 by ensuring low cost,yet credible,healthcare services.

关键词： Smart healthcare healthcare industry data security

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Brain Tumor Segmentation in Multimodal MRI Using U-Net Layered Structure

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Computers, Materials & Continua 2023年第3期74卷 5267-5281页

作者： Muhammad Javaid Iqbal Muhammad Waseem Iqbal Muhammad Anwar Muhammad Murad Khan Abd Jabar Nazimi mohammad Nazir ahmad Department of Information Technology The Superior UniversityLahorePakistan Department of Software Engineering The Superior UniversityLahorePakistan Department of Information Sciences Division of Science and TechnologyUniversity of EducationLahorePakistan Department of Computer Science Government College UniversityFaisalabadPakistan Deptment of Oral and Maxillofacial Surgery Faculty of DentistryUniversiti Kebangsaan MalaysiaKuala LumpurMalaysia Institute of IR4.0 Universiti Kebangsaan MalaysiaBangiSelangorMalaysia

The brain tumour is the mass where some tissues become old or damaged,but they do not die or not leave their *** brain tumour masses occur due to malignant *** tissues must die so that new tissues are allowed to be born and take their *** segmentation is a complex and time-taking problem due to the tumour’s size,shape,and appearance *** finding such masses in the brain by analyzing Magnetic Resonance Images(MRI)is a crucial task for experts and *** could not work for large volume images simultaneously,and many errors occurred due to overwhelming image *** main objective of this research study is the segmentation of tumors in brain MRI images with the help of digital image processing and deep learning *** research study proposed an automatic model for tumor segmentation in MRI *** proposed model has a few significant steps,which first apply the pre-processing method for the whole dataset to convert Neuroimaging Informatics Technology Initiative(NIFTI)volumes into the 3D NumPy *** the second step,the proposed model adopts U-Net deep learning segmentation algorithm with an improved layered structure and sets the updated *** the third step,the proposed model uses state-of-the-art Medical Image Computing and Computer-Assisted Intervention(MICCAI)BRATS 2018 dataset withMRI modalities such as T1,T1Gd,T2,and Fluidattenuated inversion recovery(FLAIR).Tumour types in MRI images are classified according to the tumour *** of these masses carried by state-of-the-art approaches such that the first is enhancing tumour(label 4),edema(label 2),necrotic and non-enhancing tumour core(label 1),and the remaining region is label 0 such that edema(whole tumour),necrosis and *** proposed model is evaluated and gets the Dice Coefficient(DSC)value for High-grade glioma(HGG)volumes for their test set-a,test set-b,and test set-c 0.9795, 0.9855 and 0.9793, respectively.

关键词： Brain tumour segmentation magnetic resonance images modalities dice coefficient low-grade glioma U-Net

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