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LiDAR-Based Climate Change Imaging in Geoscience Using Spatio Extreme Fuzzy Gradient Model

Remote Sensing in Earth systems sciences 2025年第2期8卷 465-472页

作者： Krushnasamy, V.S. Al-Omari, Omaia Sundaram, Ajith Varghese, Issac K. Muniyandy, Elangovan Rao, M. V. A. L. Narasimha Dept. of EIE Dayananda Sagar College of Engineering Bangalore India Information Systems Department College of Computer and Information Sciences Prince Sultan University Riyadh Saudi Arabia Amrita School of Business Amrita Vishwa Vidyapeetham Kochi India T A Pai Management Institute Manipal Academy of Higher Education Manipal India Department of Biosciences Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai 602105 India Applied Science Research Center Applied Science Private University Amman Jordan Department of MBA Koneru Lakshmaiah Education Foundation Andhra Pradesh Vaddeswaram Guntur 522302 India

In order to estimate high-resolution air temperatures, computationally demanding procedures are required because climate models do not provide the resolution required for urban climate studies. Data-driven methods, on the other hand, provide air temperature downscaling that is quicker and more precise. Lidar technology has become a vital tool for researching these atmospheric components because of its capacity to measure backscattered signals and investigate the atmosphere at extremely high spatial and temporal resolution. However, machine learning has become a potent technique for sophisticated data processing and analysis because of the complexity and diversity of lidar technology. This research proposes a novel technique in urban–rural interface analysis in remote sensing by machine learning (ML) model. Here the input is collected as urban–rural landscape data and processed for noise removal as well as normalisation. Then these data features have been extracted and classified using a spatio extreme fuzzy gradient model with reinforcement Markov vector perceptron neural networks. Experimental analysis has been carried out for various geographical regions in terms of training accuracy, average precision, recall, RMSE, and F-1 score. The proposed model attained an F-1 score of 92%, training accuracy of 98%, average precision of 95%, recall of 93%, and RMSE of 55%. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2025.

关键词： Lidar technology Machine learning model Reinforcement Markov vector Remote sensing Spatio extreme fuzzy gradient

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CONSTRUCTION PROGRESS MONITORING IN SMART CITIES USING DEEP ALEXNET

CONSTRUCTION PROGRESS MONITORING IN SMART CITIES USING DEEP ...

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2023 IEEE International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication engineering, RMKMATE 2023

作者： Rajavel, A. Karkuzhali, S. Sharma, Sarvdaman Singh, Sitesh Kumar Senthilkumar, P. Ida, S. Jhansi Electronics and Instrumentation Engineering Kamaraj College of Engineering and Technology Virudhnagar India Department of Electrical and Electronics Engineering R.M.D. Engineering College Chennai India Department of Civil Engineering University Institute of Engineering and Technology University of Jammu Jammu & Kashmir India Department of Civil Engineering Wollega University Nekemte Oromia Ethiopia KL School of Architecture Koneru Lakshmaiah Education Foundation Vaddeswaram Greenfield AP Guntur India Department of Computer Science and Business Systems R.M.K Engineering College India

ISBN: (纸本)9798350305708

Construction progress monitoring plays a crucial role in ensuring the timely and efficient completion of infrastructure projects within smart cities. This paper proposes a novel approach utilizing the Deep AlexNet architecture for construction progress assessment in smart cities. The Deep AlexNet model is trained on a diverse dataset of images captured from construction sites, enabling it to accurately analyze the visual cues indicative of construction advancement. By leveraging deep learning techniques, our system extracts and processes features from images, enabling automated and real-time progress evaluation. The proposed method contributes to enhancing construction management practices by providing stakeholders with a reliable tool to monitor and manage construction projects efficiently. Experimental results demonstrate the effectiveness and robustness of the Deep AlexNet-based approach in accurately assessing construction progress, thereby facilitating informed decision-making throughout the construction lifecycle. © 2023 IEEE.

关键词： Construction progress monitoring Deep AlexNet Deep learning Infrastructure projects Smart cities

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Adaptive Federated Learning for Efficient Network Traffic Management in Edge Computing

Adaptive Federated Learning for Efficient Network Traffic Ma...

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Ubiquitous Computing and Intelligent Information systems (ICUIS), International Conference on

作者： Kuricheti Suresh Babu S Venkatasubramanian S. Kishore K Kavya Ramya Sree Ch.Lavanya Susanna Goda Srinivasa Rao Ajanthaa Lakkshmanan Department of Computer Science and Engineering PACE Institute of Technology and Sciences Valluru AndhraPradesh Department of Computer Science and Business Systems Saranathan college of engineering Trichy India Department of CSBS B V RAJU INSTITUTE OF TECHNOLOGY Narsapur Medak Telangana Department of AI&ML Aditya University Surampalem Department of Computer Science and Engineering Koneru Lakshmaiah Education Foundation Vaddeswaram Andhra Pradesh India Department of CSE KL University Vaddeswaram Guntur Andhra Pradesh India Department of Computing Technologies School of Computing SRM Institute of Science and Technology Kattankulathur Campus Kattankulathur

ISBN: (数字)9798331529635

ISBN: (纸本)9798331529642

With the increasing prevalence of edge computing environment, there is a need to establish effective network traffic management that are able to manage vast data while also protecting the privacy of users. The proposed method enhances efficiency of bandwidth, reduce the network latency and manages computational demands without managing data privacy. This is achieved by utilizing the design of edge devices. The adaptable nature of the method enables it to react in real time to different traffic situations. It optimizes the distribution of resources and improves the overall performance of the network. Additionally, it can reduce the possibility of centralized data exposure, providing robust privacy preservation through the allowance of local model training on edge devices. Finally, this method is superior. The employment of federated learning to network traffic management provide efficiency to optimize the traffic in edge computing which is both scalable and safe. This makes it suitable for a wide variety of applications that are utilized in next generation networks

关键词： Training Adaptive systems Federated learning Computational modeling Telecommunication traffic Bandwidth Real-time systems Optimization Next generation networking Edge computing

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Lightweight Spiking Neural Network Based Detector for Interweave Cognitive Radios

Lightweight Spiking Neural Network Based Detector for Interw...

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IEEE International Conference on Communications (ICC)

作者： Md Mehedi Hassan Galib Mohamed Younis Sultan Ahmed Dept. of Computer Science and Electrical and Engineering University of Maryland Baltimore County Baltimore Maryland Information Systems Department University of Maryland Baltimore County Baltimore Maryland

ISBN: (数字)9781728190549

ISBN: (纸本)9781728190556

The major advances in wireless communication technology have led to increased adoption across almost all application domains. However, the massive growth has caused spectrum scarcity despite the fact that many of the frequency bands are not fully-utilized. Cognitive radios have emerged as a viable means to support dynamic spectrum access. Particularly, supporting opportunistic access through passive spectrum monitoring is of great interest. Existing techniques for detecting white space either require modification to commodity radio transceivers, or involve computationally complex models that do not suit resource-constrained devices. This paper opts to fill the technical gap by proposing a novel lightweight white space detector that employs spiking neural networks (SNN). SNN is a bio-inspired technique for creating data-driven models. The proposed design relies on the sensed energy in the medium to determine whether a primary user is active. The validation results using live LTE data demonstrate the effectiveness of our novel detector. Suitability for edge devices is confirmed through implementation on a Raspberry-PI platform.

关键词： Accuracy Biological system modeling Image edge detection Computational modeling Dynamic spectrum access Detectors Spiking neural networks

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A Toolbox of Feminist Wonder: Theories and methods that can make a difference 26

A Toolbox of Feminist Wonder: Theories and methods that can ...

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26th ACM Conference on computer-Supported Cooperative Work and Social Computing, CSCW 2023

作者： Hansson, Karin Bardzell, Shaowen Bhandari, Aparajita Boulicault, Marion Doyle, Dylan Thomas Erete, Sheena Cerratto Pargman, Teresa Lazem, Shaimaa Muller, Michael Normark, Maria Petterson, Adrian Rosén, Anton Poikolainen Taylor, Alex S. Thomas, Jakita O. Watson, Julia Södertörn University The School of Natural Sciences Technology and Environmental Studies Sweden Georgia Institute of Technology The School of Interactive Computing United States Cornell University Department of Communication United States University of Edinburgh Department of Philosophy United States University of Colorado Boulder Department of Information Science United States University of Maryland College of Information United States Stockholm University The Department of Computer and Systems Sciences Sweden City for Scientific Research and Technological Applications The Informatics Research Institute Egypt Ibm Research Human Centered Ai United States Uppsala University Department of Informatics and Media Sweden University of Toronto Faculty of Information Canada Aalto University The School of Arts Design and Architecture Finland City University of London The Centre for Human Computer Interaction Design United Kingdom Auburn University Department of Computer Science and Software Engineering United States University of Toronto Department of Computer Science Canada

ISBN: (纸本)9798400701290

This one-day hybrid workshop builds on previous feminist CSCW workshops to explore feminist theoretical and methodological approaches that have provided us with useful tools to see things differently and make space for change. Since its inception over a decade ago, feminist HCI has progressed from the margins to mainstream HCI, with numerous references in the literature. Feminist HCI has also evolved to incorporate other critical HCI practices such as Queer HCI, participatory design, and speculative design. While feminist approaches have grown in popularity and become mainstream, it is getting more difficult to distinguish the feminist emancipatory core from other attempts of developing and improving society in various ways. In this workshop, we therefore want to revisit our feminist roots, where theory is a liberatory and creative practice, motivated by affect, curiosity, and wonder. From this standpoint, we consider which of our feminist tools can make a significant difference today, in a highly datafied world. The goal of this workshop is to;1) create an inventory of feminist theories and concepts that have had an impact on our work as designers, educators, researchers, and activists;2) develop a feminist toolbox for the CSCW community to strengthen our feminist literacy. © 2023 Owner/Author.

关键词： Computation theory

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Thermal-Aware Channel Capacity

Thermal-Aware Channel Capacity

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2023 IEEE International Symposium on Information Theory, ISIT 2023

作者： Meng Chee, Yeow Etzion, Tuvi Schouhamer Immink, Kees A. Thanh Nguyen, Tuan Khu Vu, Van Weber, Jos H. Yaakobi, Eitan National University of Singapore Department of Industrial Systems Engineering and Management Singapore Technion - Israel Institute of Technology Department of Computer Science Haifa3200003 Israel Turing Machines Inc. Rotterdam3016 DK Netherlands Singapore University of Technology and Design Science Mathematics and Technology Cluster Singapore Delft University of Technology Department of Applied Mathematics Delft2628 CD Netherlands

ISBN: (纸本)9781665475549

High temperatures in electronic devices have a negative effect on their performance. Various techniques have been proposed and studied to address and combat this thermal challenge. To guarantee that the peak temperature of the devices will be bounded by some maximum temperature, the transmitted signal has to satisfy some *** this motivation, we study the constrained channel that only accepts sequences that satisfy prescribed thermal constraints. The main goal in this paper is to compute the capacity of this channel. We provide the exact capacity of the channel with some certain parameters and we also present some bounds on the capacity in various ***, we consider the model that multiple wires are available to use and find out the smallest number of wires required to satisfy the thermal constraints. © 2023 IEEE.

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Enhancing Energy Sector Resilience: Integrating Security by Design Principles

arXiv

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arXiv 2024年

作者： Shirtz, Dov Koberman, Inna Elyashar, Aviad Puzis, Rami Elovici, Yuval Cyber@BGU Cyber Labs Ben-Gurion University Israel Department of Software and Information Systems Engineering Ben-Gurion University Israel Department of Computer Science Shamoon College of Engineering Beer-Sheva Israel

Security by design (SbD) is a concept for developing and maintaining systems that are, to the greatest extent possible, free from security vulnerabilities and impervious to security attacks. In addition to technical aspects, such as how to develop a robust Industrial control system (ICS), hardware (HW), software (SW), firmware, communication product, etc., SbD also includes soft aspects, such as organizational management's attitude and behavior, and employee awareness. Under the SbD concept, systems, i.e., in our context ICS, will be considered more trustworthy by users;users' trust in the systems will be derived from meticulous adherence to SbD processes and policies. In accordance with the SbD concept, security is considered. Security measures are implemented, at every stage of the product and system development lifecycle, rather than afterward, which is beneficial, enabling the identification of vulnerabilities early in the development process;when vulnerabilities are identified at an early stage, the ability to address them is improved, and the cost of resolving them is reduced, saving time, money, and effort. As mentioned above, the SbD approach focuses on making systems as secure and immune to attack as possible through the use of measures such as continuous testing, authentication, safeguards, and adherence to best programming practices. As such, SbD enables an organization to formalize the design of its infrastructure and applications and build and integrate security into its IT and OT processes. This document presents the security requirements for the implementation of SbD in industrial control systems. The information presented does not negate any existing security and cyber security standards, quality assurance standards, best practices, or management methods such as COBIT. Instead, we strongly recommend that organizations should implement and comply with those standards and best practices. Security by design is not a one-time process. It starts at the ve

关键词： Cybersecurity

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Exploring the Frontiers of Firmware Fuzzing: μAFL’s Application on Cortex M4 and Unix programs

Exploring the Frontiers of Firmware Fuzzing: μAFL’s Applic...

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International Wireless Communications and Mobile Computing Conference, IWCMC

作者： Safayat Bin Hakim Muhammad Adil Jordi Mongay Batalla Constandinos X. Mavromoustakis Houbing Herbert Song Department of Information Systems University of Maryland Baltimore County Baltimore MD USA Computer Science and Engineering The State University of New York at Buffalo Buffalo NY USA Institute of Telecommunications Electronics and Information Technology Warsaw University of Technology Warsaw Poland Department of Computer Science School of Sciences and Engineering University of Nicosia Nicosia Cyprus

ISBN: (数字)9798350361261

ISBN: (纸本)9798350361278

The aim of this study is to investigate into $\mu \mathrm{AFL}$, a non-intrusive, feedback-driven fuzzing framework, evaluated on Cortex M4 embedded systems and Unix platforms, focusing on the STM32F407VE Cortex M4 microcontroller. By leveraging the SEGGER J-Trace Pro for trace collection, it demonstrates $\mu$AFL’s utility beyond its traditional scope, showcasing its efficacy in both embedded and general-purpose computing environments. Our analysis, enriched by juxtaposing $\mu$AFL’s capabilities with traditional AFL, emphasizes the adaptability and effectiveness of fuzzing methodologies in firmware security enhancement. Furthermore, the study provides a deep understanding of fuzzing execution on different hardware, presenting an execution strategy for the STM32F407VE that highlights the framework’s potential in identifying vulnerabilities, evidenced by tests on specific firmware programs such as an LED blinking program integrated with semihosting breakpoints and ETM tracing. The use of uninitialized memory sections and strategically placed break-points offers significant insights into the firmware’s execution flow. The results of our comparative analysis clearly show that $\mu \mathrm{AFL}$ excels at uncovering vulnerabilities, reinforcing the need for evolving fuzzing methodologies to build stronger security systems for embedded devices. This contribution underscores the importance of refining fuzzing techniques to meet the intricate security demands of contemporary computing environments.

关键词： Wireless communication Macrocell networks Embedded systems Microcontrollers Refining Fuzzing Hardware

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Blockchain-Based Key Management Solution for Clustered Flying Ad-Hoc Network 5

Blockchain-Based Key Management Solution for Clustered Flyin...

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5th International Conference on Blockchain Computing and Applications, BCCA 2023

作者： Abdelhafidh, Maroua Zaghdoud, Nesrine Charef, Nadia Ben Mnaouer, Adel SM-RTS Digital Research Center of Sfax Tunisia Canadian University Dubai Dubai United Arab Emirates Tunisia Canadian University Dubai Sup'Com Dubai United Arab Emirates Lorraine University France Canadian University Dubai Department of Computer Engineering and Computational Science Dubai United Arab Emirates College of Computer and Information Systems Prince Sultan University Saudi Arabia

ISBN: (纸本)9798350339239

The Flying ad hoc networks (FANETs) have been recognized as one of the most emergent technologies for ensuring the performance and safety of different systems. However, its security presents a major concern inviting researchers to propose and implement new efficient solutions. In this context, due to the dynamic behavior of FANETs, the Key Management (KM)-based solution is increasingly explored as a security issue. In this paper, we investigate a Blockchain-based Key Management solution for Clustered FANETs (BKM-CF) to effectively perform cluster key dissemination, allow UAVs to update their public/private keys, migrate between clusters, and revoke malicious UAVs. Through security analysis and performance evaluation, our solution can resist against various attacks and provide reduced network energy consumption. © 2023 IEEE.

关键词： Ad hoc networks

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Leader Rotation Is Not Enough: Scrutinizing Leadership Democracy of Chained BFT Consensus

arXiv

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arXiv 2025年

作者： Tang, Yining Han, Runchao Niu, Jianyu Feng, Chen Zhang, Yinqian The Research Institute of Trustworthy Autonomous Systems The Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China Babylon Labs Blockchain@UBC The School of Engineering The University of British Columbia Okanagan Campus KelownaBC Canada

With the growing popularity of blockchains, modern chained BFT protocols combining chaining and leader rotation to obtain better efficiency and leadership democracy have received increasing interest. Although the efficiency provisions of chained BFT protocols have been thoroughly analyzed, the leadership democracy has received little attention in prior work. In this paper, we scrutinize the leadership democracy of four representative chained BFT protocols, especially under attack. To this end, we propose a unified framework with two evaluation metrics, i.e., chain quality and censorship resilience, and quantitatively analyze chosen protocols through the Markov Decision Process (MDP). With this framework, we further examine the impact of two key components, i.e., voting pattern and leader rotation on leadership democracy. Our results indicate that leader rotation is not enough to provide the leadership democracy guarantee;an adversary could utilize the design, e.g., voting pattern, to deteriorate the leadership democracy significantly. Based on the analysis results, we propose customized countermeasures for three evaluated protocols to improve their leadership democracy with only slight protocol overhead and no change of consensus rules. We also discuss future directions toward building more democratic chained BFT protocols. Copyright © 2025, The Authors. All rights reserved.

关键词： Efficiency

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