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New Frontiers in Communication, Automation, Management and Security (ICCAMS), International Conference on

作者： Haewon Byeon Ismail Keshta V. Mahalakshmi Mukesh Soni Ihtiram Raza Khan Ramya Maranan Department of Digital Anti-Aging Healthcare Inje University Gimhae Republic of Korea Computer Science and Information Systems Department College of Applied Sciences AlMaarefa University Riyadh Saudi Arabia Department of Computer Science College of Computer Science & Information Technology Jazan University Jazan Saudi Arabia Dr. D. Y. Patil Vidyapeeth Pune Dr. D. Y. Patil School of Science & Technology Tathawade Pune India Academician Jamia hamdard Delhi Department of Research and Innovation Saveetha School of Engineering SIMATS Chennai Tamil Nadu India

ISBN: (数字)9798350317060

ISBN: (纸本)9798350317077

This research paper presents a blockchain-based approach for fault detection and secure communication in vehicular ad hoc networks (VANETs). VANETs are an emerging technology that allows vehicles to communicate with each other and with the surrounding infrastructure to improve safety and efficiency on the roads. However, the decentralized and dynamic nature of VANETs makes them vulnerable to various types of attacks, including false data injection and communication interference. To address these challenges, the proposed approach utilizes blockchain technology to ensure the integrity and authenticity of data exchanged among vehicles and the infrastructure. The system also includes a fault detection mechanism that can detect and isolate faulty vehicles to prevent them from disrupting the communication network. However, VANETs are distinct from conventional mobile ad hoc networks due to the high mobility of vehicles, which creates dynamic network environments and frequent link interruptions that result in message loss. A hierarchical defect detection method based on dead reckoning is proposed to address these issues. The technique uses the dead reckoning model to predict the transmission time of pulse messages and builds a hierarchical detection architecture with Roadside Units (RSUs) functioning as static nodes. This architecture enhances the efficacy of VANET fault detection. The proposed method was validated by NS-2 simulations, demonstrating superior performance in terms of detection speed, accuracy, and detection burden compared to the baseline fault detection method.

关键词： Fault tolerance Dead reckoning Event detection Fault detection Fault tolerant systems Vehicular ad hoc networks Predictive models

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A Review Paper on Automatic Number Plate Recognition using Machine Learning : An In-Depth Analysis of Machine Learning Techniques in Automatic Number Plate Recognition: Opportunities and Limitations

A Review Paper on Automatic Number Plate Recognition using M...

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Computational Intelligence, Communication Technology and Networking (CICTN), International Conference on

作者： Rajat Kumar Prajapati Yatharth Bhardwaj Ritesh Kumar Jain Dr. Kamal Kant Hiran Department of Computer Science & Engineering Geetanjali Institute of Technical Studies Udaipur Rajasthan India CSE Geetanjali Institute of Technical Studies Udaipur Rajasthan India CSE Symbiosis University of Applied Sciences Indore Madhya Pradesh India

The recognition of license plates, known as Automatic Number Plate Recognition (ANPR), is an important topic in the fields of smart transportation systems and image recognition. ANPR has the potential to significantly improve traffic control and safety measures in urban areas. Its primary objective is to automatically detect and recognize the characters on vehicle license plates using modern technology and image processing techniques. With the rapid increase in the number of vehicles, ANPR has become a crucial tool for traffic control and management. In recent years, ANPR technology has advanced significantly, leading to the development of protocols such as OCR, which enables the recognition of license plate locations and allows traffic surveillance to address various issues, such as criminal investigations, toll collection, speed control, and parking management. ANPR systems play a vital role in traffic control and surveillance, and several systems have been developed to recognize license plates, each with its specific advantages. The key steps involved in an ANPR system are the precise localization of the number plate, segmentation, and recognition. This paper presents an efficient and layout-independent ANPR system that can accurately detect and recognize license plates, thus enhancing traffic control and surveillance measures.

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Phase-field modeling and effective simulation of non-isothermal reactive transport

arXiv

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arXiv 2023年

作者： Bringedal, Carina Jaust, Alexander Department of Computer science Electrical engineering and Mathematical sciences Western Norway University of Applied Sciences Norway Institute for Modelling Hydraulic and Environmental Systems University of Stuttgart Germany Institute for Parallel and Distributed Systems University of Stuttgart Germany

We consider single-phase flow with solute transport where ions in the fluid can precipitate and form a mineral, and where the mineral can dissolve and release solute into the fluid. Such a setting includes an evolving interface between fluid and mineral. We approximate the evolving interface with a diffuse interface, which is modeled with an Allen-Cahn equation. We also include effects from temperature such that the reaction rate can depend on temperature, and allow heat conduction through fluid and mineral. As Allen-Cahn is generally not conservative due to curvature-driven motion, we include a reformulation that is conservative. This reformulation includes a non-local term which makes the use of standard Newton iterations for solving the resulting non-linear system of equations very slow. We instead apply L-scheme iterations, which can be proven to converge for any starting guess, although giving only linear convergence. The three coupled equations for diffuse interface, solute transport and heat transport are solved via an iterative coupling scheme. This allows the three equations to be solved more efficiently compared to a monolithic scheme, and only few iterations are needed for high accuracy. Through numerical experiments we highlight the usefulness and efficiency of the suggested numerical scheme and the applicability of the resulting *** Codes 35R37, 65M08, 65M22, 76D10, 76D05, 76V05, 80A32, 80M12 © 2023, CC BY.

关键词： Minerals

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H-Packer: Holographic Rotationally Equivariant Convolutional Neural Network for Protein Side-Chain Packing

arXiv

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arXiv 2023年

作者： Visani, Gian Marco Galvin, William Pun, Michael N. Nourmohammad, Armita Paul G. Allen School of Computer Science and Engineering University of Washington United States Department of Physics University of Washington United States Department of Applied Mathematics University of Washington United States Fred Hutch Cancer Research Center SeattleWA United States

Accurately modeling protein 3D structure is essential for the design of functional proteins. An important sub-task of structure modeling is protein side-chain packing: predicting the conformation of side-chains (rotamers) given the protein's backbone structure and amino-acid sequence. Conventional approaches for this task rely on expensive sampling procedures over hand-crafted energy functions and rotamer libraries. Recently, several deep learning methods have been developed to tackle the problem in a data-driven way, albeit with vastly different formulations (from image-to-image translation to directly predicting atomic coordinates). Here, we frame the problem as a joint regression over the side-chains' true degrees of freedom: the dihedral χ angles. We carefully study possible objective functions for this task, while accounting for the underlying symmetries of the task. We propose Holographic Packer (H-Packer), a novel two-stage algorithm for side-chain packing built on top of two light-weight rotationally equivariant neural networks. We evaluate our method on CASP13 and CASP14 targets. H-Packer is computationally efficient and shows favorable performance against conventional physics-based algorithms and is competitive against alternative deep learning solutions. © 2023, CC BY.

关键词： Degrees of freedom (mechanics)

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The UbiLAB Framework for Remote Laboratories

The UbiLAB Framework for Remote Laboratories

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International Conference on Systems, Signals and Image Processing, IWSSIP

作者： Marija Kalendar Zivko Kokolanski Branislav Gerazov Gorjan Nadzinski Marija Poposka Aleksandra Zlatkova Filip Donchevski Marija Markovska Anastasiia Sapeha Kirill Karpov Danijela Efnusheva Dusan Gleich Andrej Sarjas Blaz Pongrac Eduard Siemens Faculty of Electrical Engineering and Information Technologies Ss Cyril and Methodius University Skopje R. N. Macedonia Department of Electrical Mechanical and Industrial Engineering Anhalt University of Applied Sciences Köthen Germany Faculty of Electrical Engineering and Computer Science University of Maribor Maribor Slovenia

Starting from the period of the Covid-19 pandemic, when the presence of students in the university laboratories was very limited, the research work on remote laboratories significantly increased. The most affected aspect of students’ study experience at that time were the laboratory experiments intended to be conducted on-premises, in the university laboratories. The UbiLAB framework was envisioned as a digital space for implementing and conducting laboratory work and experiments that are rarely completely transferred into the digital world. Here we have identified two most difficult challenges: achieving a nearly realistic substitute for learning experiences in the actual physical laboratories, and a nearly realistic substitute for the social element of collaborative learning and “making friends” in the process. The innovative cloud-based UbiLAB framework addresses both challenges, digitizing various and diverse actual laboratory experiments through a simple and widely available platform, while enhancing the reality of students’ experience in the process.

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Deep Feature Extraction Framework Based on DNN for Enhancing Mirai Attachment Classification in Machine Learning

Deep Feature Extraction Framework Based on DNN for Enhancing...

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Electrical, Energy, and Artificial Intelligence (EICEEAI), International engineering Conference on

作者： Hasan Gharaibeh Mohammad Aljaidi Ahmad Nasayreh Qais Al-Na'amneh Ameera S. Jaradat Ghassan Samara Rabia Emhamed Al Mamlook Dep. Computer Science Yarmouk University Irbid Jordan Dep. of Computer Science Zarqa University Zarqa Jordan Dep. of Cyber Security Applied Science Private University Amman Jordan Dep. of Business Administration Trine University Indiana USA Department of Mechanical and Industrial Engineering University of Zawia Tripoli Libia

ISBN: (数字)9798350373363

ISBN: (纸本)9798350373370

Nowadays, the rapid growth of Internet of Things (IoT) devices has changed many parts of our lives by providing seamless connectivity and automation. However, this expansion has created new challenges and vulnerabilities, especially with regard to security. Mirai botnet, a strain of malware that has severely damaged the IoT ecosystem, is one of the prominent risks to IoT security. This research examines the impact of the Mirai botnet on IoT devices. In this study, we present a hybrid model to detect Mirai attacks. Deep neural networks (DNNs) are used to extract significant deep features, which are subsequently passed to the (Light Gradient Boosting Machine) LGBM algorithm for classification. A dataset from the Canadian Institute 2023 that included several kinds of Internet of Things assaults was used to assess the model. The model achieved excellent feature extraction and promising results with accuracy, recall, precision, and F1-score scoring up to 95 % for all. These accuracy results demonstrated the superior performance of the suggested model over competing techniques, which had scores of 71 %, 85%, and 52%, respectively, for Support Vector Machine (SVM), Light Gradient Boosting Machine (LGBM), and Stochastic Gradient Descent (SGD). Furthermore, the model outperforms the DNN model, which received a score of 65%.

关键词： Support vector machines Accuracy Machine learning algorithms Botnet Artificial neural networks Feature extraction Boosting

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Microgravity analysis of periodic oscillations of heat and mass transfer of Darcy-Forchheimer nanofluid along radiating stretching surface with Joule heating effects

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Results in Physics 2024年 62卷

作者： Ullah, Zia El-Zahar, Essam. R. Seddek, Laila F. Eladeb, Aboulbaba Kolsi, Lioua Alsharari, Abdulrhman M. Asad, Jihad Akgül, Ali Department of Mathematics and Statistics The University of Lahore Sargodha-Campus Sargodha 40100 Pakistan Department of Mathematics College of Science and Humanities in Al-Kharj Prince Sattam Bin Abdulaziz University P.O. Box 83 Al-Kharj 11942 Saudi Arabia Department of Basic Engineering Science Faculty of Engineering Menoufia University Shebin El-Kom 32511 Egypt Department of Engineering Mathematics and Physics Faculty of Engineering Zagazig University Zagazig 44519 Egypt Department of Chemical and Materials Engineering College of Engineering Northern Border University P.O. Box 1321 Arar Saudi Arabia Department of Mechanical Engineering College of Engineering University of Ha'il Ha'il City Saudi Arabia Department of Physics University of Tabuk Tabuk 71491 Saudi Arabia Department of Physics Faculty of Applied Science Palestine Technical University Tulkarm P Kadoorie 305 Palestine Department of Computer Science and Mathematics Lebanese American University Beirut Lebanon Siirt University Art and Science Faculty Department of Mathematics Siirt 56100 Turkey

Reduced gravity impact on mixed convection flow plays a significant role for designing of electric-generating plants in space, unwanted effects of free convection, thermodynamic stability, space devices, surface tension and movement of nanoparticles. The novelty of present work is to find the impact of reduced gravity, Joule heating and thermal radiations on Darcy Forchheimer magnetized flow of nanofluid along the stretching porous sheet. The variable gravity is assumed as temperature dependent with maximum density and maximum density. The governing model is converted into convenient model to find physical thermo parameters. The primitive steady, real and imaginary equations are formed by using stokes and primitive transformations. To make programming algorithm in FORTRAN Lahey-90/95, the primitively terms are deduced in each equation. For tabular and numerical findings of steady velocity, temperature and concentration, the implicit form of finite difference approach is applied with Gaussian elimination method. The fluctuating skin friction, fluctuating heat transfer and fluctuating mass transfer are displayed by using steady outcomes in main formula. It is found that the magnitude of fluid velocity enhances as magnetic force, reduced gravity and Darcy Forchheimer parameter enhances. It is concluded that temperature distribution decreases as magnetic force enhances. It is noted that oscillating frequency in skin friction and heat transfer enhances as Schmidt number enhances. It is found that the maximum fluctuating layer in heat and mass transfer enhances as Prandtl number enhances. © 2024 The Author(s)

关键词： Darcy Forchheimer porous medium Heat and mass transfer Joule heating Magnetic field Microgravity Oscillatory flow Thermal radiations

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Ultrasonic Smart Stick Vision-Based EyeTech Digital System for Movement Tracking

Ultrasonic Smart Stick Vision-Based EyeTech Digital System f...

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International RF and Microwave Conference, RFM

作者： Khadega Ahmed Mohammed Gubran Muna Rabea Salim Hanien Mohammed Salem Farag BinWahlan Samir Salem Al-Bawri Computer Science Department College of Applied Sciences Seiyun University Hadhramout Yemen Space Science Centre Institute of Climate Change University Kebangsaan Malaysia (UKM) Bangi Malaysia Department of Electronics & Communication Engineering Faculty of Engineering & Petroleum Hadhramout University Yemen

There is no doubt that contemporary technology is the main engine of society's acceleration of growth and progress worldwide. It has become tactile for everything that people do daily. The smart stick approach is highly needed in the special needs group to help the blind and visually impaired on movement and mobility easily surround their environment. This paper uses a group of sensors and Arduino-Mega microcontroller to receive, process and analysis RF signals and issue an alert in a voice message that distinguishes the type of obstacles for the blind. This approach uses ultrasonic sensors to detect obstacles and constraints in the way of the blind and differentiate whether they are small in size and can be bypassed or a significant obstacle which highly required to change the direction directly. The proposed stick sensors also recognize the water puddles on the blind way. Moreover, the system contains a remote control and IR receiver to help the blind in case it falls or is lost in the surround of him, the stick is equipped with an RTC module to help the blind know the time anywhere easily by clicking on the remote control. In this project, we seek to provide an affordable lightweight, and easy-to-use this smart stick that serves the blind and helps them to move from one place to another.

关键词： Radio frequency Technological innovation Tracking Microcontrollers RF signals Prototypes Receivers

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Stability of Vibrations of a Complex Mechanical Oscillator Moving Along a Three-Part Rail System

SSRN

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SSRN 2023年

作者： Stojanović, Vladimir Deng, Jian Petković, Marko D. Milić, Dunja Department of Engineering Lakehead University Thunder BayONP7B 5E1 Canada Department of Theoretical and Applied Mechanics Faculty of Mechanical Engineering University of Niš A. Medvedeva 14 Niš18000 Serbia Department of Computer Science Faculty of Sciences and Mathematics University of Niš Višegradska 33 Niš18000 Serbia

The paper investigates the dynamic behavior and stability of vibrations of a complexly coupled mechanical oscillator that moves on an endlessly long continuous beam-foundation system. The beam-foundation system comprises three parts. The system can become unstable due to the elastic waves, which are generated by the moving of the complex discrete oscillator. The varying stiffness of the primary suspension and its asymmetricity present the novelty in the model which is deeply analyzed. The study is complemented with parametric analysis. mathematical description of the present model that represents the complex moving oscillator system contains involved expressions, to handle them the D-decomposition method and the argument principle which are used. Here, the model that represents the complex moving oscillator has two rows of suspension—the primary and the secondary suspension. The bogies’ supports are composed of wheels with primary suspension elements. The intervals of instability are determined for varying stiffness moduli of the primary suspension, the emphasis is put on the case with a nontraditional suspension (asymmetric—stiffness moduli of the primary suspension elements have diverse values among each other) that poses local stability benefits. © 2023, The Authors. All rights reserved.

关键词： Elastic waves

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Revealing the proton slingshot mechanism in solid acid electrolytes through machine learning molecular dynamics

arXiv

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arXiv 2025年

作者： Wang, Menghang Ding, Jingxuan Xiong, Grace Zhan, Ni Owen, Cameron J. Musaelian, Albert Xie, Yu Molinari, Nicola Adams, Ryan P. Haile, Sossina Kozinsky, Boris Harvard John A. Paulson School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States Materials Science and Engineering Northwestern University EvanstonIL60208 United States Department of Computer Science Princeton University PrincetonNJ08544 United States Department of Chemistry and Chemical Biology Harvard University CambridgeMA02138 United States Robert Bosch Research and Technology Center WatertownMA02472 United States

In solid acid solid electrolytes CsH2PO4 and CsHSO4, mechanisms of fast proton conduction have long been debated and attributed to either local proton hopping or polyanion rotation. However, the precise role of polyanion rotation and its interplay with proton hopping remained unclear. Nanosecond-scale molecular dynamics simulations, driven by equivariant neural network force fields, reveal a nuanced proton slingshot mechanism: protons are initially carried by rotating polyanions, followed by O−H bond reorientation, and the combined motion enables long-range jumps. This challenges the conventional revolving paddlewheel model and reveals significant independent proton motion that is assisted by limited rotations. Despite structural similarities, we identify qualitative differences in transport mechanisms between CsH2PO4 and CsHSO4, caused by different proton concentrations. CsH2PO4 exhibits two distinct rates of rotational motions with different activation energies, contrasting with CsHSO4’s single-rate behavior. The higher proton concentration in CsH2PO4 correlates with frustrated PO4 polyanion orientations and slower rotations compared to SO4 in CsHSO4. Additionally, we reveal a correlation between O-sharing and proton transport in CsH2PO4, a unique feature due to extra proton per polyanion compared to CsHSO4. Our findings suggest that reducing proton concentration could accelerate rotations and enhance conductivity. This work provides a unified framework for understanding and optimizing ionic mobility in solid-acid compounds, offering new insights into the interplay between proton hopping and disordered dynamics in polyanion rotation. Copyright © 2025, The Authors. All rights reserved.

关键词： Activation energy

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