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Edge-Computing with Graph Computation:A Novel Mechanism to Handle Network Intrusion and Address Spoofing in SDN

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Computers, Materials & Continua 2020年第12期65卷 1869-1890页

作者： Rashid Amin mudassar hussain Mohammed Alhameed Syed Mohsan Raza Fathe Jeribi Ali Tahir University of Engineering and Technology TaxilaPakistan University of Wah Wah CanttPakistan Jazan University JazanSaudi Arabia Abasyn University Islamabad IslamabadPakistan

Software Defined Networking(SDN)being an emerging network control model is widely recognized as a control and management *** model provides efficient techniques to control and manage the enterprise *** emerging paradigm is edge computing in which data processing is performed at the edges of the network instead of a central *** data processing at the edge nodes reduces the latency and bandwidth *** SDN,the controller is a single point of *** security issues related to the traditional network can be solved by using SDN central management and *** Spoofing and Network Intrusion are the most common *** attacks severely degrade performance and *** propose an edge computing-based mechanism that automatically detects and mitigates those *** this mechanism,an edge system gets the network topology from the controller and the Address Resolution Protocol(ARP)traffic is directed to it for further *** such,the controller is saved from unnecessary processing related to addressing *** propose a graph computation based method to identify the location of an attacker or intruder by implementing a graph difference *** using the correct location information,the exact attacker or intruder is blocked,while the legitimate users get access to the network *** proposed mechanism is evaluated in a Mininet simulator and a POX *** results show that it improves system performance in terms of attack mitigation time,attack detection time,and bandwidth requirements.

关键词： Software Defined Networking(SDN) edge computing Address Resolution Protocol(ARP) ARP inspection security graph difference

Revisiting the N=1 supersymmetric trinification models from intersecting D6-branes

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Communications in Theoretical Physics 2024年第9期76卷 27-36页

作者： Adeel Mansha Tianjun Li mudassar Sabir Department of Physics Zhejiang Normal UniversityJinhua 321004China Zhejiang Institute of Photoelectronics Zhejiang Normal UniversityJinhua 321004China Centre For High Energy Physics University of the PunjabLahore 54590Pakistan CAS Key Laboratory of Theoretical Physics Institute of Theoretical PhysicsChinese Academy of SciencesBeijing 100190China School of Physical Sciences University of Chinese Academy of SciencesBeijingChina School of Physics University of Electronic Science and Technology of ChinaChengduSichuan 611731China

We revisit the construction of the N=1 supersymmetric trinification models with gauge group U(3)_(C)×U(3)_(L)×U(3)_(R) in TypeⅡA string theory on T^(6)(Z_(2)×Z_(2))orientifold with intersecting *** non-trivial K-theory conditions and tadpole cancellation conditions severely restrict the number of allowed models even for the case of rectangular *** a supervised search algorithm,we find a few four-family models where the highest wrapping number is *** these models,we present the complete particle spectra and the gauge coupling relations at the string-scale.

关键词： string phenomenology D branes trinification

Deep Convolutional Neural Networks for Accurate Classification of Gastrointestinal Tract Syndromes

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Computers, Materials & Continua 2024年第1期78卷 1207-1225页

作者： Zahid Farooq Khan Muhammad Ramzan mudassar Raza Muhammad Attique Khan Khalid Iqbal Taerang Kim Jae-Hyuk Cha Department of Computer Science COMSATS University IslamabadWah CampusWah47040Pakistan Department of Computer Science and Mathematics Lebanese American UniversityBeirut13-5053Lebanon Department of Computer Science HITEC UniversityTaxila47080Pakistan Department of Computer Science COMSATS University IslamabadAttock CampusAttock43600Pakistan Department of Computer Science Hanyang UniversitySeoul04763Korea

Accurate detection and classification of artifacts within the gastrointestinal(GI)tract frames remain a significant challenge in medical image *** science combined with artificial intelligence is advancing to automate the diagnosis and treatment of numerous *** to this is the development of robust algorithms for image classification and detection,crucial in designing sophisticated systems for diagnosis and *** study makes a small contribution to endoscopic image *** proposed approach involves multiple operations,including extracting deep features from endoscopy images using pre-trained neural networks such as Darknet-53 and ***,feature optimization utilizes the binary dragonfly algorithm(BDA),with the fusion of the obtained feature *** fused feature set is input into the ensemble subspace k nearest neighbors(ESKNN)*** Kvasir-V2 benchmark dataset,and the COMSATS University Islamabad(CUI)Wah private dataset,featuring three classes of endoscopic stomach images were *** assessments considered various feature selection techniques,including genetic algorithm(GA),particle swarm optimization(PSO),salp swarm algorithm(SSA),sine cosine algorithm(SCA),and grey wolf optimizer(GWO).The proposed model excels,achieving an overall classification accuracy of 98.25% on the Kvasir-V2 benchmark and 99.90% on the CUI Wah private *** approach holds promise for developing an automated computer-aided system for classifying GI tract syndromes through endoscopy images.

关键词： Feature fusion Darknet-53 Xception binary dragonfly algorithm ensemble

Bond-Slip Behavior of Steel Bar and Recycled Steel Fibre-Reinforced Concrete

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Journal of Renewable Materials 2024年第1期12卷 167-186页

作者： Ismail Shah Jing Li Nauman Khan Hamad R.Almujibah Muhammad mudassar Rehman Ali Raza Yun Peng School of Architecture and Civil Engineering Yunnan Agricultural UniversityKunming650000China Institute of Mountain Hazards and Environment Chinese Academy of SciencesChengdu610041China Yunnan International Joint R&D Center of Smart Agriculture and Water Security Yunnan Agricultural UniversityKunming650201China School of Water Conservancy Yunnan Agricultural UniversityKunming650201China School of Civil Engineering Guizhou UniversityGuiyang550025China Department of Civil Engineering College of EngineeringTaif UniversityP.O.Box 11099Taif City21974Saudi Arabia School of Civil Engineering Zhengzhou UniversityZhengzhou450001China

Recycled steel fiber reinforced concrete is an innovative construction material that offers exceptional mechanical properties and *** is considered a sustainable material due to its low carbon footprint and environmental friendly *** study examines the key influencing factors that affect the behavior of this material,such as the steel fiber volume ratio,recycled aggregate replacement rate,concrete strength grade,anchorage length,and stirrup *** study investigates the bond failure morphology,bond-slip,and bond strength constitutive relationship of steel fiber recycled *** results show that the addition of steel fibers at 0.5%,1.0%,and 1.5%volume ratios can improve the ultimate bond strength of pull-out specimens by 9.05%,6.94%,and 5.52%,*** replacement rate of recycled aggregate has minimal effect on the typical bond strength of pull-out ***,the ultimate bond strengths of pull-out specimens with concrete strength grades C45 and C60 have improved compared to those with C30 *** specimens with longer anchorage lengths exhibit lower ultimate bond strength,with a reduction of 33.19%and 46.37%for anchorage lengths of 5D and 7D,respectively,compared to those without *** restraint of 1φ8 and 2φ8 improves the ultimate bond strength by 5.29%and 6.90%,*** fibers have a significant effect on the behavior of concrete after it cracks,especially during the stable expansion stage,crack instability expansion stage,and failure stage.

关键词： Recycled coarse aggregates(RCA) steel fiber bonding performance bond-slip environmental challenges

Recent Developments in Authentication Schemes Used in Machine-Type Communication Devices in Machine-to-Machine Communication: Issues and Challenges

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Computers, Materials & Continua 2024年第4期79卷 93-115页

作者： Shafi Ullah Sibghat Ullah Bazai Mohammad Imran Qazi mudassar Ilyas Abid Mehmood Muhammad Asim Saleem Muhmmad Aasim Rafique Arsalan Haider Ilyas Khan Sajid Iqbal Yonis Gulzar Kauser Hameed Department of Computer Engineering Balochistan University of Information TechnologyEngineering and Management SciencesQuetta87300Pakistan Department of Information Technology Balochistan University of Information TechnologyEngineeringand Management SciencesQuetta87300Pakistan Department of Information Systems College of Computer Sciences and Information TechnologyKing Faisal UniversityHofuf in Al-Ahsa31982Saudi Arabia Department of Management Information Systems College of Business AdministrationKing Faisal UniversityHofuf in Al-Ahsa31982Saudi Arabia Department of Software Engineering College of ComputingRiphah International UniversityFaisalabad44000Pakistan Department of Electrical Engineering Balochistan University of Information Technology Engineeringand Management SciencesQuetta87300Pakistan Department of Mathematics College of Science Al-ZulfiMajmaah UniversityAl-Majmaah11952Saudi Arabia

Machine-to-machine (M2M) communication plays a fundamental role in autonomous IoT (Internet of Things)-based infrastructure, a vital part of the fourth industrial revolution. Machine-type communication devices(MTCDs) regularly share extensive data without human intervention while making all types of decisions. Thesedecisions may involve controlling sensitive ventilation systems maintaining uniform temperature, live heartbeatmonitoring, and several different alert systems. Many of these devices simultaneously share data to form anautomated system. The data shared between machine-type communication devices (MTCDs) is prone to risk dueto limited computational power, internal memory, and energy capacity. Therefore, securing the data and devicesbecomes challenging due to factors such as dynamic operational environments, remoteness, harsh conditions,and areas where human physical access is difficult. One of the crucial parts of securing MTCDs and data isauthentication, where each devicemust be verified before data transmission. SeveralM2Mauthentication schemeshave been proposed in the literature, however, the literature lacks a comprehensive overview of current M2Mauthentication techniques and the challenges associated with them. To utilize a suitable authentication schemefor specific scenarios, it is important to understand the challenges associated with it. Therefore, this article fillsthis gap by reviewing the state-of-the-art research on authentication schemes in MTCDs specifically concerningapplication categories, security provisions, and performance efficiency.

关键词： Authentication cyber security internet of things machine-type communication devices machine-to-machine communication

Deep Learning with a Novel Concoction Loss Function for Identification of Ophthalmic Disease

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Computers, Materials & Continua 2023年第9期76卷 3763-3781页

作者： Sayyid Kamran hussain Ali Haider Khan Malek Alrashidi Sajid Iqbal Qazi mudassar Ilyas Kamran Shah Department of Computer Science TIMES InstituteMultan60000Pakistan Department of Software Engineering Faculty of Computer ScienceLahore Garrison UniversityLahore54000Pakistan Department of Computer Science Applied CollegeUniversity of TabukTabukSaudi Arabia Department of Information Systems College of Computer Sciences and Information TechnologyKing Faisal UniversityAl Hofuf31982Saudi Arabia Department of Mechanical Engineering College of EngineeringKing Faisal UniversityAl HofufSaudi Arabia

As ocular computer-aided diagnostic(CAD)tools become more widely accessible,many researchers are developing deep learning(DL)methods to aid in ocular disease(OHD)*** eye diseases like cataracts(CATR),glaucoma(GLU),and age-related macular degeneration(AMD)are the focus of this study,which uses DL to examine their *** imbalance and outliers are widespread in fundus images,which can make it difficult to apply manyDL algorithms to accomplish this analytical *** creation of efficient and reliable DL algorithms is seen to be the key to further enhancing detection *** the analysis of images of the color of the retinal fundus,this study offers a DL model that is combined with a one-of-a-kind concoction loss function(CLF)for the automated identification of *** study presents a combination of focal loss(FL)and correntropy-induced loss functions(CILF)in the proposed DL model to improve the recognition performance of classifiers for biomedical *** is done because of the good generalization and robustness of these two types of losses in addressing complex datasets with class imbalance and *** classification performance of the DL model with our proposed loss function is compared to that of the baseline models using accuracy(ACU),recall(REC),specificity(SPF),Kappa,and area under the receiver operating characteristic curve(AUC)as the evaluation *** testing shows that the method is reliable and efficient.

关键词： Deep learning multi-classification focal loss CNN eye disease

Modeling transmission dynamics of Ebola virus disease

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International Journal of Biomathematics 2017年第4期10卷 297-331页

作者： mudassar Imran Adnan Khan Ali R. Ansari Syed Touqeer hussain Shah International Center for Applied Mathematics and Computational Bioengineering Department of Mathematics and Natural Sciences Gulf University for Science and Technology Hawally Kuwait Department of Mathematics Lahore University of Management Sciences Lahore Pakistan

Ebola virus disease （EVD） has emerged as a rapidly spreading potentially fatal disease. Several studies have been performed recently to investigate the dynamics of EVD. In this paper, we study the transmission dynamics of EVD by formulating an SEIR-type transmission model that includes isolated individuals as well as dead individuals that are not yet buried. Dynamical systems analysis of the model is performed, and it is consequently shown that the disease-free steady state is globally asymptotically stable when the basic reproduction number, R0 is less than unity. It is also shown that there exists a unique endemic equilibrium when R0 〉 1. Using optimal control theory, we propose control strategies, which will help to eliminate the Ebola disease. We use data fitting on models, with and without isolation, to estimate the basic reproductive numbers for the 2014 outbreak of EVD in Liberia and Sierra Leone.

关键词： Ebola virus disease endemic equilibrium basic reproduction number hos-pitalization infectiousness optimal control transmission dynamics time series datafitting.

Improved Shark Smell Optimization Algorithm for Human Action Recognition

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Computers, Materials & Continua 2023年第9期76卷 2667-2684页

作者： Inzamam Mashood Nasir mudassar Raza Jamal hussain Shah Muhammad Attique Khan Yun-Cheol Nam Yunyoung Nam Department of Computer Science COMSATS University IslamabadWah CampusWah Cantt47040Pakistan Department of Computer Science HITEC UniversityTaxilaPakistan Department of Architecture Joongbu UniversityGoyang10279South Korea Department of ICT Convergence Soonchunhyang UniversityAsan31538Korea

Human Action Recognition(HAR)in uncontrolled environments targets to recognition of different actions froma *** effective HAR model can be employed for an application like human-computer interaction,health care,person tracking,and video *** Learning(ML)approaches,specifically,Convolutional Neural Network(CNN)models had beenwidely used and achieved impressive results through feature *** accuracy and effectiveness of these models continue to be the biggest challenge in this *** this article,a novel feature optimization algorithm,called improved Shark Smell Optimization(iSSO)is proposed to reduce the redundancy of extracted *** proposed technique is inspired by the behavior ofwhite sharks,and howthey find the best prey in thewhole search *** proposed iSSOalgorithmdivides the FeatureVector(FV)into subparts,where a search is conducted to find optimal local features fromeach subpart of *** local optimal features are selected,a global search is conducted to further optimize these *** proposed iSSO algorithm is employed on nine(9)selected CNN *** CNN models are selected based on their top-1 and top-5 accuracy in ImageNet *** evaluate the model,two publicly available datasets UCF-Sports and Hollywood2 are selected.

关键词： Action recognition improved shark smell optimization convolutional neural networks machine learning

CEER:Cooperative Energy-Efficient Routing Mechanism for Underwater Wireless Sensor Networks Using Clusters

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Computer Systems Science & Engineering 2023年第6期45卷 2587-2602页

作者： Sayyed mudassar Shah Tariq hussain Babar Shah Farman Ali Khalid Zaman Kyung-Sup Kwak Institute of Computer Science&Information Technology the University of Agriculture Peshawar25000Pakistan High Performance Computing and Networking Institute National Research Council(ICAR-CNR)Naples80131Italy College of Technological Innovation Zayed UniversityDubai19282UAE Department of Software Sejong UniversitySeoul05006Korea Department of Information and Communication Engineering Inha UniversityIncheon22212Korea

Underwater acoustic sensor networks(UWASNs)aim to find varied offshore ocean monitoring and exploration *** most of these applications,the network is composed of several sensor nodes deployed at different depths in the *** nodes located at depth on the seafloor cannot invariably communicate with nodes close to the surface level;these nodes need multihop communication facilitated by a suitable routing *** this research work,a Cluster-based Cooperative Energy Efficient Routing(CEER)mechanism for UWSNs is proposed to overcome the shortcomings of the Co-UWSN and LEACH *** optimal role of clustering and cooperation provides load balancing and improves the network *** simulation results using MATLAB show better performance of CEER routing protocol in terms of various parameters as compared to Co-UWSN routing protocol,i.e.,the average end-to-end delay of CEER was 17.39,Co-UWSN was 55.819 and LEACH was *** addition,the average total energy consumption of CEER was 9.273,Co-UWSN was 12.198,and LEACH was *** packet delivery ratio of CEER was 53.955,CO-UWSN was 42.047,and LEACH was *** stability period CEER was 130.9,CO-UWSN was 129.3,and LEACH was *** obtained results maximized the lifetime and improved the overall performance of the CEER routing protocol.

关键词： Cluster head co-UWSN UWSN relay LEACH CEER