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An Efficient Solver for Cumulative Density Function-based Solutions of Uncertain Kinematic Wave Models

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arXiv 2019年

作者： Cheng, Ming Qin, Yi Narayan, Akil Zhong, Xinghui Zhu, Xueyu Wang, Peng School of Mathematics and System Sciences Beihang University Beijing China Institute University of Utah Salt Lake CityUT School of Mathematics Zhejiang University Hangzhou China Department of Mathematics University of Iowa Iowa United States Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China

We develop a numerical framework to implement the cumulative density function (CDF) method for obtaining the probability distribution of the system state described by a kinematic wave model. The approach relies on Monte Carlo Simulations (MCS) of the fine-grained CDF equation of system state, as derived by the CDF method. This fine-grained CDF equation is solved via the method of characteristics. Each method of characteristics solution is far more computationally efficient than the direct solution of the kinematic wave model, and the MCS estimator of the CDF converges relatively quickly. We verify the accuracy and robustness of our procedure via comparison with direct MCS of a particular kinematic wave system, the Saint-Venant *** Codes 65M22, 65M25 Copyright © 2019, The Authors. All rights reserved.

关键词： Monte Carlo methods

Urban flows prediction from spatial-temporal data using machine learning: A survey

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arXiv 2019年

作者： Xie, Peng Li, Tianrui Liu, Jia Du, Shengdong Yang, Xin Zhang, Junbo School of Information Science and Technology Southwest Jiaotong University Chengdu611756 China Institute of Artificial Intelligence Southwest Jiaotong University Chengdu611756 China National Engineering Laboratory of Integrated Transportation Big Data Application Technology Southwest Jiaotong University Chengdu611756 China Urban Computing Business Unit JD Finance China

Urban spatial-temporal flows prediction is of great importance to traffic management, land use, public safety, etc. Urban flows are affected by several complex and dynamic factors, such as patterns of human activities, weather, events and holidays. datasets evaluated the flows come from various sources in different domains, e.g. mobile phone data, taxi trajectories data, metro/bus swiping data, bike-sharing data and so on. To summarize these methodologies of urban flows prediction, in this paper, we first introduce four main factors affecting urban flows. Second, in order to further analysis urban flows, a preparation process of multi-sources spatial-temporal data related with urban flows is partitioned into three groups. Third, we choose the spatial-temporal dynamic data as a case study for the urban flows prediction task. Fourth, we analyze and compare some well-known and state-of-the-art flows prediction methods in detail, classifying them into five categories: statistics-based, traditional machine learning-based, deep learning-based, reinforcement learning-based and transfer learning-based methods. Finally, we give open challenges of urban flows prediction and an outlook in the future of this field. This paper will facilitate researchers find suitable methods and open datasets for addressing urban spatial-temporal flows forecast problems. Copyright © 2019, The Authors. All rights reserved.

关键词： data fusion

Math teaching aids in shape topics for PT3 students

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IOP Conference Series: Materials Science and Engineering 2020年第1期979卷

作者： R E Roshidan N A F Ismail N Z S Othman N M Suaib School of Computing Faculty of Engineering Universiti Teknologi Malaysia 81310 Skudai Johor Bahru Malaysia UTM Big Data Center Ibnu Sina Institute of Scientific and Industrial Research Universiti Teknologi Malaysia 81310 UTM Skudai Johor Malaysia.

Mathematics is a significant pillar in science as mathematics has built technology, machines and digital as progress in this century. Therefore, mathematics is essential to practice since childhood. Although various efforts have been made in updating the teaching methods to students by teachers, students still have difficulty in understanding mathematical concepts, especially in the topic of form. Most students memorize more than they know logic and discoveries in mathematics. Teaching aids are interactive software that can be used simulated. Therefore, the goal of this project is to develop mathematics teaching aids for shape topics for Form Three Assessment (Pentaksiran Tingkatan Tiga - PT3) students. The study involves three main phases which are initial research and data collection, design and implementation and assessment.

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Spatially-resolved spectro-photometric SED Modeling of NGC 253’s Central Molecular Zone I. Studying the star formation in extragalactic giant molecular clouds

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arXiv 2025年

作者： Humire, Pedro K. Dey, Subhrata Ronconi, Tommaso Sasse, Victor H. Fernandes, Roberto Cid Martín, Sergio Donevski, Darko Malek, Katarzyna Fernández-Ontiveros, Juan A. Song, Yiqing Hamed, Mahmoud Mangum, Jeffrey G. Henkel, Christian Rivilla, Víctor M. Colzi, Laura Harada, N. Demarco, Ricardo Goyal, Arti Meier, David S. Panda, Swayamtrupta Krabbe, Ângela C. Yan, Yaoting Lopes, Amanda R. Sakamoto, K. Muller, S. Tanaka, K. Yoshimura, Y. Nakanishi, K. Kanaan, Antonio Ribeiro, Tiago Schoenell, William de Oliveira, Claudia Mendes Departamento de Astronomia Instituto de Astronomia Geofísica e Ciências Atmosféricas da USP Cidade Universitária SP São Paulo05508-090 Brazil Astronomical Observatory The Jagiellonian University Orla 171 Kraków30-244 Poland National Center for Nuclear Research ul. Pasteura 7 Warsaw02-093 Poland Via Bonomea 265 TriesteIT-34136 Italy Via Beirut 2 TriesteIT-34151 Italy Via Gobetti 93/3 BolognaI-40127 Italy ICSC – Centro Nazionale di Ricerca in High Performance Computing Big Data e Quantum Computing Via Magnanelli 2 Bologna Italy Universidade Federal de Santa Catarina Campus Universitário Reitor João David Ferreira Lima SC Florianópolis88040-900 Brazil European Southern Observatory Alonso de Córdova 3107 Vitacura Santiago763-0355 Chile Joint ALMA Observatory Alonso de Córdova 3107 Vitacura Santiago763-0355 Chile Plaza San Juan 1 TeruelE–44001 Spain CSIC-INTA Carretera de Ajalvir km 4 Torrejón de Ardoz Madrid28850 Spain National Radio Astronomy Observatory 520 Edgemont Road CharlottesvilleVA22903-2475 United States Max-Planck-Institut für Radioastronomie Auf-dem-Hügel 69 Bonn53121 Germany Xinjiang Astronomical Observatory Chinese Academy of Sciences Urumqi830011 China National Astronomical Observatory of Japan 2-21-1 Osawa Mitaka Tokyo181-8588 Japan Institute of Astronomy and Astrophysics Academia Sinica 11F of AS/NTU Astronomy-Mathematics Building No.1 Sec. 4 Roosevelt Rd Taipei106319 Taiwan 2-21-1 Osawa Mitaka Tokyo181-1855 Japan Institute of Astrophysics Facultad de Ciencias Exactas Universidad Andrés Bello Sede Concepción Talcahuano Chile New Mexico Institute of Mining and Technology 801 Leroy Place SocorroNM87801 United States International Gemini Observatory NSF NOIRLab Casilla 603 La Serena Chile Instituto de Astrofísica de La Plata CONICET-UNLP Paseo del Bosque s/n B1900FWA Argentina Department of Space Earth and Environment Chalmers University of Technology Onsala Space Observatory OnsalaSE-4

Context. Studying the interstellar medium in nearby starbursts is essential for gaining insights into the physical mechanisms driving these extreme objects, thought to be analogs of young, primeval, star-forming galaxies. This task is now feasible due to deep spectro-photometric data enabled by rapid advancements in ground- and space-based facilities. To fully leverage this wealth of information, extracting insights from the spectral line properties, and the spectral energy distribution (SED) is imperative. Aims. This study aims to produce and analyze the physical properties of the first spatially-resolved multi-wavelength SED of an extragalactic source that covers six decades in frequency (from near-ultraviolet to centimeter wavelengths) at an angular resolution of 3′′ which corresponds to linear scale of ∼51 pc at the distance of NGC 253. We focus on the central molecular zone (CMZ) of this starburst galaxy, which contains giant molecular clouds (GMCs) responsible for half of the galaxy’s star formation. Methods. We retrieve archival data from optical to centimeter wavelengths, covering six decades of spectral range. We compute SEDs to fit the observations using the GalaPy code and confronting results with the CIGALE code for validation. We also employ starlight library to analyze the stellar optical spectra of the GMCs. Results. Our results reveal significant differences between central and external GMCs in terms of stellar and dust masses, star formation rates (SFRs), and bolometric luminosities, to provide a few. We have obtained tight relations between monochromatic stellar tracers and star-forming conditions obtained from panchromatic emission. We find that the best SFR tracers are radio continuum bands at 33 GHz, radio recombination lines (RRLs), and the total infrared (IR) luminosity range (LIR;8–1000µm) as well as the IR emission at 60µm. The emission line diagnostics based on the BPT and WHAN diagrams suggest that the nuclear region of NGC 253 exhibits sh

关键词： Optical emission spectroscopy

The Multi-modality Cell Segmentation Challenge: Towards Universal Solutions

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arXiv 2023年

作者： Ma, Jun Xie, Ronald Ayyadhury, Shamini Ge, Cheng Gupta, Anubha Gupta, Ritu Gu, Song Zhang, Yao Lee, Gihun Kim, Joonkee Lou, Wei Li, Haofeng Upschulte, Eric Dickscheid, Timo de Almeida, José Guilherme Wang, Yixin Han, Lin Yang, Xin Labagnara, Marco Gligorovski, Vojislav Scheder, Maxime Rahi, Sahand Jamal Kempster, Carly Pollitt, Alice Espinosa, Leon Mignot, Tâm Middeke, Jan Moritz Eckardt, Jan-Niklas Li, Wangkai Li, Zhaoyang Cai, Xiaochen Bai, Bizhe Greenwald, Noah F. Van Valen, David Weisbart, Erin Cimini, Beth A. Cheung, Trevor Brück, Oscar Bader, Gary D. Wang, Bo Peter Munk Cardiac Centre University Health Network TorontoON Canada Department of Laboratory Medicine and Pathobiology University of Toronto TorontoON Canada Vector Institute TorontoON Canada Department of Molecular Genetics University of Toronto TorontoON Canada Donnelly Centre University of Toronto TorontoON Canada Princess Margaret Cancer Centre University Health Network TorontoON Canada School of Medicine and Pharmacy Ocean University of China Qingdao China New Delhi India Laboratory Oncology Dr. BRA-IRCH All India Institute of Medical Sciences New Delhi India Department of Image Reconstruction Nanjing Anke Medical Technology Co. Ltd. Nanjing China Shanghai Artificial Intelligence Laboratory Shanghai China Graduate School of AI KAIST Seoul Korea Republic of Shenzhen Research Institute of Big Data Shenzhen China Shenzhen China Helmholtz AI Research Center Jülich Jülich Germany Faculty of Mathematics and Natural Sciences Institute of Computer Science Heinrich Heine University Düsseldorf Düsseldorf Germany Hinxton United Kingdom Champalimaud Foundation - Centre for the Unknown Lisbon Portugal Department of Bioengineering Stanford University Palo AltoCA United States Tandon School of Engineering New York University New YorkNY United States School of Biomedical Engineering Health Science Center Shenzhen University Shenzhen China Lausanne Switzerland School of Biological Sciences University of Reading Reading United Kingdom Laboratoire de Chimie Bactérienne CNRS Université Aix Marseille UMR Institut de Microbiologie de la Méditerranée Marseille France Department of Internal Medicine I University Hospital Dresden Technical University Dresden Dresden Germany Else Kroener Fresenius Center for Digital Health Technical University Dresden Dresden Germany Department of Automation University of Science and Technology of China Hefei China Institute of Advanced Technology University of Science and Technology of China Hefei Chi

Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or require manual interventions to specify hyper-parameters in different experimental settings. Here, we present a multi-modality cell segmentation benchmark, comprising over 1500 labeled images derived from more than 50 diverse biological experiments. The top participants developed a Transformer-based deep-learning algorithm that not only exceeds existing methods but can also be applied to diverse microscopy images across imaging platforms and tissue types without manual parameter adjustments. This benchmark and the improved algorithm offer promising avenues for more accurate and versatile cell analysis in microscopy imaging. © 2023, CC BY-NC-ND.

关键词： Deep learning

Erratum: “Spin wave propagation in a ferrimagnetic thin film with perpendicular magnetic anisotropy” [Appl. Phys. Lett. 117, 232407 (2020)]

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Applied Physics Letters 2021年第2期118卷

作者： Lutong Sheng Yawen Liu Jilei Chen Hanchen Wang Jianyu Zhang Mingfeng Chen Ji Ma Chuanpu Liu Sa Tu Ce-Wen Nan Haiming Yu 1Fert Beijing Institute School of Integrated Circuit Science and Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing 100191 China 2Department of Physics and Astronomy University of California Riverside California 92521 USA 3State Key Lab of New Ceramics and Fine Processing School of Materials Science and Engineering Tsinghua University Beijing 100084 China

In the original article,1 the line spectrum in Fig. 2(b) is missing. The correct Fig. 2(b), given here, shows how we get the frequency difference from this spec

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User Behavior Analysis of Location-Based Social Network

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User Behavior Analysis of Location-Based Social Network

IIAI International Conference on Advanced Applied Informatics (IIAIAAI)

作者： Jun Zeng Xin He Yingbo Wu Sachio Hirokawa Key Laboratory of Dependable Service Computing in Cyber Physical Society School of Big Data and Software Engineering Chongqing China School of Big Data and Software Engineering Chongqing China Research Institute for Information Technology Kyushu University Fukuoka Japan

ISBN: (纸本)9781538674482;9781538674475

User behavior changes over time under the influence of their activities. We contend that these activities are non-random behavior and have a desire to explore the underlying information behind these changes. In this paper, we analyze user behavior by using the check-in data in Location Based Social Networks (LBSNs), and examine whether they have the features of trend, periodicity and surprise or not. We explore some dynamics behaviors of people through their check-in times, and divide time into annually, monthly and even weekly analysis to find out the pattern of their behavior. Eventually, we found the check-in data do exhibit these three features by analyzing them deeply. The analytical work lays the foundation for the further recommendation research.

关键词： Market research Social networking (online) big data Software engineering Accidents Trajectory Motion pictures

Cultural heritage preservation efforts in Malaysia: A survey

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IOP Conference Series: Materials Science and Engineering 2020年第1期979卷

作者： N M Suaib N A F Ismail S Sadimon Z Mohd Yunos UTM Big Data Center Ibnu Sina Institute of Scientific and Industrial Research Universiti Teknologi Malaysia 81310 UTM Skudai Johor Malaysia. School of Computing Faculty of Engineering Universiti Teknologi Malaysia 81310 UTM Skudai Johor Malaysia.

Malaysia, just like its neighbouring countries in the region, has a rich and diverse culture and heritage treasures. What makes Malaysia more unique is its diversity as a multi-racial and multicultural country. These cultural heritages might become lost and extinct without any efforts in preserving and safeguarding due to modernization, assimilation, and globalization. We present an overview of different cultural heritage in Malaysia and available efforts to preserve these treasures found from literature. Digital preservation efforts that computer graphics, media scientists and practitioners could offer as alternatives in preservation of culture and heritage preservation will also be included in this paper.

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Systematic Resource Allocation in Cloud RAN with Caching as a Service under Two Timescales

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Systematic Resource Allocation in Cloud RAN with Caching as ...

作者： Tang, Jianhua Quek, Tony Q. S. Chang, Tsung-Hui Shim, Byonghyo Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing College of Information Science and Engineering Hunan Normal University Changsha410081 China Institute of New Media and Communications Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore487372 Singapore Department of Electronic Engineering Kyung Hee University Yongin17104 Korea Republic of School of Science and Engineering Chinese University of Hong Kong Shenzhen518172 China Shenzhen Research Institute of Big Data Shenzhen518172 China Department of Electrical and Computer Engineering Institute of New Media and Communications Seoul National University Seoul08826 Korea Republic of

Recently, cloud radio access network (C-RAN) with caching as a service (CaaS) was proposed to merge the functionalities of communication, computing, and caching (CCC) together. In this paper, we dissect the interactions of CCC in C-RAN with CaaS from two dimensions: physical resource dimension and time dimension. In the physical resource dimension, we identify how to segment the baseband unit (BBU) pool resources (i.e., computation and storage) into different types of virtual machines (VMs). In the time dimension, we address how the long-term resource segmentation in the BBU pool impacts on the short-term transmit beamforming at the remote radio heads. We formulate the problem as a stochastic mixed-integer nonlinear programming (SMINLP) to minimize the system cost, including the server cost, VM cost and wireless transmission cost. After a series of approximation, including sample average approximation, successive convex approximation, and semidefinite relaxation, the SMINLP is approximated as a global consensus problem. The alternating direction method of multipliers (ADMM) is utilized to obtain the solution in a parallel fashion. Simulation results verify the convergence of our proposed algorithm, and also confirm that the proposed scheme is more cost-saving than that without considering the integration of CCC. © 1972-2012 IEEE.

关键词： Integer programming