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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 36894 条记录，以下是621-630 订阅

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Towards a Development Process for Multi-CPU Distributed Synchronous Software applications

Towards a Development Process for Multi-CPU Distributed Sync...

引用

ACM/ieee international conference on Model Driven Engineering Languages and systems (MODELS)

作者： Lubat, Eric Jenn, Eric Blouin, Dominique Kaufmann, Marc IRT St Exupery Toulouse France Inst Polytech Paris LTCI Telecom Paris Palaiseau France Safran Elect & Def Massy France

ISBN: (纸本)9798350324983

In the domain of safety critical real-time computing, the ever increasing demand for processing power and robust safety guarantees has fueled the development of solutions to support the development of multicore and multi-CPU distributed software architectures. These architectures offer the potential for achieving enhanced computational power by exploiting the high-level of hardware parallelism, but they also raise significant challenges in ensuring temporal guarantees, such as the absence of deadlocks and race conditions, compliance with time budgets, etc. In this paper we present our ongoing work of developing a workflow for developing multi-CPU software applications from high level requirements down to the integrated system. The workflow is supported by several models and is specified with the FTG+PM formalism. We illustrate the workflow using two industrial applications from the aeronautical domain.

关键词： MBSE Process Multi-CPU Distributed Requirements

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Simulating Synchronization Issues on a Multiprocessor embedded System for Testing 2

Simulating Synchronization Issues on a Multiprocessor Embedd...

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2nd international conference on Business Analytics for Technology and Security, ICBATS 2023

作者： Zafar, Fareeha Ahmad, Saeed Amjad, Muhammad Waqar, Nazish Al-Khasawneh, Mahmoud Ahmad Ali, Sehrish GC University Lahore Department of Computer Science Pakistan Riphah International University Lahore Pakistan Administration and Economics National College of Business Lahore Pakistan Applied Science Private University Applied Science Research Center Amman11937 Jordan Skyline University College School of Information Technology University City Sharjah Sharjah1797 United Arab Emirates

ISBN: (纸本)9798350335644

Widely used embedded systems are applied to conquer the rapidly increasing demands of embedded systems of today, which start with a simple home device to systems with extensive architecture. They can perform a number of complex jobs in a lot of working conditions. The most common issue faced by embedded software is synchronization and it is used to maintain system integrity while conducting applications, the processing. While testing multi-PEs-based embedded systems is more complex to undertake so these issues are focused on synchronous or asynchronous real-time inter-processor communication in order to improve accuracy and timing. The research introduces a method for possible synchronization challenges across PEs. © 2023 ieee.

关键词： embedded systems

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Cloud computing and AI for Cyberstalking Prevention: A Comprehensive Approach 5

Cloud Computing and AI for Cyberstalking Prevention: A Compr...

引用

5th international conference on IoT Based Control Networks and Intelligent systems, ICICNIS 2024

作者： Sinha, Pallav Chandra Sinha, Raj Jayoti Vidyapeeth Women's University Department of Computer Science Rajasthan Jaipur India School of Computer Applications Lovely Professional University Punjab Jalandhar India

ISBN: (纸本)9798331518097

Cyberstalking has become an increasingly prevalent and concerning issue in today's digital landscape. The widespread use of online platforms and social media has made individuals more susceptible to predatory behavior. This study delves into the potential of utilizing cloud computing and artificial intelligence (AI) to improve the identification, prevention, and reduction of cyberstalking. It investigates how AI-driven models and cloud infrastructure can work together to provide scalable, real-time solutions to combat this problem. The research also delves into the ethical considerations, technological frameworks, and legal ramifications of integrating AI into the battle against cyberstalking, with the goal of presenting a comprehensive strategy for future implementations. © 2024 ieee.

关键词： Cloud platforms

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IoT and BSN applications for real time Monitoring and Disease Prediction

IoT and BSN Applications for Real Time Monitoring and Diseas...

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2024 OPJU international Technology conference on Smart computing for Innovation and Advancement in Industry 4.0, OTCON 2024

作者： Meena, Jaishree Shukla, Vivek Jain, Amit Gupta, Vishan Kumar Jain, Paras Amity University Punjab Amity School of Biological Science Mohali India Amity University Punjab Amity Law School Mohali India Op Jindal University Department of Cse Raigarh India Amity University Punjab Amity School of Engineering and Technology Mohali India Vit Bhopal University School of Computing Science and Engineering Madhya Pradesh Sehore India

ISBN: (纸本)9798350373783

IoT applications have been applied to health areas, so in the most advanced healthcare application environment, using them makes medical professionals and patients' lives easier. BSN (Body Sensor Network) technology is essential to the Internet of Things (IoT) in the healthcare system because it allows for the use of low-power, lightweight wireless sensor nodes to monitor patients. Healthcare systems utilizing BSN and IoT technologies are the subject of this paper. There are several sensors in this system, including blood pressure, temperature, and pulse rate sensors. The controller receives the data from these sensors after they have detected the parameters. When the temperature rises above the specified range, the buzzer will sound, per the conditions. For display on the LCD, it transports the sensed data. Doctors receive data via the internet at the same time, enabling them to provide prompt, appropriate solutions in real time. Many patients endure suffering because of not receiving prompt, appropriate assistance and solutions to their problems. Thus, the suggested system aids in an emergency and a real-time solution. Because this system is portable, it can be carried around by an individual. As a result, ongoing health monitoring is feasible. Moreover, the system uses a variety of supervised learning algorithms to forecast the illness for a specific patient based on their current reading. © 2024 ieee.

关键词： Body sensor networks

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A proof-of-concept real-time processing to characterize vascular flow 44

A proof-of-concept real-time processing to characterize vasc...

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44th Annual international conference of the ieee-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Shah, Sahil Toreyin, Hakan Noyan, Utku Lee, Yoo Jin Univ Maryland Dept Elect & Comp Engn College Pk MD 20742 USA San Diego State Univ Dept Elect & Comp San Diego CA 92182 USA Univ Calif San Francisco Dept Radiol & Biomed Imaging San Francisco CA 94143 USA

ISBN: (数字)9781728127828

ISBN: (纸本)9781728127828

In dialysis patients, monitoring vascular flow of the surgically created arteriovenous fistula (AVF) is critical to indicate the success of the AVF as a dialysis access site. Current gold standard to quantify vascular flow involves external doppler evaluation which requires frequent visits to the clinic. In this paper, we present a proof-of-concept cost-efficient vascular flow monitoring system towards a wearable and robust blood flow monitoring system. The proposed system captures beat-to-beat blood flow from impedance plethysmography (IPG) signal and performs embedded computing to robustly map the changes in the IPG to peripheral blood flow. We present the proof-of-concept results for the embedded real-time blood flow computing from measurements obtained using a custom electrical bioimpedance hardware presented previously elsewhere. We anticipate the results serving as the first step towards potentially eliminating the need for using expensive and bulky systems that require specialized personnel to operate for peripheral blood flow monitoring.

关键词： Patient monitoring embedded computing Surgery real-time systems Hardware Personnel Impedance

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Enhancing IoT Workloads: A Comparative Study of Fog and Edge computing Scheduling Algorithms

Enhancing IoT Workloads: A Comparative Study of Fog and Edge...

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2024 international conference on Circuit, systems and Communication, ICCSC 2024

作者： Chafi, Saad-Eddine Balboul, Younes Fattah, Mohammed Mazer, Said El Bekkali, Moulhime Sidi Mohamed Ben Abdellah University Artificial Intelligence Data Sciences and Emerging Systems Laboratory Fez Morocco

ISBN: (纸本)9798350365306

This work presents a comparative analysis of fog and edge computing scheduling algorithms, focusing on their impact on IoT workload optimization. The analysis considers task allocation, load balancing, energy efficiency, latency, and scalability. An advanced experimental setup with diverse workload scenarios simulates real-world IoT environments. Existing algorithms, alongside modifications and novel introductions, are evaluated. real-world applications showcase practical considerations and the adaptability of these algorithms. Refined metrics capture both immediate and long-term effects on scalability. The results inform future fog and edge computing research, considering emerging technologies. The study identifies key factors for optimizing IoT workloads and highlights the importance of scheduling algorithms for maximizing performance. © 2024 ieee.

关键词： Scheduling algorithms

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Computational Offloading for Non-time-Critical applications 42

Computational Offloading for Non-Time-Critical Applications

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42nd ieee international conference on Distributed computing systems (ICDCS)

作者： Patsch, Richard Univ Appl Sci Tech Wien Vienna Austria

ISBN: (数字)9781665471770

ISBN: (纸本)9781665471770

The increasing demand for computational resources keeps outpacing available User Equipment (UE). To overcome intrinsic hardware limitations of UEs, computational offloading was proposed. The combination of UE and seemingly endless computational capacity in the cloud aims to cope with those limitations. Numerous frameworks leverage Edge computing (EC) but a significant drawback of this is the required infrastructure. Some use cases however, do not benefit from lower response time and can remain in the cloud, where more potent resources are at one's disposal. Main contributions are to determine computational demands, allocate serverless resources, partition code and integrate computational offloading into a modern software deployment process. By focusing on non-time-critical use cases, drawbacks of EC can be neglected to create a more developerfriendly approach. Originality lies in the resource allocation of serverless resources for such endeavours, appropriate deployment of partitions and integration into CI/CD pipelines. Methodology used will be Design Science Research. Thus, many iterations and proof-of-concept implementations yield knowledge and artefacts.

关键词： computational offloading mobile cloud computing partitioning serverless

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Research on the Application of Artificial Intelligence Technology in Microelectronics Testing and Fault Diagnosis 3

Research on the Application of Artificial Intelligence Techn...

引用

3rd international conference on Data Analytics, computing and Artificial Intelligence, ICDACAI 2024

作者： Zhang, Yiqun Liu, Hailin Xu, Feng Weifang Engineering Vocational College Shandong Qingzhou262500 China

ISBN: (纸本)9798331519032

This paper explores the integration of Artificial Intelligence (AI) technologies in the field of microelectronics testing and troubleshooting. Traditional methods for testing and troubleshooting microelectronic devices often face challenges such as high complexity, time-consumption, and the need for expert *** technologies, with their advanced capabilities in machine learning, neural networks, and expert systems, offer promising solutions to these problems. This study provides an overview of the key AI approaches employed in microelectronics, discusses their implementation in various test and diagnostic scenarios, and evaluates their impact in terms of improved accuracy, efficiency, and automation. Through a detailed analysis of case studies and real-world applications, the paper demonstrates how AI-driven approaches are revolutionizing the microelectronics industry, paving the way for more reliable and sophisticated electronic devices. The study concludes with a discussion of the current limitations of AI technologies in the field and suggests potential directions for future research and development. © 2024 ieee.

关键词： Expert systems

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Autonomous realization of Safety- and time-Critical embedded Artificial Intelligence

Autonomous Realization of Safety- and Time-Critical Embedded...

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27th Design, Automation and Test in Europe conference and Exhibition (DATE)

作者： Linden, Joakim Ermedahl, Andreas Salomonsson, Hans Daneshtalab, Masoud Forsberg, Bjorn Carbone, Paris SAAB AB Dept Aeronaut Engn Linkoping Sweden Ericsson AB Network Div Kista Sweden EMBEDL AB Gothenburg Sweden Malardalens Univ Sch Innovat Design & Engn Vasteras Sweden RISE Res Inst Sweden AB Dept Comp Sci Kista Sweden KTH Royal Inst Technol Sch Elect Engn & Comp Sci Kista Sweden

ISBN: (纸本)9798350348606;9783981926385

There is an evident need to complement embedded critical control logic with AI inference, but today's AI-capable hardware, software, and processes are primarily targeted towards the needs of cloud-centric actors. Telecom and defense airspace industries, which make heavy use of specialized hardware, face the challenge of manually hand-tuning AI workloads and hardware, presenting an unprecedented cost and complexity due to the diversity and sheer number of deployed instances. Furthermore, embedded AI functionality must not adversely affect real-time and safety requirements of the critical business logic. To address this, end-to-end AI pipelines for critical platforms are needed to automate the adaption of networks to fit into resource-constrained devices under critical and real-time constraints, while remaining interoperable with de-facto standard AI tools and frameworks used in the cloud. We present two industrial applications where such solutions are needed to bring AI to critical and resource-constrained hardware, and a generalized end-to-end AI pipeline that addresses these needs. Crucial steps to realize it are taken in the industry-academia collaborative FASTER-AI project.

关键词： machine learning embedded systems

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A Lightweight RGB-T Fusion Network for Practical Semantic Segmentation 26

A Lightweight RGB-T Fusion Network for Practical Semantic Se...

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ieee 26th international conference on Intelligent Transportation systems (ITSC)

作者： Zhang, Haoyuan Li, Zifeng Wu, Zhenyu Wang, Danwei EEE NTU Singapore Singapore

ISBN: (纸本)9798350399462

Semantic segmentation of RGB-T images is a complex task due to the challenges involved in fusing information from multi-modalities, which requires significant computational resources. This paper presents a novel and lightweight network architecture for RGB-T semantic segmentation that incorporates a parameter-free feature fusion module to integrate complementary information from different modalities. Furthermore, we propose a pretrained parameter selection strategy to improve convergence speed and accuracy. The network is designed to be computationally efficient and lightweight, making it well-suited for real-time applications. Our network architecture employs middle fusion techniques to extract features with separate encoders from the different modalities, and then a parameter-free cross-modal attention mechanism is designed to selectively connect the most relevant information from each modality. Additionally, we investigate the impact of pretrained parameter selection on the performance of the network. Experimental results on an urban scene dataset demonstrate that our approach outperforms real-time state-of-the-art methods in the literature while showing comparable performance with state-of-the-art methods that require up to 100 times the computational complexity. Our findings highlight the potential of the RGB-T fusion-based semantic segmentation for applications in real-world scenarios.

关键词： RGB-T fusion semantic segmentation multi-spectrum deep-learning applications

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