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Maximizing Harvested Energy in Natural Energy Powered RF WPT with Nonlinear EH Model

IEEE Transactions on Wireless Communications 2025年

作者： Zhang, Xiang Xiong, Ke Chen, Wei Fan, Pingyi Gao, Bo Letaief, Khaled Ben Collaborative Innovation Center of Railway Traffic Safety School of Computer Science and Technology Engineering Research Center of Network Management Technology for High Speed Railway Ministry of Education China Beijing Jiaotong University National Engineering Research Center of Advanced Network Technologies Beijing100044 China Department of Electronic Engineering China Tsinghua University Beijing National Research Center for Information Science and Technology Beijing100084 China Department of Electrical and Computer Engineering Hong Kong Hong Kong

In the typical radio frequency (RF)-based wireless power transfer (WPT) system, the wireless power station (WPS) connected to the grid transmits energy to charge low-power sensors via radio signals. Such a system may not be green and also difficult to deploy in some special areas including deserts and mountainous areas, because it depends on the grid. To achieve a green RF WPT system design, this paper considers that the WPS is powered by natural energy sources rather than the grid. To explore the maximal total amount of the energy that can be harvested by the sensors, we focus on the offline setting, so similar to many existing works on offline optimization, we assume that the WPS knows prior knowledge about energy arrivals and channel changes, and then formulate an optimization problem to maximize the total harvested energy via optimizing the WPS's time-domain transmit power subject to multiple constraints, including the finite battery capacity at the WPS, the causal relationship between the natural energy harvesting and the WPT, and the transmit power budget of the WPS, where for practicality, the nonlinear energy harvesting (EH) model is also taken into account. To solve this non-convex problem, we first equivalently transform it by using the epigraph reformulation and the variable substitution, and then use the first-order Taylor expansion to get an approximate convex version. Then, we present a successive convex approximation (SCA)-based algorithm to improve the accuracy of the obtained solution for approaching the optimal one. For the special case with a single sensor, we further propose a branch and bound (BB)-based algorithm that is able to get a more accurate solution with lower complexity than the SCA-based one. Numerical results demonstrate that the proposed algorithms are able to achieve the near-global optimal solution. As the average recharge rate increases, compared with the other two baselines, i.e., the greedy power (GP) policy and the constant pow

关键词： Budget control

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Handling Imbalanced Data for Credit Card Fraudulent Detection: A Machine Learning Approach 1st

Handling Imbalanced Data for Credit Card Fraudulent Detectio...

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1st International Conference on Advances in Artificial Intelligence and Machine Learning in Big Data Processing, AAIMB 2023

作者： Sujatha, E. Umarani, V. Rekha, K.S. Gopirajan, P.V. Manickavasagan, V. Sriperumbudur India Department of Computational Intelligence SRM Institute of Science and Technology Chennai India Department of Computer Science and Business Systems Sri Sairam Engineering College Chennai India

ISBN: (纸本)9783031730672

Imbalanced data is crucial for contemporary machine learning models. Evaluating the effectiveness of machine learning classifiers under an unfair dataset is problematic. Several resampling techniques were applied to the unwarranted dataset and pre-processing stages to increase the accuracy of prognosis classifiers. This proposed work discusses the basics of resampling techniques such as Random under-sampling, Random oversampling, SMOTE (Synthetic Minority Over-sampling Technique), SMOTE-ENN (Synthetic minority over-sampling technique and Edited nearest neighbor), ADASYN (Adaptive Synthetic), and SMOTE-Tomek to handle this Weakness with unbalanced data. The proposed system uses an unstable credit card fraudulent dataset collected from Kaggle, which contains 21 columns and 28382 rows, of which 18497 negative samples and 4208 positive samples. The balanced dataset got by applying resampling methods SMOTE, SMOTE-ENN, ADASYN, and SMOTE-Tomek. Afterward, it uses machine learning techniques such as Logistic Regression (LR), Decision tree (DT), and Random Forest (RF) for classification. From this analysis, it selects the optimal scheme and classifier. The grey wolf optimization technique improves the classifier’s performance, which optimizes the samples after sampling. This hybrid method’s effectiveness was evaluated with standard evaluation parameters. The hybrid Random Forest technique achieved 92% accuracy from this analysis compared to hybrid models. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Adversarial machine learning

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Self-Supervised Enhancement of Forward-Looking Sonar Images: Bridging Cross-Modal Degradation Gaps through Feature Space Transformation and Multi-Frame Fusion

arXiv

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arXiv 2025年

作者： Zhang, Zhisheng Zhang, Peng Wang, Fengxiang Ma, Liangli Sun, Fuchun College of Electronic Engineering Naval University of Engineering Wuhan430033 China College of Meteorology and Oceanography National University of Defense Technology Changsha410073 China College of Computer Science and Technology National University of Defense Technology Changsha410073 China Department of Computer Science and Technology Tsinghua University Beijing100084 China

Enhancing forward-looking sonar images is critical for accurate underwater target detection. Current deep learning methods mainly rely on supervised training with simulated data, but the difficulty in obtaining high-quality real-world paired data limits their practical use and generalization. Although self-supervised approaches from remote sensing partially alleviate data shortages, they neglect the cross-modal degradation gap between sonar and remote sensing images. Directly transferring pretrained weights often leads to overly smooth sonar images, detail loss, and insufficient brightness. To address this, we propose a feature-space transformation that maps sonar images from the pixel domain to a robust feature domain, effectively bridging the degradation gap. Additionally, our self-supervised multi-frame fusion strategy leverages complementary inter-frame information to naturally remove speckle noise and enhance target-region brightness. Experiments on three self-collected real-world forward-looking sonar datasets show that our method significantly outperforms existing approaches, effectively suppressing noise, preserving detailed edges, and substantially improving brightness, demonstrating strong potential for underwater target detection applications. © 2025, CC BY.

关键词： Underwater acoustics

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Parallel fault diagnosis using hierarchical fuzzy Petri net by reversible and dynamic decomposition mechanism

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Frontiers of Information technology & Electronic engineering 2025年第1期26卷 93-108页

作者： Yinhong XIANG Kaiqing ZHOU Arezoo SARKHEYLI-HÄGELE Yusliza YUSOFF Diwen KANG Azlan Mohd ZAIN School of Communication and Electronics Engineering Jishou UniversityJishou 416000China Internet of Things and People Research Center Department of Computer Science and Media TechnologyMalmöUniversityMalmö20506Sweden Faculty of Computing Universiti Teknologi MalaysiaSkudai 81310Malaysia

The state space explosion,a challenge analogous to that encountered in a Petri net(PN),has constrained the extensivestudy of fuzzy Petri nets(FPNs).Current reasoning algorithms employing FPNs,which operate through forward,backward,andbidirectional mechanisms,are *** algorithms streamline the inference process by eliminating irrelevant componentsof the ***,as the scale of the FPN grows,the complexity of these algorithms escalates sharply,posing a significantchallenge for practical *** address the state explosion issue,this work introduces a parallel bidirectional reasoningalgorithm for an FPN that utilizes reverse and decomposition strategies to optimize the implementation *** algorithminvolves hierarchically dividing a large-scale FPN into two sub-FPNs,followed by a converse operation to generate the reversalsub-FPN for the *** detailed mapping between the original and reversed FPNs is thoroughly *** operations are then conducted on the left-sub-FPN and the resulting reversal right-sub-FPN,with the final resultderived by computing the Euclidean distance between the outcomes from the output places of the two sub-FPNs.A case study ispresented to illustrate the implementation process,demonstrating the algorithm’s significant enhancement of inference efficiencyand substantial reduction in execution time.

关键词： Fuzzy Petri net(FPN) State explosion Decomposition Parallel Bidirectional reasoning

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A Study on Impact-Aware Aerial Robots Colliding with the Environment at Non-Vanishing Speed

A Study on Impact-Aware Aerial Robots Colliding with the Env...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Gayatri Indukumar Alessandro Saccon Antonio Franchi Chiara Gabellieri Robotics and Mechatronics Department Electrical Engineering Mathematics and Computer Science (EEMCS) Faculty University of Twente Enschede The Netherlands Department of Mechanical Engineering Eindhoven University of Technology Eindhoven The Netherlands Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

Enabling aerial robots to handle dynamic contacts happening at non-vanishing speeds can enlarge the range of their applications. In this work, we propose an impactaware strategy to allow aerial multirotor robots to recover from impacts. The method leverages a reactive strategy not requiring low-level changes to the motion controller commonly implemented onboard quadrotors, which might be not viable or not desirable for most users. Extensive simulation tests show that the proposed strategy considerably increases the tolerated velocity at impact in tasks in which the robot either picks an object up or collides against an object to clear its way. Preliminary experimental results using Crazyflie UAVs are also presented.

关键词： Trajectory tracking Dynamics Lead Autonomous aerial vehicles Stability analysis Robustness computer crashes Trajectory Robots Quadrotors

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Machine Learning Techniques for Enhancing Security in Wireless Communication Systems

Machine Learning Techniques for Enhancing Security in Wirele...

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Pervasive Computational Technologies (ICPCT), International Conference on

作者： S. Surya Rajshri Trimbak Ingle Megha Saxena Jaipal Reddy Poddutoori Dr. Budesh Kanwer Dhiraj Kapila Sri Ramachandra Faculty of Engineering & Technology(SRET) Sri Ramachandra Institute of Higher Education & Research Porur Chennai DY Patil College of Engineering Akurdi Pune Maharashtra Department of Computer Science & Engineering SRM Institute of Science & Technology Ghaziabad UP Solution Architect Affiliation BBU Downingtown PA United States Poornima Institute of Engineering and Technology Jaipur Rajasthan Department of Computer Science & Engineering Lovely Professional University Phagwara Punjab India

ISBN: (数字)9798331508685

ISBN: (纸本)9798331519476

Web of Things or IoT frameworks rely upon wireless communication systems or WCS to accumulate and send measurements, their norm of execution is in danger from security assaults. In IoT frameworks, the Steering Conventions that can be routing protocols for Lower-Power (RPL) and Misfortune Systems administration are fundamental for successful measurements move; in any case, attacks can seriously disable usefulness. Utilizing the change of steering insights, traffic fascination through maverick focuses, and information passages to destructive places, these weaknesses compromise the legitimacy of organizations. To work on RPL's security and execution quality, this examination proposes a progressive AI and ML framework. This strategy joins a support learning calculation for adaptable and versatile highways, an irregular timberland framework for exact traffic classification, and modified RPL goals that consider order results while pursuing directing decisions. Displaying shows that this approach keeps up with negligible jitter while accomplishing extensive enhancements in bundle dispersion extents, network speed, and deferral. Also, it further develops execution quality in IoT-based WCS and solidly gets the RPL convention by accomplishing an extraordinary acknowledgment rate, scarcely any misleading up-sides, and speedy responses to somewhere safe occasions. The study's conclusions provide significant additions to the area and give a thorough way to safeguard RPL against common safety risks

关键词： Wireless communication Road transportation Optical wavelength conversion Reinforcement learning Organizations Routing protocols Safety Security Motion measurement Random forests

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How Large Language Models are Transforming Teachers' Assessment of Student Competency: A Case Study on LLM-Based Report Writing

How Large Language Models are Transforming Teachers' Assessm...

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International Conference on Electronics, Information and Communications (ICEIC)

作者： Dongyub Lee Daejung Kim Martin Loeser Kyoungwon Seo Department of Applied Artificial Intelligence Seoul National University of Science and Technology Seoul Republic of Korea Department of Environmental Engineering Seoul National University of Science and Technology Seoul Republic of Korea Department of Computer Science Electrical Engineering and Mechatronics ZHAW Zurich University of Applied Sciences Winterthur Switzerland

ISBN: (数字)9798331510756

ISBN: (纸本)9798331510763

Evaluating student competencies is critical to fostering academic success, but the traditional process of assessment and report generation is time-consuming and labor-intensive for teachers. The emergence of Large Language Models (LLMs) presents an opportunity to automate this process, potentially reducing the workload for educators. However, concerns such as hallucinations in LLM outputs and the lack of usability studies involving teachers raise questions about their reliability and practical application. In response, we developed an LLM-based report writing system specifically designed for real-time competency evaluation. To assess its effectiveness, we conducted a case study involving five educational experts, each with over 15 years of experience. These experts used the system to generate student competency reports and found them to be both sensible and specific. While they expressed concerns about issues like insufficient detail, they recognized the system's significant time-saving benefits. Our findings demonstrate that LLMs can positively impact teachers' competency assessments by streamlining the reporting process, offering valuable support for educators.

关键词： Large language models Writing Real-time systems Reliability Usability

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Secure and fast mobility handover scheme for IoMT in 5 G and future 6 G networks

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Alexandria engineering Journal 2025年 128卷 127-143页

作者： Islam, Shayla Topazal, S.M. Hasan, Mohammad Kamrul Kolandaisamy, Raenu AL Abbas, Huda Saleh Vo, Nguyen Thakkar, Rahul Khan, Muhammad Attique Gupta, Deepak AlHammadi, Dina Abdulaziz Institute of Computer Science and Digital Innovation UCSI University Kuala Lumpur56000 Malaysia Center for Cyber Security Faculty of Information Science and Technology the National University of Malaysia Selangor Bangi43600 Malaysia Department of computer science College of Computer Science and Engineering Taibah University Madina Saudi Arabia Victorian Institute of Technology Melbourne Australia Center of AI College of Computer Engineering and Science Prince Mohammad Bin Fahd University Al-Khobar Saudi Arabia Maharaja Agrasen Institute of Technology Delhi India Department of Information Systems College of Computer and Information Sciences Princess Nourah bint Abdulrahman University P.O.Box 84428 Riyadh11671 Saudi Arabia

The emergence of 5 G and 6 G networks promises significant advancements in the Internet of Medical Things (IoMT) by enabling real-time medical data transmission and continuous connectivity for mobile healthcare devices. However, traditional Handover (HO) mechanisms face latency, security, energy consumption, and scalability challenges when supporting fast-moving and dense IoMT environments. This paper presents a secure and fast mobility handover scheme for IoMT in 5 G and future 6 G networks, incorporating a predictive algorithm, Blockchain-Based (BC-B) decentralized authentication mechanism, and AI-driven anomaly detection. The predictive algorithm anticipates device movement and pre-allocates resources at the target Base Station (BS), reducing HO latency by 20–30 % in 5 G and up to 40 % in 6 G. Meanwhile, blockchain-based authentication ensures tamper-proof and decentralized security, reducing vulnerability to cyberattacks by 90 % compared to traditional methods. Additionally, the energy consumption during HO events is reduced by 20–35 %, dropping from 15 mJ in traditional schemes to 12 mJ in 5 G and further to 10 mJ in 6 G. The scheme also incorporates AI-driven anomaly detection, achieving an accuracy of 96.7 %, ensuring proactive identification and mitigation of potential security threats. The analyzed scheme maintains consistent throughput with less than 5 % reduction and scales effectively for up to 300 devices per cell. The simulation results demonstrate significant improvements across key performance metrics, including latency, security, energy efficiency, and scalability, making this approach highly suitable for critical IoMT applications such as telesurgery, remote patient monitoring, and innovative healthcare environments. These advancements position the analyzed framework as a cornerstone for next-generation (NG) healthcare networks. © 2025 The Authors

关键词： Remote patient monitoring

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The Influence of Eye Gaze Interaction Technique Expertise and the Guided Evaluation Method on Text Entry Performance Evaluations

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Proceedings of the ACM on Human-computer Interaction 2025年第3期9卷 1-19页

作者： Aunnoy K Mutasim Anil Ufuk Batmaz Moaaz Hudhud Mughrabi Wolfgang Stuerzlinger School of Interactive Arts + Technology SIAT) Simon Fraser University Vancouver BC Canada Computer Science & Software Engineering Department Concordia University Montreal QC Canada Mechatronics Engineering Department Kadir Has University Istanbul Turkiye

Any investigation of learning unfamiliar text entry systems is affected by the need to train participants on multiple new components simultaneously, such as novel interaction techniques and layouts. The Guided Evaluation Method (GEM) addresses this challenge by bypassing the need to learn layout-specific skills for text entry. However, a gap remains as the GEM's performance has not been assessed in situations where users are unfamiliar with the interaction technique involved, here eye-gaze-based dwell. To address this, we trained participants on only the eye-gaze-based interaction technique over eight days with QWERTY and then evaluated their performance on the OPTI layout with the GEM. Results showed that the unfamiliar OPTI layout outperformed QWERTY, with QWERTY's speed aligning with previous findings, suggesting that interaction technique expertise significantly impacts performance outcomes. Importantly, we also identified that for scenarios where the familiarity with the involved interaction technique(s) is the same, the GEM analyzes the performance of keyboard layouts effectively and quickly identifies the best option.

关键词： OPTI QWERTY dwell eye tracking soft keyboards text entry virtual reality

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A Linear Complexity Algorithm for Optimal Transport Problem with Log-type Cost

arXiv

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arXiv 2025年

作者： Lyu, Ziyuan Wang, Zihao Wu, Hao Yang, Shuai Department of Mathematical Sciences Tsinghua University Beijing100084 China Department of Computer Science and Engineering Hong Kong University of Science and Technology Clear Water Bay Hong Kong

In [Q. Liao et al., Commun. Math. Sci., 20(2022)], a linear-time Sinkhorn algorithm is developed based on dynamic programming, which significantly reduces the computational complexity involved in solving optimal transport problems. However, this algorithm is specifically designed for the Wasserstein-1 metric. We are curious whether the preceding dynamic programming framework can be extended to tackle optimal transport problems with different transport costs. Notably, two special kinds of optimal transport problems, the Sinkhorn ranking and the far-field reflector and refractor problems, are closely associated with the log-type transport costs. Interestingly, by employing series rearrangement and dynamic programming techniques, it is feasible to perform the matrix-vector multiplication within the Sinkhorn iteration in linear time for this type of cost. This paper provides a detailed exposition of its implementation and applications, with numerical simulations demonstrating the effectiveness and efficiency of our methods. Copyright © 2025, The Authors. All rights reserved.

关键词： Dynamic programming

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