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arXiv 2024年

作者： Feriani, Sophia Julia Cosnefroy, Matthias Engsig-Karup, Allan Peter Warburton, Tim Pind, Finnur Jeong, Cheol-Ho Acoustic Technology Department of Electrical and Photonics Engineering Technical University of Denmark Ørsteds Plads Bygning 352 Kongens Lyngby2800 Denmark Treble Technologies Hafnartorg Kalkofnsvegur 2 Reykjavík101 Iceland Scientific Computing Department of Applied Mathematics and Computer Science Technical University of Denmark Richard Petersens Plads Building 324 Kongens Lyngby2800 Denmark Data & Decision Sciences Virginia Tech 727 Prices Fork Road BlacksburgVA24060 United States

In outdoor acoustics, the calculations of sound propagating in air can be computationally heavy if the domain is chosen large enough to fulfil the Sommerfeld radiation condition. By strategically truncating the computational domain with a efficient boundary treatment, the computational cost is lowered. One commonly used boundary treatment is the perfectly matched layer (PML) that dampens outgoing waves without polluting the computed solution in the inner domain. The purpose of this study is to propose and assess a new perfectly matched layer formulation for the 3D acoustic wave equation, using the nodal discontinuous Galerkin finite element method. The formulation is based on an efficient PML formulation that can be decoupled to further increase the computational efficiency and guarantee stability without sacrificing accuracy. This decoupled PML formulation is demonstrated to be long-time stable and an optimization procedure of the damping functions is proposed to enhance the performance of the formulation. Copyright © 2024, The Authors. All rights reserved.

关键词： Computational efficiency

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Corrigendum to “Mobility Management Solutions for 5G: Architecture and Services” computer Networks Volume 169 (2020) 107082

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computer Networks 2020年 181卷

作者： Nadine Akkari Nikos Dimitriou Faculty of Computing and Information Technology Computer Science Department King Abdulaziz University Jeddah Saudi Arabia Institute of Informatics and Telecommunications National Center for Scientific Research “Demokritos” Athens Greece

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A Comparative Study of Enriched Computational Homogenization Schemes Applied to Two-Dimensional Pattern-Transforming Elastomeric Mechanical Metamaterials

arXiv

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arXiv 2023年

作者： Sperling, S.O. Guo, T. Peerlings, R.H.J. Kouznetsova, V.G. Geers, M.G.D. Rokoš, O. Mechanics of Materials Department of Mechanical Engineering Eindhoven University of Technology P.O. Box 513 Eindhoven5600 MB Netherlands Centre for Analysis Scientific Computing and Applications Department of Mathematics and Computer Science Eindhoven University of Technology P.O. Box 513 Eindhoven5600 MB Netherlands Department of Mechanics Faculty of Civil Engineering Czech Technical University in Prague Thákurova 7 Prague 6166 29 Czech Republic

Elastomeric mechanical metamaterials exhibit unconventional behaviour, emerging from their microstructures often deforming in a highly nonlinear and unstable manner. Such microstructural pattern transformations lead to non-local behaviour and induce abrupt changes in the effective properties, beneficial for engineering applications. To avoid expensive simulations fully resolving the underlying microstructure, homogenization methods are employed. In this contribution, a systematic comparative study is performed, assessing the predictive capability of several computational homogenization schemes in the realm of two-dimensional elastomeric metamaterials with a square stacking of circular holes. In particular, classical first-order and two enriched schemes of second-order and micromorphic computational homogenization type are compared with ensemble-averaged full direct numerical simulations on three examples: uniform compression and bending of an infinite specimen, and compression of a finite specimen. It is shown that although the second-order scheme provides good qualitative predictions, it fails in accurately capturing bifurcation strains and slightly over-predicts the homogenized response. The micromorphic method provides the most accurate prediction for tested examples, although soft boundary layers induce large errors at small scale ratios. The first-order scheme yields good predictions for high separations of scales, but suffers from convergence issues, especially when localization occurs. © 2023, CC BY.

关键词： Homogenization method

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Predictive analytics in quality assurance for assembly processes: lessons learned from a case study at an industry 4.0 demonstration cell

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Procedia CIRP 2021年 104卷 641-646页

作者： Peter Burggräf Johannes Wagner Benjamin Heinbach Fabian Steinberg Alejandro R. Pérez M. Lennart Schmallenbach Jochen Garcke Daniela Steffes-lai Moritz Wolter Chair of International Production Engineering and Management (IPEM) Universität Siegen Paul-Bonatz-Straße 9-11 57076 Siegen Germany Fraunhofer Institute for Algorithms and Scientific Computing (SCAI) Schloss Birlinghoven 1 53757 Sankt Augustin Germany Fraunhofer Center for Machine Learning Schloss Birlinghoven 1 53757 Sankt Augustin Germany Institute for Numerical Simulation Universität Bonn Endenicher Allee 19b 53115 Bonn Germany Institute for Computer Science Universität Bonn Endenicher Allee 19a 53115 Bonn Germany

Quality assurance (QA) is an important task in manufacturing to assess whether products meet their specifications. However, QA might be expensive, time-consuming, or incomplete. This paper presents a solution for predictive analytics in QA based on machine sensor values during production while employing specialized machine-learning models for classification in a controlled environment. Furthermore, we present lessons learned while implementing this model, which helps to reduce complexity in further industrial applications. The paper’s outcome proves that the developed model was able to predict product quality, as well as to identify the correlation between machine-status and faulty product occurrence.

关键词： Machine-Learning Predictive Quality Production Quality Assurance Classification

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New Three and Four-Dimensional Toric and Burst-Error-Correcting Quantum Codes

arXiv

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arXiv 2023年

作者： Trinca, Cibele Cristina Palazzo, Reginaldo Watanabe, Ricardo Augusto de Albuquerque, Clarice Dias Interlando, Jose Carmelo de Andrade, Antonio Aparecido Department of Biotechnology and Bioprocess Engineering Federal University of Tocantins TO Gurupi Brazil School of Electrical and Computer Engineering State University of Campinas Brazil School of Mathematics Statistics and Scientific Computing State University of Campinas Brazil Science and Technology Center Federal University of Cariri Juazeiro do Norte Brazil Department of Mathematics and Statistics San Diego State University San DiegoCA United States Department of Mathematics São Paulo State University Brazil

Ongoing research and experiments have enabled quantum memory to realize the storage of qubits. On the other hand, interleaving techniques are used to deal with burst of errors. Effective interleaving techniques for combating burst of errors by using classical error-correcting codes have been proposed in several articles found in the literature, however, to the best of our knowledge, little is known regarding interleaving techniques for combating clusters of errors in topological quantum error-correcting codes. Motivated by that, in this work, we present new three and four-dimensional toric quantum codes which are featured by lattice codes and apply a quantum interleaving method to such new three and four-dimensional toric quantum codes. By applying such a method to these new codes we provide new three and four-dimensional quantum burst-error-correcting codes. As a consequence, new three and four-dimensional toric and burst-error-correcting quantum codes are obtained which have better information rates than those three and four-dimensional toric quantum codes from the literature. In addition to these proposed three and four-dimensional quantum burst-error-correcting codes improve such information rates, they can be used for burst-error-correction in errors which are located, quantum data stored and quantum channels with memory. © 2023, CC BY.

关键词： Error correction

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Quantum Statistical Transport Phenomena in Memristive computing Architectures

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Physical Review Applied 2021年第5期15卷 054030-054030页

作者： Christopher N. Singh Brian A. Crafton Mathew P. West Alex S. Weidenbach Keith T. Butler Allan H. MacDonald Arjit Raychowdury Eric M. Vogel W. Alan Doolittle L.F.J. Piper Wei-Cheng Lee Department of Physics Applied Physics and Astronomy Binghamton University Binghamton New York 13902 USA Materials Science and Technology Division Los Alamos National Laboratory Los Alamos New Mexico 87545 USA Department of Electrical and Computer Engineering Georgia Institute of Technology Atlanta Georgia 30332 USA SciML Scientific Computing Department Rutherford Appleton Laboratory Didcot OX110QX United Kingdom Department of Physics University of Texas at Austin Austin Texas 78712-1081 USA WMG University of Warwick Coventry CV4 7AL United Kingdom

The advent of reliable nanoscale memristive components is promising for next-generation compute-in-memory paradigms; however, the intrinsic variability in these devices has prevented widespread adoption. Here, we show coherent electron wave functions play a pivotal role in the nanoscale transport properties of these emerging nonvolatile memories. By characterizing both filamentary and nonfilamentary memristive devices as disordered Anderson systems, the switching characteristics and intrinsic variability arise directly from the universality of electron transport in disordered media. Our framework suggests that localization phenomena in nanoscale solid-state memristive systems are directly linked to circuit-level performance. We discuss how quantum conductance fluctuations in the active layer set a lower bound on device variability. This finding implies that there is a fundamental quantum limit on the reliability of memristive devices and that electron coherence will play a decisive role in surpassing or maintaining Moore’s law with these systems.

关键词： Anderson localization Quantum transport Amorphous semiconductors Artificial neural networks Devices Transition metal oxides Density functional theory Linear response theory

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Measuring prominence of scientific work in online news as a proxy for impact

arXiv

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arXiv 2020年

作者： Ravenscroft, James Clare, Amanda Liakata, Maria Centre for Scientific Computing University of Warwick CV4 7AL United Kingdom Department of Computer Science Aberystwyth University SY23 3DB United Kingdom Alan Turing Institute 96 Euston Rd LondonNW1 2DB United Kingdom Filament AI 22 Tudor St LondonEC4Y 0AY United Kingdom

The impact made by a scientific paper on the work of other academics has many established metrics, including metrics based on citation counts and social media commenting. However, determination of the impact of a scientific paper on the wider society is less well established. For example, is it important for scientific work to be newsworthy? Here we present a new corpus of newspaper articles linked to the scientific papers that they describe. We find that Impact Case studies submitted to the UK Research Excellence Framework (REF) 2014 that refer to scientific papers mentioned in newspaper articles were awarded a higher score in the REF assessment. The papers associated with these case studies also feature prominently in the newspaper articles. We hypothesise that such prominence can be a useful proxy for societal impact. We therefore provide a novel baseline approach for measuring the prominence of scientific papers mentioned within news articles. Our measurement of prominence is based on semantic similarity through a graph-based ranking algorithm. We find that scientific papers with an associated REF case study are more likely to have a stronger prominence score. This supports our hypothesis that linguistic prominence in news can be used to suggest the wider non-academic impact of scientific work. Copyright © 2020, The Authors. All rights reserved.

关键词： Newsprint

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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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A novel transfer learning-based model for diagnosing malaria from parasitized and uninfected red blood cell images

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Decision Analytics Journal 2023年 9卷

作者： Qadri, Azam Mehmood Raza, Ali Eid, Fatma Abualigah, Laith Institute of Computer Science Khwaja Fareed University of Engineering and Information Technology Rahim Yar Khan 64200 Pakistan Technology Management Stony Brook University 11794 NY United States Department of Applied Artificial Intelligence College of Computing and Informatics Sungkyunkwan University Seoul 03063 South Korea Computer Science Department Al al-Bayt University Mafraq 25113 Jordan Department of Electrical and Computer Engineering Lebanese American University Byblos 13-5053 Lebanon Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman 19328 Jordan MEU Research Unit Middle East University Amman 11831 Jordan Applied Science Research Center Applied science private university Amman 11931 Jordan School of Computer Sciences Universiti Sains Malaysia Pulau Pinang 11800 Malaysia School of Engineering and Technology Sunway University Malaysia Petaling Jaya 27500 Malaysia

Malaria represents a potentially fatal communicable illness triggered by the Plasmodium parasite. This disease is transmitted to humans through the bites of Anopheles mosquitoes that carry the infection. This disease has significant and devastating consequences on the health systems of fragile countries, particularly in sub-Saharan Africa. Malaria affects red blood cells by invading and replicating within them, destroying them, and releasing toxic byproducts into the bloodstream. The parasite's ability to stick and modify the surface of red blood cells can cause them to become sticky, obstructing blood flow in vital organs such as the brain and spleen. Therefore, efficient approaches for the early detection of malaria are critical to saving patients’ lives. The main aim of this study is to develop an efficient model for early malaria diagnosis. We used malaria images based on parasitized and uninfected red blood cells for the study experiments. We applied neural network-based approaches such as Neural Search Architecture Network (NASNet) and compared its performance with machine learning techniques. Moreover, we proposed a novel NNR (NASNet Random forest) method for feature engineering. The proposed NNR approach first extracts spatial features from input malaria images, then class prediction probability features are extracted from these spatial features. The feature set obtained from the data extraction trains machine learning models. Our comprehensive experiments show that the support vector machine outperformed state-of-the-art models, achieving a high-performance score of 99% and having an inference time near 0.025 s. We validated the performance using k-fold cross-validation and optimized the hyperparameters through tuning. Our proposed research has improved the early diagnosis of malaria and can assist medical specialists in reducing the mortality rate. © 2023 The Author(s)

关键词： Deep learning Machine learning Malaria diagnosis Neural search architecture network Red blood cells Transfer learning

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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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