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International IEEE Conference and Workshop: Óbuda on Electrical and Power engineering (CANDO-EPE)

作者： Imre Farkas Attila Kovari Mónika Rajcsanyi-Molnar Department of Computer Systems and Control Technology Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Institute of Digital Technology Faculty of Computer Science Eszterházy Károly Catholic University Eger Hungary Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Obuda University Budapest Hungary GAMF Faculty of Engineering and Computer Science John Von Neumann University Kecskemét Hungary Department of Economics and Management Institute of Social Sciences University of Dunaujvaros Dunaujvaros Hungary

ISBN: (数字)9798331531119

ISBN: (纸本)9798331531126

During the COVID19 epidemic, people of all ages from all walks of life around the world have become inevitably familiar with and almost dependent on the digital tools of the age and the opportunities they offer. A change had to take place very quickly that was unprecedented. This process has also affected education. During the time of the reading lock-in, there was a proliferation of digital curricular content. The second time around, online education came to the fore, thanks to less or well-functioning online platforms, and has since become part of everyday teaching. What is the effectiveness and usefulness of sharing knowledge in this way? Is literacy still needed at all? Can online and hybrid (a controlled mix of face-to-face and online) education replace the well-established contact and face-to-face education? The study show that the respondents believe that online education has had an impact on literacy and that it is perceived to have a positive impact. The results indicate that online education has a positive impact on the literacy levels of students, as it facilitates knowledge acquisition and enhances digital literacy skills.

关键词： Power engineering Epidemics Navigation Knowledge acquisition Digital transformation Education Information age Digital intelligence Cultural differences Problem-solving

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Real-Time Implementation of Quadrotor UAV control System Based on a Deep Reinforcement Learning Approach

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computers, Materials & Continua 2024年第12期81卷 4757-4786页

作者： Taha Yacine Trad Kheireddine Choutri Mohand Lagha Souham Meshoul Fouad Khenfri Raouf Fareh Hadil Shaiba Aeronautical Sciences Laboratory Aeronautical and Spatial Studies InstituteBlida 1 UniversityBlida0900Algeria Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Energy and Embedded Systems for Transportation Research Department ESTACA-LABMontigny-Le-Bretonneux78066France Department of Electrical Engineering University of SharjahSharjah27272United Arab Emirates Department of Computer Science College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia

The popularity of quadrotor Unmanned Aerial Vehicles(UAVs)stems from their simple propulsion systems and structural ***,their complex and nonlinear dynamic behavior presents a significant challenge for control,necessitating sophisticated algorithms to ensure stability and accuracy in *** strategies have been explored by researchers and control engineers,with learning-based methods like reinforcement learning,deep learning,and neural networks showing promise in enhancing the robustness and adaptability of quadrotor control *** paper investigates a Reinforcement Learning(RL)approach for both high and low-level quadrotor control systems,focusing on attitude stabilization and position tracking tasks.A novel reward function and actor-critic network structures are designed to stimulate high-order observable states,improving the agent’s understanding of the quadrotor’s dynamics and environmental *** address the challenge of RL hyper-parameter tuning,a new framework is introduced that combines Simulated Annealing(SA)with a reinforcement learning algorithm,specifically Simulated Annealing-Twin Delayed Deep Deterministic Policy Gradient(SA-TD3).This approach is evaluated for path-following and stabilization tasks through comparative assessments with two commonly used control methods:Backstepping and Sliding Mode control(SMC).While the implementation of the well-trained agents exhibited unexpected behavior during real-world testing,a reduced neural network used for altitude control was successfully implemented on a Parrot Mambo mini *** results showcase the potential of the proposed SA-TD3 framework for real-world applications,demonstrating improved stability and precision across various test scenarios and highlighting its feasibility for practical deployment.

关键词： Deep reinforcement learning hyper-parameters optimization path following quadrotor twin delayed deep deterministic policy gradient and simulated annealing

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Segmentation of butterflies from complex agro-ecological images using quantum mechanics and spatial refinement

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Digital Signal Processing: A Review Journal 2023年 135卷

作者： Filali, Idir Achour, Brahim Ramdani, Mohamed LARI laboratory Department of Computer Science Faculty of Electronic Engineering and Computer Science Mouloud Mammeri University Tizi-Ouzou15000 Algeria

The presence of butterflies is an important indicator of environmental health and stability. Its pollination ability increases agricultural yields. However, some butterflies may also cause crop degradation. Butterfly segmentation in complex agro-ecological environments is therefore a preliminary step whose accuracy affects species recognition. We propose in this paper a segmentation method composed of a sequence of three steps. First, we combine background connectivity with local distinctiveness measures to locate roughly butterfly areas. Second, we deploy an adaptation of the Schrödinger equation on a graph propagation process that checks regional similarities to those areas. Finally, we perform a spatial refinement that optimizes the butterfly detection. Both objective and subjective comparative experiments suggest that our method performs well against image artifacts. Obtained results outperform those of some state-of-the-art methods that reach high performance. © 2023 Elsevier Inc.

关键词： Quantum theory

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Emergency Vehicle Detection Using Deep ConvNet2D and computer Vision

Emergency Vehicle Detection Using Deep ConvNet2D and Compute...

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Emerging Trends in Information Technology and engineering (ic-ETITE), Conference on

作者： Elumalaivasan Poongavanam Prathik. A Munirathinam. T Kayalvizhi. V Rajesh. R Mahavishnu. C Department of Data Science and Business Systems SRM Institute of Science and Technology Kattankulathur Chennai India Department of Computer Science and Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai India Department of Information Technology Sona College of Technology Salem India School of Computer Science and Engineering and Information Science Presidency University Bangalore India School of Computer Science and Engineering Vellore Institute of Technology Chennai India Department of Computer Science and Engineering Shreenivasa Engineering College Dharmapuri India

A surveillance system detects emergency vehicles stuck in traffic. This system helps manage traffic because the number of vehicles on the road has been increasing daily for years, causing congestion. This project implements Deep ConvNet2D (Convolutional Network 2D) and computer Vision emergency vehicle recognition. We propose a CNN-based real-time image processing model for emergency vehicle detection. The signal control unit can be set to terminate the round robin sequence when an emergency vehicle is detected. A CNN trained on Indian ambulance images solves the problem. Tensor Flow, a Python library, was used for training. Our method detects and classifies emergency cars well. Existing systems use ANN algorithm, which is inaccurate and inefficient. The system uses Deep ConvNet2D Algorithm. The proposed real-time system is accurate. The proposed system loads and executes faster than the existing system. The system is efficient, scalable, and enhanced for complex use cases.

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Effective Anatomy Learning Using Markerless Augmented Reality Interface for Medical Education

Effective Anatomy Learning Using Markerless Augmented Realit...

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Advances in Data engineering and Intelligent Computing systems (ADICS), International Conference on

作者： S. Athinarayanan M. Masthan Saravanan Chandrasekaran V. Ashwin Ram Mahesh T R Vivek V Department of CSE School of Computing Vel Tech Rangarajan Dr Sagunthala R&D Institute of Science and Technology (Deemed to be University) Avadi Chennai India Arffy Technologies Private Limited Bengaluru Karnataka India Department of Computer Science and Engineering SRM Institute of Science and Technology Ramapuram Chennai Tamil Nadu Department of Computer Science and Engineering (AIML) SRM Institute of Science and Technology Ramapuram Chennai India Department of Computer Science & Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bengaluru Department of Computer Science & Engineering Faculty of Engineering and Technology JAIN (Deemed-to-be University) Bengaluru India

ISBN: (数字)9798350364828

ISBN: (纸本)9798350364835

Anatomy is a branch of biology dealing with the identification and explanation of living things body systems. Human anatomy is a significant chapter in every Biology class for secondary and post-secondary students. Traditional approaches and tools for studying human body anatomy include manuals with illustrations and images, as well as artificial anatomy mannequins. It isn't sufficient but and its miles tough to assist medical students to recognize it with actual and correct information and images approximately the anatomy of our human body. This is due to students' inability to visualize the actual configuration of human anatomy body parts and their lack of familiarity with 2D representations in textbooks. Furthermore, some students have difficulty interpreting 2D representations in textbooks, making it impossible for them to comprehend and gain information as quickly as possible in studying the layout of human anatomy body parts. Using Google AR Core and Unity3D, we proposed a system that builds a human anatomy learning android application that assists the medical students to visualize and analyze the Human Anatomy subject in an interactive way by using the Augmented Reality (AR) technique. The markerless AR approach is being used to create this scheme which uses the novel method to use the mobile computing platform as an alternative learning tool for studying the intricate structures of human body anatomy more practically and engagingly.

关键词： Human anatomy Image recognition Operating systems Layout Manuals Biology Internet

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Intelligent Energy Management Energy Storage systems Using Machine Learning

Intelligent Energy Management Energy Storage Systems Using M...

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Intelligent systems for Cybersecurity (ISCS), International Conference on

作者： Chinnaraj Govindasamy T.R Nisha Dayana Siddhika Dilip Adkar D. Shyam Prakash A. Shilpa Gupta Sanjeev Kumar Trivedi Department of Computer Science and Engineering Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai Tamilnadu India Department of Computer Science Vels Institute of Science Technology and Advance Studies Chennai School of Computer Science Engineering and Applications D Y Patil International University Akurdi Department of Computer Science and Business Systems Sri Eshwar College of Engineering Coimbatore Department of Electrical and Electronics Engineering Aurora's Technological Research Institute Uppal Hyderabad Department of Electronics Faculty of Engineering and Technology Khwaja Moinuddin chishti Language University Lucknow

ISBN: (数字)9798350375237

ISBN: (纸本)9798350375244

A nevertheless-emerging generation called cloud computing permits customers to pay for services on a usage-based foundation. Internet-primarily based IT offerings are supplied through cloud computing, at the same time as virtualization enables the availability of PC sources. The muse of cloud computing is the information center, which is made up of networked computers, cables, electricity components, and different components that host and shop corporate records. With cloud facts centers, high overall performance has continually been the most critical concern, yet it compromises strength utilization. The key hassle is to lessen power consumption at the same time as preserving provider nice and performance a good way to stability device performance and strength intake. A detailed grasp of strength use styles within the cloud environment is needed for our suggested technique. We look at power consumption tendencies and reveal how, through the use of the right optimization standards based on our strength intake models, we can keep more strength in cloud records facilities. All through the prediction section, tablet optimization, which has a 97 percent accuracy rate, permits this era to provide extra correct future price forecasts.

关键词： Performance evaluation Cloud computing Power demand Electricity Stability criteria Machine learning Load management

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A Trend Analysis of Test Smells in Python Test Code Over Commit History

A Trend Analysis of Test Smells in Python Test Code Over Com...

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Euromicro Conference on Software engineering and Advanced Applications (SEAA)

作者： Yuki Fushihara Hirohisa Aman Sousuke Amasaki Tomoyuki Yokogawa Minoru Kawahara Department of Computer Science Faculty of Engineering Ehime University Ehime Japan Center for Information Technology Ehime University Ehime Japan Faculty of Computer Science and Systems Engineering Okayama Prefectural University Okayama Japan

Software testing is an essential activity for developing and maintaining high-quality software. Unit testing with test code (test cases) is a fundamental testing activity, and developers can test their production code whenever they create or modify the code. However, such quality assurance relies on the correctness of the test code. If a test code had a flaw, it would mislead the developers about the hidden faults and prevent early detection of the faults. This paper focuses on "test smells," which may cause test code flaws in Python programs, and analyzes their changing trends over commit history (code changes) toward better Python test code management. Through an empirical data analysis of 100 open-source projects, the paper reports the following findings: (1) a few kinds of test smells constitute the majority of smells detected in the studied projects, and (2) most kinds of smells tend to increase over commits, i.e., many test smells are likely to have remained in test code as technical debt.

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Self-Configured Workflow Platform for MapReduce Job Execution in Cloud Environment

Self-Configured Workflow Platform for MapReduce Job Executio...

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2022 Applied Informatics International Conference, AiIC 2022

作者： Saadoon, Muntadher Admodisastro, Novia University of Malaya Faculty of Computer Science and Information Technology Department of Software Engineering Kuala Lumpur50603 Malaysia Universiti Putra Malaysia Faculty of Computer Science and Information Technology Selangor Serdang43400 Malaysia

ISBN: (数字)9781728184289

ISBN: (纸本)9781728184289

Hadoop MapReduce becomes the essential framework to store, process and analyse big data in large-scale computing environments. The framework provides numerous opportunities to handle data-intensive applications like web crawling and indexing, data mining, anomaly prediction and machine learning. However, manual configurations of the framework parameters expose to human errors and lead to performance overhead and resource consumption penalties. Existing deployment automation solutions intended to mitigate the limitations by only facilitating the application execution workflow without considering crucial conditions that violates the overall performance after setting up the infrastructure parameters. This paper proposes a self-configured workflow platform with a user-friendly collaborating environment that provides automated setups of the framework paraments to obtain ideal performance compared to the native deployment of Hadoop MapReduce. The self-configured workflow platform has been evaluated in experiments on a real Hadoop cloud-based cluster and the results shows that the execution times are comparable to the native application. © 2022 IEEE.

关键词： MapReduce

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An AOP-Based Security Verification Environment for KECCAK Hash Algorithm

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computers, Materials & Continua 2022年第11期73卷 4051-4066页

作者： Hassen Mestiri Imen Barraj Mohsen Machhout Department of Computer Engineering College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityAl-Kharj 11942Saudi Arabia Higher Institute of Applied Sciences and Technology of Sousse University of SousseTunisia Electronics and Micro-Electronics Laboratory Faculty of Sciences of MonastirUniversity of MonastirTunisia Electrical Engineering Department Systems Integration&Emerging Energies(SI2E)National Engineers School of SfaxUniversity of SfaxTunisia Higher Institute of Computer Science and Multimedia of Gabes University of GabesTunisia

Robustness of the electronic cryptographic devices against fault injection attacks is a great concern to ensure *** to significant resource constraints,these devices are limited in their *** increasing complexity of cryptographic devices necessitates the development of a fast simulation environment capable of performing security tests against fault injection *** is a good choice for Electronic System Level(ESL)modeling since it enables models to run at a faster *** enable fault injection and detection inside a SystemC cryptographic model,however,the model’s source code must be *** altering the source code,Aspect-Oriented Programming(AOP)may be used to evaluate the robustness of cryptographic *** might replace conventional cryptanalysis methods in the real *** the ESL,we discuss a unique technique for simulating security fault attacks on cryptographic *** current study presents a fault injection/detection environment for assessing the KECCAK SystemC model’s resistance against fault injection *** approach of injecting faults into KECCAK SystemC model is accomplished via the use of weaving faults in AspectC++based on AOP programming *** confirm our technique by applying it to two scenarios using a SystemC KECCAK hash algorithm case study:The first concerns discuss the effect of the AOP on fault detection capabilities,while the second concerns discuss the effect of the AOP on simulation time and executable file *** simulation results demonstrate that this technique is fully capable of evaluating the fault injection resistance of a KECCAK *** demonstrate that AOP has a negligible effect on simulation time and executable file size.

关键词： Aspect-Oriented Programming SystemC AspectC++ cryptographic circuits KECCAK fault detection fault attacks

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Design and Implementation of Blockchain-Based Smart Contracts for Enhancing Ancillary Services Management in Electricity Markets 10

Design and Implementation of Blockchain-Based Smart Contract...

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10th IEEE International Conference on Power and Energy, PECon 2024

作者： bt Junaidi, Nazreen Abdullah, Md Pauzi Shaaban, Mohamed Hashim, Nurul Izzati bt Abdullah, Johari B. Fazari, Atiq Firdaus bin Department of Electrical and Electronics Engineering University of Malaysia Sarawak Sarawak Kota Samarahan94300 Malaysia Faculty of Electrical Engineering University Teknologi Malaysia Johor Bharu Johor81310 UTM Malaysia Department of Electrical Engineering National Chung Cheng University Minxiong Chiayi621301 Taiwan Faculty of Computer Science and Information Technology University of Malaysia Sarawak Kota Sarawak Samarahan94300 Malaysia

ISBN: (纸本)9798350361971

This paper presents a possible solution to the challenges of managing ancillary services on power systems, focusing on the development and execution of robust smart contracts on the Ethereum blockchain. These contracts automate essential procedures like bid submission, Market Clearing Price (MCP) calculation, and settlement, reducing manual involvement and improving operational efficiency. They ensure transparency and accountability through security mechanisms like role-based access restriction and event monitoring. The contracts were created using Solidity programming language and implemented on the Ethereum Sepolia test network. Unit tests using Foundry confirmed the functionality of each contract component, indicating their accuracy and effectiveness. The study highlights the novel features of the smart contract architecture and its potential impact on ancillary service administration. ©2024 IEEE.

关键词： Smart contract

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