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An Edge Computing System with AMD Xilinx FPGA AI Customer Platform for Advanced Driver Assistance System

Sensors 2024年第10期24卷 3098页

作者： Chi, Tsun-Kuang Chen, Tsung-Yi Lin, Yu-Chen Lin, Ting-Lan Zhang, Jun-Ting Lu, Cheng-Lin Chen, Shih-Lun Li, Kuo-Chen Abu, Patricia Angela R. Department of Electronic Engineering Chung Yuan Christian University Taoyuan320314 Taiwan Department of Electronic Engineering Feng Chia University Taichung40724 Taiwan Department of Automatic Control Engineering Feng Chia University Taichung40724 Taiwan Department of Electronic Engineering National Taipei University of Technology Taipei10608 Taiwan Department of Information Management Chung Yuan Christian University Taoyuan320317 Taiwan Department of Information Systems and Computer Science Ateneo de Manila University Quezon1108 Philippines

The convergence of edge computing systems with Field-Programmable Gate Array (FPGA) technology has shown considerable promise in enhancing real-time applications across various domains. This paper presents an innovative edge computing system design specifically tailored for pavement defect detection within the Advanced Driver-Assistance systems (ADASs) domain. The system seamlessly integrates the AMD Xilinx AI platform into a customized circuit configuration, capitalizing on its capabilities. Utilizing cameras as input sensors to capture road scenes, the system employs a Deep Learning Processing Unit (DPU) to execute the YOLOv3 model, enabling the identification of three distinct types of pavement defects with high accuracy and efficiency. Following defect detection, the system efficiently transmits detailed information about the type and location of detected defects via the controller Area Network (CAN) interface. This integration of FPGA-based edge computing not only enhances the speed and accuracy of defect detection, but also facilitates real-time communication between the vehicle’s onboard controller and external systems. Moreover, the successful integration of the proposed system transforms ADAS into a sophisticated edge computing device, empowering the vehicle’s onboard controller to make informed decisions in real time. These decisions are aimed at enhancing the overall driving experience by improving safety and performance metrics. The synergy between edge computing and FPGA technology not only advances ADAS capabilities, but also paves the way for future innovations in automotive safety and assistance systems. © 2024 by the authors.

关键词： Deep learning

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Awareness in robotics: An early perspective from the viewpoint of the EIC Pathfinder Challenge "Awareness Inside"

arXiv

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arXiv 2024年

作者： Santina, Cosimo Della Corbato, Carlos Hernandez Sisman, Burak Leiva, Luis A. Arapakis, Ioannis Vakalellis, Michalis Vanderdonckt, Jean D’Haro, LuisFernando Manzi, Guido Becchio, Cristina Elamrani, Aïda Alirezaei, Mohsen Castellano, Ginevra Dimarogonas, Dimos V. Ghosh, Arabinda Haesaert, Sofie Soudjani, Sadegh Stroeve, Sybert Verschure, Paul Bacciu, Davide Deroy, Ophelia Bahrami, Bahador Gallicchio, Claudio Hauert, Sabine Sanz, Ricardo Lanillos, Pablo Iacca, Giovanni Sigg, Stephan Gasulla, Manel Steels, Luc Sierra, Carles Department of Cognitive Robotics Delft University of Technology Delft Netherlands Oberpfaffenhofen Germany Department of Computer Science University of Luxembourg Luxembourg 4 Telefónica I+D Spain AEGIS IT Research GmbH Germany Université catholique de Louvain Belgium Speech Technology and Machine Learning Group ETSI de Telecomunicación Universidad Politécnica de Madrid Madrid Spain Alien Venture Studio Alien Technology Transfer Rome Italy Hamburg Germany Institut Jean Nicod École Normale Supérieure Paris France Research Technology and Development Department Digital Industry Software Helmond Netherlands Department of Information Technology Uppsala University Uppsala Sweden Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Max Planck Institute for Software Systems Kaiserslautern Germany Department of Electrical Engineering Control Systems Group Eindhoven University of Technology Eindhoven Netherlands Amsterdam Netherlands Donders Centre for Neuroscience Radboud University Nijmegen Netherlands Computer Science Department University of Pisa Pisa Italy Faculty of Philosophy Philosophy of Science The Study of Religion Ludwig Maximilian University of Munich Munich Germany School of Engineering Mathematics and Technology University of Bristol Bristol United Kingdom Autonomous Systems Laboratory Universidad Politécnica de Madrid Spain Madrid Spain Department of Information Engineering and Computer Science University of Trento Trento Italy Department of Information and Communications Engineering Aalto University Espoo Finland Department of Electronic Engineering Universitat Politècnica de Catalunya Barcelona Spain Studio Stelluti Brussels Belgium Barcelona Spain

Consciousness has been historically a heavily debated topic in engineering, science, and philosophy. On the contrary, awareness had less success in raising the interest of scholars in the past. However, things are changing as more and more researchers are getting interested in answering questions concerning what awareness is and how it can be artificially generated. The landscape is rapidly evolving, with multiple voices and interpretations of the concept being conceived and techniques being developed. The goal of this paper is to summarize and discuss the ones among these voices that are connected with projects funded by the EIC Pathfinder Challenge called "Awareness Inside", a nonrecurring call for proposals within Horizon Europe that was designed specifically for fostering research on natural and synthetic awareness. In this perspective, we dedicate special attention to challenges and promises of applying synthetic awareness in robotics, as the development of mature techniques in this new field is expected to have a special impact on generating more capable and trustworthy embodied systems. © 2024, CC BY.

关键词： Robotics

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A Bayesian k-vector estimation method for electromagnetic waves in magnetized cold plasma

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URSI Radio Science Bulletin 2023年第378期2021卷 77-82页

作者： Yuji Tanaka Mamoru Ota Shoya Matsuda Yoshiya Kasahara Division of Electrical Engineering Graduate School of Engineering Kyoto University Kyotodaigaku-Katsura Nishikyo-ku Kyoto Kyoto Japan Department of Electrical and Control Systems Engineering National Institute of Technology Toyama College 13 Hongo-machi Toyama Toyama Japan Division of Electrical Engineering and Computer Science Graduate School of Natural Science and Technology Kanazawa University Kakuma Kanazawa Ishikawa Japan

Using the plasma wave characteristics and remote sensing technology, the k-vector direction of plasma waves can provide important information for understanding the global features of space plasma. In this study, we proposed a Bayesian k-vector estimation method in magnetized cold plasma based on the wave distribution function method. The proposed method can be applied to various types of sensors with easy visualization and calculation of the estimation accuracy. We verified the effectiveness of the proposed method through simulations.

关键词： Estimation Plasmas Electromagnetics Mathematical models Magnetic sensors Bayes methods Plasma waves

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Sensing metric-based hybrid underlay/overlay transmission framework for CR-IoT networks for smart city applications

Sensing metric-based hybrid underlay/overlay transmission fr...

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7th IET Smart Cities Symposium (SCS 2023)

作者： Indu Bala Maad M. Mijwil Mostafa Abotaleb El-Sayed M. El-kenawy Abdelhameed Ibrahim School of Electrical and Electronics Engineering Lovely Professional University Punjab India Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

With the increasing number of IoT devices, there is a growing need for bandwidth to support their communication. Unfortunately, there is a shortage of available bandwidth due to preallocated bands for various services. To address this issue, Cognitive Internet of Things (CR-IoT) enables devices to optimize their efficiency and enhance their communication capabilities by intelligently accessing available bandwidth. This is achieved through the use of soft sensing metrics, where devices continuously monitor the RF environment and transmit data opportunistically in overlay mode if a free channel is detected, or in underlay mode if not. In this paper, a soft sensing metric based hybrid transmission framework is proposed for CR-IoT devices to meet the data rate requirement for the smart city applications. The efficacy of this approach is demonstrated through simulation results.

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Identification of the oculo-motor system based on the Volterra model using eye tracking technology 4

Identification of the oculo-motor system based on the Volter...

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4th International Conference on Applied Physics, Simulation and Computing, APSAC 2020

作者： Pavlenko, Vitaliy D. Milosz, Marek Dzienkowski, Mariusz Computerized Control Systems Department Odessa National Polytechnic University Odessa Ukraine Department of Computer Science Lublin University of Technology Lublin Poland

Instrumental algorithmic and software tools for constructing a nonparametric dynamic model of the human oculo-motor system (OMS) based on its inertial and nonlinear properties are developed in the paper on the basis of the experimental studies data of 'input-output' in the form of the Volterra model. Taking into account the specificity of the object investigated, test multistage signals (visual stimulus) were used for identification. Based on the experimental data obtained using the developed computational algorithms and data processing software, a nonparametric dynamic model of OMS in the form of a transition function and transition functions of the 2nd and 3rd orders is constructed. Verification of the constructed model showed its adequacy to the object investigated - a practical coincidence (within the acceptable error) of the object and model feedback for the same test effect. © Published under licence by IOP Publishing Ltd.

关键词： Dynamic models

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RGB Arabic Alphabets Sign Language Dataset

arXiv

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arXiv 2023年

作者： Al-Barham, Muhammad Alsharkawi, Adham Al-Yaman, Musa Al-Fetyani, Mohammad Elnagar, Ashraf Sa’aleek, Ahmad Abu Al-Odat, Mohammad MLALP Research Group University of Sharjah United Arab Emirates Mechatronics Engineering Department The University of Jordan Jordan AppsWave for Information Technology Jordan Department of Computer Science University of Sharjah United Arab Emirates Al-Wefaq Control Systems Doha Qatar Student Guidance Department The University of Jordan Jordan

This paper introduces the RGB Arabic Alphabet Sign Language (AASL) dataset. AASL comprises 7,857 raw and fully labelled RGB images of the Arabic sign language alphabets, which to our best knowledge is the first publicly available RGB dataset. The dataset is aimed to help those interested in developing real-life Arabic sign language classification models. AASL was collected from more than 200 participants and with different settings such as lighting, background, image orientation, image size, and image resolution. Experts in the field supervised, validated and filtered the collected images to ensure a high-quality dataset. AASL is made available to the public on Kaggle.1 © 2023, CC BY.

关键词： Classification (of information)

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Three-dimensional tracking and height verification of polystyrene particles with piezo actuator positioning by means of multi-wavelength evanescent fields 20

Three-dimensional tracking and height verification of polyst...

引用

20th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2020

作者： Blattler, Aran Khajornrungruang, Panart Suzuki, Keisuke Permpatdechakul, Thitipat Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Fukuoka Japan Department of Intelligent and Control Systems Advanced Mechanical Division Kyushu Institute of Technology Fukuoka Japan

ISBN: (纸本)9780995775176

To understand the nanoparticle motion behaviours on a surface, we have studied to investigate the three-dimension tracking of an individual nanoparticle with nanometre localisation accuracy. In three-dimensional nanoparticle moving position, the X and Y coordinates are on the parallel plane to the surface, which their coordinates can be tracked in general microscopy. However, the Z coordinate is the nanoparticle height position perpendicularly to the surface plane, which could not be generally tracked without longitudinal scanning method. In this paper, the polystyrene 100 nm standard particles were used to investigate the three-dimensional tracking. The individual standard nanoparticles were fixed on the tip, which was vertically travelled with the piezo actuator for movement control on the third dimension to verify the actual height Z. Our developed optical microscopy apparatus has been applying multi-wavelength evanescent fields, and obtaining multi scattering light intensities from the observed nanoparticles near to surface. Commonly, the X and Y coordinates of nanoparticle were determined by the centre of mass of each scattering light intensity. The height Z was investigated from the integration of the detected scattering intensities of each wavelength. By using our method, the height Z uncertainty could be measured approximately less than ±20 nm, and the penetration height measurability was approximately 250 nm far from the reference surface. Consequently, we could three-dimensionally track the individual standard nanoparticle in recording speed higher than 50 frames per second. Copyright © Proceedings of the 20th International Conference of the European Society for Precision Engineering and Nanotechnology, EUSPEN 2020. All rights reserved.

关键词： Nanoparticles

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Context-aware Emotion Recognition Based on Vision-Language Pre-trained Model

Context-aware Emotion Recognition Based on Vision-Language P...

引用

International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： XingLin Li Xinde Li Chuanfei Hu Huaping Liu School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China Nanjing Center for Applied Mathematics Nanjing China Southeast University Shenzhen Research Institute Shenzhen China Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

Given the difficulty of recognizing ambiguous emotions in facial expression recognition tasks, we propose a visual-language model named CAER-CLIP to address this challenge. The proposed CAER-CLIP standed for Context-Aware Emotion Recognition (CAER), and were incorporated structure of the Contrastive Language–Image Pre-training (CLIP) model as promising alternative to classifier. There are two parts in CAER-CLIP model. In the visual part, facial expressions and contextual information of the image are simultaneously extracted to obtain the final feature embeddings, which are then used as a learnable “class” token for text-image pairing with desired module. In the textual part, we use text labels for emotion recognition classes as input. The outputs were merged to participate the comparative study to generated parameters of the model. The experiments demonstrate the effectiveness of the proposed method and show that our CAER-CLIP outperforms the state-of-the-art results on the CAER benchmark. The ablation experiment verified the effectiveness of both the classifier-based and text-based (ours without classifier) models, demonstrating that our method with the CAER-CLIP structure performed better, and the incorporation of a text encoder in the deep network model architecture effectively enhancing recognition accuracy.

关键词： Training Emotion recognition Visualization Accuracy Text recognition Face recognition Benchmark testing Feature extraction Data mining Context modeling

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A Cyclic Small Phase Theorem

arXiv

引用

arXiv 2023年

作者： Chen, Chao Chen, Wei Zhao, Di Chen, Jianqi Qiu, Li KU Leuven Leuven3001 Belgium The Department of Mechanics and Engineering Science State Key Laboratory for Turbulence and Complex Systems Peking University Beijing100871 China The Department of Control Science and Engineering Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai200092 China The Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong

This paper introduces a brand-new phase definition called the segmental phase for multi-input multi-output linear time-invariant systems. The underpinning of the definition lies in the matrix segmental phase which, as its name implies, is graphically based on the smallest circular segment covering the matrix normalized numerical range in the unit disk. The matrix segmental phase has the crucial product eigen-phase bound, which makes itself stand out from several existing phase notions in the literature. The proposed bound paves the way for stability analysis of a cyclic feedback system consisting of multiple subsystems. A cyclic small phase theorem is then established as our main result, which requires the loop system phase to lie between −π and π. The proposed theorem complements a cyclic version of the celebrated small gain theorem. In addition, a generalization of the proposed theorem is made via the use of angular scaling techniques for reducing conservatism. Copyright © 2023, The Authors. All rights reserved.

关键词： Linear time-invariant system

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Advance Artificial Intelligence Technique for Designing Double T-Shaped Monopole Antenna

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computers, Materials & Continua 2021年第12期69卷 2983-2995页

作者： El-Sayed M.El-kenawy Hattan F.Abutarboush Ali Wagdy Mohamed Abdelhameed Ibrahim Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Electrical Engineering Department College of EngineeringTaibah UniversityMedina 42353Saudi Arabia Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza 12613Egypt Wireless Intelligent Networks Center(WINC) School of Engineering and Applied SciencesNile UniversityGizaEgypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt

Machine learning(ML)has taken the world by a tornado with its prevalent applications in automating ordinary tasks and using turbulent insights throughout scientific research and design *** is a massive area within artificial intelligence(AI)that focuses on obtaining valuable information out of data,explaining why ML has often been related to stats and data *** advanced meta-heuristic optimization algorithm is proposed in this work for the optimization problem of antenna architecture *** algorithm is designed,depending on the hybrid between the Sine Cosine Algorithm(SCA)and the Grey Wolf Optimizer(GWO),to train neural networkbased Multilayer Perceptron(MLP).The proposed optimization algorithm is a practical,versatile,and trustworthy platform to recognize the design parameters in an optimal way for an endorsement double T-shaped monopole *** proposed algorithm likewise shows a comparative and statistical analysis by different curves in addition to the ANOVA and *** offers the superiority and validation stability evaluation of the predicted results to verify the procedures’accuracy.

关键词： Antenna optimization machine learning artificial intelligence multilayer perceptron sine cosine algorithm grey wolf optimizer

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