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Advancing Crowd Object Detection: A Review of YOLO, CNN and ViTs hybrid Approach*

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Journal of Intelligent Learning Systems and Applications 2024年第3期16卷 175-221页

作者： Mahmoud Atta mohammed ali Tarek Aly Atef Tayh Raslan Mervat Gheith Essam A. Amin Faculty of Graduate Studies for Statistical Research Software Engineering Department Cairo University Giza Egypt

One of the most basic and difficult areas of computer vision and image understanding applications is still object detection. Deep neural network models and enhanced object representation have led to significant progress in object detection. This research investigates in greater detail how object detection has changed in the recent years in the deep learning age. We provide an overview of the literature on a range of cutting-edge object identification algorithms and the theoretical underpinnings of these techniques. Deep learning technologies are contributing to substantial innovations in the field of object detection. While Convolutional Neural Networks (CNN) have laid a solid foundation, new models such as You Only Look Once (YOLO) and Vision Transformers (ViTs) have expanded the possibilities even further by providing high accuracy and fast detection in a variety of settings. Even with these developments, integrating CNN, YOLO and ViTs, into a coherent framework still poses challenges with juggling computing demand, speed, and accuracy especially in dynamic contexts. Real-time processing in applications like surveillance and autonomous driving necessitates improvements that take use of each model type’s advantages. The goal of this work is to provide an object detection system that maximizes detection speed and accuracy while decreasing processing requirements by integrating YOLO, CNN, and ViTs. Improving real-time detection performance in changing weather and light exposure circumstances, as well as detecting small or partially obscured objects in crowded cities, are among the goals. We provide a hybrid architecture which leverages CNN for robust feature extraction, YOLO for rapid detection, and ViTs for remarkable global context capture via self-attention techniques. Using an innovative training regimen that prioritizes flexible learning rates and data augmentation procedures, the model is trained on an extensive dataset of urban settings. Compared to solo YOLO,

关键词： Object Detection Deep Learning Computer Vision YOLO Convolutional Neural Networks (CNN) Vision Transformers Neural Networks Transfer Learning Autonomous Driving Self-Drive Vehicles

Catalytic Effect of Transition Metal Complexes of Triaminoguanidine on the Thermolysis of Energetic NC/DEGDN Composite

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火炸药学报 2024年第3期47卷 209-219,I0003页

作者： mohammed Dourari Ahmed Fouzi Tarchoun Djalal Trache Amir Abdelaziz Roufaida Tiliouine Tessnim Barkat Weiqiang Pang Energetic Materials Laboratory(EMLab) Teaching and Research Unit of Energetic ProcessesEcole Militaire PolytechniqueBP 17Bordj El-Bahri16046AlgiersAlgeria Xi′an Modern Chemistry Research Institute Xi′an 710065China

The transition metal complexes of triaminoguanidine(TAG-M,where M=Cobalt(Co)or Iron(Fe))have been *** catalytic effect of these complexes on the thermolysis of energetic composite based on nitrocellulose and diethylene glycol dinitrate,has been *** characterization of the resulting energetic composites was carried out using scanning electron microscopy(SEM),X-ray diffraction(XRD),Fourier transform infrared spectroscopy(FTIR),and differential scanning calorimetry(DSC).Isoconversional kinetic analysis was performed to determine the Arrhenius parameters associated with the thermolysis of the elaborated energetic *** is found that TAG-M complexes have strong catalytic effect on the thermo-kinetic decomposition of NC/DEGDN by decreasing the apparent activation energy and significantly increased the total heat *** models that govern the decomposition processes are also studied,and it is revealed that different reaction processes are accomplished by introduction metal complexes of ***,this study serves as a valuable reference for future research focused on the investigation of catalytic combustion features of solid propellants.

关键词： triaminoguanidine transition metal complexes nitrocellulose diethylene glycol dinitrate catalytic effect

Exploring public perception and willingness to pay for a renewable source of energy:evidence from an emerging economy of renewable-energy development

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Clean Energy 2024年第2期8卷 177-188页

作者： mohammed J.K.Bashir Senadjki Abdelhak Wael A.Salah Mai Abuhelwa School of Engineering&Technology Central Queensland University120 Spencer St.MelbourneQLD 3000Australia Faculty of Business and Finance Universiti Tunku Abdul RahmanKamparPerakMalaysia Department of Electrical Engineering College of Engineering and TechnologyPalestine Technical University-KadooriePO Box 7Yafa StreetTulkarmPalestine Department of Electrical Engineering and Computer Science University of MissouriColumbiaMO 65211USA

The study focuses on the transition from conventional energy sources to sustainable renewable energy(RE)in Palestine,particularly in the West Bank and Gaza *** research aims to understand the relationship between key factors and residents’willingness to invest in the RE sector,with a specific focus on the impact of *** the unified theory of acceptance and use of technology,the study analyzes data from 400 residents through a questionnaire and employs ordinary least-squares regression analysis with Eviews *** key findings indicate that residents’inclination to invest in RE is significantly influenced by factors such as resource availability,knowledge level and power ***,the study suggests that educated residents are more likely to invest in RE when factors such as knowledge,effort expectation,enabling conditions and resource availability are relatively *** conclusion emphasizes the importance of policymakers’allocating sufficient funds to research and development to promote technological innovation in RE sources,thereby enhancing the population’s energy efficiency.

关键词： renewable energy technology energy security public perceptions sustainable development

Chest Radiography: General Practitioners’ Compliance with Recommendations

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Open Journal of Medical Imaging 2024年第2期14卷 56-63页

作者： Milckisédek Judicaël Marouruana Some Aïda Ida Tankoano Pakisba ali Ouedraogo Bassirou Kindo Nina-Astrid Ouedraogo mohammed ali harchaoui Department of Medical Imaging The Ouahigouya Regional University Hospital University of Ouahigouya Ouahigouya Burkina Faso Department of Medical Imaging Souro Sanou University Hospital Nazi Boni University Bobo Dioulasso Burkina Faso Department of Medical Imaging Bogodogo University Hospital Joseph Ki Zerbo University Ouagadougou Burkina Faso Private Radiologist Lille France

Introduction: Chest radiography is the most frequently prescribed imaging test in general practice in France. We aimed to assess the extent to which general practitioners follow the recommendations of the French National Authority for health in prescribing chest radiography. Methodology: We conducted a retrospective analysis study, in two radiology centers belonging to the same group in Saint-Omer and Aire-sur-la-Lys, of requests for chest radiography sent by general practitioners over the winter period between December 22, 2013, and March 21, 2014, for patients aged over 18 years. Results: One hundred and seventy-seven requests for chest X-rays were analyzed, 71.75% of which complied with recommendations. The most frequent reason was the search for bronchopulmonary infection, accounting for 70.08% of prescriptions, followed by 11.2% for requests to rule out pulmonary neoplasia, whereas the latter reason did not comply with recommendations. Chest X-rays contributed to a positive diagnosis in 28.81% of cases. The positive diagnosis was given by 36.22% of the recommended chest X-rays, versus 10% for those not recommended. Conclusion: In most cases, general practitioners follow hAS recommendations for prescribing chest X-rays. Non-recommended chest X-rays do not appear to make a major contribution to diagnosis or patient management, confirming the value of following the recommendations of the French National Authority for health.

关键词： Chest X-Ray Recommendations General Practitioners Prescription

Results Involving Partial Differential Equations and Their Solution by Certain Integral Transform

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1593-1616页

作者： Rania Saadah mohammed Amleh Ahmad Qazza Shrideh Al-Omari Ahmet Ocak Akdemir Department of Mathematics Faculty of ScienceZarqa UniversityZarqa13110Jordan Department of Mathematics Faculty of ScienceAl-Balqa Applied UniversityAmman11134Jordan Department of Mathematics Faculty of Science and LettersAgri Ibrahim莈鏴n UniversityAgri04100Turkey

In this study,we aimto investigate certain triple integral transformand its application to a class of partial *** discuss various properties of the new transformincluding inversion, linearity, existence, scaling andshifting, etc. Then,we derive several results enfolding partial derivatives and establish amulti-convolution ***, we apply the aforementioned transform to some classical functions and many types of partial differentialequations involving heat equations,wave equations, Laplace equations, and Poisson equations ***,wedraw some figures to illustrate 3-D contour plots for exact solutions of some selected examples involving differentvalues in their variables.

关键词： ARA transform double ARA transform triple ARA transform partial differential equations integral transform

Terrorism Attack Classification Using Machine Learning: The Effectiveness of Using Textual Features Extracted from GTD Dataset

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1427-1467页

作者： mohammed Abdalsalam Chunlin Li Abdelghani Dahou Natalia Kryvinska School of Computer Science and Technology Wuhan University of TechnologyWuhan430070China LDDI Laboratory Faculty of Science and TechnologyUniversity of Ahmed DRAIAAdrar01000Algeria Information Systems Department Faculty of ManagementComenius UniversityBratislava82005Slovakia

One of the biggest dangers to society today is terrorism, where attacks have become one of the most significantrisks to international peace and national security. Big data, information analysis, and artificial intelligence (AI) havebecome the basis for making strategic decisions in many sensitive areas, such as fraud detection, risk management,medical diagnosis, and counter-terrorism. however, there is still a need to assess how terrorist attacks are related,initiated, and detected. For this purpose, we propose a novel framework for classifying and predicting terroristattacks. The proposed framework posits that neglected text attributes included in the Global Terrorism Database(GTD) can influence the accuracy of the model’s classification of terrorist attacks, where each part of the datacan provide vital information to enrich the ability of classifier learning. Each data point in a multiclass taxonomyhas one or more tags attached to it, referred as “related tags.” We applied machine learning classifiers to classifyterrorist attack incidents obtained from the GTD. A transformer-based technique called DistilBERT extracts andlearns contextual features from text attributes to acquiremore information from text data. The extracted contextualfeatures are combined with the “key features” of the dataset and used to perform the final classification. Thestudy explored different experimental setups with various classifiers to evaluate the model’s performance. Theexperimental results show that the proposed framework outperforms the latest techniques for classifying terroristattacks with an accuracy of 98.7% using a combined feature set and extreme gradient boosting classifier.

关键词： Artificial intelligence machine learning natural language processing data analytic DistilBERT feature extraction terrorism classification GTD dataset

Nodule Detection Using Local Binary Pattern Features to Enhance Diagnostic Decisions

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Computers, Materials & Continua 2024年第3期78卷 3377-3390页

作者： Umar Rashid Arfan Jaffar Muhammad Rashid mohammed S.Alshuhri Sheeraz Akram Faculty of Computer Science and Information Technology The Superior UniversityLahore54600Pakistan Intelligent Data Visual Computing Research(IDVCR) Lahore54600Pakistan Department of Computer Science National University of TechnologyIslamabad45000Pakistan Department of Radiological Sciences and Medical Imaging College of AppliedMedical SciencesPrince Sattam Bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia Information Systems Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh12571Saudi Arabia

Pulmonary nodules are small, round, or oval-shaped growths on the lungs. They can be benign (noncancerous) or malignant (cancerous). The size of a nodule can range from a few millimeters to a few centimeters in diameter. Nodules may be found during a chest X-ray or other imaging test for an unrelated health problem. In the proposed methodology pulmonary nodules can be classified into three stages. Firstly, a 2D histogram thresholding technique is used to identify volume segmentation. An ant colony optimization algorithm is used to determine the optimal threshold value. Secondly, geometrical features such as lines, arcs, extended arcs, and ellipses are used to detect oval shapes. Thirdly, histogram Oriented Surface Normal Vector (hOSNV) feature descriptors can be used to identify nodules of different sizes and shapes by using a scaled and rotation-invariant texture description. Smart nodule classification was performed with the XGBoost classifier. The results are tested and validated using the Lung Image Consortium Database (LICD). The proposed method has a sensitivity of 98.49% for nodules sized 3–30 mm.

关键词： Pulmonary nodules segmentation histogram thresholding

Chemically Radiative MhD Flow of a Micropolar Nanofluid over a Stretching/ Shrinking Sheet with a heat Source or Sink

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Fluid Dynamics & Materials Processing 2024年第2期20卷 257-274页

作者： Parakapali Roja Shaik mohammed Ibrahim Thummala Sankar Reddy Giulio Lorenzini Department of Mathematics Annamacharya Institute of Technology and SciencesKadapa516126India Department of Engineering Mathematics College of EngineeringKoneru Lakshmaiah Education FoundationVaddeswaram522302India Department of Mathematics Annamacharya Institute of Technology and SciencesKadapa516003India Department of Engineering and Architecture University of ParmaParma43124Italy

This study examines the behavior of a micropolar nanoﬂuidﬂowing over a sheet in the presence of a transverse magneticﬁeld and thermal *** addition,chemical(ﬁrst-order homogeneous)reactions are taken into account.A similarity transformation is used to reduce the system of governing coupled non-linear partial differ-ential equations(PDEs),which account for the transport of mass,momentum,angular momentum,energy and species,to a set of non-linear ordinary differential equations(ODEs).The Runge-Kutta method along with shoot-ing method is used to solve *** impact of several parameters is *** is shown that the micro-rota-tional velocity of theﬂuid rises with the micropolar ***,the radiation parameter can have a remarkable inﬂuence on theﬂow and temperature proﬁles and on the angular momentum distribution.

关键词： Chemical(ﬁrst order homogeneous)reaction magnetohydrodynamics micropolar nanoﬂuid stretching/shrinking sheet heat source

Enhancing IoT Data Security with Lightweight Blockchain and Okamoto Uchiyama homomorphic Encryption

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1731-1748页

作者： Mohanad A.mohammed hala B.Abdul Wahab Computer Science Department The University of TechnologyBaghdadIraq

Blockchain technology has garnered significant attention from global organizations and researchers due to its potential as a solution for centralized system ***,the Internet of Things(IoT)has revolutionized the Fourth Industrial Revolution by enabling interconnected devices to offer innovative services,ultimately enhancing human *** paper presents a new approach utilizing lightweight blockchain technology,effectively reducing the computational burden typically associated with conventional blockchain *** integrating this lightweight blockchain with IoT systems,substantial reductions in implementation time and computational complexity can be ***,the paper proposes the utilization of the Okamoto Uchiyama encryption algorithm,renowned for its homomorphic characteristics,to reinforce the privacy and security of IoT-generated *** integration of homomorphic encryption and blockchain technology establishes a secure and decentralized platformfor storing and analyzing sensitive data of the supply chain *** platformfacilitates the development of some business models and empowers decentralized applications to perform computations on encrypted data while maintaining data *** results validate the robust security of the proposed system,comparable to standard blockchain implementations,leveraging the distinctive homomorphic attributes of the Okamoto Uchiyama algorithm and the lightweight blockchain paradigm.

关键词： Blockchain IoT integration of IoT and blockchain consensus algorithm Okamoto Uchiyama homomorphic encryption lightweight blockchain