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检索条件"任意字段=IEEE International Conference on Embedded and Real-Time Computing Systems and Applications"

共 37219 条记录，以下是1841-1850 订阅

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FPGA Implementation of Modified Compressor for Signal Processing applications

FPGA Implementation of Modified Compressor for Signal Proces...

引用

2023 ieee international conference on Next Generation Electronics, NEleX 2023

作者： Harikrishna, K. Tripathy, S.K. National Institute of Technology Department of Electronics and Communication Assam Silchar788010 India

ISBN: (纸本)9798350319088

Multiplication plays the key role in digital signal processing, digital image processing, mobile computing, very large-scale integration (VLSI), embedded systems and several other fields. To obtain better, accurate and fast output in today's technology world we need efficient processors. To accomplish this task, we have designed a novel multiplier using (7,3) and (15,4) compressor. The high compression ratio compressors are used in the multiplication process to add the partial products results in better performance. Further, proposed method performance parameters are compared with all existing literature and found that our design is better than the existing researches. © 2023 ieee.

关键词： Field programmable gate arrays (FPGA)

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ProSwap: Period-aware Proactive Swapping to Maximize embedded Application Performance 16

ProSwap: Period-aware Proactive Swapping to Maximize Embedde...

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16th ieee international conference on Networking, Architecture and Storage (NAS)

作者： Seo, Dongjoo Maity, Biswadip Chen, Ping-Xiang Yun, Dukyoung Donyanavard, Bryan Dutt, Nikil Univ Calif Irvine Irvine CA USA Samsung Elect Suwon South Korea San Diego State Univ San Diego CA USA

ISBN: (数字)9781665454087

ISBN: (纸本)9781665454087

Linux prevents errors due to physical memory limits by swapping out active application memory from main memory to secondary storage. Swapping degrades application performance due to swap-in/out latency overhead. To mitigate the swapping overhead in periodic applications, we present ProSwap: a period-aware proactive and adaptive swapping policy for embedded systems. ProSwap exploits application periodic behavior to proactively swap-out rarely-used physical memory pages, creating more space for active processes. A flexible memory reclamation time-window enables adaptation to memory limitations that vary between applications. We demonstrate ProSwap's efficacy for an autonomous vehicle application scenario executing multi-application pipelines, and show that our policy achieves up to 1.26 x performance gain via proactive swapping.

关键词： Swap system Periodic application memory reclamation

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Checkpoint/Restart for CUDA Kernels

Checkpoint/Restart for CUDA Kernels

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2023 international conference on High Performance computing, Network, Storage, and Analysis, SC Workshops 2023

作者： Eiling, Niklas Lankes, Stefan Monti, Antonello Institute for Automation of Complex Power Systems Rwth Aachen University Aachen Germany

ISBN: (纸本)9798400707858

In HPC clusters, it has become common to employ Checkpoint/Restart (C/R), that is, saving the execution state of applications in order to restore their computational progress at a later point in time. The benefits of this technique for clusters include more flexibility when reacting to changing workloads and an increased fault tolerance. While many clusters already benefit from C/R tools for traditional CPU applications, there is a lack of comparable tools enabling preemptive and transparent C/R for heterogeneous computing, where applications execute partly on accelerator devices, such as s. This is despite the increasing use of s as accelerators in High-Performance computing (HPC) clusters. Therefore, we propose a novel C/R tool that enables saving the execution state of CUDA kernels, thus allowing preemptive C/R of applications without the need to wait for kernels to finish. We show that full-featured C/R for NVIDIA s is possible despite the proprietary nature of the hardware and software of these devices. © 2023 Owner/Author.

关键词： Fault tolerance

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applications of Digital Twin in Precision Medicine: A Systematic Review

Applications of Digital Twin in Precision Medicine: A System...

引用

2025 international conference on New Trends in computing Sciences, ICTCS 2025

作者： Pişirgen, Ali Hiziroglu, Ourania Areta Department of Management and Organization Karamanoğlu Mehmetbey University Karaman Turkey Department of Management Information Systems Izmir Bakırçay University İzmir Turkey

ISBN: (纸本)9798331523411

Digital twin (DT) technology has emerged as a transformative tool in healthcare and precision medicine, enabling personalized care through real-time simulations, predictive modelling, and patient-specific diagnostics. This systematic review analyses 94 peer-reviewed articles from the Scopus database, highlighting the role of machine learning (ML) techniques—such as supervised, unsupervised, and hybrid methods—in advancing DT applications. The study explores the integration of emerging technologies, including blockchain and generative artificial intelligence (AI), to enhance DT functionality and data security. Spanning disciplines such as cardiology, oncology, neurology, and metabolic disorders, the research underscores the interdisciplinary applications of DTs while addressing critical ethical concerns like data privacy, algorithmic bias, and regulatory challenges. Despite limitations, including reliance on a single database and subjective categorization, this review demonstrates the transformative potential of DTs and suggests future research directions in quantum computing integration and patient-centered DT design. ©2025 ieee.

关键词： artificial intelligence digital twin precision medicine

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Artificial Intelligence Models in Power Generation for Energy Consumption Prediction 4

Artificial Intelligence Models in Power Generation for Energ...

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4th international conference on Emerging Trends in Networks and Computer Communications, ETNCC 2024

作者： Tan, Lit Yang Chen Kwan, Charis Shwu Ajibade, Samuel-Soma M. Ramly, Athirah Mohd School of Engineering and Technology Sunway University Department of Computing and Information Systems Selangor Malaysia School of Architecture Computing and Engineering University of East London Department of Computing London United Kingdom

ISBN: (纸本)9798350353266

The incorporation of artificial intelligence (AI) into power-related applications signifies a new and unexplored domain in machine learning for predicting power generation. This novel method utilizes prediction models, often used in different fields, to predict energy-related patterns, providing a unique and specialized viewpoint. The synergy of academicians, AI experts, and industry professionals in the energy sector has resulted in the creation of customized AI models to optimize operational efficiency. By customizing various AI models to suit the distinct attributes of energy scenarios and datasets, these models are positioned to transform energy management methods. This study examines the utilization of AI models to enhance energy efficiency in power generation in Malaysia. The project seeks to predict future power consumption in various sectors, analyze growth rates, and identify sectors with investment potential by developing a Linear Regression model. In addition, a thorough power plan is developed using the estimated energy usage. A comparative analysis is performed to determine the most appropriate model for this particular scenario, which will improve decision-making in the energy sector. The results of this study present promising opportunities for further investigation. By broadening the study's focus to encompass a broader array of AI models and their assessment of performance, it is possible to gain useful insights for predicting power generation. Furthermore, the integration of real-time data streams and the inclusion of feedback loops in the AI models could improve their ability to adapt and increase their accuracy as time progresses. © 2024 ieee.

关键词： Prediction models

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Hardware-in-the-loop simulations of remote sensing disaster monitoring systems with real-time on-board computation 1

Hardware-in-the-loop simulations of remote sensing disaster ...

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ieee international conference on Metrology for Extended reality, Artificial Intelligence and Neural Engineering (ieee MetroXRAINE)

作者： Spiller, Dario Carbone, Andrea Latorre, Francesco Curti, Fabio Sapienza Univ Rome Sch Aerosp Engn Rome Italy

ISBN: (数字)9781665485746

ISBN: (纸本)9781665485746

real-time monitoring systems in remote sensing could enable a variety of new applications concerning emergency and disaster management. Coupling remote sensing imaging devices with hardware accelerators for artificial intelligence (AI) post-processing algorithms can pave the way for future constellations of small satellites offering services such as detection of wildfires, volcanoes eruptions, landslides, floods, etc. This paper presents MONSTER, a robotic facility hosted in the ARCA laboratory (ARCAlab) at the School of Aerospace Engineering in Rome. The facility was born as a simulator of lunar landing operations, but is currently being updated to perform hardware-in-the-loop simulation campaigns of many different scenarios including wildfires and volcanic eruption observation from space or airborne platforms. Having the possibility to perform translation and rotation maneuvers of the target observation platform, properly simulating the terrain, and performing the AI-aided computation on hardware accelerators such as graphics processing units (GPUs), visual processing units (VPUs), and field programmable gate arrays (FPGAs), the MONSTER facility could be used to efficiently simulate new remote sensing paradigms for disaster monitoring through on-the-edge artificial intelligence.

关键词： MONSTER disaster monitoring artificial intelligence real-time system edge computing

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Navigating the Future: Advancing Autonomous Vehicles through Robust Target Recognition and real-time Avoidance 4

Navigating the Future: Advancing Autonomous Vehicles through...

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4th international conference on Control Theory and applications, ICoCTA 2024

作者： Hussein, Mohammed A. M. Habib, Maki K. The American University in Cairo Robotics Control and Smart Systems Cairo Egypt The American University in Cairo Department of Mechanical Engineering Cairo Egypt

ISBN: (纸本)9798331506155

This research addresses the critical challenge of enhancing object recognition and real-time response capabilities in autonomous vehicles (AVs) under varying simulated conditions, which is crucial for ensuring both navigational safety and operational efficiency. Utilizing the Carla 0.9.14 simulator and Unreal Engine 4.26 on Ubuntu 20.04, we focus on improving the detection and classification of key on-road obstacles-vehicles, pedestrians, and cyclists-using the YOLOv7 object detection algorithm. By integrating advanced sensory technologies, specifically stereo vision cameras and LIDAR, we create a dynamic testing environment that simulates diverse urban and rural scenarios. Our methodology enhances the YOLOv7 algorithm's accuracy and speed through extensive training on a meticulously curated dataset of 4,113 images, reflecting a broad spectrum of environmental conditions, including varying lighting and weather conditions. This rigorous approach yielded a significant increase in mean average precision (mAP) from 64.3% to 76.3%, and enhanced the algorithm's reliability, with notable improvements over previous models. The research delineates a clear advancement in AV technology by demonstrating substantial improvements in object detection metrics, contributing foundational insights for future implementations in real-world settings and supporting the further development of real-time avoidance systems. This study not only progresses the field of AV but also sets a new benchmark for object detection performance, aligning with industry and academic goals to optimize AV systems for complex and unpredictable driving scenarios. © 2024 ieee.

关键词： Stereo image processing

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A Mathematical Model for the Selection of Software Requirements Elicitation Techniques 14

A Mathematical Model for the Selection of Software Requireme...

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14th international conference on Cloud computing, Data Science and Engineering, Confluence 2024

作者： Saxena, Virat Raj Yadav, Rajeev Parveen, Azra Sadiq, Mohd. Mangalayatan University Department of Computer Science and Engineering Uttar Pradesh Aligarh202001 India Indraprastha Institute of Information Sciences Private Limited Indraprastha Research Laboratory New Delhi110025 India Upfet Jamia Millia Islamia A Central University Software Engineering Laboratory Computer Engineering Section New Delhi110025 India

ISBN: (纸本)9798350344837

Various techniques have been developed for the identification of different types of requirements like interview, questionnaire, group elicitation techniques, attributed goal-oriented requirements analysis, fuzzy based goal-oriented requirements analysis method, non-functional requirements framework, etc. Based on the critical analysis of requirements elicitation methods, we found that single elicitation technique is not suitable to understand the need of the stakeholders. In real life applications, multiple elicitation techniques are required to elicit and select the requirements of an information system because each technique has its strength and limitations. Therefore, to address this issue, this paper presents a mathematical model for the selection of requirements elicitation techniques so that complete set of requirements along with its priority can be identified before the development of an information system. The institute examination system is considered to show the applicability of the proposed mathematical model. © 2024 ieee.

关键词： Information systems

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Emotion-Adaptive Pneumatic Haptic systems for Affective Movie Experiences: Integrating Biomimetic Robotics and Machine Learning

Emotion-Adaptive Pneumatic Haptic Systems for Affective Movi...

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2024 ieee international conference on Robotics and Biomimetics, ROBIO 2024

作者： Liu, Yang Shangguan, Zhegong Safin, Stephane Detienne, Francoise Lecolinet, Eric LTCI Télécom Paris Institut Polytechnique de Paris France U2is ENSTA-Paris Institut Polytechnique de Paris France Stéphane Safin is with Faculty of i3 UMR 9217-CNRS Télécom Paris Institut Polytechnique de Paris France Faculty of i3 UMR 9217-CNRS Télécom Paris Institut Polytechnique de Paris France Faculty of LTCI Telecom Paris Institut Poly-technique de Paris France

ISBN: (纸本)9781665481090

This paper presents an innovative pneumatic haptic system integrating biomimetic robotics, machine learning, and emotional engagement in cinema. Our soft robotic tactile interface, inspired by biological mechanisms, enhances movie-watching experiences through dynamic shape changes and texture patterns mimicking natural sensations. We investigate how these biologically-inspired interactions affect viewers' emotional connections to movie content. Our two-stage study demon-strates that emotions can be conveyed through biomimetic haptic stimuli and examines the impact of congruent and non-congruent feedback on emotional experiences. Additionally, we introduce a machine learning approach enabling real-time detection and response to viewers' emotional states, creating an adaptive, personalized cinematic experience. This system also provides valuable feedback for cinema managers and directors. Our work advances the intersection of robotics, biomimetics, affective computing, and human-computer interaction, contributing to the development of emotionally adaptive interfaces for entertainment applications. © 2024 ieee.

关键词： Pneumatics

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An Enhanced Copy-deterrence scheme for Secure Image Outsourcing in Cloud 3

An Enhanced Copy-deterrence scheme for Secure Image Outsourc...

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3rd ieee international conference on computing, Communication, and Intelligent systems, ICCCIS 2022

作者： Anju, J. Shreelekshmi, R. A. P. J. Abdul Kalam Technological University College of Engineering Trivandrum Department of Computer Science and Engineering Kerala Thiruvananthapuram India A. P. J. Abdul Kalam Technological University College of Engineering Trivandrum Department of Computer Applications Kerala Thiruvananthapuram India

ISBN: (纸本)9781665462006

In this paper, we propose a novel watermarking-based copy deterrence scheme for identifying data leaks through authorized query users in secure image outsourcing systems. The scheme generates watermarks unique to each query user, which are embedded in the retrieved encrypted images. During unauthorized distribution, the watermark embedded in the image is extracted to determine the untrustworthy query user. Experimental results show that the proposed scheme achieves minimal information loss, faster embedding and better resistance to JPEG compression attacks compared with the state-of-the-art schemes. © 2022 ieee.

关键词： Watermarking

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