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A kinetic model with analysis for the oxidation of sugars by permanganate in simple aqueous media with sustainable fractional approach

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Computational Biology and Chemistry 2025年 119卷

作者： Muhammad Farman Aamir Shehzad Faisal Sultan Kottakkaran Sooppy Nisar Mustafa Bayrium Aceng Sambas Faculty of Arts and Sciences Department of Mathematics Near East University Turkey Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Campus Besut 22200 Terengganu Malaysia Research Center of Applied Mathematics Khazar University Baku Azerbaijan Institute of Mathematics Khwaja Fareed University of Engineering and Information Technology Rahim Yar Khan Pakistan Department of Mathematics College of Science and Humanities in Al Kharj Prince Sattam Bin Abdulaziz University Al Kharj 11942 Saudi Arabia Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman Jordan Department of Computer Engineering Biruni University 34010 Topkapi Istanbul Turkey Department of Mechanical Engineering Universitas Muhammadiyah Tasikmalaya Tasikmalaya 46196 Indonesia Artificial Intelligence Research Centre for Islamic and Sustainalbility Universiti Sultan Zainal Abidin Gongbadak Terengganu 21300 Terengganu Malaysia

The development of a recycling method for manganese dioxide, a byproduct of reactions, has made permanganate, a persistent oxidant in organic chemistry, more environmentally benign. This makes permanganate developments in technology more cost-effective and less hazardous to the environment. Understanding the rate and mechanisms of chemical reactions is important in a variety of fields, including chemistry and biology. Sugars, as organic substrates, are sensitive to oxidation by the potent oxidant permanganate. We utilized the commonly used oxidants in permanganate oxidation, D-glucose, D-fructose, and D-sucrose. This study investigates the importance of efficient oxidation processes by creating extended fractal fractional models for computer analysis. It looks at possible ways permanganate can be oxidized by analyzing these equations both qualitatively and quantitatively with the Mittag-Leffler kernel, which is not commonly studied. Using advanced fixed-point theory results, the kinetic system’s solutions are analyzed and found to be unique. A Lyapunov function is offered for the proposed kinetic system, which necessitates consideration of the oxidation process kinetics as well as a thorough stability analysis of chemical parameters. In addition, we stabilize the kinetic system utilizing the proposed linear feedback regulate technique for chaos control and system sensitivity analysis. We use the Spectral Quasi Equilibrium Manifold (SQEM) approach, an advanced modeling simplification tool, to study the complex behavior of multi-step reaction processes. A strong numerical technique based on the Newton polynomial is used in computational simulations to examine the influence of the fractal-fractional operator on surface and contour graphs. Graphs with differing fractal and fractional orders have a substantial effect on the correlations of kinetic system compartments at different parameter values. The findings aim to increase perception and process representation in orde

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Correction to: A Fused Heterogeneous Deep Neural Network and Robust Feature Selection Framework for Human Actions Recognition

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Arabian Journal for Science and engineering 2022年 1-1页

作者： Khan, Muhammad Attique Zhang, Yu-Dong Alhaisoni, Majed Kadry, Seifedine Wang, Shui-Hua Saba, Tanzila Iqbal, Tassawar Department of Computer Science HITEC University Taxila Pakistan Department of Informatics University of Leicester Leicester UK College of Computer Science and Engineering University of Ha’il Ha’il Saudi Arabia Department of Applied Data Science Noroff University College Noroff Oslo Norway Department of Mathematics University of Leicester Lecicester UK College of Computer and Information Sciences Prince Sultan University Riyadh Saudi Arabia Department of Computer Science COMSATS University Islamabad Wah Campus Islamabad Pakistan

A Correction to this paper has been published: 10.1007/s13369-021-05881-4

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Assessing Trustworthy AI in Times of COVID-19: Deep Learning for Predicting a Multiregional Score Conveying the Degree of Lung Compromise in COVID-19 Patients

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IEEE Transactions on Technology and Society

IEEE Transactions on Technology and Society 2022年第4期3卷 272-289页

作者： Allahabadi, Himanshi Amann, Julia Balot, Isabelle Beretta, Andrea Binkley, Charles Bozenhard, Jonas Bruneault, Frederick Brusseau, James Candemir, Sema Cappellini, Luca Alessandro Chakraborty, Subrata Cherciu, Nicoleta Cociancig, Christina Coffee, Megan Ek, Irene Espinosa-Leal, Leonardo Farina, Davide Fieux-Castagnet, Genevieve Frauenfelder, Thomas Gallucci, Alessio Giuliani, Guya Golda, Adam Van Halem, Irmhild Hildt, Elisabeth Holm, Sune Kararigas, Georgios Krier, Sebastien A. Kuhne, Ulrich Lizzi, Francesca Madai, Vince I. Markus, Aniek F. Masis, Serg Mathez, Emilie Wiinblad Mureddu, Francesco Neri, Emanuele Osika, Walter Ozols, Matiss Panigutti, Cecilia Parent, Brendan Pratesi, Francesca Moreno-Sanchez, Pedro A. Sartor, Giovanni Savardi, Mattia Signoroni, Alberto Sormunen, Hanna-Maria Spezzatti, Andy Srivastava, Adarsh Stephansen, Annette F. Theng, Lau Bee Tithi, Jesmin Jahan Tuominen, Jarno Umbrello, Steven Vaccher, Filippo Vetter, Dennis Westerlund, Magnus Wurth, Renee Zicari, Roberto V. Ey Netherlands Enterprise Intelligence Department Amsterdam1083 HP Netherlands Eth Zurich Health Ethics and Policy Lab Department of Health Sciences and Technology Zürich8092 Switzerland Center for Diplomatic and Strategic Studies Postgraduate Studies in Diplomacy and International Relations Paris75015 France Pisa56124 Italy Hackensack Meridian Health Bioethics Center EdisonNJ08820 United States University of Oxford Faculty of Philosophy OxfordOX2 6GG United Kingdom Collège André- Laurendeau Philosophie Department MontrealQCH8N 2J4 Canada Université du Québec À Montréal École des Médias MontrealQCH2L 2C4 Canada Pace University Philosophy Department New YorkNY10038 United States The Ohio State University Wexner Medical Center Department of Radiology ColumbusOH43210 United States Humanitas Research Hospital Department of Radiology Milan20089 Italy Humanitas University Department of Biomedical Sciences Milan20089 Italy University of New England Faculty of Science Agriculture Business and Law ArmidaleNSW2351 Australia University of Technology Sydney Faculty of Engineering and Information Technology SydneyNSW2007 Australia Scuola Superiore Sant'Anna European Centre of Excellence on the Regulation of Robotics and Ai Pisa56127 Italy University of Bremen Group of Computer Architecture Bremen28359 Germany New York University Grossman School of Medicine Division of Infectious Diseases and Immunology Department of Medicine New YorkNY10016 United States Digital Institute Ai Research Section Stockholm16731 Sweden Arcada University of Applied Sciences Department of Business Management and Analytics Helsinki00550 Finland University of Brescia Radiological Sciences and Public Health Department of Medical and Surgical Specialties Brescia25121 Italy Sncf Reseau Sa Ethique Groupe La Plaine93418 France Institute of Diagnostic and Interventional Radiology University Hospital Zurich Zürich8091 Switzerland Eindhoven University of Tech

This article's main contributions are twofold: 1) to demonstrate how to apply the general European Union's High-Level Expert Group's (EU HLEG) guidelines for trustworthy AI in practice for the domain of healthcare and 2) to investigate the research question of what does 'trustworthy AI' mean at the time of the COVID-19 pandemic. To this end, we present the results of a post-hoc self-assessment to evaluate the trustworthiness of an AI system for predicting a multiregional score conveying the degree of lung compromise in COVID-19 patients, developed and verified by an interdisciplinary team with members from academia, public hospitals, and industry in time of pandemic. The AI system aims to help radiologists to estimate and communicate the severity of damage in a patient's lung from Chest X-rays. It has been experimentally deployed in the radiology department of the ASST Spedali Civili clinic in Brescia, Italy, since December 2020 during pandemic time. The methodology we have applied for our post-hoc assessment, called Z-Inspection®, uses sociotechnical scenarios to identify ethical, technical, and domain-specific issues in the use of the AI system in the context of the pandemic. © 2020 IEEE.

关键词： COVID-19

JARVIS-Leaderboard: A Large Scale Benchmark of Materials Design Methods

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arXiv 2023年

作者： Choudhary, Kamal Wines, Daniel Garrity, Kevin F. Williams, Maureen Tavazza, Francesca Li, Kangming Hattrick-Simpers, Jason Gupta, Vishu Romero, Aldo H. Krogel, Jaron T. Saritas, Kayahan Fuhr, Addis Ganesh, Panchapakesan Kent, Paul R.C. Yan, Keqiang Lin, Yuchao Ji, Shuiwang Blaiszik, Ben Reiser, Patrick Friederich, Pascal Agrawal, Ankit Tiwary, Pratyush Beyerle, Eric Minch, Peter Rhone, Trevor David Takeuchi, Ichiro Wexler, Robert B. Mannodi-Kanakkithodi, Arun Ertekin, Elif Mishra, Avanish Mathew, Nithin Wood, Mitchell Rohskopf, Andrew Dale Wang, Shih-Han Achenie, Luke E.K. Xin, Hongliang Biacchi, Adam J. Material Measurement Laboratory National Institute of Standards and Technology MD20899 United States Department of Materials Science and Engineering University of Toronto 27 King’s College Cir TorontoON Canada Department of Electrical and Computer Engineering Northwestern University EvanstonIL60208 United States Lewis-Sigler Institute for Integrative Genomics Princeton University PrincetonNJ08544 United States Ludwig Institute for Cancer Research Princeton University PrincetonNJ08544 United States Department of Physics and Astronomy West Virginia University MorgantownWV26506 United States Materials Science and Technology Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Center for Nanophase Materials Science Oak Ridge National Laboratory Oak RidgeTN37831 United States Computational Sciences and Engineering Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Computer Science and Engineering Texas A&M University College StationTX77843 United States Globus University of Chicago IL60637 United States Data Science Learning Division National Lab ArgonneIL60439 United States Institute of Nanotechnology Karlsruhe Institute of Technology Kaiserstraße 12 Karlsruhe76131 Germany Institute of Theoretical Informatics Karlsruhe Institute of Technology Kaiserstraße 12 Karlsruhe76131 Germany Department of Chemistry and Biochemistry Institute for Physical Science and Technology University of Maryland College ParkMD20742 United States Department of Physics Applied Physics and Astronomy Rensselaer Polytechnic Institute TroyNY12180 United States Department of Materials Science and Engineering University of Maryland College ParkMD20742 United States Department of Chemistry Institute of Materials Science and Engineering Washington University in St. Louis St. LouisMO63130 United States School of Materials Engineering Purdue University West LafayetteIN47907 United States Department of Mechan

Lack of rigorous reproducibility and validation are significant hurdles for scientific development across many fields. Materials science, in particular, encompasses a variety of experimental and theoretical approaches that require careful benchmarking. Leaderboard efforts have been developed previously to mitigate these issues. However, a comprehensive comparison and benchmarking on an integrated platform with multiple data modalities with perfect and defect materials data is still lacking. This work introduces JARVIS-Leaderboard, an open-source and community-driven platform that facilitates benchmarking and enhances reproducibility. The platform allows users to set up benchmarks with custom tasks and enables contributions in the form of dataset, code, and meta-data submissions. We cover the following materials design categories: Artificial Intelligence (AI), Electronic Structure (ES), Force-fields (FF), Quantum Computation (QC) and Experiments (EXP). For AI, we cover several types of input data, including atomic structures, atomistic images, spectra, and text. For ES, we consider multiple ES approaches, software packages, pseudopotentials, materials, and properties, comparing results to experiment. For FF, we compare multiple approaches for material property predictions. For QC, we benchmark Hamiltonian simulations using various quantum algorithms and circuits. Finally, for experiments, we use the inter-laboratory approach to establish benchmarks. There are 1281 contributions to 274 benchmarks using 152 methods with more than 8 million data-points, and the leaderboard is continuously expanding. The JARVIS-Leaderboard is available at the website: https://***/jarvis_leaderboard/ © 2023, CC BY.

关键词： Electronic structure

The conceptual approach of system for automatic vehicle accident detection and searching for life signs of casualties 5th

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The conceptual approach of system for automatic vehicle acci...

5th International Doctoral Symposium on applied Computation and Security Systems, ACSS 2018

作者： Lupinska-Dubicka, Anna Tabedzki, Marek Adamski, Marcin Rybnik, Mariusz Omieljanowicz, Miroslaw Omieljanowicz, Andrzej Szymkowski, Maciej Gruszewski, Marek Klimowicz, Adam Rubin, Grzegorz Saeed, Khalid Faculty of Computer Science Bialystok University of Technology Bialystok Poland Faculty of Mathematics and Informatics University of Bialystok Bialystok Poland Faculty of Mechanical Engineering Department of Automatic Control and Robotics Bialystok University of Technology Bialystok Poland Faculty of Computer and Food Science Lomza State University of Applied Sciences Lomza Poland

ISBN: (纸本)9789811337017

The European eSafety initiative aims to improve the safety and efficiency of road transport. The main element of eSafety is the pan-European eCall project—an in-vehicle system which idea is to inform about road collisions or serious accidents. As estimated by the European Commission, the implemented system will reduce services’ response time by 40%. This will save 2,500 people a year. In 2015, the European Parliament adopted the legislation that from the end of March 2018 all new cars from the EU should be equipped with the eCall system. The limitation of this idea is that only small part of cars driven in UE are brand new (about 3.7% brand new cars were sold in 2015). This paper presents the first concept of an onboard eCall device which can be installed at the owners’ request in used vehicles. The proposed system will be able to detect a road accident, indicate the number of vehicle’s occupants, report their vital functions, and send that information to dedicated emergency services via duplex communication channel. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Emergency services

Why is the winner the best?

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arXiv 2023年

作者： Eisenmann, M. Reinke, A. Weru, V. Tizabi, M.D. Isensee, F. Adler, T.J. Ali, S. Andrearczyk, V. Aubreville, M. Baid, U. Bakas, S. Balu, N. Bano, S. Bernal, J. Bodenstedt, S. Casella, A. Cheplygina, V. Daum, M. de Bruijne, M. Depeursinge, A. Dorent, R. Egger, J. Ellis, D.G. Engelhardt, S. Ganz, M. Ghatwary, N. Girard, G. Godau, P. Gupta, A. Hansen, L. Harada, K. Heinrich, M. Heller, N. Hering, A. Huaulmé, A. Jannin, P. Kavur, A.E. Kodym, O. Kozubek, M. Li, J. Li, H. Ma, J. Martín-Isla, C. Menze, B. Noble, A. Oreiller, V. Padoy, N. Pati, S. Payette, K. Rädsch, T. Rafael-Patiño, J. Bawa, V. Singh Speidel, S. Sudre, C.H. van Wijnen, K. Wagner, M. Wei, D. Yamlahi, A. Yap, M.H. Yuan, C. Zenk, M. Zia, A. Zimmerer, D. Aydogan, D. Bhattarai, B. Bloch, L. Brüngel, R. Cho, J. Choi, C. Dou, Q. Ezhov, I. Friedrich, C.M. Fuller, C. Gaire, R.R. Galdran, A. Faura, Á. García Grammatikopoulou, M. Hong, S. Jahanifar, M. Jang, I. Kadkhodamohammadi, A. Kang, I. Kofler, F. Kondo, S. Kuijf, H. Li, M. Luu, M. Martinčič, T. Morais, P. Naser, M.A. Oliveira, B. Owen, D. Pang, S. Park, J. Park, S. Plotka, S. Puybareau, E. Rajpoot, N. Ryu, K. Saeed, N. Shephard, A. Shi, P. Štepec, D. Subedi, R. Tochon, G. Torres, H.R. Urien, H. Vilaça, J.L. Wahid, K.A. Wang, H. Wang, J. Wang, L. Wang, X. Wiestler, B. Wodzinski, M. Xia, F. Xie, J. Xiong, Z. Yang, S. Yang, Y. Zhao, Z. Maier-Hein, K. Jäger, P.F. Kopp-Schneider, A. Maier-Hein, L. Heidelberg Germany Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Heidelberg Germany Heidelberg Germany School of Computing Faculty of Engineering and Physical Sciences University of Leeds Leeds United Kingdom Institute of Informatics School of Management HES-SO Valais-Wallis University of Applied Sciences and Arts Western Switzerland Sierre Switzerland Department of Nuclear Medicine and Molecular Imaging Lausanne University Hospital Lausanne Switzerland Technische Hochschule Ingolstadt Ingolstadt Germany University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Radiology University of Washington SeattleWA United States Department of Computer Science University College London London United Kingdom Universitat Autònoma de Barcelona & Computer Vision Center Barcelona Spain Dresden Dresden Germany Department of Advanced Robotics Istituto Italiano di Tecnologia Italy IT University of Copenhagen Copenhagen Denmark Department of General Visceral and Transplantation Surgery Heidelberg University Hospital Heidelberg Germany Biomedical Imaging Group Rotterdam Department of Radiology and Nuclear Medicine Erasmus MC Rotterdam Netherlands Department of Computer Science University of Copenhagen Copenhagen Denmark Sierre Switzerland Harvard Medical School Brigham and Women’s Hospital BostonMA United States School of Biomedical Engineering and Imaging Sciences King’s College London London United Kingdom Essen Germany University of Nebraska Medical Center OmahaNE United States Department of Internal Medicine III Heidelberg University Hospital Heidelberg Germany Neurobiology Research Unit Copenhagen University Hospital Rigshospitalet C

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really generate scientific progress? What are common and successful participation strategies? What makes a solution superior to a competing method? To address this gap in the literature, we performed a multicenter study with all 80 competitions that were conducted in the scope of IEEE ISBI 2021 and MICCAI 2021. Statistical analyses performed based on comprehensive descriptions of the submitted algorithms linked to their rank as well as the underlying participation strategies revealed common characteristics of winning solutions. These typically include the use of multi-task learning (63%) and/or multi-stage pipelines (61%), and a focus on augmentation (100%), image preprocessing (97%), data curation (79%), and postprocessing (66%). The "typical" lead of a winning team is a computer scientist with a doctoral degree, five years of experience in biomedical image analysis, and four years of experience in deep learning. Two core general development strategies stood out for highly-ranked teams: the reflection of the metrics in the method design and the focus on analyzing and handling failure cases. According to the organizers, 43% of the winning algorithms exceeded the state of the art but only 11% completely solved the respective domain problem. The insights of our study could help researchers (1) improve algorithm development strategies when approaching new problems, and (2) focus on open research questions revealed by this work. © 2023, CC BY.

关键词： Benchmarking

Digital Twins of Business Processes: A Research Manifesto

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arXiv 2024年

作者： Fornari, Fabrizio Compagnucci, Ivan De Donato, Massimo Callisto Bertrand, Yannis Beyel, Harry H. Carrión, Emilio Franceschetti, Marco Groher, Wolfgang Grüger, Joscha Kilic, Emre Koschmider, Agnes Leotta, Francesco Li, Chiao-Yun Lugaresi, Giovanni Malburg, Lukas Mangler, Juergen Mecella, Massimo Pastor, Oscar Riss, Uwe Seiger, Ronny Serral, Estefania Torres, Victoria Valderas, Pedro University of Camerino School of Science and Technology Computer Science Department Via Madonna delle Carceri 7 Camerino62032 Italy Gran Sasso Science Institute Computer Science Department Viale Francesco Crispi 7 L’Aquila67100 Italy University of St.Gallen Institute of Computer Science Rosenbergstrasse 30 St.Gallen9000 Switzerland University of Bayreuth Business Informatics and Process Analytics Wittelsbacherring 8 Bayreuth95444 Germany Fraunhofer Institute for Applied Information Technology Schloss Birlinghoven Sankt Augustin53757 Germany RWTH Aachen University Ahornstraße 55 Aachen52074 Germany Mercadona Tech Mercadona Plaza de Amèrica 2 Valencia46004 Spain PROS Research Center - VRAIN Institute Universitat Politècnica de València Camino de Vera Valencia46022 Spain TU Dortmund University Leonhard-Euler-Str. 5 Dortmund44227 Germany KU Leuven Warmoesberg 26 Brussels1000 Belgium Sapienza Università di Roma DIAG via Ariosto 25 Rome00185 Italy KU Leuven Faculty of Engineering Technology Celestijnenlaan 300 Leuven3001 Belgium Branch Trier University Behringstraße 21 Trier54296 Germany Artificial Intelligence and Intelligent Information Systems Trier University Universitätsring 15 Trier54296 Germany OST Eastern Switzerland University of Applied Sciences Rosenbergstrasse 59 St. Gallen9001 Switzerland TUM School of Computation Information and Technology Boltzmannstraße 3 Garching bei München85748 Germany

Modern organizations necessitate continuous business processes improvement to maintain efficiency, adaptability, and competitiveness. In the last few years, the Internet of Things, via the deployment of sensors and actuators, has heavily been adopted in organizational and industrial settings to monitor and automatize physical processes influencing and enhancing how people and organizations work. Such advancements are now pushed forward by the rise of the Digital Twin paradigm applied to organizational processes. Advanced ways of managing and maintaining business processes come within reach as there is a Digital Twin of a business process - a virtual replica with real-time capabilities of a real process occurring in an organization. Combining business process models with real-time data and simulation capabilities promises to provide a new way to guide day-to-day organization activities. However, integrating Digital Twins and business processes is a non-trivial task, presenting numerous challenges and ambiguities. This manifesto paper aims to contribute to the current state of the art by clarifying the relationship between business processes and Digital Twins, identifying ongoing research and open challenges, thereby shedding light on and driving future exploration of this innovative interplay. © 2024, CC BY-NC-ND.

关键词： Virtual corporation

BDoTs: Blockchain-based Evaluation Scheme for Online Teaching under COVID-19 Environment

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BDoTs: Blockchain-based Evaluation Scheme for Online Teachin...

International Conference on computer, Information and Telecommunication Systems (CITS)

作者： Arpit Shukla Nirav Patel Sudeep Tanwar Balqies Sadoun Mohammad S. Obaidat Nirma University India Department of Computer Science and Engineering Nirma University India College of Engineering Sharjah Universiiy UAE College of Engineering Al-Balqa' Applied Universiiy Jordan College of Computing and Informatics University of Sharjah UAE King Abdullah II School of IT University of Jordan Jordan University of Science and Technology Beijing China

ISBN: (数字)9781728165448

ISBN: (纸本)9781728165455

Online teaching has become mandatory across the globe during the COVID-19 pandemic situations. Hence, there is a need to uplift the online teaching technology for data privacy preservation and transparency in the system. Various online teaching schemes have been proposed by various authors, but they lack in handling decentralised governance, transparency, trust and communication issues. Blockchain (BC) Technology has emerged to provide decentralised solution in solving the real-time problems. Motivated by these facts, in this paper, we propose a BC-based decentralised online teaching scheme known as BDoTs. The security and data privacy issues in BDoTs are resolved by developing smart contracts (SCs) over BC. Moreover, the data storage cost issues are handled by the Inter Planetary File System (IPFS) protocol for Off-Chain data storage. Moreover, we present a real-time BC simulation and deployment of SC in Truffle suite. Results show that the proposed scheme performs better in comparison to the state-of-the-art schemes in terms of scalability, data storage cost, and packet loss.

关键词： Education Peer-to-peer computing Internet Distributed databases COVID-19 Security Scalability

A new class of scaling matrices for scaled trust region algorithms

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arXiv 2019年

作者： Ayanzadeh, Aydin Yazdanian, Shokoufeh Shahamatnia, Ehsan Department of Applied Informatics Informatics Institute Istanbul Technical University Istanbul Turkey Department of Computer Science University of Tabriz Tabriz Iran Department of Computer and Electrical Engineering Universidade Nova de Lisboa Lisbon Portugal

A new class of affine scaling matrices for the interior point Newton-type methods is considered to solve the nonlinear systems with simple bounds. We review the essential properties of a scaling matrix and consider several wellknown scaling matrices proposed in the literature. We define a new scaling matrix that is the convex combination of these matrices. The proposed scaling matrix inherits those interesting properties of the individual matrices and satisfies additional desired requirements. The numerical experiments demonstrate the superiority of the new scaling matrix in solving several important test problems. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning