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Secure Channel Estimation Using Norm Estimation Model for 5G Next Generation Wireless Networks

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Computers, Materials & Continua 2025年第1期82卷 1151-1169页

作者： Khalil ullah Song Jian muhammad Naeem ul Hassan Suliman Khan Mohammad Babar Arshad Ahmad Shafiq Ahmad Faculty of Information Engineering and Automation Kunming University of Science and TechnologyKunming650500China Department of Computer Science Abbottabad University of Science and TechnologyHavelianAbbottabad22500Pakistan Department of Computing and Electronics Engineering Middle East CollegeMuscat124Oman Department of CS&IT Pak-Austria Fachhochschule Institute of Applied Sciences and Technology MangHaripur22621Pakistan Industrial Engineering Department College of EngineeringKing Saud UniversityRiyadh11421Saudi Arabia

The emergence of next generation networks(NextG),including 5G and beyond,is reshaping the technological landscape of cellular and mobile *** networks are sufficiently scaled to interconnect billions of users and *** in academia and industry are focusing on technological advancements to achieve highspeed transmission,cell planning,and latency reduction to facilitate emerging applications such as virtual reality,the metaverse,smart cities,smart health,and autonomous *** continuously improves its network functionality to support these *** input multiple output(MIMO)technology offers spectral efficiency,dependability,and overall performance in *** article proposes a secure channel estimation technique in MIMO topology using a norm-estimation model to provide comprehensive insights into protecting NextG network components against adversarial *** technique aims to create long-lasting and secure NextG networks using this extended *** viability of MIMO applications and modern AI-driven methodologies to combat cybersecurity threats are explored in this ***,the proposed model demonstrates high performance in terms of reliability and accuracy,with a 20%reduction in the MalOut-RealOut-Diff metric compared to existing state-of-the-art techniques.

关键词： Next generation networks massive mimo communication network artificial intelligence 5G adversarial attacks channel estimation information security

A Latency-Aware and Fault-Tolerant Framework for Resource Scheduling and Data Management in Fog-Enabled Smart City Transportation Systems

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Computers, Materials & Continua 2025年第1期82卷 1377-1399页

作者： Ibrar Afzal Noor ul Amin Zulfiqar Ahmad Abdulmohsen Algarni Department of Computer Science and Information Technology Hazara UniversityMansehra21300Pakistan Department of Computer Science King Khalid UniversityAbha61421Saudi Arabia

Thedeployment of the Internet of Things(IoT)with smart sensors has facilitated the emergence of fog computing as an important technology for delivering services to smart environments such as campuses,smart cities,and smart transportation *** computing tackles a range of challenges,including processing,storage,bandwidth,latency,and reliability,by locally distributing secure information through end *** of endpoints,fog nodes,and back-end cloud infrastructure,it provides advanced capabilities beyond traditional cloud *** smart environments,particularly within smart city transportation systems,the abundance of devices and nodes poses significant challenges related to power consumption and system *** address the challenges of latency,energy consumption,and fault tolerance in these environments,this paper proposes a latency-aware,faulttolerant framework for resource scheduling and data management,referred to as the FORD framework,for smart cities in fog *** framework is designed to meet the demands of time-sensitive applications,such as those in smart transportation *** FORD framework incorporates latency-aware resource scheduling to optimize task execution in smart city environments,leveraging resources from both fog and cloud *** simulation-based executions,tasks are allocated to the nearest available nodes with minimum *** the event of execution failure,a fault-tolerantmechanism is employed to ensure the successful completion of *** successful execution,data is efficiently stored in the cloud data center,ensuring data integrity and reliability within the smart city ecosystem.

关键词： Fog computing smart cities smart transportation data management fault tolerance resource scheduling

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

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

Natural convection of CuO–water nanofluid filled in a partially heated corrugated cavity:KKL model approach

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Communications in Theoretical Physics 2020年第8期72卷 27-42页

作者： Rizwan ul haq muhammad Usman Ebrahem A Algehyne Department of Electrical Engineering Bahria UniversityIslamabadPakistan BIC-ESAT College of EngineeringPeking UniversityBeijing 100871China State Key Laboratory for Turbulence and Complex Systems Department of Mechanics and Engineering SciencePeking UniversityBeijing 100871China Department of Mathematics Faculty of SciencesUniversity of TabukP.O.Box 741Tabuk 71491Saudi Arabia

In this article, flow and heat transfer inside a corrugated cavity is analyzed for natural convection with a heated inner obstacle. Thermal performance is analyzed for Cu O–water inside a partially heated domain by defining the constraint along the boundaries. For nanofluid analysis, the Koo and Kleinstreuer Li(KKL) model is implemented to deal with the effective thermal conductivity and viscosity. A heated thin rod is placed inside the corrugated cavity and the bottom portion of the corrugated cavity is partially heated. The dimensionless form of nonlinear partial differential equations are obtained through the compatible transformation along with the boundary constraint. The finite element method is executed to acquire the numerical solution of the obtained dimensional system. Streamlines, isotherms and heat transfers are analyzed for the flow field and temperature distribution. The Nusselt number is calculated at the surface of the partially heated domain for various numerical values of emerging parameters by considering the inner obstacle at cold, adiabatic and heated conditions. The computational simulation was performed by introducing various numerical values of emerging parameters. Important and significant results have been attained for temperature and velocities(in both x-and y-directions) at the vertically and horizontally mean positions of the corrugated duct.

关键词： heat transfer nanofluid finite element method KKL corrugated cavity

Revealing the Trends in the Academic Landscape of the Health Care System Using Contextual Topic Modeling

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Data Intelligence 2023年第4期5卷 923-946页

作者： muhammad Inaam ul haq Qianmu Li School of computer science and Engineering Nanjing University of Science and Technology

The health care system encompasses the participation of individuals,groups,agencies,and resources that offer services to address the requirements of the person,community,and population in terms of *** to the rising debates on the healthcare systems in relation to diseases,treatments,interventions,medication,and clinical practice guidelines,the world is currently discussing the healthcare industry,technology perspectives,and healthcare *** gain a comprehensive understanding of the healthcare systems research paradigm,we offered a novel contextual topic modeling approach that links up the CombinedTM model with our healthcare Bert to discover the contextual topics in the domain of *** research work discovered 60 contextual topics among them fteen topics are the hottest which include smart medical monitoring systems,causes,and effects of stress and anxiety,and healthcare cost estimation and twelve topics are the ***,thirty-three topics are showing in-significant *** further investigated various clusters and correlations among the topics exploring inter-topic distance maps which add depth to the understanding of the research structure of this scientific *** current study enhances the prior topic modeling methodologies that examine the healthcare literature from a particular disciplinary *** further extends the existing topic modeling approaches that do not incorporate contextual information in the topic discovery process adding contextual information by creating sentence embedding vectors through transformers-based *** also utilized corpus tuning,the mean pooling technique,and the hugging face *** method gives a higher coherence score as compared to the state-of-the-art models(LSA,LDA,and Ber Topic).

关键词： Contextual topic modeling health care Bert content analysis health care system

Growth,yield and water productivity of dry direct seeded rice and transplanted aromatic rice under different irrigation management regimes

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Journal of Integrative Agriculture 2020年第11期19卷 2656-2673页

作者： muhammad Ishfaq Nadeem Akbar Shakeel Ahmed Anjum muhammad Anwar-ul-haq Department of Agronomy University of AgricultureFaisalabad 38040Pakistan Department of Plant Science University of CaliforniaCalifornia 95616-8780USA Institute of Soil and Environmental Sciences University of AgricultureFaisalabad 38040Pakistan

Sustainability of traditionally cultivated rice in the rice-wheat cropping zone(RWCZ)of Pakistan is dwindling due to the high cost of production,declining water resources and escalating labour ***,farmers and researchers are compelled to find promising alternatives to traditional transplanted rice(TPR).A field study was conducted in Punjab,Pakistan,in 2017 and 2018 to explore the trade-offs between water saving and paddy yield,water productivity and economics of two aromatic rice varieties under dry direct seeded rice(DDSR)and *** experiment was comprised of three irrigation regimes on the basis of soil moisture tension(SMT)viz.,continuous flooded(>–10 kPa SMT),alternate wetting and drying(AWD)(–20 kPa SMT)and aerobic rice(–40 kPa SMT),maintained under TPR and DDSR *** aromatic rice verities:Basmati-515 and Chenab Basmati-2016 were used during both years of *** both years,DDSR produced higher yields(13–18%)and reduced the total water inputs(8–12%)in comparison to *** comparison to traditional continuous flooded(CF),AWD under DDSR reduced total water input by 27–29%and improved the leaf area index(LAI),tillering,yield(7–9%),and water productivity(44–50%).The performance of AWD with regard to water savings and increased productivity was much higher in DDSR system as compared to AWD in TPR *** of DDSR with aerobic irrigation improved water savings(49–55%)and water productivity(22–30%)at the expense of paddy yield reduction(36–39%)and spikelet *** regard to variety,the highest paddy yield(6.6 and 6.7 t ha–1)was recorded in DDSR using Chenab Basmati-2016 under AWD irrigation threshold that attributed to high tiller density and *** economic analysis showed DDSR as more beneficial rice establishment method than TPR with a high benefit-cost ratio(BCR)when the crop was irrigated with AWD irrigation *** results highlighted that with the use of short duration varieties,DDSR cultivation in conjunction wit

关键词： rice establishment aerobic alternate wetting and drying water input tillering yield

Two paths, one goal: mechanism of calcium homeostasis to balance plant growth and immunity

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Science China Life Sciences 2025年第1期 306-308页

作者： Aziz ul Ikram Yanping Jing Huan Chen Jian Chen International Genome Center Jiangsu University Joint Center for Single Cell Biology School of Agriculture and BiologyShanghai Jiao Tong University

Calcium(Ca2+) is an essential nutrient and a cellular signal in plants. The level of free Ca2+in the apoplast is ～10,000-fold higher than that in the cytoplasm at the resting state. This large Ca2+level gradient across the membrane between the interior and exterior can cause Ca2+overload and toxicity. Plants have evolved mechanisms to export Ca2+out of the cytoplasm or store it in intracellular organelles, such as endoplasmic reticulum（ER）, mitochondria, and vacuole.

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Electroencephalogram (EEG) Brain Signals to Detect Alcoholism Based on Deep Learning

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Computers, Materials & Continua 2021年第6期67卷 3329-3348页

作者： Emad-ul-haq Qazi muhammad Hussain Hatim A.AboAlsamh Visual Computing Lab Department of Computer ScienceCollege of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia

The detection of alcoholism is of great importance due to its effects on individuals and *** alcoholism detection system(AADS)based on electroencephalogram(EEG)signals is effective,but the design of a robust AADS is a challenging ***’current designs are based on conventional,hand-engineered methods and restricted *** by the excellent deep learning(DL)success in many recognition tasks,we implement an AAD system based on EEG signals using DL.A DL model requires huge number of learnable parameters and also needs a large dataset of EEG signals for training which is not easy to obtain for the AAD *** order to solve this problem,we propose a multi-channel Pyramidal neural convolutional(MP-CNN)network that requires a less number of learnable *** the deep CNN model,we build an AAD system to detect from EEG signal segments whether the subject is alcoholic or *** validate the robustness and effectiveness of proposed AADS using KDD,a benchmark dataset for alcoholism detection *** order to find the brain region that contributes significant role in AAD,we investigated the effects of selected 19 EEG channels(SC-19),those from the whole brain(ALL-61),and 05 brain regions,i.e.,TEMP,OCCIP,CENT,FRONT,and *** results show that SC-19 contributes significant role in AAD with the accuracy of 100%.The comparison reveals that the state-of-the-art systems are outperformed by the *** proposed AADS will be useful in medical diagnosis research and health care systems.

关键词： Electroencephalogram convolutional neural network deep learning alcoholism