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First-passage times for generalized heterogeneous telegrapher's processes

Physical Review E 2025年第4期111卷 044105-044105页

作者： T. Sandev R. K. Singh V. Méndez L. Kocarev Research Center for Computer Science and Information Technologies Macedonian Academy of Sciences and Arts Bul. Krste Misirkov 2 1000 Skopje Macedonia Institute of Physics Faculty of Natural Sciences and Mathematics Ss. Cyril and Methodius University Arhimedova 3 1000 Skopje Macedonia and Department of Physics Korea University Seoul 02841 Korea Department of Biomedical Engineering Ben-Gurion University of the Negev Be'er Sheva 85105 Israel Grup de Física Estadística Departament de Física Facultat de Ciències Universitat Autònoma de Barcelona 08193 Barcelona Spain Research Center for Computer Science and Information Technologies Macedonian Academy of Sciences and Arts Bul. Krste Misirkov 2 1000 Skopje Macedonia and Faculty of Computer Science and Engineering Ss. Cyril and Methodius University PO Box 393 1000 Skopje Macedonia

We consider two different fractional generalizations of the heterogeneous telegrapher's process with and without stochastic resetting. Both governing fractional heterogeneous telegrapher's equations can be obtained from the corresponding standard heterogeneous telegrapher's equations by using the subordination approach. The first-passage time problems are solved analytically for both models by finding the survival probabilities, the first-passage time densities, and the mean first-passage times. We showed that for both cases there are optimal resetting rates for which the mean first-passage times are minimal. The present work carries implications toward our understanding of anomalous diffusion and random search in heterogeneous media.

关键词： Stochastic systems

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GP-FL: Model-Based Hessian Estimation for Second-Order Over-the-Air Federated Learning

arXiv

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arXiv 2024年

作者： Hamidi, Shayan Mohajer Bereyhi, Ali Asaad, Saba Poor, H. Vincent The Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada University of Toronto TorontoM5S 2E4 Canada The Department of Electrical Engineering and Computer Science York University TorontoONM3J 1P3 Canada Princeton University PrincetonNJ08544 United States

Second-order methods are widely adopted to improve the convergence rate of learning algorithms. In federated learning (FL), these methods require the clients to share their local Hessian matrices with the parameter server (PS), which comes at a prohibitive communication cost. A classical solution to this issue is to approximate the global Hessian matrix from the first-order information. Unlike in idealized networks, this solution does not perform effectively in over-the-air FL settings, where the PS receives noisy versions of the local gradients. This paper introduces a novel second-order FL framework tailored for wireless channels. The pivotal innovation lies in the PS’s capability to directly estimate the global Hessian matrix from the received noisy local gradients via a non-parametric method: the PS models the unknown Hessian matrix as a Gaussian process, and then uses the temporal relation between the gradients and Hessian along with the channel model to find a stochastic estimator for the global Hessian matrix. We refer to this method as Gaussian process-based Hessian modeling for wireless FL (GP-FL) and show that it exhibits a linear-quadratic convergence rate. Numerical experiments on various datasets demonstrate that GP-FL outperforms all classical baseline first and second order FL approaches. © 2024, CC BY.

关键词： Federated learning

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Flexible Base Station Sleeping and Resource Cooperation Enabled Green Fully-Decoupled RAN

arXiv

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arXiv 2023年

作者： Sun, Yu Yu, Kai Xu, Yunting Zhou, Haibo Shen, Xuemin The School of Electronic Science and Engineering Nanjing University Nanjing210023 China The Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada

Base station (BS) sleeping, a promising technique to address the growing energy consumption in wireless communication networks, encounters challenges such as coverage holes and coupled uplink and downlink transmissions. As an innovative architecture designed for future-generation mobile communication networks, the fully-decoupled radio access network (FD-RAN) is anticipated to overcome these challenges by fully decoupled control-data planes and uplink-downlink transmissions. In this paper, we investigate energy-efficient uplink FD-RAN leveraging flexible BS sleeping and resource cooperation. First, we introduce a holistic energy consumption model and formulate a bi-level energy efficiency maximizing problem for FD-RAN, involved with the joint optimization of user equipment (UE) association, BS sleeping, and power control. Subsequently, through employing the Tammer decomposition method, the formulated bi-level problem is converted into two equivalent upper-level and lower-level problems. The lower-level problem encompassed with UE power control is addressed by introducing a successive lower-bound maximization-based Dinkelbach’s algorithm, and the upper-level problem for UE association and BS sleeping is solved through a modified low-complexity many-to-many swap matching algorithm, respectively. Extensive simulation results not only demonstrate the superior effectiveness of FD-RAN and our proposed algorithms but also reveal the sources of energy efficiency gains within FD-RAN. Copyright © 2023, The Authors. All rights reserved.

关键词： Energy efficiency

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A Comprehensive Survey of Spectrum Sharing Schemes from a Standardization and Implementation Perspective

arXiv

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arXiv 2022年

作者： Parvini, Mohammad Zarif, Amir Hossein Nouruzi, Ali Mokari, Nader Javan, Mohammad Reza Abbasi, Bijan Ghasemi, Amir Yanikomeroglu, Halim The Department of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran The Department of Electrical and Computer Engineering Shahrood University of Technology Iran The Commutations Research Centre Innovation Science and Economic Development Canada OttawaONK2H 8S2 Canada The Department of Systems and Computer Engineering Carleton University Ottawa Canada

As the services and requirements of next-generation wireless networks become increasingly diversified, it is estimated that the current frequency bands of mobile network operators (MNOs) will be unable to cope with the immensity of anticipated demands. Due to spectrum scarcity, there has been a growing trend among stakeholders toward identifying practical solutions to make the most productive use of the exclusively allocated bands on a shared basis through spectrum sharing mechanisms. However, due to the technical complexities of these mechanisms, their design presents challenges, as it requires coordination among multiple entities. To address this challenge, in this paper, we begin with a detailed review of the recent literature on spectrum sharing methods, classifying them on the basis of their operational frequency regime-that is, whether they are implemented to operate in licensed bands (e.g., licensed shared access (LSA), spectrum access system (SAS), and dynamic spectrum sharing (DSS)) or unlicensed bands (e.g., LTE-unlicensed (LTE-U), licensed assisted access (LAA), MulteFire, and new radio-unlicensed (NR-U)). Then, in order to narrow the gap between the standardization and vendor-specific implementations, we provide a detailed review of the potential implementation scenarios and necessary amendments to legacy cellular networks from the perspective of telecom vendors and regulatory bodies. Next, we analyze applications of artificial intelligence (AI) and machine learning (ML) techniques for facilitating spectrum sharing mechanisms and leveraging the full potential of autonomous sharing scenarios. Finally, we conclude the paper by presenting open research challenges, which aim to provide insights into prospective research endeavors. © 2022, CC BY.

关键词： Standardization

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Development of Localized Cutaneous Force Feedback System for Robotics Assisted Surgery Systems 28th

Development of Localized Cutaneous Force Feedback System for...

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28th International Conference on Knowledge Based and Intelligent information and engineering Systems, KES 2024

作者： See, Aaron Raymond Tiong, Thad Jacob De Guzman, Lanz Benedict Contee, Kenneth Lim, Garfield Greg Yebes, Carl Sebastian Department of Electrical Engineering Southern Taiwan University of Science and Technology No. 1 Nantai St Yongkang District Tainan City71005 Taiwan Department of Electronic Engineering National Chin-Yi University of Technology No. 57 Section 2 Zhongshan Rd Taiping District Taichung City411030 Taiwan Department of Electrical Engineering Universitas Katolik Indonesia Atma Jaya Jl. Jend. Sudirman No.51 5 RT.004/RW.4 Karet Semanggi Kecamatan Setiabudi Kota Jakarta Selatan Daerah Khusus Jakarta12930 Indonesia School of Computer Studies University of San Jose - Recoletos Basak Pardo Cebu City6000 Philippines College of Computer Studies Cebu Institute of Technology - University Natalio B. Bacalso Ave Cebu City Cebu6000 Philippines

This study explores integrating a novel cutaneous force feedback system for robotic-assisted surgery (RAS) systems aimed at improving tactile perception for surgical precision and safety. The system developed comprises two major components: a force-sensitive matrix sensor and a 4x4 tactile pin interface. Forces experienced by the sensors are mirrored through the tactile interface, conveying the sensation of knowing which part of the sensor is in contact and how much force is subjected to it. An algorithm called Dynamic Interval Localization (DIL) was developed to manipulate pin actuation by scheduling individualized dynamic oscillation. The system successfully detected operating forces from 0.1N to 5N while concurrently providing respective cutaneous feedback. The system's performance in force localization suggests significant potential and promises in elevating the haptic features of RAS systems. © 2024 The Authors.

关键词： Robotic surgery

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An Ensemble Learning Method Based on Deep Neural and Pca-Based Svm Network for Baggage Threat and Smoke Recognition

An Ensemble Learning Method Based on Deep Neural and Pca-Bas...

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Advances in science and engineering Technology International Conferences (ASET)

作者： Abdelfatah Hassan Ahmed Muaz Al Radi Naoufel Werghi Department of Electrical Engineering and Computer Sciences Center for Cyber-Physical System (C2PS) Khalifa University of Science and Technology Abu Dhabi United Arab Emirates

Ensemble learning methods are emerging as one of the most widely used image classification and object recognition techniques. They have the advantage of achieving higher classification and recognition performance compared to single models while being easy to implement in various applications. This work proposes an ensemble-based classification network that leverages the recognition performance of both threat and smoke detection tasks. The method utilizes ensemble learning of a deep Convolutional Neural Network (CNN) combined with a Principal Component Analysis (PCA)-based Support Vector Machine (SVM) classifier. Comparisons to several single model classifiers and other state-of-the-art methods and the proposed methods were carried out. The proposed method showed superior performance in comparison for the problems of baggage X-ray imagery classification and smoke recognition.

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Melaleuca leaves extract as eco-friendly inhibitor for low carbon steel in sulfuric acid

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Case Studies in Chemical and Environmental engineering 2024年 9卷

作者： Gapsari, Femiana Setyarini, Putu H. Utaminingrum, Fitri Sulaiman, Abdul M. Haidar, Muhamad F. Julian, Tobias S. Department of Mechanical Engineering Faculty of Engineering Brawijaya University MT Haryono 167 Malang 65145 Indonesia Computer Vision Research Group Faculty of Computer Science Brawijaya University Veteran 12-14 Malang 65145 Indonesia Department of Mechanical and Industrial Engineering Univiversitas Gadjah Mada Jalan Grafika No. 2 Yogyakarta 55281 Indonesia

A by-product of the making of essential oil from Melaleuca leaves can be re-extracted to produce an inhibitor. Melaleuca leaves extract (MLE), as an alternative corrosion inhibitor, was employed to protect low-carbon steel (LCS) in a sulfuric acid medium. Adsorption and corrosion inhibition were examined using electrochemical tests. MLE functioned as a mixed-type inhibitor with an optimal inhibitory efficacy of 98.99%. The inhibition by MLE on LCS was based on the Temkin adsorption isotherm and physisorption. The study demonstrated the potential of MLE derived from biomass by-product as a nature-friendly corrosion inhibitor that offers new insights and opportunities. © 2024 The Authors

关键词： Adsorption By-product Corrosion Inhibitor Melaleuca leaf extract (MLE)

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A Systematic Literature Review on Latest Keystroke Dynamics Based Models

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IEEE Access 2022年 1-1页

作者： Roy, Soumen Pradhan, Jitesh Kumar, Abhinav Adhikary, Dibya Ranjan Das Roy, Utpal Sinha, Devadatta Pal, Rajat Kumar Department of Computer Science and Engineering University of Calcutta Acharya Prafulla Chandra Roy Siksha Prangan JD-2 Sector - III Saltlake City Kolkata India Department of Computer Science and Engineering Siksha O' Anusandhan Deemed to be University Bhubaneswar Odisha India Department of Computer System Sciences VisvaBharati Santiniketan India

The purpose of this study is to conduct a comprehensive evaluation and analysis of the most recent studies on the implications of keystroke dynamics (KD) patterns in user authentication, identification, and the determination of useful information. Another aim is to provide an extensive and up-to-date survey of the recent literature and potential research directions to understand the present state-of-the-art methodologies in this particular domain that are expected to be beneficial for the KD research community. From January 1st, 2017 to March 13th, 2022, the popular six electronic databases have been searched using a search criterion (keystroke dynamics OR typing pattern) AND (authentication OR verification OR identification). With this criterion, a total of nine thousand three hundred forty-eight results, including duplicates, were produced. However, one thousand five hundred forty-seven articles have been chosen after removing duplicates and preliminary screening. Due to insufficient information, only one hundred twenty-seven high-quality quantitative research articles have been included in the article selection process. We compared and summarised several factors with multiple tables to comprehend the various methodologies, experimental settings, and findings. In this study, we have identified six unique KD-based designs and presented the status of findings toward an effective solution in authentication, identification, and prediction. We have also discovered considerable heterogeneity across studies in each KD-based design for desktops and smartphones separately. Finally, this paper found a few open research challenges and provided some indications for a deeper understanding of the issues and further study. Author

关键词： Authentication

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A split target detection and tracking algorithm for ballistic missile tracking during the re-entry phase

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Defence Technology（防务技术） 2020年第6期16卷 1142-1150页

作者： Muhammad Asad Sumair Khan Ihsanullah Zahid Mehmood Yifang Shi Sufyan Ali Memon Uzair Khan Department of Electrical and Computer Engineering COMSATS University IslamabadAbbottabad CampusPakistan Department of Computer Science COMSATS University IslamabadAbbottabad CampusPakistan Electrical Engineering Department Indus UniversityKarachiPakistan Department of Automation Hangzhou Dianzi UniversityXiasha Higher Education Zone2nd StreetHangzhou310018China

In the re-entry phase of a ballistic missile,decoys can be deployed as a mean to overburden enemy *** results in a single track being split into multiple *** of these track-lets is a critical task as any miss in the tracking procedure can become a cause of a major *** tracking process becomes more complicated in the presence of *** low detection rate is one of the factors that may contribute to increasing the difficulty level in terms of tracking in the cluttered *** work introduces a new algorithm for the split event detection and target tracking under the framework of the joint integrated probabilistic data association(JIPDA)*** proposed algorithm is termed as split event-JIPDA(SE-JIPDA).This work establishes the mathematical foundation for the split target detection and tracking *** performance analysis is made under different simulation conditions to provide a clear insight into the merits of the proposed *** performance parameters in these simulations are the root mean square error(RMSE),confirmed true track rate(CTTR)and confirmed split true track rate(CSTTR).

关键词： Split event probability JIPDA Data association Ballistic missile Estimation

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Individual Plant Detection on Post-Harvest Forest Floor Using Aerial Imagery

Individual Plant Detection on Post-Harvest Forest Floor Usin...

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International Conference on Software, Telecommunications and computer Networks (SoftCOM)

作者： Aashish Raviraj Maximilian Johenneken Ahmad Drak Alexander Asteroth Sebastian Houben Department of Computer Science Bonn-Rhein-Sieg University of Applied Sciences Sankt Augustin Germany Resource and Energy-efficient Engineering (TREE) Institute of Technology Institute for Artificial Intelligence and Autonomous Systems (A2S)

ISBN: (数字)9789532901382

ISBN: (纸本)9798350354614

Effectively identifying and locating plants on the forest floor is essential for successful reforestation efforts and forest health assessment. This task is challenging due to the diverse range of plants, the high variance in appearance, the limited availability of accurately labeled data, and the complexity of data collection in post-harvest forest areas. These challenges are addressed by integrating field-surveyed plant data with images captured by Unmanned Aerial Vehicles (UAVs) to produce labeled training data. A custom Faster-RCNN model is trained using the aforementioned data to detect individual plants and clustered plant groups. Two different annotation approaches (unified class and distinct classes) are explored to address plant groupings and compare their performance using Mean Average Precision at 50% overlap (mAP50) and F1 score. The model trained using the unified class approach shows promise in detecting plants and plant groups larger than 0.15 square meters (F1 score: 0.44) but struggles with those smaller than 0.15 square meters. The inclusion of field-labeled data makes detection more challenging but ensures reliability. Meanwhile, the distinct class approach shows limited success. This work underscores the value of high-resolution imagery and comprehensive temporal analysis in enhancing detection accuracy and reliability.

关键词： Meters Reforestation Vegetation mapping Training data Forestry Software Telecommunications Sensors Reliability Floors

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