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Road Traffic Monitoring from Aerial Images Using Template Matching and Invariant Features

Computers, Materials & Continua 2024年第3期78卷 3683-3701页

作者： asifa mehmood qureshi Naif Al Mudawi Mohammed Alonazi Samia Allaoua Chelloug Jeongmin Park Department of Creative Technologies Air UniversityIslamabad46000Pakistan Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Engineering Tech University of KoreaGyeonggi-do15073South Korea

Road traffic monitoring is an imperative topic widely discussed among *** used to monitor traffic frequently rely on cameras mounted on bridges or ***,aerial images provide the flexibility to use mobile platforms to detect the location and motion of the vehicle over a larger *** this end,different models have shown the ability to recognize and track ***,these methods are not mature enough to produce accurate results in complex road ***,this paper presents an algorithm that combines state-of-the-art techniques for identifying and tracking vehicles in conjunction with image *** extracted frames were converted to grayscale,followed by the application of a georeferencing algorithm to embed coordinate information into the *** masking technique eliminated irrelevant data and reduced the computational cost of the overall monitoring ***,Sobel edge detection combined with Canny edge detection and Hough line transform has been applied for noise *** preprocessing,the blob detection algorithm helped detect the *** of varying sizes have been detected by implementing a dynamic thresholding *** was done on the first image of every ***,to track vehicles,the model of each vehicle was made to find its matches in the succeeding images using the template matching *** further improve the tracking accuracy by incorporating motion information,Scale Invariant Feature Transform(SIFT)features have been used to find the best possible match among multiple *** accuracy rate of 87%for detection and 80%accuracy for tracking in the A1 Motorway Netherland dataset has been *** the Vehicle Aerial Imaging from Drone(VAID)dataset,an accuracy rate of 86%for detection and 78%accuracy for tracking has been achieved.

关键词： Unmanned Aerial Vehicles(UAV) aerial images dataset object detection object tracking data elimination template matching blob detection SIFT VAID

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Semantic Segmentation and YOLO Detector over Aerial Vehicle Images

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Computers, Materials & Continua 2024年第8期80卷 3315-3332页

作者： asifa mehmood qureshi Abdul Haleem Butt Abdulwahab Alazeb Naif Al Mudawi Mohammad Alonazi Nouf Abdullah Almujally Ahmad Jalal Hui Liu Faculty of Computing and AI Air UniversityIslamabad44000Pakistan Department of Computer Science College of Computer Science and Information SystemNajran UniversityNajran55461Saudi Arabia Department of Information Systems College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj16273Saudi Arabia Department of Information Technology College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Cognitive Systems Lab University of BremenBremen28359Germany

Intelligent vehicle tracking and detection are crucial tasks in the realm of highway ***,vehicles come in a range of sizes,which is challenging to detect,affecting the traffic monitoring system’s overall *** learning is considered to be an efficient method for object detection in vision-based *** this paper,we proposed a vision-based vehicle detection and tracking system based on a You Look Only Once version 5(YOLOv5)detector combined with a segmentation *** model consists of six *** the first step,all the extracted traffic sequence images are subjected to pre-processing to remove noise and enhance the contrast level of the *** pre-processed images are segmented by labelling each pixel to extract the uniform regions to aid the detection phase.A single-stage detector YOLOv5 is used to detect and locate vehicles in *** detection was exposed to Speeded Up Robust Feature(SURF)feature extraction to track multiple *** on this,a unique number is assigned to each vehicle to easily locate them in the succeeding image frames by extracting them using the feature-matching ***,we implemented a Kalman filter to track multiple *** the end,the vehicle path is estimated by using the centroid points of the rectangular bounding box predicted by the tracking *** experimental results and comparison reveal that our proposed vehicle detection and tracking system outperformed other state-of-the-art *** proposed implemented system provided 94.1%detection precision for Roundabout and 96.1%detection precision for Vehicle Aerial Imaging from Drone(VAID)datasets,respectively.

关键词： Semantic segmentation YOLOv5 vehicle detection and tracking Kalman filter SURF

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Intelligent Traffic Surveillance through Multi-Label Semantic Segmentation and Filter-Based Tracking

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Computers, Materials & Continua 2023年第9期76卷 3707-3725页

作者： asifa mehmood qureshi Nouf Abdullah Almujally Saud S.Alotaibi Mohammed Hamad Alatiyyah Jeongmin Park Department of Creative Technologies Air UniversityIslamabad44000Pakistan Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Information Systems Department Umm Al-Qura UniversityMakkahSaudi Arabia Department of Computer Science College of Sciences and Humanities in AflajPrince Sattam Bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Computer Engineering Tech University of KoreaSiheung-siGyeonggi-do15073Korea

Road congestion,air pollution,and accident rates have all increased as a result of rising traffic density andworldwide population *** the past ten years,the total number of automobiles has increased significantly over the *** this paper,a novel method for intelligent traffic surveillance is *** proposed model is based on multilabel semantic segmentation using a random forest classifier which classifies the images into five *** improve the results,mean-shift clustering was applied to the segmented ***,the pixels given the label for the vehicle were extracted and blob detection was applied to mark each *** the validation of each detection,a vehicle verification method based on the structural similarity index is *** tracking of vehicles across the image frames is done using the Identifier(ID)assignment technique and particle ***,vehicle counting in each frame along with trajectory estimation was done for each *** proposed system demonstrated a remarkable vehicle detection rate of 0.83 over Vehicle Aerial Imaging from Drone(VAID),0.86 over AU-AIR,and 0.75 over the Unmanned Aerial Vehicle Benchmark Object Detection and Tracking(UAVDT)dataset during the experimental *** proposed system can be used for several purposes,such as vehicle identification in traffic,traffic density estimation at intersections,and traffic congestion sensing on a road.

关键词： Traffic surveillance multi-label segmentation random forest particle filter computer vision

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Limits of Depth: Over-Smoothing and Over-Squashing in GNNs

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Big Data Mining and Analytics 2024年第1期7卷 205-216页

作者： Aafaq Mohi ud din Shaima qureshi Department of Computer Science and Engineering National Institute of Technology SrinagarSrinagar 190006India

Graph Neural Networks(GNNs)have become a widely used tool for learning and analyzing data on graph structures,largely due to their ability to preserve graph structure and properties via graph representation ***,the effect of depth on the performance of GNNs,particularly isotropic and anisotropic models,remains an active area of *** study presents a comprehensive exploration of the impact of depth on GNNs,with a focus on the phenomena of over-smoothing and the bottleneck effect in deep graph neural *** research investigates the tradeoff between depth and performance,revealing that increasing depth can lead to over-smoothing and a decrease in performance due to the bottleneck *** also examine the impact of node degrees on classification accuracy,finding that nodes with low degrees can pose challenges for accurate *** experiments use several benchmark datasets and a range of evaluation metrics to compare isotropic and anisotropic GNNs of varying depths,also explore the scalability of these *** findings provide valuable insights into the design of deep GNNs and offer potential avenues for future research to improve their performance.

关键词： Graph Neural Networks(GNNs) learning on graphs over-smoothing over-squashing isotropic-GNNs anisotropic-GNNs

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Computational Approach for Automated Segmentation and Classification of Region of Interest in Lateral Breast Thermograms

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Computers, Materials & Continua 2024年第9期80卷 4749-4765页

作者： Dennies Tsietso Abid Yahya Ravi Samikannu Basit qureshi Muhammad Babar Department of Electrical Computer and Telecommunications EngineeringBotswana International University of Science and TechnologyPalapyePrivate Bag 16Botswana College of Computer and Information Sciences Prince Sultan UniversityRiyadh11586Saudi Arabia Robotics and Internet of Things Lab Prince Sultan UniversityRiyadh11586Saudi Arabia

Breast cancer is one of the major health issues with high mortality rates and a substantial impact on patients and healthcare systems *** Computer-Aided Diagnosis(CAD)tools,based on breast thermograms,have been developed for early detection of this ***,accurately segmenting the Region of Interest(ROI)fromthermograms remains *** paper presents an approach that leverages image acquisition protocol parameters to identify the lateral breast region and estimate its bottomboundary using a second-degree *** proposed method demonstrated high efficacy,achieving an impressive Jaccard coefficient of 86%and a Dice index of 92%when evaluated against manually created ground *** features were extracted from each view’s ROI,with significant features selected via Mutual Information for training Multi-Layer Perceptron(MLP)and K-Nearest Neighbors(KNN)*** findings revealed that the MLP classifier outperformed the KNN,achieving an accuracy of 86%,a specificity of 100%,and an Area Under the Curve(AUC)of *** consistency of the method across both sides of the breast suggests its viability as an auto-segmentation ***,the classification results suggests that lateral views of breast thermograms harbor valuable features that can significantly aid in the early detection of breast cancer.

关键词： Breast cancer CAD machine learning ROI segmentation thermography

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Aggravation of Cancer,Heart Diseases and Diabetes Subsequent to COVID-19 Lockdown via Mathematical Modeling

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 485-512页

作者： Fatma Nese Efil Sania qureshi Nezihal Gokbulut Kamyar Hosseini Evren Hincal Amanullah Soomro Near East University Department of MathematicsNicosia99010North Cyprus Mehran University of Engineering and Technology Department of Basic Sciences and Related StudiesJamshoro76090Pakistan Department of Computer Science and Mathematics Lebanese American UniversityP.O.Box 13-5053BeirutLebanon Near East University Mathematics Research CenterNicosia99010North Cyprus

The global populationhas beenandwill continue to be severely impacted by theCOVID-19 *** primary objective of this research is to demonstrate the future impact of COVID-19 on those who suffer from other fatal conditions such as cancer,heart disease,and ***,using ordinary differential equations(ODEs),two mathematical models are developed to explain the association between COVID-19 and cancer and between COVID-19 and diabetes and heart *** that,we highlight the stability assessments that can be applied to these *** analysis is used to examine how changes in certain factors impact different aspects of *** sensitivity analysis showed that many people are still nervous about seeing a doctor due to COVID-19,which could result in a dramatic increase in the diagnosis of various ailments in the years to *** correlation between diabetes and cardiovascular illness is also illustrated *** effects of smoking and obesity are also found to be significant in disease *** fitting is also provided for interpreting the relationship between real data and the results of *** people,in particular,need tomonitor their health conditions closely and practice heart health *** with heart diseases should undergo regular checks so that they can protect themselves from diabetes and take some precautions including suitable *** main purpose of this study is to emphasize the importance of regular checks,to warn people about the effects of COVID-19(including avoiding healthcare centers and doctors because of the spread of infectious diseases)and to indicate the importance of family history of cancer,heart diseases and *** provision of the recommendations requires an increase in public consciousness.

关键词： COVID-19 mathematical modeling cancer diabetes heart diseases sensitivity analysis

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New therapy for metabolic syndrome:Gut microbiome supplementation

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World Journal of Diabetes 2024年第9期15卷 1833-1836页

作者： Waseem qureshi Maqsood Ahmad Dar Mohd Younis Rather Hospital Administration Government Medical CollegeUniversity of KashmirJammu and KashmirSrinagar 190010India Department of Medicine Government Medical CollegeUniversity of KashmirJammu and KashmirSrinagar 190010India Multidisciplinary Research Unit Government Medical CollegeUniversity of KashmirJammu and KashmirSrinagar 190010India

The gut microbiota is important in the development and progression of metabolic illnesses such type 2 diabetes,cardiovascular disease(CVD),and *** diverse community of microorganisms controls a variety of physiological functions,including metabolism,inflammation,and immune *** these interactions has resulted in novel therapeutic options,including microbiome *** gut microbiome is extremely susceptible to dietary changes,which can alter its makeup and function,influencing metabolite synthesis that affects host *** metabolites,such as butyrate and propionate,have been proven to protect against metabolic illnesses,whereas trimethylamine has been linked to ***,probiotics,synbiotics,and postbiotics are being investigated by researchers as ways to change the gut microbiome and boost metabolic *** advances in therapy and lifestyle adjustments,the prevalence of metabolic syndrome is increasing,emphasizing the need for new medicines.

关键词： Probiotics Prebiotics Synbiotics Postbiotics Microbiome Type 2 diabetes mellitus Cardiovascular disease Obesity

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Dust particle surface potential in an argonhelium plasma using the(r,q)-distribution function

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Communications in Theoretical Physics 2024年第9期76卷 141-148页

作者： Bahaaudin M Raffah A A Abid Abdullah Khan Amin Esmaeili Yas Al-Hadeethi M N S qureshi Department of Physics Faculty of SciencesKing Abdulaziz UniversityJeddah 21589Saudi Arabia Lithography in Devices Fabrication and Development Research Group Deanship of Scientific ResearchKing Abdulaziz UniversityJeddah 21589Saudi Arabia Joint Laboratory of Plasma Application Technology Institute of Advanced TechnologyUniversity of Science and Technology of ChinaHefei230026China CAS Key Laboratory of Geospace Environment University of Science and Technology of ChinaHefei230026China Department of Physics Zhejiang Normal UniversityJinhua321005China Department of Physics Graduate School of ScienceTokyo Metropolitan UniversityMinami-Osawa 1-1Hachioji City192-0397Japan Department of Physics GC UniversityLahore 54000Pakistan

In this paper,the dust particle surface potential for argon-helium plasma is evaluated analytically and numerically in the context of negatively charged dust particles by employing a power-law(r,q)-distribution *** studies have reported the argon-helium plasma and conducted a brief theoretical and experimental *** deepen our understanding further,this study aims to analyze the argon-helium plasma comprehensively using the same pattern but with the(r,q)-distribution *** this purpose,the current balance equations are derived for electron,helium and argon ions,when these charge species attain the quasineutrality *** numerically examined the currents of plasma species for a broad range of effective distribution function parameters r and *** is revealed that the surface potential of dust particles is significantly affected by the parameters r and q,helium ion-to-electron temperature ratio,argon ion-to-electron temperature ratio,and helium ion to argon ion number density *** incorporating the multi-ion(argon-helium)species,the significance of low-temperature nonMaxwellian dusty(complex)plasma is briefly examined.

关键词： dusty plasma dust charge potential plasma physics helium argon plasma r q distribution function non-Maxwellian distribution

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Artificial Intelligence Based Meteorological Parameter Forecasting for Optimizing Response of Nuclear Emergency Decision Support System

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原子能科学技术 2024年第10期58卷 2068-2076页

作者： BILAL Ahmed Khan HASEEB ur Rehman QAISAR Nadeem MUHAMMAD Ahmad Naveed qureshi JAWARIA Ahad MUHAMMAD Naveed Akhtar AMJAD Farooq MASROOR Ahmad Pakistan Institute of Engineering and Applied Sciences Islamabad 44000Pakistan

This paper presents a novel artificial intelligence (AI) based approach to predict crucial meteorological parameters such as temperature,pressure,and wind speed,typically calculated from computationally intensive weather research and forecasting (WRF) *** meteorological data is indispensable for simulating the release of radioactive effluents,especially in dispersion modeling for nuclear emergency decision support *** of meteorological conditions during nuclear emergencies using the conventional WRF model is very complex and ***,a new artificial neural network (ANN) based technique was proposed as a viable alternative for meteorological prediction.A multi-input multi-output neural network was trained using historical site-specific meteorological data to forecast the meteorological *** evaluation of this technique was conducted to test its performance in forecasting various parameters including atmospheric pressure,temperature,and wind speed components in both East-West and North-South *** performance of developed network was evaluated on an unknown dataset,and acquired results are within the acceptable range for all meteorological *** show that ANNs possess the capability to forecast meteorological parameters,such as temperature and pressure,at multiple spatial locations within a grid with high accuracy,utilizing input data from a single ***,accuracy is slightly compromised when predicting wind speed *** mean square error (RMSE) was utilized to report the accuracy of predicted results,with values of 1.453℃for temperature,77 Pa for predicted pressure,1.058 m/s for the wind speed of U-component and 0.959 m/s for the wind speed of *** conclusion,this approach offers a precise,efficient,and wellinformed method for administrative decision-making during nuclear emergencies.

关键词： prediction of meteorological parameters weather research and forecasting model artificial neural networks nuclear emergency support system

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Feeding behavior and hormoligosis associated with imidacloprid resistance in Asian citrus psyllid,Diaphorina citri

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Insect Science 2024年第4期31卷 1211-1221页

作者： Xue Dong Chen Justin George Lauren M.Diepenbrock Hunter Gossett Guoping Liu Jawwad A.qureshi Lukasz L.Stelinski Entomology and Nematology Department University of FloridaCitrus Research and Education CenterLake AlfredFloridaUSA Southern Insect Management Research Unit USDA-ARSStonevilleMississippiUSA Entomology and Nematology Department University of FloridaSouthwest Florida Research and Education CenterImmokaleeFloridaUSA

Imidacloprid is a neonicotinoid insecticide used for managing the Asian citrus psyllid,Diaphorina citri Kuwayama,which serves as vector of phytopathogens causing citrus ***,development of resistance to neonicotinoids among populations of *** has coincided with occasional control failures in the *** objectives of this research were to(1)survey current levels of imidacloprid resistance in Florida citrus;(2)compare feeding behavior between imidacloprid-resistant and susceptible *** using electrical penetration graph recordings,and(3)investigate the possible amplification of insecticide hormoligosis associated with *** surveys confirmed that the susceptibility of *** populations to imidacloprid has decreased in commercial Florida citrus groves compared with a laboratory-susceptible *** 12 generations of selection,resistance to imidacloprid increased by 438 fold compared with the susceptible ***-susceptible *** feeding on citrus exhibited significantly more bouts associated with intercellular pathway(C),phloem penetration(D),phloem salivation(E1),and nonprobing(Np)activities than imidacloprid-resistant ***,there were no differences observed in the frequency or duration of phloem ingestion or xylem feeding between susceptible and resistant *** was no statistical difference in fecundity between resistant and susceptible ***,the fecundity of imidacloprid-susceptible female *** treated with a sublethal concentration of imidacloprid(LC_(25))increased significantly compared with controls,while such hormoligosis was less pronounced among imidacloprid-resistant *** results suggest that imidacloprid-resistant psyllids may cease feeding sooner than susceptible counterparts following sublethal exposure to this insecticide,indicative of a behavioral resistance mechanism.

关键词： artificial selection electrical penetration graph feeding behavior hormoligosis insecticide resistance sublethal exposure

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