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HighTech and Innovation Journal 2024年第3期5卷 534-550页

作者： Aljabri, Malak Shaahid, Afrah Alnasser, Fatima Saleh, Asalah Alomari, Dorieh Aboulnour, Menna Al-Eidarous, Walla Althubaity, Areej Department of Computer and Network Engineering College of Computing Umm Al-Qura University Makkah21955 Saudi Arabia College of Computer Science and Information Technology Imam Abdulrahman Bin Faisal University P.O. Box 1982 Dammam31441 Saudi Arabia Depatment of Cybersecurity College of Computing Umm Al-Qura University Makkah21955 Saudi Arabia

In recent times, the growing significance of Internet of Things (IoT) devices in people's lives is undeniable, driven by their myriad benefits. However, these devices confront cybersecurity threats akin to traditional network devices, as they depend on networks for connectivity and synchronization. Artificial Intelligence (AI) techniques, specifically Machine Learning (ML) and Deep Learning (DL), have demonstrated notable reliability in the field of cyberattack detection. This study focuses on detecting Flood and Brute Force cyberattacks using Machine Learning (ML) and Deep Learning (DL) models. The primary emphasis lies in identifying traffic features that significantly detect these types of attacks. The experimental study incorporates eight models: Decision Tree (DT), K-Nearest Neighbor (KNN), Random Forest (RF), Support Vector Machines (SVM), Logistic Regression (LR), Gradient Boosting (GB), Naïve Bayes (NB), and Artificial Neural Network (ANN). Two sets of experiments were conducted, with the first set involving six features and the subsequent set, after feature selection, focusing on a reduced set of three features. The evaluation of the proposed model's efficiency and performance relied on metrics such as Accuracy, Precision, Recall, and F1-score. Remarkably, all proposed models exhibited high performance in both sets of experiments. However, the Gradient Boosting (GB) classifier suppressed others, attaining an impressive accuracy level of 95.94% and 95.28% in the sets with six features and three features, respectively. © 2024, Ital Publication. All rights reserved.

关键词： Support vector machines

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Sustainable energy management in the AI era: a comprehensive analysis of ML and DL approaches

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computing 2025年第6期107卷 1-64页

作者： Javed, Haseeb Eid, Fatma El-Sappagh, Shaker Abuhmed, Tamer Department of Computer Science and Engineering College of Computing and Informatics Sungkyunkwan University Suwon Korea Republic of Technology Management Stony Brook University NY11794 United States Applied Artificial Intelligence College of Computing and Informatics Sungkyunkwan University Suwon Korea Republic of Faculty of Computer Science and Engineering Galala University Suez435611 Egypt Information Systems Department Faculty of Computers and Artificial Intelligence Benha University Banha13518 Egypt

This study comprehensively analyzes the application of innovative deep learning (DL) and machine learning (ML) techniques in smart energy management systems (EMSs), with an emphasis on load forecasting, demand response, and the development of smart energy sectors. The application of various ML and DL models were examined in over 200 studies from 2014 to 2024 in an electrical network's EMS to highlight the key benefits and advances made by each technology for the sustainable management systems in energy sector. The findings emphasize DL and ML models’ enhanced precision and predictive capabilities in load forecasting, their efficacy in enabling efficient demand response mechanisms, and their significance in supporting the development of smart energy sectors. Furthermore, recommendations are made based on the survey results to assist in incorporating these techniques into EMS frameworks, such as investment in data infrastructure, model training and validation, and collaboration between researchers, industry experts, and policymakers. The study also discusses the limitations identified in the literature, such as limited real-world implementations, challenges regarding quality and data availability, and the need for enhanced ML and DL model interpretability. Addressing these limitations can assist in increasing the application and efficacy of ML and DL techniques in EMSs, enabling a more efficient and sustainable energy landscape. Finally, this study facilitates researchers' exploration of ML and DL in energy management, highlighting relevant limitations, strengths, and alternative approaches associated with sustainable energy management. It also indicates potential future research directions for further investigation. © The Author(s) 2025.

关键词： Power management (telecommunication)

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Efficient Uncertainty Quantification with Subspace Pursuit for FDTD Based Microwave Circuit Models

Efficient Uncertainty Quantification with Subspace Pursuit f...

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2024 Photonics and Electromagnetics Research Symposium, PIERS 2024

作者： An, Sicheng Qin, Hao Zhang, Xingqi University of Alberta Department of Electrical and Computer Engineering Edmonton Canada University College Dublin School of Electrical and Electronic Engineering Dublin Ireland

ISBN: (纸本)9798350375909

The polynomial chaos expansion (PCE) method has been employed to quantify the uncertainty of microwave structures, offering advantages over the conventionally used yet computationally burdensome Monte Carlo (MC) method. However, the computational cost experiences a significant increase with the number of input random variables, known as the "curse of dimensionality". In this paper, we applied a subspace pursuit algorithm to improve the computational efficiency of PCE, particularly within the domain of uncertainty analysis of finite-difference time-domain (FDTD) models of microwave circuits. The performance of the proposed approach is demonstrated by modeling a cascaded stub filter with 13 material and geometric parameters, showcasing a notable computational advantage. © 2024 IEEE.

关键词： Time domain analysis

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Navigation On Mobile computing Devices with A Walking Using Object-Oriented Techniques to Communicate Stick 3

Navigation On Mobile Computing Devices with A Walking Using ...

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3rd International Conference on Communication, Control, and Intelligent Systems, CCIS 2024

作者： Ramesh Prabhakaran, R. Guhan, P. Raj, E George Dharma Prakash Karthika, K. Angel Maanu, P. Mizoram University Department of Computer Engineering Mizoram India Panimalar Engineering College Department of Electrical and Electronical Engineering Chennai India Bharathidasan University School of Computer Science and Engineering Trichy India Karpagam College of Engineering Department of Information Technology Coimbatore India Panimalar Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798331528201

Moving around in their surroundings is challenging for elderly people and people with visual impairments. The majority of functional sticks in use today are not intelligent and lack an innate ability to recognize obstacles. In an effort to address this issue, mobility and orientation specialists who assist the blind by teaching them to move freely and safely using their remaining senses are brought in. They can navigate around obstacles with the aid of guidance dogs as well. These techniques have drawbacks, such as the dogs' inability to comprehend complicated instructions, the high cost of maintaining these trained dogs, and the need to hire an expert. In light of the aforementioned difficulties, the "Smart walking stick"has become a potential answer. The "Mobile based walking stick"is a useful mobility aid with the capacity to call a relative who can help in the event of an accident, detect obstacles above ground level and pits using ultrasonic sensors, recognize when a collision has occurred, and call the user's mobile phone if it has been misplaced to share the location's GPS for use with GSM connectivity and to share with the user's mention contacts. With some visually disabled people as test subjects, a test case was run, and 95% of the time it was successful. © 2024 IEEE.

关键词： Ultrasonic sensors

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Developing a novel battery management algorithm with energy budget calculation for low Earth orbit (LEO) spacecraft

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Aerospace Systems 2024年第1期7卷 143-157页

作者： Mokhtar, Mohamed Ahmed ElTohamy, H. Amer Fawzy Elhalwagy Yehia, Z. Mohamed, E. Hanafy Aircraft Electric Equipment Department Military Technical College Kobry Elkobbah Cairo12627 Egypt Electrical and Computer Engineering Military Technical College Kobry Elkobbah Cairo12627 Egypt

The electrical power system (EPS) of a spacecraft (SC) plays a crucial role in the mission's success. This system provides electrical power to all loads of SC until its end of life (EOL). The primary power source onboard for the SC is the solar array (SA), while the storage battery serves as the secondary power source. We have developed a software program called the SC Charging Analysis Tool with Battery Management Algorithm (BMA) to address the challenges associated with the SC battery's charging and discharging processes. This tool fulfills two main objectives: first, to develop a BMA that effectively controls the battery charging and discharging processes through all modes of SC operation;second, to create a battery management environment with SC energy budget calculation capabilities to simulate the dynamic behavior of the SC battery using the developed BMA, thereby ensuring battery health. The battery management environment is specifically designed to verify the proper performance of the battery throughout the SC's lifetime and to execute operations during nominal conditions and throughout worst-case scenarios. Moreover, through the SC energy budget calculation, we can optimize the requirements of the chosen scenario to fit with the selected battery. However, during worst-case scenarios, the battery's vital parameters, including state of charge (SOC), thermal emission, voltage, and pressure, are calculated to verify its proper operation under the developed BMA. The dynamic behavior of the battery, in conjunction with the developed algorithms, will be validated using real telemetry data. The key result of this paper is the invention of a BMA, which contributes to the advanced management of SC battery systems and, consequently, better durability during challenging operational scenarios. © Shanghai Jiao Tong University 2023.

关键词： Digital storage

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Ultrasensitive textile strain sensors redefine wearable silent speech interfaces with high machine learning efficiency

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npj Flexible Electronics 2024年第1期8卷 664-674页

作者： Chenyu Tang Muzi Xu Wentian Yi Zibo Zhang Edoardo Occhipinti Chaoqun Dong Dafydd Ravenscroft Sung-Min Jung Sanghyo Lee Shuo Gao Jong Min Kim Luigi Giuseppe Occhipinti Electrical Engineering Division Department of EngineeringUniversity of CambridgeCambridgeUK Department of Electronic and Electrical Engineering University College LondonLondonUK UKRI Centre for Doctoral Training in AI for Healthcare Department of ComputingImperial College LondonLondonUK School of Materials Science and Engineering Kumoh National Institute of Technology(KIT)GumiSouth Korea School of Instrumentation Science and Optoelectronic Engineering Beihang UniversityBeijingChina

This work introduces a silent speech interface(SSI),proposing a few-layer graphene(FLG)strain sensing mechanism based on thorough cracks and AI-based self-adaptation capabilities that overcome the limitations of state-of-the-art technologies by simultaneously achieving high accuracy,high computational efficiency,and fast decoding speed while maintaining excellent user *** demonstrate its application in a biocompatible textile-integrated ultrasensitive strain sensor embedded into a smart choker,which conforms to the user’s *** to the structure of ordered through cracks in the graphene-coated textile,the proposed strain gauge achieves a gauge factor of 317 with<5%strain,corresponding to a 420%improvement over existing textile strain sensors fabricated by printing and coating technologies reported to *** high sensitivity allows it to capture subtle throat movements,simplifying signal processing and enabling the use of a computationally efficient neural *** resulting neural network,based on a one-dimensional convolutional model,reduces computational load by 90%while maintaining a remarkable 95.25%accuracy in speech *** synergy in sensor design and neural network optimization offers a promising solution for practical,wearable SSI systems,paving the way for seamless,natural silent communication in diverse settings.

关键词： strain wear neural

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Joint trust-based detection and signature-based authentication technique for secure localization in underwater wireless sensor network

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Multimedia Tools and Applications 2025年 1-20页

作者： Kumar, Manni Goyal, Nitin Qaisi, Ramy Mohammed Aiesh Najim, Mohd Gupta, Sachin Kumar Department of Computer Science & Engineering Chandigarh University Gharuan Punjab India Department of Computer Science Engineering School of Engineering and Technology Central University of Haryana Haryana Mahendergarh123031 India Department of Electrical and Electronic Engineering College of Engineering University of Jeddah Jeddah21589 Saudi Arabia Department of Electronics and Communication Engineering Central University of Jammu UT of J&K Jammu181143 India

Ensuring secure and accurate node localization in Underwater Wireless Sensor Networks (UWSN) is a significant challenge, as conventional methods tend to neglect the security risks associated with malicious node interference. This research addresses this issue by proposing a Joint Trust-based Detection and Signature-based Authentication (JTDSA) technique, aimed at improving both the security and accuracy of node localization in UWSNs. The technique utilizes Intrusion Detection System (IDS) methods to calculate the trust values of secondary-anchor nodes (SNs), ensuring only the most trusted SNs are selected. Furthermore, a digital signature algorithm secures the Received Signal Strength (RSS) data from tampering. The method incorporates a hybrid approach combining Angle of Arrival (AoA) and RSS ranging techniques to achieve robust localization. Simulation results demonstrate that JTDSA improves localization accuracy by 4% compared to existing methods, achieving an overall accuracy of 99.2%. The technique also reduces packet drop by 35% and enhances attack detection accuracy by 3%. These results indicate that the proposed JTDSA technique offers an effective solution for secure and reliable localization in UWSNs. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Sensor nodes

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CRLB-based Data-driven Covariance Tuning for 5G KF Vehicular Tracking

CRLB-based Data-driven Covariance Tuning for 5G KF Vehicular...

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2024 IEEE Global Communications Conference, GLOBECOM 2024

作者： Bader, Qamar Saleh, Sharief Noureldin, Aboelmagd Chalmers University of Technology Department of Electrical Engineering Gothenburg Sweden Queen's University Department of Electrical and Computer Engineering KingstonON Canada Research Lab Gothenburg Sweden Royal Military College of Canada Department of Electrical and Computer Engineering KingstonON Canada

ISBN: (纸本)9798350351255

5G mmWave offers a high-precision positioning solution, functioning effectively in both line-of-sight (LoS) and operable non-line-of-sight (NLoS) conditions. However, in scenarios with complete signal blockage, integrating with motion-based models becomes crucial. This integration is achieved through Bayesian-based estimators, which entail a prediction and a correction stage weighted by their respective covariance matrices. Although covariance matrices of different prediction models have been extensively studied in the literature, the measurement covariance matrix derived from 5G-based position computations remains largely unexplored. In this paper, we propose a measurement covariance matrix tuning scheme based on a data-driven Cramér-Rao lower bound CRLB model. We validate the proposed algorithm within a simple linear Kalman filter (LKF) positioning framework. The methodology was tested in a controlled simulation scenario using a real 24-minute-long vehicular trajectory in a deep-urban environment. The results demonstrate that the developed data-driven model is reliable, maintaining a standard deviation error of less than 7 cm for 95% of the time and less than 0.5 m for 100% of the time relative to the true computed CRLB. The proposed adaptive KF sustains a position error below 30 cm for 99.3% of the time. © 2024 IEEE.

关键词： Kalman filters

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Robust graph‐based localization for industrial Internet of things in the presence of flipping ambiguities

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CAAI Transactions on Intelligence Technology 2023年第4期8卷 1140-1149页

作者： Mian Imtiaz ul Haq Ruhul Amin Khalil Muhannad Almutiry Ahmad Sawalmeh Tanveer Ahmad Nasir Saeed Faculty of Electrical Engineering Swedish College of Engineering and TechnologyWah CanttPakistan Department of Electrical Engineering Faculty of Electrical and Computer EngineeringUniversity of Engineering and TechnologyPeshawarPakistan Department of Electrical Engineering Remote Sensing UnitNorthern Border UniversityArarSaudi Arabia Data Science and Artificial Intelligence Department‐College of Science and Information Technology Irbid National UniversityIrbadJordan Innovation Education and Research Center for On‐Device AI Software(Bk21) Department of Computer Science and EngineeringChungnam National UniversityDaejeonRepublic of Korea Department of Electrical and Communication Engineering United Arab Emirates University(UAEU)Al AinUnited Arab Emirates

Localisation of machines in harsh Industrial Internet of Things(IIoT)environment is necessary for various ***,a novel localisation algorithm is proposed for noisy range measurements in IIoT *** position of an unknown machine device in the network is estimated using the relative distances between blind machines(BMs)and anchor machines(AMs).Moreover,a more practical and challenging scenario with the erroneous position of AM is considered,which brings additional uncertainty to the final position ***,the AMs selection algorithm for the localisation of BMs in the IIoT network is *** those AMs will participate in the localisation process,which increases the accuracy of the final location ***,the closed‐form expression of the proposed greedy successive anchorization process is derived,which prevents possible local convergence,reduces computation,and achieves Cramér‐Rao lower bound accuracy for white Gaussian measurement *** results are compared with the state‐of‐the‐art and verified through numerous simulations.

关键词： Cramér‐Rao lower bound greedy successive anchorization industrial internet of things localization

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A Model Driven Framework Enabling the Development of Standardized Text-Free User Interface for Smartphones 21

A Model Driven Framework Enabling the Development of Standar...

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21st International Bhurban Conference on Applied Sciences and Technology, IBCAST 2024

作者： Rasheed, Uzair Khalid, Sadia Mehmood, Rabia Ahmad, Muhammad Muneer, Mishal College of Electrical and Mechanical Engineering NUST Department of Computer and Software Engineering Islamabad Pakistan Lahore College for Women University Department of Computer Science Lahore Pakistan International Univesity of Rostock Department of Computer science Germany

ISBN: (纸本)9798331516680

Smartphones offer a wide range of applications globally, and usability is a key factor in their quality. Human-computer Interaction (HCI) continuously evolves to enhance usability by improving user interface (UI) components. However, most UI trends are designed for literate users, neglecting a significant portion of the population who cannot read or write. These users often rely on others for assistance with smartphone applications, and text-based UIs hinder their learning and usage, reducing overall usability. This research addresses the limitations of text-based standards by introducing a standardized framework for developing text-free user interfaces for smartphones. The framework utilizes static and dynamic images instead of text to convey widget or button functions, aiming to enhance usability for illiterate users, including preschoolers. Developed with Obeo Designer and Sirius, the framework's Platform Independent Metamodel (PIM) was validated through case studies representing the target user groups. Future work involves Model to Text (M2T) transformation, and results show the framework's potential for automating applications with text-free UIs. © 2024 IEEE.

关键词： Smartphones

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