Výsledky vyhledávání - Computer systems organization Embedded and cyber-physical systems Embedded systems

Hybrid brain–computer interface for biomedical cyber-physical system application using wireless embedded EEG systems Autor Chai, Rifai, Naik, Ganesh R., Ling, Sai Ho, Nguyen, Hung T.

“…Background One of the key challenges of the biomedical cyber-physical system is to combine cognitive neuroscience with the integration of physical systems to assist people with disabilities…”
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Siemens AG Files Patent Application for Method and Computer-Program-Product Determining Measures for the Development, Design and/or Deployment of Complex Embedded or Cyber-Physical Systems, in Particular Complex Software Architectures Used Therein, of Different Technical Domains

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Siemens (SIE) issued patent titled "Method and computer-program-product determining measures for the development, design and/or deployment of complex embedded or cyber-physical systems, in particular complex software architectures used therein, of different technical domains"

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WIPO PUBLISHES PATENT OF SIEMENS FOR "METHOD AND COMPUTER-PROGRAM-PRODUCT DETERMINING MEASURES FOR THE DEVELOPMENT, DESIGN AND/OR DEPLOYMENT OF COMPLEX EMBEDDED OR CYBER-PHYSICAL SYSTEMS, IN PARTICULAR COMPLEX SOFTWARE ARCHITECTURES USED THEREIN, OF DIFFERENT TECHNICAL DOMAINS" (GERMAN INVENTORS)

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US Patent Issued to Siemens on April 5 for "Method and computer-program-product determining measures for the development, design and/or deployment of complex embedded or cyber-physical systems, in particular complex software architectures used therein, of different technical domains" (German, American Inventors)

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Saveetha Institute of Medical and Technical Sciences Files Patent Application for Cyber Physical System to Manage Human Resource of an Organization Employing Computer Network

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Analyzing and Improving Fault Tolerance of Learning-Based Navigation Systems Autor Wan, Zishen, Anwar, Aqeel, Hsiao, Yu-Shun, Jia, Tianyu, Reddi, Vijay Janapa, Raychowdhury, Arijit

“…Learning-based navigation systems are widely used in autonomous applications, such as robotics, unmanned vehicles and drones…”
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Control Variate Approximation for DNN Accelerators Autor Zervakis, Georgios, Spantidi, Ourania, Anagnostopoulos, Iraklis, Amrouch, Hussam, Henkel, Jorg

“…In this work, we introduce a control variate approximation technique for low error approximate Deep Neural Network (DNN) accelerators. The control variate…”
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Reinforcement Learning-Assisted Management for Convertible SSDs Autor Wei, Qian, Li, Yi, Jia, Zhiping, Zhao, Mengying, Shen, Zhaoyan, Li, Bingzhe

“…Convertible SSDs, which allow flash cells to convert between different types of flash cells (e.g., SLC/MLC/TLC/QLC), are designed for achieving both high…”
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DyREM: Dynamically Mitigating Quantum Readout Error with Embedded Accelerator Autor Zhou, Kaiwen, Lu, Liqiang, Zhang, Hanyu, Xiang, Debin, Tao, Chenning, Zhao, Xinkui, Zheng, Size, Yin, Jianwei

“… In this paper, we propose DyREM, a software-hardware codesign approach that mitigates readout errors with an embedded accelerator…”
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Dancing along Battery: Enabling Transformer with Run-time Reconfigurability on Mobile Devices Autor Song, Yuhong, Jiang, Weiwen, Li, Bingbing, Qi, Panjie, Zhuge, Qingfeng, Sha, Edwin Hsing-Mean, Dasgupta, Sakyasingha, Shi, Yiyu, Ding, Caiwen

“…A pruning-based AutoML framework for run-time reconfigurability, namely RT 3 , is proposed in this work. This enables Transformer-based large Natural Language…”
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PowerPruning: Selecting Weights and Activations for Power-Efficient Neural Network Acceleration Autor Petri, Richard, Zhang, Grace Li, Chen, Yiran, Schlichtmann, Ulf, Li, Bing

“…Deep neural networks (DNNs) have been successfully applied in various fields. A major challenge of deploying DNNs, especially on edge devices, is power…”
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TEASER: Simulation-Based CAN Bus Regression Testing for Self-Driving Cars Software Autor Birchler, Christian, Rohrbach, Cyrill, Kim, Hyeongkyun, Gambi, Alessio, Liu, Tianhai, Horneber, Jens, Kehrer, Timo, Panichella, Sebastiano

“…Safety-critical systems such as self-driving cars (SDCs) must be rigorously tested…”
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KLiNQ: Knowledge Distillation-Assisted Lightweight Neural Network for Qubit Readout on FPGA Autor Guo, Xiaorang, Bunarjyan, Tigran, Liu, Dai, Lienhard, Benjamin, Schulz, Martin

“…Superconducting qubits are among the most promising candidates for building quantum information processors. Yet, they are often limited by slow and error-prone…”
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Mirage: An RNS-Based Photonic Accelerator for DNN Training Autor Demirkiran, Cansu, Yang, Guowei, Bunandar, Darius, Joshi, Ajay

“… and the analog noise inherent in photonic hardware. This paper proposes Mirage, a photonic DNN training accelerator that overcomes the precision challenges in photonic hardware using the Residue Number System (RNS…”
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MOSAIC: Heterogeneity-, Communication-, and Constraint-Aware Model Slicing and Execution for Accurate and Efficient Inference Autor Han, Myeonggyun, Hyun, Jihoon, Park, Seongbeom, Park, Jinsu, Baek, Woongki

“…Heterogeneous embedded systems have surfaced as a promising solution for accurate and efficient deep-learning inference on mobile devices…”
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DeepPUFSCA: Deep learning for Physical Unclonable Function attack based on Side Channel Analysis support Autor Doan, Ngoc Phu, Pham, Tuan Dung, Zhang, Zichi, Tran, Viet Hung, Miskelly, Jack, Vandierendonck, Hans, Hoang, Anh Tuan, O'Neill, Maire, Mai, Thai Son

“…Physical Unclonable Function (PUF) poses a vulnerability that it could be imitated by machine learning attacks and side channel attacks, which break its…”
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LA-MTL: Latency-Aware Automated Multi-Task Learning Autor Sampath, Shambhavi Balamuthu, Sawani, Sami, Thoma, Moritz, Frickenstein, Lukas, Mori, Pierpaolo, Fasfous, Nael, Vemparala, Manoj Rohit, Frickenstein, Alexander, Schlichtmann, Ulf, Passerone, Claudio, Stechele, Walter

“… This is particularly attractive for real-time applications that require simultaneous execution of multiple workloads in resource-constrained embedded environments…”
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OmniBoost: Boosting Throughput of Heterogeneous Embedded Devices under Multi-DNN Workload Autor Karatzas, Andreas, Anagnostopoulos, Iraklis

“… Equipped with a diverse set of accelerators, newer embedded system present architectural heterogeneity, which current run-time controllers are unable to fully utilize…”
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Recommending Pre-Trained Models for IoT Devices Autor Patil, Parth V., Jiang, Wenxin, Peng, Huiyun, Lugo, Daniel, Kalu, Kelechi G., LeBlanc, Josh, Smith, Lawrence, Heo, Hyeonwoo, Aou, Nathanael, Davis, James C.

“…The availability of pre-trained models (PTMs) has enabled faster deployment of machine learning across applications by reducing the need for extensive…”
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