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Communication, computing and Energy Efficient Technologies (I3CEET), International Conference on

作者： Achilov Docent Saurabh Dhanik Pardeep Kumar Jindal Saif O. Husain Diwakar Bhardwaj Varsha Mittal Department of Physics and Chemistry Tashkent Institute of Irrigation and Agricultural Mechanization Engineers National Research University Tashkent Uzbekistan Scientific Researcher Western Caspian University Baku Azerbaijan School of Computing Graphic Era Hill University Bhimtal India Department of Electrical and Communication Engineering Chandigarh Engineering College Chandigarh Group of Colleges Mohali Punjab India Department of Computers Techniques Engineering College of Technical Engineering The Islamic University of Al Diwaniyah Al Diwaniyah Iraq Department of Computer Engineering and Applications GLA University Mathura India Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun India

ISBN: (数字)9798331541583

ISBN: (纸本)9798331541590

With the stark increase due to smarter homes using online of Things, or IoT devices exchanging info far more frequently than we used to — all wirelessly. IoT devices are affected by several issues like possible cyberattacks, the unpredictability of network connectivity and data leakage since there are many types of IoT devices being used today. OBJECTIVES: To improve the privacy of data provided from web of Things (IoT) smart home devices by using machine training and computational modeling to detect anomalies. At its core the experiment contribution is how reliable Web of Things (WoT), i.e. IoT technologies transferring values from or to home things, reasons are taking different features such as average sq rate error origin and feature value in account of evaluations about internet-connected device efficacy. It is a metric that seems so important when we consider our dependency on every attached Internet of Things (IoT) device, in the network's architecture. The proposed method is applied and validated using a dataset of smart homes along with real temperature information collected for public access. Using Time series evidence collected by iot devices, the suggested method works extremely well as it can detect any anomaly or spam. This technique helps with the general health and safety of your entire structure by creating a solid base for evaluating the acceptability of Sea-of-things (SoT) gadgets in just a smart home network..

关键词： Training Data privacy Time series analysis Smart homes Smart meters Telecommunication computing Internet of Things Reliability Object recognition Tuning

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High Statistics Measurements of Pedestrian Dynamics

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Transportation Research Procedia 2014年 2卷 96-104页

作者： Alessandro Corbetta Luca Bruno Adrian Muntean Federico Toschi CASA- Centre for Analysis Scientific computing and Applications Department of Mathematics and Computer Science Eindhoven University of Technology P.O. Box 513 5600 MB Eindhoven The Netherlands Department of Structural Geotechnical and Building Engineering Politecnico di Torino Corso Duca degli Abruzzi 24 10126 Torino Italy Department of Architecture and Design Politecnico di Torino Viale Mattioli 39 10125 Torino Italy ICMS - Institute for Complex Molecular Systems Eindhoven University of Technology The Netherlands Department of Applied Physics Eindhoven University of Technology 5600 MB Eindhoven The Netherlands CNR-IAC Via dei Taurini 19 00185 Rome Italy

Aiming at a quantitative understanding of basic aspects of pedestrian dynamics, extensive and high-accuracy measurements of real-life pedestrian trajectories have been performed. A measurement strategy based on Microsoft Kinect TM has been used. Specifically, more than 100.000 pedestrians have been tracked while walking along a trafficked corridor at the Eindhoven University of Technology, The Netherlands. The obtained trajectories have been analyzed as ensemble data. The main result consists of a statistical descriptions of pedestrian characteristic kinematic quantities such as positions and fundamental diagrams, possibly conditioned to the local crowd flow (e.g. co-flow or counter-flow).

关键词： pedestrian dynamics pedestrian tracking high statistics measurements statistical mechanics

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What if?.. Fabulating African HCI Futures within the Veil of HCI 23

What if?.. Fabulating African HCI Futures within the Veil of...

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Proceedings of the 4th African Human computer Interaction Conference

作者： Shaimaa Lazem Muhammad Sadi Adamu Yasmeen Abdrabou Chris Muashekele Sheena Erete Jakita Thomas Hafeni Mthoko Heike Winschiers-Teophilus Nicola Bidwell Aderonke Sakpere Anicia Peters City of Scientific Research and Technology Applications (SRTA-City) Egypt Imagination Lancaster Lancaster University United Kingdom School of Computing and Communications Lancaster University United Kingdom Aalborg University Denmark College of Information Studeies University of Maryland USA Department of Computer science and software Engineering (CSSE) Auburn University USA NurtureID8 Namibia Department of Software Engineering Namibia University of Science and Technology Namibia Intenational Uiversity of Management Namibia and University of Melbourne Australia University of Ibadan Nigeria National Commission of Research Sicence and Technology (NCRST) Namibia

ISBN: (纸本)9798400708879

This workshop aims to bring together researchers and practitioners (African and otherwise) engaging with diverse communities and industries to discuss the geopolitics of knowledge production in computing research and design. Our proposal builds on existing works that have explored the modalities of the knowledge economy - particularly as knowledge is created, legitimized, and circulated as objective truth via the exercise of power. For example, engaging indigenous communities in conferences and knowledge fairs have sought to challenge disciplinary silos and boundaries imposed on non-Western academics and practitioners. This workshop, as a platform for interaction and discussion with no “sage on the stage”, is the first of its kind within AfriCHI and it seeks to explore and promote more subtle discussions about HCI knowledge production and dissemination practices.

关键词： African HCI Critical fabulation Decolonizing HCI Indigenous knowledge alt.HCI

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A Greedy Sensor Selection Algorithm for Hyperparameterized Linear Bayesian Inverse Problems

arXiv

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arXiv 2023年

作者： Aretz, Nicole Chen, Peng Degen, Denise D. Veroy, Karen Oden Institute for Computational Engineering and Sciences University of Texas at Austin 201 E 24th St AustinTX78712 United States School of Computational Science and Engineering Georgia Institute of Technology 756 W Peachtree St NW AtlantaGA30308 United States Computational Geoscience Geothermics and Reservoir Geophysics RWTH Aachen University Mathieustr. 30 Aachen52074 Germany Center for Analysis Scientific Computing and Applications Department of Mathematics and Computer Science Eindhoven University of Technology Eindhoven5612 AZ Netherlands

We consider optimal sensor placement for a family of linear Bayesian inverse problems characterized by a deterministic hyper-parameter. The hyper-parameter describes distinct configurations in which measurements can be taken of the observed physical system. To optimally reduce the uncertainty in the system’s model with a single set of sensors, the initial sensor placement needs to account for the non-linear state changes of all admissible configurations. We address this requirement through an observability coefficient which links the posteriors’ uncertainties directly to the choice of sensors. We propose a greedy sensor selection algorithm to iteratively improve the observability coefficient for all configurations through orthogonal matching pursuit. The algorithm allows explicitly correlated noise models even for large sets of candidate sensors, and remains computationally efficient for high-dimensional forward models through model order reduction. We demonstrate our approach on a large-scale geophysical model of the Perth Basin, and provide numerical studies regarding optimality and scalability with regard to classic optimal experimental design utility functions. © 2023, CC BY.

关键词： Inverse problems

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A Lightweight Feature Selection Method Based on Rankability

SSRN

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SSRN 2024年

作者： Kong, Lingping Velasquez, Juan D. Perfilieva, Irina Pant, Millie Pan, Jeng-Shyang Snášel, Václav Department of Computer Science VSB-Technical University of Ostrava Ostrava Czech Republic Department of Industrial Engineering University of Chile Santiago Chile Santiago Chile Institute for Research and Applications of Fuzzy Modeling Centre of Excellence IT4Innovations division of The University of Ostrava Ostrava Czech Republic Department of Applied Mathematics and Scientific Computing Indian Institute of Technology Uttarakhand Roorkee247667 India School of Artificial Intelligence Nanjing University of Information Science and Technology China Instituto Sistemas Complejos de Ingeniería Santiago Chile Santiago Chile Faculty of Computer Science and Telecommunications Cracow University of Technology Kraków Poland Mehta Family School of Data Science and Artificial Intelligence Indian Institute of Technology Uttarakhand Roorkee247667 India College of Computer Science and Engineering Shandong University of Science and Technology China

Within the realm of data mining and machine learning, feature selection stands out as an essential technique for dimensionality reduction, presenting both popularity and complexity. Feature selection involves a nuanced trade-off that results in information loss. This distinction underscores the necessity for the development of lightweight, efficient, and practical methods capable of minimizing information loss while executing dimensional reduction. In this paper, we introduce a rankability-based feature selection method. The concept of rankability, proposed in 2019 and similar to the entropy concept, remains relatively unexplored. Our proposed method distinguishes itself by its lightweight complexity, eliminating the need for iterative *** evaluate the effectiveness of our approach, we conducted experiments on forty-one datasets and compared the results with four other algorithms using refined data with 10\%, 30\%, and 50\% feature dimension reduction. The findings reveal that our rankability-based feature selection method consistently outperforms the other four methods across a majority of datasets in terms of accuracy, precision, recall, and F1-macro performance. Specifically, the classification score exceeds 0.9 on accuracy for 50\% feature dimension reduction in twelve datasets, with nine datasets achieving scores over 0.9 in recall, F1-macro, and precision. Overall, our proposed feature selection method demonstrates promising performance. © 2024, The Authors. All rights reserved.

关键词： Feature Selection

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Solving the Klein-Gordon equation using Fourier spectral methods: A benchmark test for computer performance 23

Solving the Klein-Gordon equation using Fourier spectral met...

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23rd High Performance computing Symposium, HPC 2015, Part of the 2015 Spring Simulation Multi-Conference, SpringSim 2015

作者： Aseeri, S. Batrašev, O. Icardi, M. Leu, B. Liu, A. Li, N. Muite, B.K. Müller, E. Palen, B. Quell, M. Servat, H. Sheth, P. Speck, R. Van Moer, M. Vienne, J. KAUST Supcrcomputing Laboratory 4700 King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Arvutitcaduse Instituut Tartu Ülikool Liivi 2 Tartu50409 Estonia Stochastic Numerics Group 4700 King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Electrical and Computer Engineering University of Michigan Ann ArborMI48109-2122 United States Numerical Algorithms Group Wilkinson House Jordan Hill Road Oxford0X2 8DR United Kingdom Numerical Mathematics Group 4700 King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia Department of Mathematical Sciences University of Bath BathBA2 7 AY United Kingdom CAEN Advanced Computing University of Michigan Ann ArborMI48109-2094 United States Lnstitut für Analysis und Scientific Computing Technische Universität Wien Wiedner Haupstrasse 8-10 Wien1040 Austria Compulcr Sciences Department BSC UPC c/Jordi Girona Barcelona Calalunya08034 Spain Biomedical Engineering University of Michigan Ann ArborMI48109-2122 United States Jülich Supercomputing Centre Forschungszentrum Jülich GmbH Germany Germany National Center for Supercomputing Applications University of Illinois at Urbiina-Chanipaign UrbanaIL61801 United States Texas Advanced Computing Center University of Texas at Austin AustinTX78758-4497 United States

ISBN: (纸本)9781510810600

The cubic Klein-Gordon equation is a simple but non-trivial partial differential equation whose numerical solution has the main building blocks required for the solution of many other partial differential equations. In this study, the library 2DE-COMP&FFT is used in a Fourier spectral scheme to solve the Klein-Gordon equation and strong scaling of the code is examined on thirteen different machines for a problem size of 5123. The results are useful in assessing likely performance of other parallel fast Fourier transform based programs for solving partial differential equations. The problem is chosen to be large enough to solve on a workstation, yet also of interest to solve quickly on a supercomputer, in particular for parametric studies. Unlike the Linpack benchmark, a high ranking will not be obtained by simply building a bigger computer. © 2015 Aseeri et al.

关键词： Fast Fourier transforms

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Enhanced hyperspectral tomography for bioimaging by spatiospectral reconstruction

arXiv

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arXiv 2021年

作者： Warr, Ryan Ametova, Evelina Cernik, Robert J. Fardell, Gemma Handschuh, Stephan Jørgensen, Jakob S. Papoutsellis, Evangelos Pasca, Edoardo Withers, Philip J. Henry Royce Institute Department of Materials The University of Manchester ManchesterM13 9PL United Kingdom Laboratory for Applications of Synchrotron Radiation Karlsruhe Institute of Technology Kaiserstr. 12 KarlsruheD-76131 Germany Scientific Computing Department Science Technology Facilities Council UK Research and Innovation Rutherford Appleton Laboratory Chilton DidcotOX11 0QX United Kingdom VetCore Facility for Research University of Veterinary Medicine Vienna Vienna Austria Department of Applied Mathematics and Computer Science Technical University of Denmark Denmark Department of Mathematics The University of Manchester ManchesterM13 9PL United Kingdom

Here we apply hyperspectral bright field imaging to collect computed tomographic images with excellent energy resolution (800 eV), applying it for the first time to map the distribution of stain in a fixed biological sample through its characteristic K-edge. Conventionally, because the photons detected at each pixel are distributed across as many as 200 energy channels, energy-selective images are characterised by low count-rates and poor signal-to-noise ratio. This means high X-ray exposures, long scan times and high doses are required to image unique spectral markers. Here, we achieve high quality energy-dispersive tomograms from low dose, noisy datasets using a dedicated iterative reconstruction algorithm. This exploits the spatial smoothness and inter-channel structural correlation in the spectral domain using two carefully chosen regularisation terms. For a multi-phase phantom, a reduction in scan time of 36 times is demonstrated. Spectral analysis methods including K-edge subtraction and absorption step-size fitting are evaluated for an ex vivo, single (iodine)-stained biological sample, where low chemical concentration and inhomogeneous distribution can affect soft tissue segmentation and visualisation. The reconstruction algorithms are available through the open-source Core Imaging Library. Taken together, these tools offer new capabilities for visualisation and elemental mapping, with promising applications for multiply-stained biological specimens. © 2021, CC BY.

关键词： Tomography

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Ground-motion modeling of the 1906 San Francisco Earthquake, part II: Ground-motion estimates for the 1906 earthquake and scenario events

Ground-motion modeling of the 1906 San Francisco Earthquake,...

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作者： Aagaard, Brad T. Brocher, Thomas M. Dolenc, David Dreger, Douglas Graves, Robert W. Harmsen, Stephen Hartzell, Stephen Larsen, Shawn McCandless, Kathleen Nilsson, Stefan Petersson, N. Anders Rodgers, Arthur Sjögreen, Björn Zoback, Mary Lou U.S. Geological Survey 345 Middlefield Rd. Menlo Park CA 94025 United States Seismological Laboratory University of California Berkeley 215 McCone Hall Berkeley CA 94720 United States URS Corporation 566 El Dorado St. Pasadena CA 91101 United States U.S. Geological Survey MS966 P.O. Box 25046 Golden CO 80225 United States Lawrence Livermore National Laboratory Box 808 L-103 Livermore CA 94551-0808 United States Computer Applications and Research Department Computations Directorate Lawrence Livermore National Laboratory Box 808 L-550 Livermore CA 94551-0808 United States Center for Applied Scientific Computing Computations Directorate Lawrence Livermore National Laboratory Box 808 L-550 Livermore CA 94551-0808 United States Atmospheric Earth and Energy Department Energy and Environment Directorate Lawrence Livermore National Laboratory Box 808 L-205 Livermore CA 94551-0808 United States

We estimate the ground motions produce by the 1906 San Francisco earthquake making use of the recently developed Song et al. (2008) source model that combines the available geodetic and seismic observations and recently constructed 3D geologic and seismic velocity models. Our estimates of the ground motions for the 1906 earthquake are consistent across five ground-motion modeling groups employing different wave propagation codes and simulation domains. The simulations successfully reproduce the main features of the Boatwright and Bundock (2005) ShakeMap, but tend to over predict the intensity of shaking by 0.1-0.5 modified Mercalli intensity (MMI) units. Velocity waveforms at sites throughout the San Francisco Bay Area exhibit characteristics consistent with rupture directivity, local geologic conditions (e.g., sedimentary basins), and the large size of the event (e.g., durations of strong shaking lasting tens of seconds). We also compute ground motions for seven hypothetical scenarios rupturing the same extent of the northern San Andreas fault, considering three additional hypocenters and an additional, random distribution of slip. Rupture directivity exerts the strongest influence on the variations in shaking, although sedimentary basins do consistently contribute to the response in some locations, such as Santa Rosa, Livermore, and San Jose. These scenarios suggest that future large earthquakes on the northern San Andreas fault may subject the current San Francisco Bay urban area to stronger shaking than a repeat of the 1906 earthquake. Ruptures propagating southward towards San Francisco appear to expose more of the urban area to a given intensity level than do ruptures propagating northward.

关键词： Earthquakes

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Foreword

Proceedings of the 2016 International Conference on Image Pr...

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Proceedings of the 2016 International Conference on Image Processing, computer Vision, and Pattern Recognition, IPCV 2016 2016年

作者： Abd-Wahab, Mohd Helmy Al-Bakry, Abbas Al-Holou, Nizar Arabnia, Hamid R. Bhattacharya, Mahua Martinez Castillo, Juan Jose Daimi, Kevin Deligiannidis, Leonidas Djoudi, Lamia Atma Duong, Trung Eshaghian-Wilner, Mary Mehrnoosh Gravvanis, George A. Huang, Ruizhu Jandieri, George Kim, Byung-Gyu Kim, Tai-hoon Korovin, Iakov Lai, Guoming Lee, Hyo Jong Bin Mansor, Muhammad Naufal Marsh, Andrew Mostafaeipour, Ali Park, James J. Patil, Shashikant Ponalagusamy, R. Schaefer, Gerald Singh, Akash Solo, Ashu M.G. Swee, Sim Kok Thomas, Jaya Tinetti, Fernando G. Vladimir, Hahanov Wang, Shiuh-Jeng Yang, Mary Yoe, Hyun You, Jane Zhao, Wenbing Department of Computer Engineering University Tun Hussein Onn Malaysia Malaysia University of IT and Communications Baghdad Iraq Electrical and Computer Engineering Department IEEE/SEM-Computer Chapter University of Detroit Mercy DetroitMI United States University of Georgia United States ABV Indian Institute of Information Technology and Management MHRD Government of India India Acantelys Alan Turing Nikola Tesla Research Group and GIPEB Universidad Nacional Abierta Venezuela Computer Science and Software Engineering Programs Department of Mathematics Computer Science and Software Engineering University of Detroit Mercy DetroitMI United States Department of Computer Information Systems Wentworth Institute of Technology BostonMA United States Synchrone Technologies France Rutgers University State University of New Jersey New Jersey United States University of Southern California California United States Electrical Engineering University of California Los Angeles Los Angeles [UCLA CA United States Advanced Scientific Computing Applied Math and Applications Research Group Applied Mathematics and Numerical Computing and Department of ECE School of Engineering Democritus University of Thrace Xanthi Greece Texas Advanced Computing Center University of Texas AustinTX United States Georgian Technical University Tbilisi Georgia Institute of Cybernetics Georgian Academy of Science Georgia Multimedia Processing CommunicationsLab.[MPCL Department of Computer Science and Engineering College of Engineering SunMoon University Korea Republic of School of Information and Computing Science University of Tasmania Australia Southern Federal University Russia Computer Science and Technology Sun Yat-Sen University Guangzhou China Center for Advanced Image and Information Technology Division of Computer Science and Engineering Chonbuk National University Korea Republic of Faculty of Engineering Technology Kampus Uniciti Alam Universiti Malaysia Perlis UniMAP Malaysi

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Sharp transitions in rotating turbulent convection: Lagrangian acceleration statistics reveal a second critical Rossby number

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Physical Review Fluids 2019年第7期4卷 074601-074601页

作者： Kim M. J. Alards Rudie P. J. Kunnen Richard J. A. M. Stevens Detlef Lohse Federico Toschi Herman J. H. Clercx Fluid Dynamics Laboratory and J.M. Burgers Center for Fluid Dynamics Department of Applied Physics Eindhoven University of Technology P.O. Box 513 5600 MB Eindhoven The Netherlands Physics of Fluids Group Max Planck Center for Complex Fluid Dynamics J.M. Burgers Center for Fluid Dynamics and MESA+ Research Institute Department of Science and Technology University of Twente P.O. Box 217 7500 AE Enschede The Netherlands Max Planck Institute for Dynamics and Self-Organization Am Fassberg 17 37077 Göttingen Germany Centre of Analysis Scientific Computing and Applications W&I Department of Mathematics and Computer Science Eindhoven University of Technology P.O. Box 513 5600 MB Eindhoven The Netherlands Istituto per le Applicazioni del Calcolo Consiglio Nazionale delle Ricerche Via dei Taurini 19 00185 Rome Italy

In Rayleigh–Bénard convection (RBC) for fluids with Prandtl number Pr≳1, rotation beyond a critical (small) rotation rate is known to cause a sudden enhancement of heat transfer, which can be explained by a change in the character of the boundary layer (BL) dynamics near the top and bottom plates of the convection cell. Namely, with increasing rotation rate, the BL signature suddenly changes from Prandtl–Blasius type to Ekman type. The transition from a constant heat transfer to an almost linearly increasing heat transfer with increasing rotation rate is known to be sharp and the critical Rossby number Roc occurs typically in the range 2.3≲Roc≲2.9 (for Rayleigh number Ra=1.3×109, Pr=6.7, and a convection cell with aspect ratio Γ=DH=1, with D the diameter and H the height of the cell). The explanation of the sharp transition in the heat transfer points to the change in the dominant flow structure. At 1/Ro≲1/Roc (slow rotation), the well-known large-scale circulation (LSC) is found: a single domain-filling convection roll made up of many individual thermal plumes. At 1/Ro≳1/Roc (rapid rotation), the LSC vanishes and is replaced with a collection of swirling plumes that align with the rotation axis. In this paper, by numerically studying Lagrangian acceleration statistics, related to the small-scale properties of the flow structures, we reveal that this transition between these different dominant flow structures happens at a second critical Rossby number, Roc2≈2.25 (different from Roc1≈2.7 for the sharp transition in the Nusselt number Nu; both values for the parameter settings of our present numerical study). When statistical data of Lagrangian tracers near the top plate are collected, it is found that the root-mean-square values and the kurtosis of the horizontal acceleration of these tracers show a sudden increase at Roc2. To better understand the nature of this transition we compute joint statistics of the Lagrangian velocity and acceleration of fluid particles and

关键词： Rayleigh-Bénard convection Turbulence Lagrangian particle tracking

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