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检索条件"任意字段=7th International Conference on Real Time Computing Systems and Applications"

共 13062 条记录，以下是81-90 订阅

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real-time Atmospheric Duct Height Prediction Framework Based on Spatio-Temporal to Ensure Maritime Communication Security 18th

Real-Time Atmospheric Duct Height Prediction Framework Based...

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18th international conference on Wireless Artificial Intelligent computing systems and applications, WASA 2024

作者： Zhang, Ben Yan, Ke Hui, Bei Huang, Qian Gao, Hui School of Computer Science and Engineering University of Electronic Science and Technology of China ChengDu China KASH Institute of Electronics and Information Industry Kashi China

ISBN: (纸本)9783031714665

Atmospheric duct (AD) is a natural phenomenon affected by humidity or air pressure diversities, which impacts the propagation of electromagnetic signals. Recent studies have been focused on ADH prediction based on meteorological data which makes the task of real-time ADH prediction challenging and impacts the global representation of ADs leading to maritime communications security issues. We address these issues by discovering a novel way to abstract the spatial and temporal features from the historical data. thus, we proposed a framework based on DNN models and attention mechanisms to predict the ADH in a real-time form from the abstracted features. Our experimental results demonstrate that our technique improves the performance of real-time prediction and reduces the acquisition cost, professional devices can receive it in real-time through IoT to avoid dangerous areas. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Ducts

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the Integration of Edge computing into IoT Application Using AdvantEDGE Platform, Case Study: Mobility

The Integration of Edge Computing into IoT Application Using...

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international Youth conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Ali J. Dayoub Department of Electronic Engineering HSE Tikhonov Moscow Institute of Electronics and Mathematics Higher School of Economics University “HSE” Moscow Russian Federation

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

As the number of the Internet of things (IoT) devices connected to the internet increases, the amount of data explodes. this leads to a higher demand for internet speed during data transfer and more requirements for computing power and storage in central servers. To address these issues and enable real-time data processing while reducing network bandwidth utilization, edge computing has become a promising solution. this article focuses on the development of the IoT application on the edge computing platform in case of the mobility of the User Equipment (UE) to solve problems like latency and network bandwidth occupation for IoT applications while moving between two zones. the methodology involves simulating a network model to evaluate performance metrics such as latency and bandwidth under mobility conditions. Results demonstrate that latency is reduced to approximately 30-50 ms during UE mobility, highlighting the efficacy of Multi-access Edge computing (MEC) in IoT systems. these findings suggest that edge computing can significantly enhance the performance of time-sensitive IoT applications.

关键词： Power engineering Multi-access edge computing Computational modeling Bandwidth Data transfer real-time systems Internet of things Servers

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19th international conference on Soft computing Models in Industrial and Environmental applications, SOCO 2024

19th International Conference on Soft Computing Models in In...

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19th international conference on Soft computing Models in Industrial and Environmental applications, SOCO 2024

ISBN: (纸本)9783031750090

the proceedings contain 61 papers. the special focus in this conference is on Soft computing Models in Industrial and Environmental applications. the topics include: Improving the Efficiency of Production Processes by Reducing Human Errors Using Intelligent Methods;automated Semantic Labelling of Images Generated with Deep Diffusion Probabilistic Models;wastewater Quality Indicator Estimation Using Machine Learning and Data Augmentation Techniques;a Virtual Avatar for Sign Language Signing;comparison of D-Wave Quantum computing Environment Solvers for a Two-Machine Jobs Scheduling Problem;hybrid Fuzzy-Based Method for Optimally Selecting Aircraft for Low-Cost Carriers Operating Medium-Haul Flights;two Way Ranging Positioning Methods Analysis Under Optimized Sensor Deployments;human Acoustic Events Detection as Anomalies in Industrial Environments Using Shallow Unsupervised Techniques;Machine Learning in the Last-Mile Delivery: Modified Q-Learning for the TSP;IoT and AI Based Security System – Design and Implementation;characterization of Cattle Behavior Based on Dimensional Reduction Techniques;time Series Forecasting in Agriculture: Explainable Deep Learning with Lagged Feature Selection;artificial Intelligence Methodology for Run-to-Target Manufacturing;multi-robot Path Planning Problem Applied to real World Enviroment;an Approach of Optimization in Capacitated Vehicle Routing Problem in Logistics Distribution;bayesian Generation of Synthetic Data;learning-Based Models for Intelligent Control Over Air Conditioning Units in a Smart Building;predicting Power Generation from Photovoltaic Energy System;photovoltaic Generation Forecasting for Intelligent Management in Energy Communities;application of Neural Models in Solar Radiation Measurements for a Better Data Gathering Quality;caravels: A Decentralized Container-Based Infrastructure for Sustainable Human-Centric Intelligent Energy Communities;Production Scheduling for Energy Cost Optimization with Constraints: Com

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On Digital Twins for Cloud Continuum applications 20th

On Digital Twins for Cloud Continuum Applications

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20th international conference on the Economics of Grids, Clouds, systems, and Services, GECON 2024

作者： Bittencourt, Luiz F. Braghetto, Kelly R. Cordeiro, Daniel Sakellariou, Rizos Instituto de Computação Universidade Estadual de Campinas Campinas Brazil Universidade de São Paulo São Paulo Brazil The University of Manchester Manchester United Kingdom

ISBN: (纸本)9783031812255

Digital Twins (DTs) are digital representations of physical objects or processes that can be used for their computer-based analysis. this technique has been used in different fields to analyze, simulate, and optimize various scenarios in real time without interfering with the real twin. Using Serverless computing as a use case, this paper discusses the underlying costs of using DTs when applied to analyze and optimize the management of computational resources for cloud-continuum applications. We argue that, although feasible, using DTs for Digital systems can be prohibitively expensive. Defining the ideal DT fidelity for a given application is challenging, as this impacts both system management and performance through heavy monitoring as well as the DT running costs. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Cloud platforms

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Universal Representation theory—applications I 5th

Universal Representation Theory—Applications I

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5th international conference on Advances in Information Communication Technology and computing, AICTC 2024

作者： Bagadi, Ramesh Chandra Bagadi, Rohith Founder & Owner Ramesh Bagadi Consulting LLC {R042752} MadisonWI53715 United States Partner Ramesh Bagadi Consulting LLC {R042752} MadisonWI53715 United States

ISBN: (纸本)9789819761050

In this research investigation, the authors present some important applications of the rigor presentment in the universal representation theory, rigor I, II, and III. these include—outline solution to the Poincare’s topological connectedness conjecture (which states that all points of an n dimensional space volume are connected (through all the dimensions from 1 through n) by one curve given by a metric of universal nature, special curves connecting any two positive real numbers, net slope or cadence change optimization along the special curve, generic representation of special curves analysis, an example—restrictions imposed on native continuum field manifestation in lieu of special curves-based compatibility condition connecting any two discretization (finite element mesh) nodes, quantum set of constitutive deformations, model validation, minimizing sample bias, centroid of a set of positive real numbers in primes basis, computation of a representative future average for a time series type of sequence of positive real numbers, sample design with minimum bias, flux emission extremization analysis based on the constraint of zero reversed time entrainment of the flux complement, universal recursive wave equation of the universe, star engineering and management, creation of a star, universal permittivity handler, static and dynamic worm-hole engineering, gravity interaction, perception window size, permittivity of free space for a graviton, universal permittivity modulator, design of the space–time potential well functions, design of a quantum tunnel, invisibility engineering, constructing special wave functions of space–time—an example of wave function of a photon, space–time bubble transportation and extension of the same to a worm-hole, some notes on time causality architecture, hyper speed time causality engineering, the modified Dirac type commutator that can explain the parallax error effects, and hyper-causal manifestation engineering. © the Author(s), under ex

关键词： Wave functions

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Inferencing CNN Model for Navigational Object and Obstacles Classification on STM32 Boards 7th

Inferencing CNN Model for Navigational Object and Obstacle...

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7th international conference on Communication, Device and Networking, ICCDN 2024

作者： Mawblei, Mainkordor Peesapati, Rangababu Binong, Juwesh North Eastern-Hill University Shillong793022 India Indian Institute of Information Technology Design and Manufacturing Kurnool518008 India

ISBN: (纸本)9789819764648

this report explores the integration of high-end neural network models into embedded systems, its advantages over the high-end computers and Cloud-based inferencing to overcome the drawbacks such as cost, power consumption, latency, security concerns, and reliability. the STM32 microcontrollers are widely used in various embedded applications and are known for their high performance, low power consumption, and extensive connectivity options. A CNN architecture, ConvNet3, is proposed and fine-tuned for object classification and navigating obstacles in real-time scenarios, leveraging the limited resources of the STM32F401RE board. the performance of these models is evaluated, considering factors like prediction speed, accuracy, and model size. the findings highlight the trade-offs between accuracy and size reduction achieved through compression techniques. Overall, this research contributes to advancing CNN-based solutions for embedded systems and offers insights for model selection and data preparation, facilitating improved navigational capabilities and object recognition in resource-constrained environments. © the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Embedded systems

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5th international conference on computing, Communications, and Cyber Security, IC4S 2023

5th International Conference on Computing, Communications, a...

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5th international conference on computing, Communications, and Cyber Security, IC4S 2023

ISBN: (纸本)9789819773701

the proceedings contain 68 papers. the special focus in this conference is on computing, Communications, and Cyber Security. the topics include: Compact and High-Gain RFID Reader Antennas for Future Internet of things applications;Enabling Modern IoT Solutions with RFID Devices via an Integrated Feeding Network-Fed Ultra-Wide HPBW Patch Antenna Array;A Compact and Extremely Stiffness CPW-Fed Metal-Only Patch Antenna Array for Unlimited Lifetime 2U CubeSat Mission Capabilities;Jeans-Based UWB UHF Textile Patch Antenna for IoT applications;Design and Fabrication of PCB-Based Proximity Sensors for Application in Automatic Railway Crossing System;feaTrim-ViT: Vision Transformer Trimming with One Shot Neural Architecture Search in Continuous Optimisation Space and Efficient Feature Selection;detecting Depressive Symptoms on Social Media: A Comprehensive Review of Methodologies and Strategies for Suicide Prevention;enhancing Video Content Accessibility through YouTube Transcript Summarization;Enhanced Rear-End Collision Detection and Localization Scheme Using LSTM, DRNN, and DNN in Fog-Based Internet of Vehicles;security threats and Data Protection Methods Used in Cloud computing: A Review;load Balancing Algorithms for Cloud computing Performance: A Review;seamless Mobility: Innovating the Digital Service Landscape in Telecom Industry;Pandemic Pulse: Unveiling Insights with the Global Health Tracker through AI and ML;CNN-Based Model for real-time Identification of Face Masks;a Systematic Review of Deepfake Detection Using Learning Techniques and Vision Transformer;probabilistic Forecasting Prediction Model for Anticipating Days with Elevated Air Pollution;optimizing Graph Colorings: Unleashing the Power of Heuristic Algorithms for Enhanced Problem-Solving;a Load Balancing Approach Using Binary Search;enhancing Software Reliability through Hybrid Metaheuristic Optimization.

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Paving the Way: Advancing V2X Safety through Innovative Attack Generation and Analysis Framework (V2X-SAF) 20th

Paving the Way: Advancing V2X Safety Through Innovative Atta...

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20th international conference on Information systems Security

作者： Tomar, Shubham Tripathi, Meenakshi Malaviya Natl Inst Technol Jaipur Rajasthan India

ISBN: (纸本)9783031800191;9783031800207

Vehicle-to-Everything (V2X) communication is crucial for the advancement of modern transportation systems, enabling real-time, dependable, and actionable data exchange. this technology facilitates the dissemination of Basic Safety Messages (BSMs) between vehicles and infrastructure, thereby enhancing safety, mobility, and environmental applications. Ensuring the integrity and accuracy of V2X data is vital for effective decision-making. this paper leverages the VEINS simulation framework to introduce 25 new sophisticated attacks aimed at four newly developed safety applications. these applications have been meticulously developed from scratch. Moreover, we introduce a multi-label attack generation technique, enabling multiple simultaneous attacks within a single data packet. For instance, coordinated attacks where speed adjustments are synchronized with changes in acceleration, increasing their complexity and detection difficulty. Central to our work are the advanced detection mechanisms designed to operate on Roadside Units (RSUs). these mechanisms employ trained algorithms to identify and neutralize malicious packets in real-time simulations, significantly bolstering the security of V2X systems. this comprehensive framework not only aims to reinforce the security infrastructure of V2X networks but also to guide standardization efforts and inform deployment strategies. Additionally, the implementation of digital certificates for digital signatures serves as a primary defense against malicious entities, ensuring the authenticity and integrity of V2X communications. Our objective is to provide the security community with an effective tool for developing a resilient and secure V2X ecosystem.

关键词： Vehicle-to-Everything (V2X) Safety applications Detection Mechanisms

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SUCP Analysis for Region-Centric UAV-Assisted MEC Networks 20th

SUCP Analysis for Region-Centric UAV-Assisted MEC Networks

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20th IFIP WG 10.3 international conference on Network and Parallel computing, NPC 2024

作者： Li, Yan Yi, Zhaozhi Long, Qingmin Luo, Lailong Guo, Deke School of Computer and Communication Engineering Changsha University of Science and Technology Changsha410004 China National Key Laboratory of Information Systems Engineering National University of Defense Technology Changsha410073 China

ISBN: (纸本)9789819628636

With the increase of computing-intensive and delay-sensitive applications, mobile edge computing (MEC) technology has sprung up. It effectively satisfies the needs of user equipment (UE) for real-time computing resources by placing servers at the edge of the network. However, traditional MEC infrastructures are constrained by their fixed locations and emergency mobility needs. Unmanned aerial vehicles (UAVs) offer an effective solution with low cost, high mobility, and flexible deployment capabilities. In this paper, we propose a region-centric UAV-assisted MEC model, where the whole network space is divided into a set of hexagonal cells of equal area, and all UAVs in the same cell jointly process UE offloading data. Assume all UAVs are assumed to be equipped with independent MEC servers, and both UAVs and terrestrial UE follow independent homogeneous Poisson point process (PPP) distributions. Using the stochastic geometry analysis framework, we derive the successful uplink communication probability (SUCP) of uplink transmission for users. Finally, we compare the simulation results with the theoretical values to verify the model’s accuracy and evaluate the influence of key performance parameters on the network performance. © IFIP international Federation for Information Processing 2025.

关键词： Stochastic systems

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Hybrid Framework for real-time Traffic Flow Estimation Using Breadth-First Search 11

Hybrid Framework for Real-Time Traffic Flow Estimation Using...

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11th international conference on Vehicle Technology and Intelligent Transport systems, VEHITS 2025

作者： Mahdaviabbasabad, Sajjad Vanderhoydonc, Ynte Vandenberghe, Roeland Mercelis, Siegfried University of Antwerp imec IDLab Faculty of Applied Engineering Sint-Pietersvliet 7 Antwerp2000 Belgium Transport & Mobility Leuven Diestsesteenweg 71 Leuven3000 Belgium

ISBN: (纸本)9789897587450

Traffic flow data is essential for urban planning, logistics, transport management, and similar applications. However, achieving full sensor coverage across a road network is often infeasible due to high installation and maintenance costs. Simulation data from traffic models can help in filling this gap. However, calibrating and validating these traffic models is time-consuming. this paper presents a framework that combines real-time traffic flow predictions from sensor-equipped road segments with 24-hour static simulation data across an entire network. By applying a method based on the Breadth-First Search algorithm, this framework updates network-wide traffic flow by utilizing the data-driven predictions at sensor-equipped road segments and simulation data. Evaluation on a network with over 27000 road segments shows that this approach improves prediction accuracy over static simulation and is viable for real-time deployment. Copyright © 2025 by SCITEPRESS - Science and Technology Publications, Lda.

关键词： Urban planning

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