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Vehicle Detection and Tracking in UAV Imagery via YOLOv3 and Kalman Filter

computers, Materials & Continua 2023年第7期76卷 1249-1265页

作者： Shuja ali Ahmad Jalal Mohammed Hamad alatiyyah Khaled alnowaiser Jeongmin Park Department of Computer Science Air UniversityIslamabad44000Pakistan Department of Computer Science College of Sciences and Humanities in AflajPrince Sattam Bin Abdulaziz UniversityAl-KharjSaudi Arabia Department of Computer Engineering College of Computer Engineering and SciencesPrince Sattam Bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia Department of Computer Engineering Tech University of Korea237 Sangidaehak-roSiheung-si15073Gyeonggi-doKorea

Unmanned aerial vehicles(UAVs)can be used to monitor traffic in a variety of settings,including security,traffic surveillance,and traffic *** academics have been drawn to this topic because of the challenges and the large variety of *** paper proposes a new and efficient vehicle detection and tracking system that is based on road extraction and identifying objects on *** is inspired by existing detection systems that comprise stationary data collectors such as induction loops and stationary cameras that have a limited field of view and are not *** goal of this study is to develop a method that first extracts the region of interest(ROI),then finds and tracks the items of *** suggested system is divided into six *** photos from the obtained dataset are appropriately georeferenced to their actual locations in the first phase,after which they are all *** ROI,or road and its objects,are retrieved using the GrabCut method in the second *** third phase entails data *** segmented images’noise is eliminated using Gaussian blur,after which the images are changed to grayscale and forwarded to the following stage for additional morphological *** YOLOv3 algorithm is used in the fourth step to find any automobiles in the *** that,the Kalman filter and centroid tracking are used to perform the tracking of the detected *** Lucas-Kanade method is then used to perform the trajectory analysis on the *** suggested model is put to the test and assessed using the Vehicle Aerial Imaging from Drone(VAID)*** detection and tracking,the model was able to attain accuracy levels of 96.7%and 91.6%,respectively.

关键词： Kalman filter georeferencing object detection object tracking YOLO

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A Particle Swarm Optimization Based Deep Learning Model for Vehicle Classification

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computer Systems Science & engineering 2022年第1期40卷 223-235页

作者： Adi alhudhaif Ammar Saeed Talha Imran Muhammad Kamran Ahmed S.alghamdi Ahmed O.Aseeri Shtwai alsubai Department of Computer Science College of Computer Engineering and Sciences in Al-KharjPrince Sattam bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942Saudi Arabia Department of Computer Science COMSATS University IslamabadWah Cantt47010Pakistan University of Jeddah College of Computer Science and Engineering Department of CybersecurityJeddah21959Saudi Arabia

Image classification is a core field in the research area of image proces-sing and computer vision in which vehicle classification is a critical *** purpose of vehicle categorization is to formulate a compact system to assist in real-world problems and applications such as security,traffic analysis,and self-driving and autonomous *** recent revolution in the field of machine learning and artificial intelligence has provided an immense amount of support for image processing related problems and has overtaken the conventional,and handcrafted means of solving image analysis *** this paper,a combina-tion of pre-trained CNN GoogleNet and a nature-inspired problem optimization scheme,particle swarm optimization(PSO),was employed for autonomous vehi-cle *** model was trained on a vehicle image dataset obtained from Kaggle that has been suitably *** trained model was classified using several classifiers;however,the Cubic SVM(CSVM)classifier was found to out-perform the others in both time consumption and accuracy(94.8%).The results obtained from empirical evaluations and statistical tests reveal that the model itself has shown to outperform the other related models not only in terms of accu-racy(94.8%)but also in terms of training time(82.7 s)and speed prediction(380 obs/sec).

关键词： Vehicle classification intelligent transport system deep learning constrained machine learning particle swarm optimization CNN GoogleNet

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Image Authenticity Detection Using DWT and Circular Block-Based LTrP Features

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computers, Materials & Continua 2021年第11期69卷 1927-1944页

作者： Marriam Nawaz Zahid Mehmood Tahira Nazir Momina Masood Usman Tariq Asmaa Mahdi Munshi Awais Mehmood Muhammad Rashid Department of Computer Science University of Engineering and TechnologyTaxila47050Pakistan Department of Computer Engineering University of Engineering and TechnologyTaxila47050Pakistan College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAl-Kharj11942Saudi Arabia College of Computer Science and Engineering University of JeddahJeddah21577Saudi Arabia Department of Computer Engineering Umm Al-Qura UniversityMakkah21421Saudi Arabia

Copy-move forgery is the most common type of digital image manipulation,in which the content from the same image is used to forge *** manipulations are performed to hide the desired ***,forgery detection methods are required to identify forged *** have introduced a novel method for features computation by employing a circular block-based method through local tetra pattern(LTrP)features to detect the single and multiple copy-move attacks from the *** proposed method is applied over the circular blocks to efficiently and effectively deal with the post-processing *** also uses discrete wavelet transform(DWT)for dimension *** obtained approximate image is distributed into circular blocks on which the LTrP algorithm is employed to calculate the feature vector as the LTrP provides detailed information about the image content by utilizing the direction-based relation of central pixel to its ***,Jeffreys and Matusita distance is used for similarity *** the evaluation of the results,three datasets are used,namely MICC-F220,MICC-F2000,and *** the qualitative and quantitative analysis shows that the proposed method exhibits state-of-the-art performance under the presence of post-processing operations and can accurately locate single and multiple copy-move forgery attacks on the images.

关键词： Copy-move forgery discrete wavelet transform LTrP features image forensic circular blocks

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Arabic sentiment analysis using ensemble learning and BERT

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AIP Conference Proceedings 2025年第1期3169卷

作者： Rafeef A. Hameed Ahmed T. Sadiq Wael J. Abed Computer Sciences Department University of Technology Baghdad Iraq Computer Techniques Engineering Department Al-Mustaqbal University College Babil Iraq

Social media platforms provide an open forum for people to express their opinions about products, services, and brands. Sentiment analysis can help businesses and organizations monitor their brand reputation in real time. Recent research has shown that deep learning models are effective at a number of jobs related to Sentiment Analysis (SA). Typically, the fully connected layer is used for feature extraction, and a layer is used to perform classification tasks. This study used a deep learning architecture that uses Long Short-Term Memory (LSTM) for feature extraction and machine learning techniques. Support Vector Machine (SVM), Xgboost, Random Forest, Decision Tree, KNN, Logistic Regression, and Naive Bayes are employed for Arabic Sentiment Analysis in order to classify the Arabic reviews. In addition, an ensemble model was proposed that uses the seven machine learning techniques by voting, and the multilingual BERT was used for sentiment analysis. Six publicly accessible datasets were used to test the suggested technique. BERT consistently achieved the highest accuracy scores on all six datasets, ranging from 83.04% to 97.45%. LSTM also performed well on most datasets, achieving the second-highest accuracy scores after BERT. Its accuracy scores ranged from 81.871% to 96.984%. The ensemble models also performed well on the datasets, with accuracy scores ranging from 81.41% to 96.51%. The other models, including SVM, Xgboost, RF, DT, KNN, LR, and NB, showed good to moderate performance on the datasets, with accuracy scores ranging from 70% to 96.75%.

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Synthesis, Characterization, and Computational Studies of Organoselenium Compounds for Bioactivity Assessment Against Pancreatic Ductal Adenocarcinoma

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Macromolecular Symposia 2025年第1期414卷

作者： Banerjee, Bhaskar Solanki, Bobby Verma, Rajaneesh Kumar Jain, Nidhi Yadav, Tarun alheetyc, Mustafa A. Yahya, M.Z.A. Singh, Munendra Verma, Vinay Kumar Singh, Ram Chandra Department of Forensic Science Sharda School of Allied Health Sciences Sharda University Uttar Pradesh Greater Noida201301 India Scube Scientific Software Solutions Pvt. Ltd. New Delhi110019 India Department of Chemistry Indian Institute of Technology Hauz Khas New Delhi110017 India Department of Engineering Science Bharati Vidyapeeth's College of Engineering Lavale Pune412115 India Department of Basic Sciences IES University Madhya Pradesh Bhopal462044 India Department of Nursing Al-Hadi University College Baghdad Iraq Kuala Lumpur57000 Malaysia Department of Physics Sharda School of Basic Sciences and Research Sharda University Uttar Pradesh Greater Noida201301 India Department of Chemistry and Biochemistry Sharda School of Basic Sciences and Research Sharda University Uttar Pradesh Greater Noida201301 India

In the present research article, two small organoselenium molecules, 2-(phenylselanyl)ethanamine, L1H and 2-(phenylselanyl)propanamine, L2H, have been synthesized via high yield synthetic route and characterized using elemental, UV–vis, FTIR, (1H and 77Se) NMR, and mass spectrometry along with computational investigation, confirming selenium integration. Density functional theory (DFT) study elucidates the optoelectronic properties and structures of L1H and L2H, providing insights into stability and reactivity of selenium bearing small organic compounds. In addition to this, molecular docking studies and pharmacokinetic profile highlights potential binding affinity with target proteins and also suggests their promising bioactivity. The interaction between the regulatory proteins involved in pancreatic ductal adenocarcinoma (PDAC) and the synthesized small molecule L1H and L2H shows the involvement of amine group and selenium atom for inhibiting the proteins to potentially stop the growth of cancer cells. The comprehensive investigation lays groundwork for further exploration of these compounds in small molecule drug development and medicinal chemistry. © 2025 Wiley-VCH GmbH.

关键词： Molecular docking

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First principles investigations of linear and nonlinear optical, radiation shielding and thermoelectric properties of the non-centrosymmetric Ba-based chalcogenides Ba2In2X5 (X=S, Te)

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Materials Science in Semiconductor Processing 2025年 185卷

作者： Irfan, Muhammad Ibrahim, Fatma A. Hamdy, Mohamed S. Issa, Shams A.M. Zakaly, Hesham M.H. University of Lahore Sargodha Campus 40100 Pakistan Department of Chemistry College of Science King Khalid University Abha61413 Saudi Arabia King Khalid University P.O. Box 9004 Abha61413 Saudi Arabia Physics Department University of Tabuk Tabuk47512 Saudi Arabia Physics Department Faculty of Science Al-Azhar University Assiut Branch Assiut71524 Egypt Istinye University Faculty of Engineering and Natural Sciences Computer Engineering Department Istanbul34396 Turkey Institute of Physics and Technology Ural Federal University Yekaterinburg620002 Russia Department of Physics and Technical Sciences Western Caspian University Baku Azerbaijan

We explore the structural, elastic, optoelectronic, Radiation Shielding, and thermoelectric properties of Ba2In2X5 (X = S, Te) using first-principles computations and semi-classical Boltzmann Transport equations. These materials are classified as semiconductors exhibiting band gaps of 2.0 eV and 3.0 eV for both investigated NLO compounds that have more significant direct band gaps of superior optical birefringence and second-order NLO coefficients. The bonding properties have been investigated by analyzing the electron charge density (ECD) contour of the (1 0 1) crystallographic plane. It is clear from the reflectivity spectra that both compounds have a high degree of reflectivity, which could make them useful as UV and visible light shields. From 0 to 14.0 eV, the approximated reflectivity values, R (ω), are displayed against the incident photon energy. Therefore, the reflectivity is around 30 % before E ≈ 12.0 eV and 40 % reflection at ∼13.0 eV. Phase matching is possible for both compounds detected, as shown by the birefringence computations. Furthermore, the radiation shielding properties of Ba2In2S5 and Ba2In2Te5 have been evaluated using Phy-X software, demonstrating their potential effectiveness in medical and nuclear energy applications. The thermoelectric properties display N-type nature at low temperatures when the Seebeck coefficient changes from N to P-type at higher temperature ranges. These compounds have remarkable optical and thermal properties, rendering them highly attractive materials for thermoelectric and optoelectronic devices. © 2024 Elsevier Ltd

关键词： Birefringence

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STGCN-LSTM FOR OLYMPIC MEDal PREDICTION: DYNAMIC POWER MODELING AND CAUSal POLICY OPTIMIZATION

arXiv

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arXiv 2025年

作者： Wang, Yiquan Wang, Jiaying Huang, Tin-Yeh Yang, Jingyi Wang, Guanjie Xu, Zihao College of Mathematics and System Science Xinjiang University Xinjiang Urumqi830046 China Intelligent Software Research Center Institute of Software Chinese Academy of Sciences Beijing100190 China Shenzhen X-Institute Shenzhen518055 China College of Architecture and Environment Sichuan University Chengdu610065 China Department of Industrial and System Engineering Faculty of Engineering The Hong Kong Polytechnic University 999077 Hong Kong School of Design and Art Hunan Institute of Engineering Xiangtan411104 China School of Computer and Artificial Intelligence Huaihua University Huaihua418099 China Faculty of Science and Engeerning The University of Nottingham-Ningbo Ningbo315100 China

This paper proposes a novel hybrid model, STGCN-LSTM, to forecast Olympic medal distributions by integrating the spatio-temporal relationships among countries and the long-term dependencies of national performance. The Spatial-Temporal Graph Convolution Network (STGCN) captures geographic and interactive factors-such as coaching exchange and socio-economic links-while the Long Short-Term Memory (LSTM) module models historical trends in medal counts, economic data, and demographics. To address zero-inflated outputs (i.e., the disparity between countries that consistently yield wins and those never having won medals), a Zero-Inflated Compound Poisson (ZICP) framework is incorporated to separate random zeros from structural zeros, providing a clearer view of potential breakthrough performances. Validation includes historical backtracking, policy shock simulations, and causal inference checks, confirming the robustness of the proposed method. Results shed light on the influence of coaching mobility, event specialization, and strategic investment on medal forecasts, offering a data-driven foundation for optimizing sports policies and resource allocation in diverse Olympic contexts. © 2025, CC BY-NC-SA.

关键词： Resource allocation

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Demonstration of synaptic and resistive switching characteristics in W/TiO_(2)/HfO_(2)/TaN memristor crossbar array for bioinspired neuromorphic computing

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Journal of Materials Science & Technology 2022年第1期96卷 94-102页

作者： Muhammad Ismail Umesh Chand Chandreswar Mahata Jamel Nebhen Sungjun Kim Division of Electronics and Electrical Engineering Dongguk UniversitySeoul 04620South Korea Department of Electrical and Computer Engineering National University SingaporeSingapore 117583Singapore College of Computer Engineering and Sciences Prince Sattam bin Abdulaziz UniversityAl-Kharj 11942Saudi Arabia

In this study,resistive random-access memory(RRAM)-based crossbar arrays with a memristor W/TiO_(2)/HfO_(2)/TaN structure were fabricated through atomic layer deposition(alD)to investigate synaptic plasticity and resistive switching(RS)characteristics for bioinspired neuromorphic computing.X-ray photoelectron spectroscopy(XPS)was employed to explore oxygen vacancy concentrations in bilayer TiO_(2)/HfO_(2)*** fitting for O1s peaks confirmed that the HfO_(2)layer contained a larger number of oxygen vacancies than the TiO_(2)*** addition,HfO_(2)had lower Gibbs free energy(ΔG°=-1010.8 kJ/mol)than the TiO_(2)layer(ΔG°=-924.0 kJ/mol),resulting in more oxygen vacancies in the HfO_(2)*** results andΔG°magnitudes confirmed that formation/disruption of oxygen-based conductive filaments took place in the TiO_(2)*** W/TiO_(2)/HfO_(2)/TaN memristive device exhibited excellent and repeatable RS characteristics,including superb 10^(3) dc switching cycles,outstanding 107 pulse endurance,and high-thermal stability(10^(4) s at 125℃)important for digital computing ***,some essential biological synaptic characteristics such as potentiation-depression plasticity,paired-pulse facilitation(PPF),and spike-timing-dependent plasticity(STDP,asymmetric Hebbian and asymmetric anti-Hebbian)were successfully mimicked herein using the crossbar-array memristive *** on experimental results,a migration and diffusion of oxygen vacancy based physical model is proposed to describe the synaptic plasticity and RS *** study demonstrates that the proposed W/TiO_(2)/HfO_(2)/TaN memristor crossbar-array has a significant potential for applications in non-volatile memory(NVM)and bioinspired neuromorphic systems.

关键词： Resistive switching Crossbar-array memristive device Synaptic plasticity TiO_(2)/HfO_(2)film Oxygen vacancy

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Pan-cancer analysis of CDC7 in human tumors: Integrative multi-omics insights and discovery of novel marine-based inhibitors through machine learning and computational approaches

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computers in Biology and Medicine 2025年 190卷 110044-110044页

作者： Saif, Ahmed Islam, Md. Tarikul Raihan, Md. Obayed Yousefi, Niloofar Rahman, Md. Ajijur Faridi, Hafeez Hasan, al Riyad Hossain, Mirza Mahfuj Saleem, Rasha Mohammed albadrani, Ghadeer M. al-Ghadi, Muath Q. Ahasan Setu, Md. ali Kamel, Mohamed Abdel-Daim, Mohamed M. Aktaruzzaman, Md. Department of Pharmacy Faculty of Science University of Rajshahi Rajshahi6205 Bangladesh Department of Genetic Engineering and Biotechnology Faculty of Biological Science and Technology Jashore University of Science and Technology Jashore7408 Bangladesh Jashore7408 Bangladesh Department of Pharmaceutical Sciences College of Health Sciences and Pharmacy Chicago State University ChicagoIL United States Department of Industrial Engineering and Management Systems University of Central Florida USA OrlandoFL United States Department of Pharmacy Faculty of Biological Science and Technology Jashore University of Science and Technology Jashore7408 Bangladesh Department of Computer Science and Engineering Faculty of Engineering and Technology Jashore University of Science and Technology Jashore7408 Bangladesh Department of Laboratory Medicine Faculty of Applied Medical Sciences Al-Baha University Al-Baha65431 Saudi Arabia Department of Biology College of Science Princess Nourah bint Abdulrahman University 84428 Riyadh11671 Saudi Arabia Department of Zoology College of Science King Saud University P.O. Box 2455 Riyadh11451 Saudi Arabia Department of Microbiology Faculty of Biological Science and Technology Jashore University of Science and Technology Jashore7408 Bangladesh Department of Medicine and Infectious Diseases Faculty of Veterinary Medicine Cairo University Giza12211 Egypt Department of Pharmaceutical Sciences Pharmacy Program Batterjee Medical College P.O. Box 6231 Jeddah21442 Saudi Arabia Pharmacology Department Faculty of Veterinary Medicine Suez Canal University Ismailia41522 Egypt

Cancer remains a significant global health challenge, with the Cell Division Cycle 7 (CDC7) protein emerging as a potential therapeutic target due to its critical role in tumor proliferation, survival, and resistance. However, a comprehensive analysis of CDC7 across multiple cancers is lacking, and existing therapeutic options have come with limited clinical success. The aim of this is to integrate a comprehensive pan-cancer analysis of CDC7 with the identification of novel marine-derived inhibitors, bridging the understanding of CDC7's role as a prognostic biomarker and therapeutic target across diverse cancer types. In this study, we conducted a pan-cancer analysis of CDC7 across 33 tumor types using publicly available datasets to evaluate its expression, genetic alterations, immune interactions, survival, and prognostic significance. Additionally, a marine-derived compound library of 31,492 molecules was screened to identify potential CDC7 inhibitors using chemoinformatics and machine learning. The top candidates underwent rigorous evaluations, including molecular docking, pharmacokinetics, toxicity, Density Functional Theory (DFT) calculations, and Molecular Dynamics (MD) simulations. The findings revealed that CDC7 is overexpressed in several cancers and is associated with poor survival outcomes and unfavorable prognosis. Enrichment analysis linked CDC7 to critical DNA replication pathways, while its role in modulating tumor-immune interactions highlighted its potential as a target for immunotherapy. Among all tested compounds, Tetrahydroaltersolanol D (CMNPD21999) exhibited the strongest binding affinity and stability, along with better drug-likeness and zero toxicity. These attributes highlight its potential as a promising drug candidate for CDC7 inhibition and future cancer treatment development. Furthermore, additional in vitro and in vivo studies are required to confirm the effectiveness of this drug candidate against the CDC7 protein. © 2025

关键词： Gene expression

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Comparative analysis of hall current impact on MHD laminar surface tension gradient 3D flow of propylene glycol based tetra hybrid nanofluid with generalized fick's and fourier's perspective

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International Journal of Thermofluids 2025年 26卷

作者： Abbas, Munawar Shomurotova, Shirin al-Mdallal, Qasem Akgül, ali Jastaneyah, Zuhair Garalleh, Hakim al Department of Mathematics The Islamia University of Bahawalpur Bahawalpur63100 Pakistan Department of Chemistry Teaching Methods Tashkent State Pedagogical University named after Nizami Bunyodkor street 27 Tashkent Uzbekistan Department of Mathematical Sciences UAE University P.O. Box 17551 Al-Ain United Arab Emirates Department of Electronics and Communication Engineering Saveetha School of Engineering SIMATS Tamilnadu Chennai India Siirt University Art and Science Faculty Department of Mathematics Siirt56100 Turkey Department of Computer Engineering Biruni University Istanbul Topkapı34010 Turkey Near East University Mathematics Research Center Department of Mathematics Near East Boulevard PC: 99138 /Mersin 10 Nicosia Turkey Department of Mathematical Science College of Engineering University of Business and Technology Jeddah21361 Saudi Arabia

Examine the significance of the Cattaneo-Christov flux model on the Marangoni convection 3D flow of tetra hybrid nanofluid combined with Hall current in the present study. When exposed to a fluctuating magnetic flux, it demonstrates electrical conductivity over a stretchy sheet. Using the Cattaneo-Christov double diffusion (CCDD) model, the problem is simulated. In this work, the CCDD model is used to analyze the mass and heat transmission tetra hybrid nanofluid. Basic Fourier's and Fick's laws are generalized by their application. A tetra hybrid nanofluid consisting of Molybdenum disulfide (Mos2), copper (Cu), Silicon dioxide (SiO2) and cobalt ferrite (CoFe2o4), propylene glycol (C3H8O2) as the base fluid is used. This model is essential for precisely predicting the behaviors of heat transfer in nanofluid flows since it takes thermal relaxation time into consideration. Its uses include optimizing heat exchanger performance, enhancing cooling systems in electronics, and better thermal management in microfluidic devices. The basic set of equations is resolved employing the numerical technique (bvp4c). The nanofluid, hybrid, trihybrid, and tetra hybrid nanofluid graphs are all compared. The stretching ratio parameter indicates rising trends in the flow distributions, although the opposite performance is observed for thermal and concentration distributions. Rate of heat and mass transmission improve of tetra hybrid, trihybrid, hybrid nanofluids as increase the values of Marangoni convection. © 2025

关键词： Molybdenum disulfide

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