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A Markov Traffic Model for Signalized Traffic Networks Based on Bayesian Estimation

IFAC-PapersOnLine 2020年第2期53卷 15029-15034页

作者： S.Y. Liu S. Lin Y.B. Wang B. De Schutter W.H.K. Lam School of Computer Science and Technology University of Chinese Academy of Sciences Beijing 100089 China Key Lab of Big Data Mining and Knowledge Management Chinese Academy of Sciences College of Civil Engineering and Architecture Zhejiang University PR China Delft Center for Systems and Control Delft University of Technology The Netherlands Department of Civil and Structural Engineering The Hong Kong Polytechnic University Hong Kong SAR China

In order to better understand the stochastic dynamic features of signalized traffic networks, we propose a Markov traffic model to simulate the dynamics of traffic link flow density for signalized urban traffic networks with demand uncertainty. In this model, we have four different state modes for the link according to different congestion levels of the link. Each link can only be in one of the four link state modes at any time, and the transition probability from one state to the other state is estimated by Bayesian estimation based on the distributions of the dynamic traffic flow densities, and the posterior probabilities. Therefore, we use a first-order Markov Chain Model to describe the dynamics of the traffic flow evolution process. We illustrate our approach for a small traffic network. Compared with the data from the microscopic traffic simulator SUMO, the proposed model can estimate the link traffic densities accurately and can give a reliable estimation of the uncertainties in the dynamic process of signalized traffic networks.

关键词： Markov traffic model Traffic signals Bayesian Urban traffic network

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An ARQ-Based Cooperative Relaying Scheme for 5G IoT Slice

An ARQ-Based Cooperative Relaying Scheme for 5G IoT Slice

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2019 IEEE Global Conference on Internet of Things, GCIoT 2019

作者： Otaru, Musa Ajiya, Mohammed Adinoyi, Abdulkareem Aljlayl, Mohammed Yanikomeroglu, Halim Telecommunications Services Nigerian Communications Satellite Ltd Abuja Nigeria Bayero University Department of Electrical Engineering Kano Nigeria Technology Enterprise Architecture Saudi Telecommunications Company Saudi Arabia Carleton University Dept. of Systems and Computer Engineering Ottawa Canada

ISBN: (纸本)9781728148731

We introduce a new twist to the classical automatic repeat request (ARQ)-based cooperative relaying scheme. Here, we target a 5G slice for offering internet-of-things (IoT)-inspired services. In this 5G application segment (e.g., utility or smart metering), utility sensors or devices are expected to last for decades and, operate on tight power budgets, and the system can tolerate periodic stops to check the fidelity of previous transmissions. For this scenario, we employ a service provider-deployed relay that alleviates the IoT devices of their communication burdens. The source transmits for a certain time window or period without requiring acknowledgments (ACK) from the destination. At the end of this window, the destination sends an ACK. If negative, the relay is expected to assist. Thus, the relay transmits only intermittently, in either one transmission time slot or a few time slots, using a suitably chosen higherorder modulation constellation. If no error occurs, the source continues its transmission. The numerical results show that with just a few antennas at the relay, the new scheme provides both a reduction in the number of ARQ transmissions and a superior probability of bit error compared with a reference scheme. We adopt the two-parameter Weibull fading model to evaluate the performance of the proposed scheme. © 2019 IEEE.

关键词： Internet of things

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Register-based implementation of the sparse general matrix-matrix multiplication on GPUs

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ACM SIGPLAN Notices 2018年第1期53卷 407-408页

作者： Liu, Junhong He, Xin Liu, Weifeng Tan, Guangming State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences China University of Chinese Academy of Sciences China Department of Computer Science Norwegian University of Science and Technology Norway

General sparse matrix-matrix multiplication (SpGEMM) is an essential building block in a number of applications. In our work, we fully utilize GPU registers and shared memory to implement an efficient and load balance... 详细信息

ISBN: (纸本)9781450349116

关键词： Matrix algebra

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Author Correction: Aerial additive manufacturing with multiple autonomous robots

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Nature 2024年第7998期626卷 E5页

作者： Ketao Zhang Pisak Chermprayong Feng Xiao Dimos Tzoumanikas Barrie Dams Sebastian Kay Basaran Bahadir Kocer Alec Burns Lachlan Orr Talib Alhinai Christopher Choi Durgesh Dattatray Darekar Wenbin Li Steven Hirschmann Valentina Soana Shamsiah Awang Ngah Clément Grillot Sina Sareh Ashutosh Choubey Laura Margheri Vijay M Pawar Richard J Ball Chris Williams Paul Shepherd Stefan Leutenegger Robert Stuart-Smith Mirko Kovac Department of Aeronautics Imperial College London London UK. School of Engineering and Materials Science Queen Mary University of London London UK. Department of Computing Imperial College London London UK. Department of Architecture and Civil Engineering University of Bath Bath UK. Department of Computer Science University College London London UK. Materials and Technology Centre of Robotics Swiss Federal Laboratories for Materials Science and Technology (Empa) Dübendorf Switzerland. Department of Informatics Technical University of Munich Garching Germany. Stuart Weitzman School of Design University of Pennsylvania Philadelphia PA USA. Department of Aeronautics Imperial College London London UK. m.kovac@imperial.ac.uk. Materials and Technology Centre of Robotics Swiss Federal Laboratories for Materials Science and Technology (Empa) Dübendorf Switzerland. m.kovac@imperial.ac.uk.

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White Rabbit: A Deterministic Time Transfer and Frequency Dissemination technology for Distrihuted Systems 2

White Rabbit: A Deterministic Time Transfer and Frequency Di...

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2nd URSI Atlantic Radio Science Meeting, AT-RASC 2018

作者： Diaz, J. Ros, E. Rodriguez-Gomez, R. University of Granada Computer Architecture and Technology Department Spain Seven Solutions S.L. Spain

ISBN: (纸本)9789082598735

Latest developments on the field of radio-communications and astrophysics rely on the development of distributed systems as a way to better sensing and optimize the utilization of the electromagnetic spectrum. From modern radio-telescopes like the Square Kilometer Array (SKA) or the Cherenkov Telescope Array (CTA), to distributed radars and communication systems, all of them require a common and highly stable frequency reference in all the antennas. This is needed to guarantee that the radio signal is sampled or emitted in a coherent way despite the location. Furthermore, all of them need a proper Pulse-Per-Second (PPS) signal. This signal is used as synchronization mechanism, key for signal timestamping as well as a mechanism to control the phase of the signal distributed at each antenna of the system. This allows the distributed instrumentation (arrays of antennas) to work as a single system, with a global time and frequency reference. © 2018 International Union of Radio Science URSI.

关键词： Antennas

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The influence of input data standardization methods on the prediction accuracy of genetic programming generated classifiers 10th

The influence of input data standardization methods on the p...

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10th International Joint Conference on Computational Intelligence, IJCCI 2018

作者： Al Shorman, Amaal R. Faris, Hossam Castillo, Pedro A. Merelo, J.J. Al-Madi, Nailah Business Information Technology Department King Abdullah II School for Information Technology University of Jordan Amman Jordan Department of Computer Architecture and Computer Technology ETSIIT and CITIC University of Granada Granada Spain Computer Science Department Princess Sumaya University for Technology Amman Jordan

ISBN: (纸本)9789897583278

Genetic programming (GP) is a powerful classification technique. It is interpretable and it can dynamically build very complex expressions that maximize or minimize some fitness functions. It has a capacity to model very complex problems in the area of Machine Learning, Data Mining and Pattern Recognition. Nevertheless, GP has a high computational complexity time. On the other side, data standardization is one of the most important pre-processing steps in machine learning. The purpose of this step is to unify the scale of all input features to have equal contribution to the model. The objective of this paper is to investigate the influence of input data standardization methods on GP, and how it affects its prediction accuracy. Six different methods of input data standardization were checked in order to determine which one allows to achieve the most accurate result with lowest computational cost. The simulations have been implemented on ten benchmarked datasets with three different scenarios (varying the population size and number of generations). The results showed that the computational efficiency of GP is highly enhanced when coupled with some standardization methods, specifically Min-Max method for scenario I and Vector method for scenario II, and scenario III. Whereas, Manhattan and Z-Score methods had the worst results for all three scenarios. Copyright 2018 by SCITEPRESS – Science and technology Publications, Lda. All rights reserved.

关键词： Genetic programming

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Thermoelectric properties of layered ternary telluride Nb3SiTe6

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Physical Review Materials 2020年第9期4卷 094205-094205页

作者： Yahui Pang Emad Rezaei Dongyun Chen Si Li Yu Jian Qinsheng Wang Zhiwei Wang Junxi Duan Mona Zebarjadi Yugui Yao Key Laboratory of Advanced Optoelectronic Quantum Architecture and Measurement (MOE) School of Physics Beijing Institute of Technology Beijing 100081 China Micronano Centre Beijing Key Lab of Nanophotonics and Ultrafine Optoelectronic Systems Beijing Institute of Technology Beijing 100081 China Department of Electrical and Computer Engineering University of Virginia Charlottesville Virginia 22932 USA School of Physics and Electronics Hunan Normal University Changsha Hunan 410081 China Department of Materials Science and Engineering University of Virginia Charlottesville Virginia 22932 USA

We report the study of the thermoelectric properties of layered ternary telluride Nb3SiTe6. The temperature dependence of the thermoelectric power (TEP) evolves from nonlinear to linear when the thickness of the devices is reduced, consistent with the suppression of electron-phonon interaction caused by quantum confinement. The magnitude of TEP strongly depends on the hole density. It increases with decreasing hole density when the hole density is low, as observed in ionic-liquid-gated thin flakes. However, the device with the largest hole density possesses the highest TEP. Theoretical analysis suggests that the high TEP in the device with the largest hole density can be ascribed to the phonon-mediated intervalley scatterings. The highest TEP reaches ∼230μV/K at 370 K while the electrical resistivity of the device is maintained below 1.5mΩcm. Therefore, a large power factor PF ∼36μWcm−1K−2 comparable to the record values reported in p-type materials is obtained.

关键词： Seebeck effect Thermoelectric effects Topological materials Transport phenomena

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Next-Generation Sequencing Analysis of Extracellular Vesicle microRNAs for Breast Cancer Staging

Journal of Liquid Biopsy, The

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Journal of Liquid Biopsy, The 2023年 1卷 100106-100106页

作者： Martínez, C. González Sánchez, F. Ortega Garrido-Navas, C. Ortuño, F. Lorente, J. Serrano, M. Centro Pfizer-Universidad de Granada-Junta de Andalucía de Genómica e Investigación Oncológica (GENYO) Granada Spain Department of Legal Medicine Toxicology and Physical Anthropology Faculty of Medicine University of Granada Granada Spain Department of Genetics Faculty of Sciences University of Granada Granada Spain Department of Architecture and Computer Technology University of Granada Granada Spain Department of Medical Oncology Biosanitary Research Institute (IBS Granada) Virgen de las Nieves University Hospital Granada Spain

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Learning collision-free space detection from stereo images: Homography matrix brings better data augmentation

arXiv

引用

arXiv 2020年

作者： Fan, Rui Wang, Hengli Cai, Peide Wu, Jin Bocus, Mohammud Junaid Qiao, Lei Liu, Ming Department of Computer Science and Engineering Department of Ophthalmology University of California San Diego San DiegoCA92093 United States Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong Department of Electrical and Electronic Engineering University of Bristol BS8 1UB United Kingdom State Key Laboratory of Ocean Engineering School of Naval Architecture Ocean and Civil Engineering Shanghai Jiao Tong University Shanghai200240 China

Collision-free space detection is a critical component of autonomous vehicle perception. The state-of-the-art algorithms are typically based on supervised deep learning. Their performance is dependent on the quality and amount of labeled training data. It remains an open challenge to train deep convolutional neural networks (DCNNs) using only a small quantity of training samples. Therefore, in this paper, we mainly explore an effective training data augmentation approach that can be employed to improve the overall DCNN performance, when additional images captured from different views are available. Due to the fact that the pixels in collision-free space (generally regarded as a planar surface) between two images, captured from different views, can be associated using a homography matrix, the target image can be transformed into the reference view. This provides a simple but effective way to generate training data from additional multi-view images. Extensive experimental results, conducted with six state-of-the-art semantic segmentation DCNNs on three datasets, validate the effectiveness of the proposed method for enhancing collision-free space detection performance. When validated on the KITTI road benchmark, our approach provides the best results, compared with other state-of-the-art stereo vision-based collision-free space detection approaches. Copyright © 2020, The Authors. All rights reserved.

关键词： Deep neural networks

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VNet: A Versatile Network for Efficient Real-Time Semantic Segmentation

VNet: A Versatile Network for Efficient Real-Time Semantic S...

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IEEE International Conference on computer Design: VLSI in computers and Processors, (ICCD)

作者： Ning Lin Hang Lu Jingliang Gao Shunjie Qiao Xiaowei Li State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences Department of Computer Science University of Hong Kong

Many recent excellent methods for efficient real-time semantic segmentation are of low precision and heavily rely on multiple GPUs for training. In this paper, we rethink the critical factors affecting the accuracy of efficient segmentation models. The previous works usually reduce the input resolution prior to training the parameters of models by cropping or resizing the images. On the contrary, our empirical study shows that the reduced images lose the important content information and details, which are vital to the high precision. However, the previous methods are unable to train the original high-resolution images due to the memory-limited GPUs. To tackle this problem, we propose a novel versatile network (VNet), which employs reversible mechanism and asymmetric convolution to achieve highly efficient and extremely low memory consumption in backward propagation. In particular, we keep all the detailed spatial information of the input images without cropping or resizing to pursue decent prediction accuracy. It is worth noting that VNet can train multiple 1024×2048 high-resolution images on only one standard GPU card. Under the same conditions, our model achieves a new state-of-the-art result on Cityscapes datasets. Specifically, it can process the 1024×2048 high-resolution inputs at a rate of 37.4 and 15.5 frames per second (fps) on a standard GPU and an edge device, respectively, with only 0.16 million parameters.

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