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Security Requirement Management for Cloud-Assisted and Internet of Things—Enabled Smart City

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Computers, Materials & Continua 2021年第4期67卷 625-639页

作者： muhammad usman tariq muhammad Babar Mian Ahmad Jan Akmal Saeed Khattak Mohammad Dahman Alshehri Abid Yahya Abu Dhabi School of Management Abu Dhabi6844United Arab Emirates Department of Computing and Technology Iqra UniversityIslamabad44000Pakistan Institute of Research and Development Duy Tan UniversityDa Nang550000Vietnam The Faculty of Information Technology Duy Tan UniversityDa Nang550000Vietnam Department of Computer Sciences Abdul Wali Khan UniversityMardan23200Pakistan Department of Computer Sciences Quaid-i-Azam UniversityIslamabad44000Pakistan Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Botswana International University of Science and Technology Palapye016Botswana

The world is rapidly changing with the advance of information *** expansion of the Internet of Things(IoT)is a huge step in the development of the smart *** IoT consists of connected devices that transfer *** IoT architecture permits on-demand services to a public pool of *** computing plays a vital role in developing IoT-enabled smart *** integration of cloud computing enhances the offering of distributed resources in the smart *** management of security requirements of cloud-assisted IoT systems can bring about risks to availability,security,performance,condentiality,and *** key reason for cloud-and IoT-enabled smart city application failure is improper security practices at the early stages of *** article proposes a framework to collect security requirements during the initial development phase of cloud-assisted IoT-enabled smart city *** three-layered architecture includes privacy preserved stakeholder analysis(PPSA),security requirement modeling and validation(SRMV),and secure cloud-assistance(SCA).A case study highlights the applicability and effectiveness of the proposed framework.A hybrid survey enables the identication and evaluation of signicant challenges.

关键词： Security privacy smart city Internet of Things cloud computing

Improving the Position Accuracy and Computational Efficiency of UAV Terrain Aided Navigation Using a Two-Stage Hybrid Fuzzy Particle Filtering Method

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Computers, Materials & Continua 2025年第1期82卷 1193-1210页

作者： Sofia Yousuf muhammad Bilal Kadri College of Engineering Karachi Institute of Economics&TechnologyKarachi75190Pakistan College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia

Terrain Aided Navigation(TAN)technology has become increasingly important due to its effectiveness in environments where Global Positioning System(GPS)is *** recent years,TAN systems have been extensively researched for both aerial and underwater navigation ***,many TAN systems that rely on recursive Unmanned Aerial Vehicle(UAV)position estimation methods,such as Extended Kalman Filters(EKF),often face challenges with divergence and instability,particularly in highly non-linear *** address these issues,this paper proposes and investigates a hybrid two-stage TAN positioning system for UAVs that utilizes Particle *** enhance the system’s robustness against uncertainties caused by noise and to estimate additional system states,a Fuzzy Particle Filter(FPF)is employed in the first *** approach introduces a novel terrain composite feature that enables a fuzzy expert system to analyze terrain non-linearities and dynamically adjust the number of particles in *** design allows the UAV to be efficiently localized in GPS-denied environments while also reducing the computational complexity of the particle filter in real-time *** the second stage,an Error State Kalman Filter(ESKF)is implemented to estimate the UAV’s *** ESKF is chosen over the conventional EKF method because it is more suitable for non-linear *** results demonstrate that the proposed fuzzy-based terrain composite method achieves high positional accuracy while reducing computational time and memory usage.

关键词： Sensor fusion fuzzy logic particle filter composite feature terrain aided navigation

Defocus Blur Segmentation Using Local Binary Patterns with Adaptive Threshold

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Computers, Materials & Continua 2022年第4期71卷 1597-1611页

作者： usman Ali muhammad tariq Mahmood Future Convergence Engineering School of Computer Science and EngineeringKorea University of Technology and Education1600Chungjeol-roByeongcheon-myeonCheonan31253Korea

Enormousmethods have been proposed for the detection and segmentation of blur and non-blur regions of the *** to the limited available information about blur type,scenario and the level of blurriness,detection and segmentation is a challenging ***,the performance of the blur measure operator is an essential factor and needs improvement to attain *** this paper,we propose an effective blur measure based on local binary pattern(LBP)with adaptive threshold for blur *** sharpness metric developed based on LBP used a fixed threshold irrespective of the type and level of blur,that may not be suitable for images with variations in imaging conditions,blur amount and ***,the proposed measure uses an adaptive threshold for each input image based on the image and blur properties to generate improved sharpness *** adaptive threshold is computed based on the model learned through support vector machine(SVM).The performance of the proposed method is evaluated using two different datasets and is compared with five state-of-the-art *** analysis reveals that the proposed method performs significantly better qualitatively and quantitatively against all of the compared methods.

关键词： Adaptive threshold blur measure defocus blur segmentation local binary pattern support vector machine

Single-cell and spatial omics:exploring hypothalamic heterogeneity

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Neural Regeneration Research 2025年第6期20卷 1525-1540页

作者： muhammad Junaid Eun Jeong Lee Su Bin Lim Department of Biochemistry&Molecular Biology Ajou University School of MedicineSuwonSouth Korea Department of Biomedical Sciences Graduate School of Ajou UniversitySuwonSouth Korea Department of Brain Science Ajou University School of MedicineSuwonSouth Korea

Elucidating the complex dynamic cellular organization in the hypothalamus is critical for understanding its role in coordinating fundamental body functions. Over the past decade, single-cell and spatial omics technologies have significantly evolved, overcoming initial technical challenges in capturing and analyzing individual cells. These high-throughput omics technologies now offer a remarkable opportunity to comprehend the complex spatiotemporal patterns of transcriptional diversity and cell-type characteristics across the entire hypothalamus. Current single-cell and single-nucleus RNA sequencing methods comprehensively quantify gene expression by exploring distinct phenotypes across various subregions of the hypothalamus. However, single-cell/single-nucleus RNA sequencing requires isolating the cell/nuclei from the tissue, potentially resulting in the loss of spatial information concerning neuronal networks. Spatial transcriptomics methods, by bypassing the cell dissociation, can elucidate the intricate spatial organization of neural networks through their imaging and sequencing technologies. In this review, we highlight the applicative value of single-cell and spatial transcriptomics in exploring the complex molecular-genetic diversity of hypothalamic cell types, driven by recent high-throughput achievements.

关键词： cellular diversity hypothalamus multi-omics single-cell transcriptomics spatial transcriptomics

HybridHR-Net:Action Recognition in Video Sequences Using Optimal Deep Learning Fusion Assisted Framework

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Computers, Materials & Continua 2023年第9期76卷 3275-3295页

作者： muhammad Naeem Akbar Seemab Khan muhammad Umar Farooq Majed Alhaisoni usman tariq muhammad usman Akram Department of Computer Engineering National University of Sciences and Technology(NUST)Islamabad46000Pakistan Department of Robotics SMME NUSTIslamabad45600Pakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Management Information System Department College of Business AdministrationPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

The combination of spatiotemporal videos and essential features can improve the performance of human action recognition(HAR);however,the individual type of features usually degrades the performance due to similar actions and complex *** deep convolutional neural network has improved performance in recent years for several computer vision applications due to its spatial *** article proposes a new framework called for video surveillance human action recognition dubbed *** a few selected datasets,deep transfer learning is used to pre-trained the EfficientNet-b0 deep learning *** optimization is employed for the tuning of hyperparameters of the fine-tuned deep *** of fully connected layer features,we considered the average pooling layer features and performed two feature selection techniques-an improved artificial bee colony and an entropy-based *** a serial nature technique,the features that were selected are combined into a single vector,and then the results are categorized by machine learning *** publically accessible datasets have been utilized for the experimental approach and obtained notable accuracy of 97%,98.7%,100%,99.7%,and 96.8%,***,a comparison of the proposed framework with contemporarymethods is done to demonstrate the increase in accuracy.

关键词： Action recognition entropy deep learning transfer learning artificial bee colony feature fusion

Novel Double-Damped Tuned AC Filters in HVDC Systems

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Computers, Materials & Continua 2023年第4期75卷 1467-1482页

作者： Rana Shaheer Mehmood Asif Hussain usman Ali muhammad tariq Mahmood Department of Electrical Engineering University of Management and TechnologyLahore54782Pakistan Department of Electrical and Computer Engineering Sungkyunkwan University2066Seobu-roJangan-guSuwon-si16419Gyeonggi-doKorea School of Computer Science and Engineering Korea University of Technology and Education1600ChungjeolnoByeogchunmyunCheonan31253Korea

This paper presents a performance analysis of novel doubledampedtuned alternating current (AC) filters in high voltage direct current(HVDC) systems. The proposed double-damped tuned AC filters offer theadvantages of improved performance of HVDC systems in terms of betterpower quality, high power factor, and lower total harmonic distortion (THD).The system under analysis consists of an 878 km long HVDC transmissionline connecting converter stations at Matiari and Lahore, two major cities inPakistan. The main focus of this research is to design a novel AC filter usingthe equivalent impedance method of two single-tuned and double-dampedtuned AC filters. Additionally, the impact of the damping resistor on the ACchannel is examined. TheTHDof theHVDCsystem with and without currentAC filters was also compared in this research and a double-damped tuned ACfilter was proposed. The results of the simulation represent that the proposeddouble-damped tuned AC filter is far smaller in size, offers better powerquality, and has a much lower THD compared to the AC filters currently inplace in the converter station. The simulation analysis was carried out utilizingpower systems computer-aided design (PSCAD) software.

关键词： Double-damped tuned AC filters harmonics high voltage DC systems long distance transmission power quality total harmonic distortion

Modeling and Comprehensive Review of Signaling Storms in 3GPP-Based Mobile Broadband Networks:Causes,Solutions,and Countermeasures

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 123-153页

作者： muhammad Qasim Khan Fazal Malik Fahad Alturise Noor Rahman Department of Computer Science Iqra National UniversityPeshawar25000Pakistan Department of Cybersecurity College of ComputerQassim UniversityBuraydah52555Saudi Arabia Department of Computer Science and Engineering Al-Fayha CollegeAl Jubayl31961Saudi Arabia

Control signaling is mandatory for the operation and management of all types of communication networks,including the Third Generation Partnership Project(3GPP)mobile broadband ***,they consume important and scarce network resources such as bandwidth and processing *** have been several reports of these control signaling turning into signaling storms halting network operations and causing the respective Telecom companies big financial *** paper draws its motivation from such real network disaster incidents attributed to signaling *** this paper,we present a thorough survey of the causes,of the signaling storm problems in 3GPP-based mobile broadband networks and discuss in detail their possible solutions and *** provide relevant analytical models to help quantify the effect of the potential causes and benefits of their corresponding *** important contribution of this paper is the comparison of the possible causes and solutions/countermeasures,concerning their effect on several important network aspects such as architecture,additional signaling,fidelity,etc.,in the form of a *** paper presents an update and an extension of our earlier conference *** our knowledge,no similar survey study exists on the subject.

关键词： Signaling storm problems control signaling load analytical modeling 3GPP networks smart devices diameter signaling mobile broadband data access data traffic mobility management signaling network architecture 5G mobile communication

Comprehensive Review and Analysis on Facial Emotion Recognition:Performance Insights into Deep and Traditional Learning with Current Updates and Challenges

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Computers, Materials & Continua 2025年第1期82卷 41-72页

作者： Amjad Rehman muhammad Mujahid Alex Elyassih Bayan AlGhofaily Saeed Ali Omer Bahaj Artificial Intelligence&Data Analytics Lab College of Computer&Information SciencesPrince Sultan UniversityRiyadh11586Saudi Arabia MIS Department College of Business Administration Prince Sattam Bin Abdulaziz UniversityAlKharj11942Saudi Arabia

In computer vision and artificial intelligence,automatic facial expression-based emotion identification of humans has become a popular research and industry *** demonstrations and applications in several fields,including computer games,smart homes,expression analysis,gesture recognition,surveillance films,depression therapy,patientmonitoring,anxiety,and others,have brought attention to its significant academic and commercial *** study emphasizes research that has only employed facial images for face expression recognition(FER),because facial expressions are a basic way that people communicate meaning to each *** immense achievement of deep learning has resulted in a growing use of its much architecture to enhance *** review is on machine learning,deep learning,and hybrid methods’use of preprocessing,augmentation techniques,and feature extraction for temporal properties of successive frames of *** following section gives a brief summary of assessment criteria that are accessible to the public and then compares them with benchmark results the most trustworthy way to assess FER-related research topics *** this review,a brief synopsis of the subject matter may be beneficial for novices in the field of FER as well as seasoned scholars seeking fruitful avenues for further *** information conveys fundamental knowledge and provides a comprehensive understanding of the most recent state-of-the-art research.

关键词： Face emotion recognition deep learning hybrid learning CK+ facial images machine learning technological development

Regression analysis of squeezing-induced hybrid nanofluid flow in Darcy-Forchheimer porous medium

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Applied Mathematics and Mechanics(English Edition) 2025年第1期46卷 193-208页

作者： K.muhammad M.SARFRAZ Department of Humanities and Sciences School of Electrical Engineering and Computer Science National University of Sciences and Technology Department of Mathematics Quaid-i-Azam University

This article presents a mathematical model addressing a scenario involving a hybrid nanofluid flow between two infinite parallel plates. One plate remains stationary, while the other moves downward at a squeezing velocity. The space between these plates contains a Darcy-Forchheimer porous medium. A mixture of water-based fluid with gold(Au) and silicon dioxide(Si O2) nanoparticles is formulated. In contrast to the conventional Fourier's heat flux equation, this study employs the Cattaneo-Christov heat flux equation. A uniform magnetic field is applied perpendicular to the flow direction, invoking magnetohydrodynamic(MHD) effects. Further, the model accounts for Joule heating, which is the heat generated when an electric current passes through the fluid. The problem is solved via NDSolve in MATHEMATICA. Numerical and statistical analyses are conducted to provide insights into the behavior of the nanomaterials between the parallel plates with respect to the flow, energy transport, and skin *** findings of this study have potential applications in enhancing cooling systems and optimizing thermal management strategies. It is observed that the squeezing motion generates additional pressure gradients within the fluid, which enhances the flow rate but reduces the frictional drag. Consequently, the fluid is pushed more vigorously between the plates, increasing the flow velocity. As the fluid experiences higher flow rates due to the increased squeezing effect, it spends less time in the region between the plates. The thermal relaxation, however, abruptly changes the temperature, leading to a decrease in the temperature fluctuations.

关键词： Nanofluidics