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Advanced Control Methods for Particle Accelerators (ACM4PA) 2019 Workshop Report
[article]
2020
arXiv
pre-print
Preserved Fulltext
existing and future accelerators and to create a plan for developing a new family of algorithms that can be shared and maintained by the community. ...
Currently, a few individual accelerator labs have been developing and applying their own diagnostics tools and custom control and ML algorithms for automated machine tuning and optimization. ...
to map the new magnet setting to the old simulation-based setting, to be fed into the NN to predict the new phase space. ...
arXiv:2001.05461v1
fatcat:xrrwhp5lfnaorpgvvuab5wm2rq
Adaptive Informative Path Planning Using Deep Reinforcement Learning for UAV-based Active Sensing
[article]
2022
arXiv
pre-print
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We introduce several components making our approach applicable for robotic tasks with high-dimensional state and large action spaces. ...
To address this, we propose a new approach for informative path planning based on deep reinforcement learning (RL). ...
ACKNOWLEDGEMENT We would like to thank Jordan Bates from Forschungszentrum Jülich for providing the real-world data. ...
arXiv:2109.13570v2
fatcat:2tkvura4xfcdjjokgrj6zwgsyy
Thermal Heating in ReRAM Crossbar Arrays: Challenges and Solutions
[article]
2023
arXiv
pre-print
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The higher speed, scalability and parallelism offered by ReRAM crossbar arrays foster development of ReRAM-based next generation AI accelerators. ...
At the same time, sensitivity of ReRAM to temperature variations decreases R_on/Roff ratio and negatively affects the achieved accuracy and reliability of the hardware. ...
A P sustainable and pollution-free temperature-controlled ReRAM devices. These can be applied for the production of temperature-controlled sensors and detectors as well as medical treatment devices. ...
arXiv:2212.13707v2
fatcat:fpnle2pl3jd27kdq72xudz7bfm
Deep-Learning-Based Drive-by Damage Detection System for Railway Bridges
2022
Infrastructures
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Among different attempts, vibration-based indirect damage identification systems have shown great promise in providing real-time information on the state of bridge damage. ...
For this purpose, a deep Convolutional Neural Network is optimised, trained and tested to detect damage using a simulated acceleration response on a nominal RC4 power car passing over a 15 m simply supported ...
This paper presents the first attempt at employing 2D CNN algorithms for vibration-based damage detection using train-borne acceleration signals. ...
doi:10.3390/infrastructures7060084
fatcat:7boki22ftndrpgmskklkvg6kga
A Survey of FPGA-Based Robotic Computing
[article]
2021
arXiv
pre-print
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With specialized designed hardware logic and algorithm kernels, FPGA-based accelerators can surpass CPU and GPU in performance and energy efficiency. ...
In this paper, we give an overview of previous work on FPGA-based robotic accelerators covering different stages of the robotic system pipeline. ...
Filter based (e.g., Extended Kalman Filter) and numerical optimization based (e.g., bundle adjustment) algorithms are two prevalent methods for SLAM back-end. ...
arXiv:2009.06034v3
fatcat:fnp5q5wcyrd2hgpllso22mv2xm
COVID-19 Pandemic Response Robot
2022
Machines
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In conclusion, Google Cartographer for building a map, Convolutional Neural Network for mask wearing detection, and only looking once for human face detection achieve the best result among all algorithms ...
This paper proposes applying Simultaneous Localization and Mapping in an unknown environment and using deep learning for detection of temperature, mask wearing, and human face on the Raspberry Pi to overcome ...
It is also a system which provides real-time SLAM in 2D and 3D. For 2D and 3D internal SLAM, the main sensor relies on LiDAR and inertial navigation [16] . ...
doi:10.3390/machines10050351
fatcat:ynem6bbvonbffegijn2hbjfwcy
Privacy-Preserved Fall Detection Method with Three-Dimensional Convolutional Neural Network Using Low-Resolution Infrared Array Sensor
2020
Sensors
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For such a situation, many kinds of human motion detection systems have been in development, many of which are based on portable devices attached to a user's body or external sensing devices such as cameras ...
In this study, a human motion detection system using a low-resolution infrared array sensor was developed to protect the safety and privacy of people who need to be cared for in hospitals and nursing homes ...
Correct answer rates of LSTM network and 3D CNN for each frame number.
Figure 12 . 12 Figure 12. Correct answer rates of LSTM network and 3D CNN for each frame number.
Figure 13 . 13 Figure 13. ...
doi:10.3390/s20205957
pmid:33096820
fatcat:vpyczieecjdi7g7o5ybcgzmalu
SPRING: A Sparsity-Aware Reduced-Precision Monolithic 3D CNN Accelerator Architecture for Training and Inference
[article]
2020
arXiv
pre-print
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In this paper, we propose SPRING, a SParsity-aware Reduced-precision Monolithic 3D CNN accelerator for trainING and inference. SPRING supports both CNN training and inference. ...
To take advantage of sparsity, some accelerator designs explore sparsity encoding and evaluation on CNN accelerators. ...
FPGA-based accelerators achieve faster time-to-market and enable prototyping of new accelerator designs. ...
arXiv:1909.00557v2
fatcat:b2kemi4qrnd2fmv32wkkh2lc7u
The Deep Convolutional Neural Network Role in the Autonomous Navigation of Mobile Robots (SROBO)
2022
Remote Sensing
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State-of-the-art Real-Time Graph-Based SLAM (RTAB-Map) was adopted to create a map of indoor environments while benefiting from deep convolutional neural network (Deep-CNN) capability. ...
The ability to navigate unstructured environments is an essential task for intelligent systems. ...
Input data in RTAB-Map are used to perform feature detection and matching, motion prediction, motion estimation, local bundle adjustment (LBA), and pose update [38, 39] . ...
doi:10.3390/rs14143324
fatcat:fqf6kfarf5fevkg3bdwjdmc2xy
Perspective and Prediction of The Rule of High Temperature Melting of SiO2 via Visual Analysis
2020
IEEE Access
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The performance of optimized CNN in terms of processing time and accuracy is significantly improved, and the fusion rate prediction model of SiO 2 is verified by 100% accuracy. ...
The prediction model of the melting rate of SiO 2 at high temperature was established by least square fitting (LSF) and dimensional analysis, and compared with the actual melting rate of SiO 2 obtained ...
., Ltd, Gree Electric Appliances and Inc. of Zhuhai, Guangdong, China for their valuable opinions and support. The relevant data was collected, processed, and completed in Yinlong Energy Co., Ltd. ...
doi:10.1109/access.2020.3021709
fatcat:owla5uyroraqfaaxs7zgvsmm3q
CCSNet: a deep learning modeling suite for CO_2 storage
[article]
2021
arXiv
pre-print
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into saline aquifers in 2d-radial systems. ...
The results are 10^3 to 10^4 times faster than conventional numerical simulators. ...
Acknowledgments This work was supported by ExxonMobil through the Strategic Energy Alliance at Stanford University and the Stanford Center for Carbon Storage. ...
arXiv:2104.01795v1
fatcat:pgn2nqpu5fhlvj5xk5ioto3on4
The Research Progress of Vision-Based Artificial Intelligence in Smart Pig Farming
2022
Sensors
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Pork accounts for an important proportion of livestock products. For pig farming, a lot of manpower, material resources and time are required to monitor pig health and welfare. ...
The precision pig farming system uses sensors such as cameras and radio frequency identification to monitor biometric information such as pig sound and pig behavior in real-time and convert them into key ...
Also particular thanks to other members of the team for their involvement and efforts in the whole experiment organization and information collection. ...
doi:10.3390/s22176541
pmid:36080994
pmcid:PMC9460267
fatcat:tgr7ry3axbf6xgpxaeuzcekzdq
The City Brain: Practice of Large-Scale Artificial Intelligence in the Real World
2019
IET Smart Cities
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Then they focus on the system overview and key technical details of each component of the City Brain system, from cognition to intervention. ...
From cognition to optimisation, to decision-making, from search to prediction and ultimately, to intervention, City Brain improves the way to manage the city, as well as the way to live in it. ...
Thereafter, crowd counting and forecasting are allowed for specific 3D spaces. Moreover, road planning can be adjusted based on the directional analysis of traffic flow and crowd flow. ...
doi:10.1049/iet-smc.2019.0034
fatcat:45qm7t5qgve7hgyvfzjl7huocq
A Review of Deep Learning Applications for Railway Safety
2022
Applied Sciences
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Finally, based on the literature reviews, we discuss the opportunities and challenges of artificial intelligence for railway safety. ...
We present fundamental problems and popular approaches for each application area. ...
[63] expected to improve system performance by analyzing other clustering algorithms or adjusting internal parameters. ...
doi:10.3390/app122010572
fatcat:ramzuqbx35e2xatlu4emk7ubuy
Recent Trends in Artificial Intelligence-inspired Electronic Thermal Management
[article]
2021
arXiv
pre-print
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Thermal management is required in electronic systems to keep them from overheating and burning, enhancing their efficiency and lifespan. ...
For a long time, numerical techniques have been employed to aid in the thermal management of electronics. However, they come with some limitations. ...
D., S., Yu, H. and Wang, K. (2015) ‘3D Many-Core Microproces-
sor Power Management by Space-Time Multiplexing Based Demand-Supply
Matching’, IEEE Transactions on Computers, 64(11), pp. 3022–3036. ...
arXiv:2112.14837v1
fatcat:w5jdrf55mnfb3iqfnrld3mqz4i
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