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IEEE International Workshop on Safety, Security, and Rescue Robotics (SSRR)

作者： Marco Salathe Brian J. Quiter Mark S. Bandstra Xin Chen Victor Negut Micah Folsom Gunther H. Weber Christopher Greulich Mathew Swinney Nicholas Prins Daniel E. Archer Applied Nuclear Physics Program at Lawrence Berkeley National Laboratory Berkeley CA USA Machine Learning and Analytics group Computer Science Research Division Lawrence Berkeley National Laboratory Oak Ridge National Laboratory Oak Ridge TN USA

ISBN: (纸本)9781665456814

A handheld system developed to digitize a contextual understanding of the scene at a chemical, biological, radiological, nuclear and/or explosives (CBRNE) events is described. The system uses LiDAR and cameras to create a colorized 3D model of the environment, which helps domain experts that are supporting responders in the field. To generate the digitized model, a responder scans any suspicious objects and the surroundings by carrying the system through the scene. The scanning system provides a real-time user interface to inform the user about scanning progress and to indicate any areas that may have been missed either by the LiDAR sensors or the cameras. Currently, the collected data are post-processed on a different device, building a colorized triangular mesh of the encountered scene, with the intention of moving this pipeline to the scanner at a later point. The mesh is sufficiently compressed to be sent over a reduced bandwidth connection to a remote analyst. Furthermore, the system tracks fiducial markers attached to diagnostic equipment that is placed around the suspicious object. The resulting tracking information can be transmitted to remote analysts to further facilitate their supporting efforts. The paper will discuss the system's design, software components, the user interface used for scanning a scene, the necessary procedures for calibration of the sensors, and the processing steps of the resulting data. The discussion will close by evaluating the system's performance on 11 scenes.

关键词： computer vision Three-dimensional displays Laser radar Computational modeling Pipelines User interfaces Position measurement

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Characterizing the mechanical response of metallic glasses to uniaxial tension using a spring network model

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Physical Review Materials 2023年第7期7卷 073605-073605页

作者： Aya Nawano Weiwei Jin Jan Schroers Mark D. Shattuck Corey S. O'Hern Department of Mechanical Engineering and Materials Science Yale University New Haven Connecticut 06520 USA Benjamin Levich Institute and Physics Department The City College of New York New York New York 10031 USA Department of Physics Yale University New Haven Connecticut 06520 USA Department of Applied Physics Yale University New Haven Connecticut 06520 USA Graduate Program in Computational Biology and Bioinformatics Yale University New Haven Connecticut 06520 USA

A coarse-grained spring network model is proposed for the prediction of the mechanical response of metallic glasses as a function of the microstructure prior to loading. This model describes the mechanical response of metallic glasses using a network of parallel springs that can break and reform, mimicking atomic rearrangements during deformation. We compare predictions of the spring network model for stress versus strain to results from numerical simulations of athermal quasistatic, uniaxial tensile deformation of Cu50Zr50 metallic glasses using Lennard-Jones (LJ) and embedded atom method (EAM) atomic interactions. We show that both the LJ and EAM models possess qualitatively similar stress σ versus strain γ curves. By specifying five parameters [ultimate strength, strain at ultimate strength, slopes of σ(γ) at γ=0 and at large strain, and strain at fracture where σ=0], we demonstrate that the spring network model can accurately describe the form of the stress-strain curves during uniaxial tension for the computational studies of Cu50Zr50, as well as recent experimental studies of several Zr-based metallic glasses.

关键词： Alloys Amorphous materials Glasses Packing & jamming problems Molecular dynamics

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Stock Price Prediction and Recommendation Approach Based on Machine Learning

Stock Price Prediction and Recommendation Approach Based on ...

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IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE)

作者： Chin-Chih Chang Kei-Wen Luo Sean Hsiao Bachelor’s Program in Applied Foreign Language and Smart Commerce Chung Hua University Hsinchu Taiwan Department of Computer Science and Information Engineering Chung Hua University Hsinchu Taiwan

ISBN: (纸本)9781665482097

Investment is a lifetime work. Investing in stocks is a popular measure. However, investing in stocks is not easy, and losing money is not uncommon. We investigate if there is a systematic way to find buyable stocks and more importantly when to buy and sell them. Nowadays, with the progress of hardwarel, artificial intelligence (AI) has become a feasible solution to many issues. Machine learning and deep learning are two widely adopted methods in AI. In this study, we show how to apply machine learning to stock prediction and recommendation. After trials, we found that LightGBM shows its potential to predict and recommend stocks. We used the data of the Taiwan stock market to validate the method. We compared the prediction and recommendation with the wellknown Taiwan ETFs 0050 and 0056. The results show that the method is feasible, effective, efficient, and has better performance than Taiwan ETFs 0050 and 0056.

关键词： Deep learning Systematics Stock markets Investment

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Designing the pressure-dependent shear modulus using tessellated granular metamaterials

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Physical Review E 2023年第3期108卷 034901-034901页

作者： Jerry Zhang Dong Wang Weiwei Jin Annie Xia Nidhi Pashine Rebecca Kramer-Bottiglio Mark D. Shattuck Corey S. O'Hern Department of Mechanical Engineering & Materials Science Yale University New Haven Connecticut 06520 USA Benjamin Levich Institute and Physics Department The City College of New York New York New York 10031 USA Department of Physics Yale University New Haven Connecticut 06520 USA Department of Applied Physics Yale University New Haven Connecticut 06520 USA Integrated Graduate Program in Physical and Engineering Biology Yale University New Haven Connecticut 06520 USA

Jammed packings of granular materials display complex mechanical response. For example, the ensemble-averaged shear modulus 〈G〉 increases as a power law in pressure p for static packings of soft spherical particles that can rearrange during compression. We seek to design granular materials with shear moduli that can either increase or decrease with pressure without particle rearrangements even in the large-system limit. To do this, we construct tessellated granular metamaterials by joining multiple particle-filled cells together. We focus on cells that contain a small number of bidisperse disks in two dimensions. We first study the mechanical properties of individual disk-filled cells with three types of boundaries: periodic boundary conditions (PBC), fixed-length walls (FXW), and flexible walls (FLW). Hypostatic jammed packings are found for cells with FLW, but not in cells with PBC and FXW, and they are stabilized by quartic modes of the dynamical matrix. The shear modulus of a single cell depends linearly on p. We find that the slope of the shear modulus with pressure λc<0 for all packings in single cells with PBC where the number of particles per cell N≥6. In contrast, single cells with FXW and FLW can possess λc>0, as well as λc<0, for N≤16. We show that we can force the mechanical properties of multicell granular metamaterials to possess those of single cells by constraining the end points of the outer walls and enforcing an affine shear response. These studies demonstrate that tessellated granular metamaterials provide a platform for the design of soft materials with specified mechanical properties.

关键词： Jamming Granular solids Mechanical metamaterials

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Customer Service Chatbot Enhanced with Conversational Language Understanding and Knowledge Base

Customer Service Chatbot Enhanced with Conversational Langua...

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IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE)

作者： Chin-Chih Chang Wen-Shing Cheng Sean Hsiao Bachelor’s Program in Applied Foreign Language and Smart Commerce Chung Hua University Hsinchu Taiwan Department of Computer Science and Information Engineering Chung Hua University Hsinchu Taiwan

ISBN: (纸本)9781665482097

A customer service chatbot enhanced with conversational language understanding and knowledge base is developed. Here, we explore LUIS and QnA Maker which are unified as Azure cognitive service for language. LUIS is a cloudbased conversational AI service that responds a user intelligence. QnA maker is a knowledge base for custom question answering. This question-and-answer knowledge base is especially useful for customer dialogs. Hence, by combining the services, we provide a smart response and provide a knowledge base to understand and improve the service. We implement this chatbot on the LINE Bot platform. Users easily access it by simply adding the representative of this chatbot on LINE. In addition, we put marketing information through this chatbot. The experiments are conducted, and the results show the chatbot is feasible and has a high user acceptance.

关键词： Customer services Knowledge based systems Chatbots Question answering (information retrieval)

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Detection of Coffee Bean Damage in the Roasting Process Based on Shape Features Analysis 2

Detection of Coffee Bean Damage in the Roasting Process Base...

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2019 2nd International Conference on Mathematics and Natural sciences, IConMNS 2019

作者： Gunadi, I.G.A. Artha, I.P.M.K. Christyaditama, I.G.P. Wicaksana, G.A.S. Martina, I.M. Departement of Physics and Natural Science Teaching Universitas Pendidikan Ganesha Indonesia Magister Program of Computer Science Universitas Pendidikan Ganesha Indonesia

Many studies raise the issue of analysis on the quality of coffee beans (green beans). Green beans are the term used to indicate coffee beans before roasting. The importance of analyzing the quality of coffee beans not only in coffee beans but also in rice seeds. Rice seeds are used as a mixture in the roasting process of coffee. Analysis of the quality of roasted coffee is very important. In roasted coffee beans can be damaged and changes to the coffee beans. Some types of damage to coffee beans include, blackened seeds, partially blackened seeds, browned seeds, broken seeds, perforated seeds, epidermis seeds, horned skin seeds, too young seeds, spotted seeds, and dirty seeds. This study focuses on one of the damage factors, namely broken coffee beans after broken beans. In this study, analysis of roasted coffee quality was determined by shape analysis. The shape analysis uses elongation values. there are two categories of classification, the first class of coffee is of good quality, and the second is coffee with poor grade. Classification is good if the elongation value is more than 0.85, for other conditions it is classified as bad. The results of this study have the following accuracy values, at coffee with a classification of good accuracy of 93.4%, while those at coffee with a bad classification of accuracy are 78.5%. © Published under licence by IOP Publishing Ltd.

关键词： Damage detection

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Towards seamless environmental prediction-development of Pan-Eurasian EXperiment(PEEX)modelling platform

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Big Earth Data 2024年第2期8卷 189-230页

作者： Alexander Mahura Alexander Baklanov Risto Makkonen Michael Boy Tuukka Petäjä Hanna KLappalainen Roman Nuterman Veli-Matti Kerminen Stephen R.Arnold Markus Jochum Anatoly Shvidenko Igor Esau Mikhail Sofiev Andreas Stohl Tuula Aalto Jianhui Bai Chuchu Chen Yafang Cheng Oxana Drofa Mei Huang Leena Järvi Harri Kokkola Rostislav Kouznetsov Tingting Li Piero Malguzzi Sarah Monks Mads Bruun Poulsen Steffen M.Noe Yuliia Palamarchuk Benjamin Foreback Petri Clusiu Till Andreas Soya Rasmussen Jun She Jens Havskov Sørensen Dominick Spracklen Hang Su Juha Tonttila Siwen Wang Jiandong Wang Tobias Wolf-Grosse Yongqiang Yu Qing Zhang Wei Zhang Wen Zhang Xunhua Zheng Siqi Li Yong Li Putian Zhou Markku Kulmala Faculty of Science Institute for Atmospheric and Earth System Research(INAR)/PhysicsUniversity of Helsinki(UHEL)HelsinkiFinland Science and Innovation Department World Meteorological Organization(WMO)GenevaSwitzerland Niels Bohr Institute University of CopenhagenCopenhagenDenmark Climate System Research Finnish Meteorological Institute(CSR-FMI)HelsinkiFinland School of Engineering Sciences Lappeenranta University of TechnologyLappeenrantaFinland Institute for Climate and Atmospheric Science School of Earth and EnvironmentUniversity of LeedsLeedsUK Biodiversity and Natural Resources Program International Institute for Applied Systems Analysis(IIASA)LaxenburgAustria Department of Physics and Technology UiT-The Arctic University of NorwayTromsoNorway Nansen Environmental and Remote Sensing Center(NERSC) BergenNorway Atmospheric Composition Finnish Meteorological Institute(AC-FMI)HelsinkiFinland Norwegian Institute for Air Research(NILU) KjellerNorway LAGEO Institute of Atmospheric PhysicsChinese Academy of Sciences(IAP-CAS)BeijingChina Max Planck Institute for Chemistry(MPI-Chem) MainzGermany Institute of Atmospheric Sciences and Climate National Research Council of Italy(CNR-15SAC)BolognaItaly Institute of Geographic Sciences and Natural Resources Research(IGSNRR) Chinese Academy of Sciences(CAS)BeijingChina Faculty of Science Helsinki Institute of Sustainability Science(HELSUS)University of Helsinki(UHEL)HelsinkiFinland Atmospheric Research Centre of Eastern Finland Finnish Meteorological Institute(ARCEF-FMI)KuopioFinland Institute of Atmospheric Physics Chinese Academy of Sciences(IAP-CAS)BeijingChina Department of Plant Physiology Estonian University of Life Sciences(EULS)Institute of Agricultural and Environmental Sciences(IAES)TartuEstonia Danish Meteorological Institute(DMI) CopenhagenDenmark State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry(LAPC) Institute of Atmospheric Physics(IAP)Chinese Academy of Sciences(CAS)BeijingChina Uni

The Pan-Eurasian Experiment Modelling Platform(PEEX-MP)is one of the key blocks of the PEEX Research *** PEEX MP has more than 30 models and is directed towards seamless envir-onmental *** main focus area is the Arctic-boreal regions and *** models used in PEEX-MP cover several main components of the Earth’s system,such as the atmosphere,hydrosphere,pedosphere and biosphere,and resolve the physicalchemicalbiological processes at different spatial and temporal scales and *** paper introduces and discusses PEEX MP multi-scale modelling concept for the Earth system,online integrated,forward/inverse,and socioeconomical modelling,and other approaches with a particular focus on applications in the PEEX geographical *** employed high-performance com-puting facilities,capabilities,and PEEX dataflow for modelling results are *** virtual research platforms(PEEXView,Virtual Research Environment,Web-based Atlas)for handling PEEX modelling and observational results are *** over-all approach allows us to understand better physical-chemicalbiological processes,Earth’s system interactions and feedbacks and to provide valuable information for assessment studies on evaluating risks,impact,consequences,*** population,envir-onment and climate in the PEEX *** work was also one of the last projects of *** Zilitinkevich,who passed away on 15 February *** the finalization took time,the paper was actually submitted in 2023 and we could not argue that the final paper text was agreed with him.

关键词： Multi-scale and-processes modelling concept seamless coupling high-performance computing data infrastructure virtual research platforms

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Performance limits due to thermal transport in graphene single-photon bolometers

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Physical Review applied 2024年第1期21卷 014006-014006页

作者： Caleb Fried B. Jordan Russell Ethan G. Arnault Bevin Huang Gil-Ho Lee Dirk Englund Erik A. Henriksen Kin Chung Fong Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge Massachusetts 02139 Department of Earth and Planetary Sciences Harvard University Cambridge Massachusetts 02138 USA Department of Physics Harvard University Cambridge Massachusetts 02138 USA Raytheon BBN Quantum Engineering and Computing Group Cambridge Massachusetts 02138 USA Department of Physics Washington University in St. Louis St. Louis Missouri USA Intelligence Community Postdoctoral Research Fellowship Program Massachusetts Institute of Technology Cambridge Massachusetts 02139 Department of Physics Pohang University of Science and Technology Pohang 790-784 Republic of Korea

In high-sensitivity bolometers and calorimeters, the photon absorption often occurs at a finite distance from the temperature sensor to accommodate antennas or avoid the degradation of superconducting circuitry exposed to radiation. As a result, thermal propagation from the input to the temperature readout can critically affect detector performance. In this paper we model the performance of a graphene bolometer, accounting for electronic thermal diffusion and dissipation via electron-phonon coupling at low temperatures in three regimes: clean, supercollision, and resonant scattering. Our results affirm the feasibility of a superconducting readout without Cooper-pair breaking by mid- and near-infrared photons, and provide a recipe for designing graphene absorbers for calorimetric single-photon detectors. We investigate the trade-off between the input-readout distance and detector efficiency, and predict an intrinsic timing jitter of approximately 2.7 ps. Based on our result, we propose a spatial-mode-resolving photon detector to increase the communication bandwidth.

关键词： Heat transfer Metrology Optical quantum information processing Graphene Josephson junctions Bolometers Calorimetry Single-photon detectors

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Not all spacetime coordinates for general-relativistic ray tracing are created equal

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Physical Review D 2023年第8期108卷 084004-084004页

作者： Gabriele Bozzola Chi-kwan Chan Vasileios Paschalidis Department of Astronomy University of Arizona Tucson Arizona USA Data Science Institute University of Arizona Tucson Arizona USA and Program in Applied Mathematics University of Arizona Tucson Arizona USA Department of Astronomy University of Arizona Tucson Arizona USA and Department of Physics University of Arizona Tucson Arizona USA

Models for the observational appearance of astrophysical black holes rely critically on accurate general-relativistic ray tracing and radiation transport to compute the intensity measured by a distant observer. In this paper, we illustrate how the choice of coordinates and initial conditions affect this process. In particular, we show that propagating rays from the camera to the source leads to different solutions if the spatial part of the momentum of the photon points towards the horizon or away from it. In doing this, we also show that coordinates that are well suited for numerical general-relativistic magnetohydrodynamic (GRMHD) simulations are typically not optimal for generic ray tracing. We discuss the implications for black hole images and show that radiation transport in optimal and nonoptimal spacetime coordinates lead to the same images up to numerical errors and algorithmic choices.

关键词： Classical black holes General relativity Accretion disk & black-hole plasma Astronomical black holes Numerical techniques Relativistic magnetohydrodynamics

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Dynamical properties of particulate composites derived from ultradense stealthy hyperuniform sphere packings

arXiv

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arXiv 2025年

作者： Vanoni, Carlo Kim, Jaeuk Steinhardt, Paul J. Torquato, Salvatore Department of Physics Princeton University PrincetonNJ08544 United States Department of Chemistry Princeton University PrincetonNJ08544 United States Princeton Institute for the Science and Technology of Materials Princeton University PrincetonNJ08544 United States Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States

Stealthy hyperuniform (SHU) many-particle systems are distinguished by a structure factor that vanishes not only at zero wavenumber (as in "standard" hyperuniform systems) but also across an extended range of wavenumbers near the origin. We generate disordered SHU packings of identical and ‘nonoverlapping’ spheres in d-dimensional Euclidean space using a modified collective-coordinate optimization algorithm that incorporates a soft-core repulsive potential between particles in addition to the standard stealthy pair potential. Compared to SHU packings without soft-core repulsions, these SHU packings are ultradense with packing fractions ranging from 0.67-0.86 for d = 2 and 0.47-0.63 for d = 3, spanning a broad spectrum of structures depending on the stealthiness parameter χ. We consider two-phase media composed of hard particles derived from ultradense SHU packings (phase 2) embedded in a matrix phase (phase 1), with varying stealthiness parameter χ and packing fractions . Our main objective is the estimation of the dynamical physical properties of such two-phase media, namely, the effective dynamic dielectric constant and the time-dependent diffusion spreadability, which is directly related to nuclear magnetic relaxation in fluid-saturated porous media. We show through spreadability that two-phase media derived from ultradense SHU packings exhibit faster interphase diffusion due to the higher packing fractions achievable compared to media obtained without soft-core repulsion. The imaginary part of the effective dynamic dielectric constant of SHU packings vanishes at a small wavenumber, implying perfect transparency for the corresponding wavevectors. While a larger packing fraction yields a smaller transparency interval, we show that it also displays a reduced height of the attenuation peak. We also obtain cross-property relations between transparency characteristics and long-time behavior of the spreadability for such two-phase media, showing that one leads to infor

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