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Contending memory in heterogeneous SoCs: Evolution in NVIDIA Tegra embedded platforms 26

Contending memory in heterogeneous SoCs: Evolution in NVIDIA...

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ieee 26th international conference on embedded and real-time computing systems and applications (RTCSA)

作者： Capodieci, Nicola Cavicchioli, Roberto Olmedo, Ignacio Sanudo Solieri, Marco Bertogna, Marko Univ Modena & Reggio Emilia Modena Italy

ISBN: (纸本)9781728144030

Modern embedded platforms are known to be constrained by size, weight and power (SWaP) requirements. In such contexts, achieving the desired performance-per-watt target calls for increasing the number of processors rather than ramping up their voltage and frequency. Hence, generation after generation, modern heterogeneous System on Chips (SoC) present a higher number of cores within their CPU complexes as well as a wider variety of accelerators that leverages massively parallel compute architectures. Previous literature demonstrated that while increasing parallelism is theoretically optimal for improving on average performance, shared memory hierarchies (i.e. caches and system DRAM) act as a bottleneck by exposing the platform processors to severe contention on memory accesses, hence dramatically impacting performance and timing predictability. In this work we characterize how subsequent generations of embedded platforms from the NVIDIA Tegra family balanced the increasing parallelism of each platform's processors with the consequent higher potential on memory interference. We also present an open-source software for generating test scenarios aimed at measuring memory contention in highly heterogeneous SoCs.

关键词： Memory Interference GP-GPU Compute Accelerators real-time Tegra

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Intelligent Industrial Controller Network Based on Modbus Fieldbus

Intelligent Industrial Controller Network Based on Modbus Fi...

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ieee/ASME international conference on Mechtronic and embedded systems and applications, MESA

作者： Ching-Han Chen Wen-Lin Chang Meng-Yan Hsieh Department of Computer Science & Information Engineering National Central University Taoyuan City Taiwan

ISBN: (纸本)9781665455718

Under the impetus of industrial internet of things and smart manufacturing applications, realizing the development and deployment of decentralized industrial controller networks is crucial. this paper designed an industrial controller network gateway, combined with the Grafcet virtual machine, for rapid development and deployment with distributed decentralized controller equipment. A gateway architecture with three microcontrollers for communication protocol management, Modbus device management, and real-time data collection and monitoring engines, respectively, was proposed in this study. the communication protocol management engine is responsible for transmission between the gateway and cloud system, thereby providing an implementation mechanism for cyber/physical system. the device management engine uses Modbus RTU to communicate with the underlying PLC controller. this engine comprises an ieee1588 time synchronization protocol that provides PLC controller time stamping and synchronization mechanisms. the real-time data collection and monitoring engine is in charge with the data sorting management function, which is used to make the database management have efficient data query function. Finally, experiments were conducted on the basis of multiple PLC controllers and robotic arms motion control to validate this industrial controller network functional usability and performance.

关键词： Cloud computing Protocols Logic gates Data collection real-time systems Virtual machining Behavioral sciences

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Student Session: Turning Over Detecting Using Super-Resolution thermal Image 26

Student Session: Turning Over Detecting Using Super-Resoluti...

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ieee 26th international conference on embedded and real-time computing systems and applications (RTCSA)

作者： Chou, Jyun-Jhe Shih, Chi-Sheng Natl Taiwan Univ Dept Comp Sci & Informat Engn Embedded Syst & Wireless Networking Lab Taipei Taiwan Natl Taiwan Univ Grad Inst Networking & Multimedia Dept Comp Sci & Informat Engn Embedded Syst & Wireless Networking Lab Taipei Taiwan

ISBN: (纸本)9781728144030

A low resolution infrared camera can use to collect the data of our daily activity, and protect privacy. However, pose detection on an extremely low resolution image will be a big challenge to deal with. Many researches show that Super-resolution may improve the accuracy of object detection on low resolution images. In this work, we detect the turning over while sleeping with low-resolution thermal sensors. To improve the accuracy of detection, we fuse the data from multiple sensors and use SRCNN to enhance the resolution. We also propose a method to reduce the noise caused by the residual body temperature on bed after turn over while detect the pose and turning over. the accuracy of pose detection is 65%, and the turning over detection has 50% recall rate and 83% precision.

关键词： Image enhancement

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Elderly smartwatch adoption: A conceptual model development 13

Elderly smartwatch adoption: A conceptual model development

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13th international conference on Electronics, Computers and Artificial Intelligence, ECAI 2021

作者： Cristescu, Irina Bajenaru, Lidia National Institute for Research and Development in Informatics Systems and Applications for Society Department Bucharest Romania

ISBN: (纸本)9781665425346

Smartwatches have become viable devices that offer older adults immediate feedback on vital signs, thus providing real-time health information and support in healthcare assistance. the present study focuses on proposing a conceptual model for elderly smartwatch adoption. the conceptual model includes factors that have been included in prior studies when analyzing the smartwatch adoption, but have never been used altogether in the Unified theory of Acceptance and Use of Technology (UTAUT) model. the proposed factors are defined and corresponding hypotheses concerning the relationship between the factors that contribute to the adoption of smartwatches among older adults are formulated. Moreover, analytical procedures that will be used to validate the conceptual model are presented. © 2021 ieee.

关键词： Internet of things

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ProAI: An Efficient embedded AI Hardware for Automotive applications - a Benchmark Study 18

ProAI: An Efficient Embedded AI Hardware for Automotive Appl...

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18th ieee/CVF international conference on Computer Vision (ICCV)

作者： Mantowsky, Sven Heuer, Falk Bukhari, Syed Saqib Keckeisen, Michael Schneider, Georg ZF Friedrichshafen AG Artificial Intelligence Lab Saarbrucken Germany ZF Friedrichshafen AG Autonomous Mobil Syst Saarbrucken Germany

ISBN: (纸本)9781665401913

Development in the field of Single Board Computers (SBC) have been increasing for several years. they provide a good balance between computing performance and power consumption which is usually required for mobile platforms, like application in vehicles for Advanced Driver Assistance systems (ADAS) and Autonomous Driving (AD). However, there is an ever-increasing need of more powerful and efficient SBCs which can run power intensive Deep Neural Networks (DNNs) in real-time and can also satisfy necessary functional safety requirements such as Automotive Safety Integrity Level (ASIL). "ProAI" is being developed by ZF mainly to run powerful and efficient applications such as multitask DNNs and on top of that it also has the required safety certification for AD. In this work, we compare and discuss state of the art SBC on the basis of power intensive multitask DNN architecture called Multitask-CenterNet with respect to performance measures such as, FPS and power efficiency. As an automotive supercomputer, ProAI delivers an excellent combination of performance and efficiency, managing nearly twice the number of FPS per watt than a modern workstation laptop and almost four times compared to the Jetson Nano. Furthermore, it was also shown that there is still power in reserve for further and more complex tasks on the ProAI, based on the CPU/GPU utilization during the benchmark.

关键词： Performance evaluation Deep learning Technological innovation Power demand Computer architecture Benchmark testing Safety

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FPGA-based real-time High-resolution Image Processing for rocket on-board processing

FPGA-based Real-time High-resolution Image Processing for ro...

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international conference on Computer Research and Development (ICCRD)

作者： Hui Zhou Xiaofeng Wang YuJia Xie Yongxiang Cao Yu Tang Yongchun Huo Huan Wen Xiongbo Zhao Chaoran Li Beijing Aerospace Automatic Control Institute National key Laboratory of Science and Technology on Aerospace Intelligent Control Beijing China Computer Science and Engineering Beihang University Beijing China National Superior College for Engineers Beihang University Beijing China

ISBN: (数字)9798331531881

ISBN: (纸本)9798331531898

the structure of the rocket-borne model is inherently complex, with processed images exhibiting high resolution and generating substantial amounts of data and calculations. Achieving robust real-time computing on an embedded platform poses significant challenges due to strictly limited resources, power consumption constraints, and size limitations. Our review of rocket-borne applications reveals considerable variability in the design resources of different devices, indicating a need for expanded design approaches. Upon evaluating existing methods, we identified two primary drawbacks. First, certain operators within the high-resolution target detection model are difficult to parallelize, resulting in significant inference delays that hinder the ability to meet task requirements. Although existing methods have been extended, there remains significant potential for performance enhancement in core scheduling for poor acceleration. this paper proposes an optimized architecture for the target detection algorithm accelerator designed for high-resolution images, along with a novel highly parallel data pre-processing and post-processing module implemented on FPGA to address these issues. Compared to the ARM implementation, this architecture demonstrates an improved performance of 24.64x. Furthermore, to ensure flexible application across various rocket launch scenarios, we introduce an optimization structure for convolution, pooling, and fusion operators and a multi-core expansion optimization method. this approach yields a 1.29x improvement in computing unit utilization compared to state-of-the-art multi-core scaling efforts. Finally, we assessed the accelerator architecture across multiple FPGA platforms, achieving a peak processing element utilization rate of 99.71% for a single core and layer. the overall computing efficiency, excluding the first layer, exceeded 90%. the peak computing power for the four cores reached 1638.4 GOPS, and the end-to-end computation time for

关键词： YOLO Rockets Power demand Convolution Multicore processing Reviews Scalability Accelerator architectures real-time systems Field programmable gate arrays

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2018 14th ieee/ASME international conference on Mechatronic and embedded systems and applications, MESA 2018

2018 14th IEEE/ASME International Conference on Mechatronic ...

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14th ieee/ASME international conference on Mechatronic and embedded systems and applications, MESA 2018

ISBN: (纸本)9781538646434

the proceedings contain 60 papers. the topics discussed include: sensor-embedded linear ball bearing for linear guide way pre-load and straightness monitoring;multi-robot coordination through mobile agent;research of vehicle parameter and sensor systems necessary to control autonomous vehicles;machine learning approach for predictive maintenance in Industry 4.0;filtering scheme for context-aware fog computing in cyber-physical systems;the sensing technology of applying the acoustic emission sensor to the grinding wheel loading phenomenon;accelerating Viterbi algorithm using custom instruction approach;design, development and experimental evaluation of a vortex actuation system;optimal map-based mode selection and powertrain control for a multi-mode plug-in hybrid electric vehicle;spline-based energy-optimal trajectory planning for functionally redundant robots;simulation analysis and performance evaluation of a vibratory feeder actuated by dielectric elastomers;machine learning-based approaches to analyse and improve the diagnosis of endothelial dysfunction;real-time and robust collaborative robot motion control with Microsoft Kinect® V2;control design of an electro-pneumatic gearbox actuator;modeling and simulation of hybrid electric ships with AC power busa case study;low-power wake-up system based on frequency analysis for environmental Internet of things;and scalability of GPU-processed 3D distance maps for industrial environments.

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Pitch and Heading Angles Estimation by Airplane Trajectory Data Available in ADS-B

Pitch and Heading Angles Estimation by Airplane Trajectory D...

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international Scientific and Practical conference on Electronics and Information Technologies (ELIT)

作者： Ivan Ostroumov Air Navigation Systems Department National Aviation University Kyiv Ukraine

A number of Automatic Dependent Surveillance- Broadcast (ADS-B) applications is increasing every year. Nowadays each airspace user should be equipped with a transponder of mode 1090ES to identify itself in the air traffic. Vary of settings of on-board transponders provides a different list of parameters for sharing. the most common parameters include a unique identification code of user and a position report including latitude, longitude, and pressure altitude. Missing airplane orientation angles in ADS-B data set could be a problem for tasks of air traffic surveillance and airplane visualization in flight simulator software. Also, orientation angles could improve performance of traj ectory filtering and prediction of airplane position in real-time data processing. In the paper, we consider calculation of pitch and heading angles based on trajectory data obtained by ADS-B. Also, analytical formulas for airplane orientation angles calculation based on ADS-B data are proposed in the paper. ADS-B trajectory data usually are not synchronized and include multiple gaps. A linear regression model with B-splines functions is used for trajectory data interpolation for a given time series. Also, surveillance data are used for vertical and ground speed calculation. Calculated orientation angles and interpolated position data form an array of six Degrees of Freedom (6DoF), which is widely used in different visualization tools.

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Identification and Validation of Markov Models with Continuous Emission Distributions for Execution times 26

Identification and Validation of Markov Models with Continuo...

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ieee 26th international conference on embedded and real-time computing systems and applications (RTCSA)

作者： Friebe, Anna Papadopoulos, Alessandro, V Nolte, thomas Malardalen Univ Vasteras Sweden

ISBN: (纸本)9781728144030

It has been shown that in some robotic applications, where the execution times cannot be assumed to be independent and identically distributed, a Markov Chain with discrete emission distributions can be an appropriate model. In this paper we investigate whether execution times can be modeled as a Markov Chain with continuous Gaussian emission distributions. the main advantage of this approach is that the concept of distance is naturally incorporated. We propose a framework based on Hidden Markov Model (HMM) methods that 1) identifies the number of states in the Markov Model from observations and fits the Markov Model to observations, and 2) validates the proposed model with respect to observations. Specifically, we apply a tree-based cross-validation approach to automatically find a suitable number of states in the Markov model. the estimated models are validated against observations, using a data consistency approach based on log likelihood distributions under the proposed model. the framework is evaluated using two test cases executed on a Raspberry Pi Model 3B+ single-board computer running Arch Linux ARM patched with PREEMPT RT. the first is a simple test program where execution times intentionally vary according to a Markov model, and the second is a video decompression using the ffmpeg program. the results show that in these cases the framework identifies Markov Chains with Gaussian emission distributions that are valid models with respect to the observations.

关键词： real-time systems Markov Chain Model Probabilistic Timing Analysis

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A Miniature Millimeter-Wave Radar Based Contactless Lithium Polymer Battery Capacity Sensing with Edge Artificial Intelligence

A Miniature Millimeter-Wave Radar Based Contactless Lithium ...

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ieee/ASME international conference on Mechtronic and embedded systems and applications, MESA

作者： Di An YangQuan Chen Electrical Engineering & Computer Science University of California Merced Department of Mechanical Engineering University of California Merced

ISBN: (纸本)9781665455718

It is widely known that the remaining capacity of any lithium polymer (Li-Po) rechargeable battery is hard to know precisely in real time. Battery management systems (BMS) are used to precisely monitor battery health including state of charge (SOC) and the remaining capacity. But, BMS is usually limited by its size, power consumption, and compatibility, which could potentially have a negative impact on the battery powered mission such as long distance drone flights. therefore, in this study, we present a new approach for (Li-Po) battery capacity sensing using a miniature millimeter Wave radar array in real-time. We assessed our contactless battery capacity sensing method with a classifier algorithm using labeled data collected from real battery discharging load circuit experiments. According to the results, our technique achieved 98.8% classification accuracy across eight different battery capacity levels. the machine learning algorithm is computationally light and easily implementable on edge computing platforms such as the Raspberry Pi. this work confirms that it is feasible to sense the real-time remaining capacity of Li-Po batteries that can lead to a capacity-aware cognitive battery management system.

关键词： Machine learning algorithms Millimeter wave radar Lithium real-time systems Batteries Sensors State of charge

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