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IEEE International Conference on Automation science and Engineering (CASE)

作者： FaJun Yang NaiQi Wu Yan Qiao MengChu Zhou Department of Industrial Engineering Guangdong University of Technology Guangzhou China Institute of Systems Engineering Macau University of Science and Technology Macau Key Laboratory of Embedded System and Service Computing Tongji University Shanghai China Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA

A multi-cluster tool is composed of a number of single-cluster tools linked by buffering modules. The capacity of a buffering module can be one or two. Aiming at finding an optimal one-wafer cyclic schedule, this work explores the effect of two-space buffering modules on the performance of a multi-cluster tool. The tool is modeled by a kind of Petri nets. The dynamic behavior of robot waiting and tasks, process modules, and buffers is well captured by the net model. With the model, this work shows that there is always a one-wafer cyclic schedule that reaches the lower bound of the cycle time of a process-dominant tool. Furthermore, a constant-time algorithm is revealed to find such a schedule for the first time for such multi-cluster tools. An illustrative example is given to show the application and power of this new method.

关键词： Schedules Robot kinematics Firing Semiconductor device modeling Fires Load modeling

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Efficient realization of givens rotation through algorithm-architecture co-design for acceleration of qr factorization

arXiv

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arXiv 2018年

作者： Merchant, Farhad Vatwani, Tarun Chattopadhyay, Anupam Raha, Soumyendu Nandy, S.K. Narayan, Ranjani Leupers, Rainer Farhad Merchant and Rainer Leupers Are with Inst. for Commun. Technologies and Embedded Systems Rwth Aachen University Germany Tarun Vatwani and Anupam Chattopadhyay Are with School of Computer Science and Engineering Nanyang Technological University Singapore Indian Institute of Science Bangalore India Morphing Machines Pvt. LTd.

We present efficient realization of Generalized Givens Rotation (GGR) based QR factorization that achieves 3-100x better performance in terms of Gflops/watt over state-of-the-art realizations on multicore, and General Purpose Graphics Processing Units (GPGPUs). GGR is an improvement over classical Givens Rotation (GR) operation that can annihilate multiple elements of rows and columns of an input matrix simultaneously. GGR takes 33% lesser multiplications compared to GR. For custom implementation of GGR, we identify macro operations in GGR and realize them on a Reconfigurable Data-path (RDP) tightly coupled to pipeline of a Processing Element (PE). In PE, GGR attains speed-up of 1.1x over Modified Householder Transform (MHT) presented in the lit ENGLerature. For parallel realization of GGR, we use REDEFINE, a scalable massively parallel Coarse-grained Reconfigurable Architecture, and show that the speed-up attained is commensurate with the hardware resources in REDEFINE. GGR also outperforms General Matrix Multiplication (gemm) by 10% in-terms of Gflops/watt which is counter-intuitive. Copyright © 2018, The Authors. All rights reserved.

关键词： Factorization

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CLOUD COMPUTING

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China Communications 2014年第4期11卷 I0001-I0002页

作者：崔勇 Rajkumar Buyya 刘江川 Tsinghua University Network Technology in Institute Tsinghua University IPv6 Transition Softwire WG of IETF Tsinghua University Computer Science and Software Engineering at the University of Melbourne Cloud Computing and Distributed Systems(CLOUDS) Laboratory at the University of Melbourne School of Computing Science at Simon Fraser University

Cloud computing is a novel computing paradigm that utilizes remote cloud resources to achieve a high-performance *** provides infrastructure,platform and software as different on-demand *** has made remarkable progress in cloudbased products and operating system *** government,enterprises and research institutions are all active in the development of cloud computing-related *** the progress,many important

关键词：计算模式性能计算基础设施操作系统科研机构远程软件

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Developing Vision-based and Cooperative Vehicular embedded systems for Enhancing Road Monitoring Services

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Procedia computer science 2015年 52卷 389-395页

作者： K. Hammoudi H. Benhabiles M. Kasraoui N. Ajam F. Dornaika K. Radhakrishnan K. Bandi Q. Cai S. Liu Research Institute on Embedded Electronic Systems (IRSEEM EA4353 Normandie Université) IIS Group St-Etienne-du-Rouvray France ESIGELEC School of Engineering Department of ICT (φMS Students) St-Etienne-du-Rouvray France Department of Computer Science and Artificial Intelligence University of the Basque Country San Sebastián Spain IKERBASQUE Basque Foundation for Science Bilbao Spain

This paper presents a generic processing architecture as well as tools and approaches for supporting road monitoring services. More precisely, a small-scale simulator is presented for experimenting the design and the implementation of vision-based vehicular embedded systems in indoor environments, i.e. a test bench for embedded system laboratories. This simulator employs embedded electronic systems, sensors as well as hybrid communication and computational technologies. In particular, these technologies are exploited in order to produce our cooperative and real-time embedded system for enhancing road monitoring services. This type of simulator can be used for developing a variety of innovative road monitoring services based on the detection of dynamical points of interest. Notably, a system has been implemented in the case of a simulated road service to aid police agency for the recognition of wanted individuals and stolen vehicles. Experimental results show the potential of the simulator for fostering the development of a next generation of vehicular embedded system as well as for the emergence of participatory road services.

关键词： sensor networks cooperative monitoring vision-based recognition systems vehicular embedded systems.

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科学研究的第五范式——以智能驱动的材料设计为例

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Engineering 2023年第5期24卷 126-137,I0003,I0004页

作者： Can Leng Zhuo Tang Yi-Ge Zhou Zean Tian Wei-Qing Huang Jie Liu Keqin Li Kenli Li Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense TechnologyChangsha 410073China Laboratory of Software Engineering for Complex Systems National University of Defense TechnologyChangsha 410073China National Supercomputing Center in Changsha Changsha 410082China College of Computer Science and Electronic Engineering Hunan UniversityChangsha 410082China Institute of Chemical Biology and Nanomedicine State Key Laboratory of Chemo/Biosensing and ChemometricsCollege of Chemistry and Chemical EngineeringHunan UniversityChangsha 410082China Department of Applied Physics School of Physics and ElectronicsHunan UniversityChangsha 410082China Department of Computer Science State University of New YorkNew PaltzNY 12561USA

科学正在进入一个新时代——第五范式——它被认为是知识整合到不同领域的主要特征,是基于无所不在的机器学习系统的计算社区中智能驱动的工作。在此,我们通过在天河一号超级计算机系统上构建的催化材料专门设计的典型平台案例,生动地... 详细信息

科学正在进入一个新时代——第五范式——它被认为是知识整合到不同领域的主要特征,是基于无所不在的机器学习系统的计算社区中智能驱动的工作。在此,我们通过在天河一号超级计算机系统上构建的催化材料专门设计的典型平台案例,生动地阐明了第五范式的本质,旨在促进第五范式在其他领域的培养。第五范式平台主要包括模型自动构建(原始数据提取)、指纹自动构建(神经网络特征选择)以及跨学科知识串联的重复迭代(“火山图”)。与分解一起进行的是对迭代中实现的体系结构的性能评估。通过讨论,第五范式的智能驱动平台可以极大地简化和改进研究中极其繁琐和具有挑战性的工作,并通过补偿机器学习中缺少样本和替代一些由于计算资源不足而导致的数值计算来实现数值计算与机器学习之间的相互反馈,从而加速探索过程。在数据驱动的学科中,跨学科专家的协同作用和对动态数据需求的急剧增长仍然是一个挑战。我们相信,对第五范式平台的一瞥可以为其在其他领域的应用铺平道路。

关键词：机器学习自动构建天河一号数据驱动神经网络动态数据知识整合科学研究

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Low Latency V2X Applications and Network Requirements: Performance Evaluation

Low Latency V2X Applications and Network Requirements: Perfo...

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IEEE Symposium on Intelligent Vehicle

作者： Zubair Amjad Axel Sikora Benoit Hilt Jean-Philippe Lauffenburger Institute of Reliable Embedded Systems and Communication Electronics (ivESK) Offenburg University of Applied Sciences Offenburg Germany Hahn-Schickard Gesellschaft für Angewandte Forschung e.V. Villingen-Schwenningen Germany Institute of Research in Computer Science Mathematics Control and Signals (IRIMAS) University of Haute Alsace Mulhouse France

Vehicle-to-Everything (V2X) communication promises improvements in road safety and efficiency by enabling low-latency and reliable communication services for vehicles. Besides using Mobile Broadband (MBB), there is a need to develop Ultra Reliable Low Latency Communications (URLLC) applications with cellular networks especially when safety-related driving applications are concerned. Future cellular networks are expected to support novel latencysensitive use cases. Many applications of V2X communication, like collaborative autonomous driving requires very low latency and high reliability in order to support real-time communication between vehicles and other network elements. In this paper, we classify V2X use-cases and their requirements in order to identify cellular network technologies able to support them. The bottleneck problem of the medium access in 4G Long Term Evolution(LTE) networks is random access procedure. It is evaluated through simulations to further detail the future limitations and requirements. Limitations and improvement possibilities for next generation of cellular networks are finally detailed. Moreover, the results presented in this paper provide the limits of different parameter sets with regard to the requirements of V2X-based applications. In doing this, a starting point to migrate to Narrowband IoT (NB-IoT) or 5G - solutions is given.

关键词： Long Term Evolution Reliability Cellular networks Autonomous vehicles Bandwidth Indexes Roads

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Supporting environmental modelling with Taverna workflows, web services and desktop grid technology 7

Supporting environmental modelling with Taverna workflows, w...

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7th International Congress on Environmental Modelling and Software, iEMSs 2014

作者： Horváth, Ferenc Ittzés, Péter Ittzés, Dóra Barcza, Zoltán Dobor, Laura Hidy, Dóra Marosi, Attila Hardisty, Alex Institute of Ecology and Botany Centre for Ecological Research Hungarian Academy of Sciences Alkotmány u. 2-4. Vácrátót2163 Hungary Department of Meteorology Eötvös Loránd University Pázmány sétány 1/A Budapest1117 Hungary Institute of Botany and Ecophysiology Szent Istvan University Páter K. u.1. Gödöllo2100 Hungary Laboratory of Parallel and Distributed Systems Institute for Computer Science and Control Hungarian Academy of Sciences P.O. Box 63 Budapest1518 Hungary School of Computer Science and Informatics Cardiff University Queen's Buildings 5 The Parade Roath CardiffCF24 3AA United Kingdom

Ecosystem functioning, climate change, and multiple interactions among biogeochemical cycles, climate system, site conditions and land use options are leading-edge topics in recent environmental modelling. Terrestrial ecosystem models are widely used to support carbon sequestration and ecosystem studies under various ecological circumstances. Our team uses the Biome-BGC model (Numerical Terradynamic Simulation Group, University of Montana), and develops an improved model version of it, called Biome-BGC MuSo. Both the original and the improved model estimate the ecosystem scale storage and fluxes of energy, carbon, nitrogen and water, controlled by various physical and biological processes on a daily time-scale. Web services were also developed and integrated with parallel processing desktop grid technology. Taverna workflow management system was used to build up and carry out elaborated workflows like seamless data flow to model simulation, Monte Carlo experiment, model sensitivity analysis, model-data fusion, estimation of ecosystem service indicators or extensive spatial modelling. Straightforward management of complex data analysis tasks, organized into appropriately documented, shared and reusable scientific workflows enables researchers to carry out detailed and scientifically challenging 'in silico' experiments and applications that could open new directions in ecosystem research and in a broader sense it supports progress in environmental modelling. The workflow approach built upon these web services allows even the most complicated computations to be initiated without the need of programming skills and deep understanding of model structure and initialization. The developments enable a wider array of scientists to perform ecosystem scale simulations, and to perform analyses not previously possible due to high complexity and computational demand.

关键词： Web services

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DOMAIN-INVARIANT REPRESENTATION LEARNING FROM EEG WITH PRIVATE ENCODERS

arXiv

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arXiv 2022年

作者： Bethge, David Hallgarten, Philipp Grosse-Puppendahl, Tobias Kari, Mohamed Mikut, Ralf Schmidt, Albrecht Özdenizci, Ozan Dr. Ing. h.c. F. Porsche AG Stuttgart Germany Ludwig-Maximilians University Munich Germany Karlsruhe Institute of Technology Germany Institute of Theoretical Computer Science Graz University of Technology Austria TU Graz - SAL Dependable Embedded Systems Lab Silicon Austria Labs Austria

Deep learning based electroencephalography (EEG) signal processing methods are known to suffer from poor test-time generalization due to the changes in data distribution. This becomes a more challenging problem when privacy-preserving representation learning is of interest such as in clinical settings. To that end, we propose a multi-source learning architecture where we extract domain-invariant representations from dataset-specific private encoders. Our model utilizes a maximum-mean-discrepancy (MMD) based domain alignment approach to impose domain-invariance for encoded representations, which outperforms state-of-the-art approaches in EEG-based emotion classification. Furthermore, representations learned in our pipeline preserve domain privacy as dataset-specific private encoding alleviates the need for conventional, centralized EEG-based deep neural network training approaches with shared parameters. Copyright © 2022, The Authors. All rights reserved.

关键词： Electroencephalography

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Cell indicator system for pharmacies

Cell indicator system for pharmacies

引用

2017 IEEE SmartWorld Ubiquitous Intelligence and Computing, Advanced and Trusted Computed, Scalable Computing and Communications, Cloud and Big Data Computing, Internet of People and Smart City Innovation, SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017

作者： Chou, Pai H. Tseng, Hua-Min Hsu, Ting-Yu Lee, Cheng-Ting Nien, Chin-Chung Chien, Su-Yu Center for Embedded and Cyber-Physical Systems University of California Irvine IrvineCA92697-2625 United States Department of Computer Science National Tsing Hua University Hsinchu City Taiwan Service Systems Technology Center Industrial Technology Research Institute Hsinchu City Taiwan Department of Pharmacy Changhua Christian Hospital Changhua City Taiwan

ISBN: (纸本)9781538604342

This paper describes an indicator system that helps prevent errors by pharmacists when filling a prescription. It uses an optical tag scanner to read a barcode or QR-code tag that encodes the prescribed medicine and lights up the corresponding cell in the medicine cabinet. The scanning subsystem used by the pharmacist is connected to the database wirelessly via Bluetooth Low Energy Technology (BLE) for easy deployment. The indicator subsystem uses a novel row-column scanning circuitry to minimize the number of general-purpose input/output (GPIO) pins that are required of the microcontroller unit (MCU) for maximum scalability and minimum hardware. Experimental results in a real pharmacy setting show the proposed system to be effective in minimizing dispensing errors while meeting cost and performance targets for commercial use. © 2017 IEEE.

关键词： Bluetooth

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Learning to Prevent Monocular SLAM Failure using Reinforcement Learning 18

Learning to Prevent Monocular SLAM Failure using Reinforceme...

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Proceedings of the 11th Indian Conference on computer Vision, Graphics and Image Processing

作者： Vignesh Prasad Karmesh Yadav Rohitashva Singh Saurabh Swapnil Daga Nahas Pareekutty K. Madhava Krishna Balaraman Ravindran Brojeshwar Bhowmick Embedded Systems & Robotics TCS Research & Innovation Kolkata India Robotics Institute Carnegie Mellon University Pittsburgh USA Dept. of Robotics Engineering John Hopkins University Baltimore USA Robotics Research Center KCIS IIIT Hyderabad India Dept. of Computer Science Indian Institute of Technology Madras India

ISBN: (纸本)9781450366151

Monocular SLAM refers to using a single camera to estimate robot ego motion while building a map of the environment. While Monocular SLAM is a well studied problem, automating Monocular SLAM by integrating it with trajectory planning frameworks is particularly challenging. This paper presents a novel formulation based on Reinforcement Learning (RL) that generates fail safe trajectories wherein the SLAM generated outputs do not deviate largely from their true values. Quintessentially, the RL framework successfully learns the otherwise complex relation between perceptual inputs and motor actions and uses this knowledge to generate trajectories that do not cause failure of SLAM. We show systematically in simulations how the quality of the SLAM dramatically improves when trajectories are computed using RL. Our method scales effectively across Monocular SLAM frameworks in both simulation and in real world experiments with a mobile robot.

关键词： Monocular SLAM

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