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arXiv 2023年

作者： Zhou, Chenyu Mun, Junsik Yao, Juntao Anbalagan, Aswin kumar Hossain, Mohammad D. McLellan, Russell A. Li, Ruoshui Kisslinger, Kim Li, Gengnan Tong, Xiao Head, Ashley R. Weiland, Conan Hulbert, Steven L. Walter, Andrew L. Li, Qiang Zhu, Yimei Sushko, Peter V. Liu, Mingzhao Center for Functional Nanomaterials Brookhaven National Laboratory UptonNY11973 United States The Condensed Matter Physics and Materials Science Department Brookhaven National Laboratory UptonNY11973 United States Department of Materials Science and Chemical Engineering Stony Brook University Stony BrookNY11794 United States National Synchrotron Light Source II Brookhaven National Laboratory UptonNY11973 United States Physical and Computational Sciences Directorate Pacific Northwest National Laboratory RichlandWA99354 United States Department of Electrical and Computer Engineering Princeton University PrincetonNJ08540 United States Department of Chemistry Stony Brook University Stony BrookNY11794 United States Materials Measurement Laboratory National Institute of Standard and Technology GaithersburgMD20899 United States Department of Physics and Astronomy Stony Brook University Stony BrookNY11794 United States

Scaling up superconducting quantum circuits based on transmon qubits necessitates substantial enhancements in qubit coherence time. Among the materials considered for transmon qubits, tantalum (Ta) has emerged as a promising candidate, surpassing conventional counterparts in terms of coherence time. However, the presence of an amorphous surface Ta oxide layer introduces dielectric loss, ultimately placing a limit on the coherence time. In this study, we present a novel approach for suppressing the formation of tantalum oxide using an ultrathin magnesium (Mg) capping layer deposited on top of tantalum. Synchrotron-based X-ray photoelectron spectroscopy (XPS) studies demonstrate that oxide is confined to an extremely thin region directly beneath the Mg/Ta interface. Additionally, we demonstrate that the superconducting properties of thin Ta films are improved following the Mg capping, exhibiting sharper and higher-temperature transitions to superconductive and magnetically ordered states. Based on the experimental data and computational modeling, we establish an atomic-scale mechanistic understanding of the role of the capping layer in protecting Ta from oxidation. This work provides valuable insights into the formation mechanism and functionality of surface tantalum oxide, as well as a new materials design principle with the potential to reduce dielectric loss in superconducting quantum materials. Ultimately, our findings pave the way for the realization of large-scale, high-performance quantum computing systems. © 2023, CC BY.

关键词： X ray photoelectron spectroscopy

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Specification of the data warehouse for the decision-making dimension of the Bid Process Information System

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Procedia computer science 2019年 159卷 1190-1197页

作者： Manel Zekri Sahbi Zahaf Faiez Gargouri University of Tunis El Manar Faculty of Sciences of Tunis Department of Computer Science El Manar II 2092 Tunisia MIRACL Laboratory Higher Institute of Computer and Multimedia Sakiet Ezzit Technopole Sfax 242-3021 Tunisia

In order to enhance the business process, the Bid Process Information System (BPIS) should be made more performant by ensuring greater flexibility and interoperability between devices. Moreover, the specication of this system has to deal with “three fit” problems. To this end, four dimensions have been identified in order to cope with potential failures: operational, organizational, decision-making, and cooperative dimensions. In this paper, we focus on the decision-making dimension of the BPIS and propose an approach for representing data warehouse schema based on an ontology that captures the multidimensional bid-knowledge.

关键词： Bid Process Information System Data Warehouse Conceptual Data Model Multidimensional Design Ontology

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Characteristics of the decision-making dimension of the BPIS

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Procedia computer science 2019年 164卷 285-291页

“Three fit” problems in the Bid Process Information System (BPIS) are still an open issue. The BPIS must be: integrated, flexible and interoperable in order to deal with the urbanization approach. Hence, operational, organizational, decision-making, and coop-erative dimensions are four dimensions that have been identified to deal with such failures. Accordingly, we propose an approach that focuses on the decision-making dimension of the BPIS. In addition, it represents data warehouse schema based on an ontology in order to capture the multidimensional bid-knowledge. This improves the resulting of data warehouse schema.

关键词： Bid Process Information System Data Warehouse Conceptual Data Model Multidimensional Design Ontology

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Switched-capacitor finite impulse response rotator filter

Switched-capacitor finite impulse response rotator filter

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Signal Processing Algorithms, Architectures, Arrangements and Applications (SPA)

作者： Paweł Pawłowski Rafał Długosz Adam Dąbrowski Division of Signal Processing and Electronic Systems Jana Pawł a II 24 Poznan University of Technology Faculty of Control Robotics and Electrical Engineering and Institute of Automation and Robotics Poznań Poland Faculty of Telecommunication Computer Science and Electrical Engineering Kaliskiego 7 UTP University of Science and Technology Bydgoszcz Poland

ISBN: (数字)9788362065394

ISBN: (纸本)9781728177465

Design of the topology and layout for an analog finite impulse response (FIR) filter realized in the CMOS technology using the switched capacitor (SC) technique, is presented. The filter is based on the so called “rotator structure” supplemented with the programmable capacitor array. This array makes the on-line adjusting of the frequency response of the filter possible in a very wide range, thus, enlarges the area of applications of this circuit, e.g., to multi-standard wireless communication, software-defined radio, adaptive systems, etc. The presented circuit realizes filters of orders up to 15 (16 filter coefficients). The maximum frequency range approaches ca. 2 MHz. The circuit dissipates ca. 8 mW from the power supply.

关键词： Finite impulse response filters Capacitors iiR filters Clocks Operational amplifiers Switches Capacitance

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Convex-concave backtracking for inertial bregman proximal gradient algorithms in non-convex optimization

arXiv

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arXiv 2019年

作者： Mukkamala, Mahesh Chandra Ochs, Peter Pock, Thomas Sabach, Shoham Faculty of Mathematics and Computer Science Saarland University Saarbrucken66123 Germany Institute of Computer Graphics and Vision Graz University of Technology Graz8010 Austria Faculty of Industrial Engineering Technion Haifa3200003 Israel

Backtracking line-search is an old yet powerful strategy for finding a better step sizes to be used in proximal gradient algorithms. The main principle is to locally find a simple convex upper bound of the objective function, which in turn controls the step size that is used. In case of inertial proximal gradient algorithms, the situation becomes much more difficult and usually leads to very restrictive rules on the extrapolation parameter. In this paper, we show that the extrapolation parameter can be controlled by locally finding also a simple concave lower bound of the objective function. This gives rise to a double convex-concave backtracking procedure which allows for an adaptive choice of both the step size and extrapolation parameters. We apply this procedure to the class of inertial Bregman proximal gradient methods, and prove that any sequence generated by these algorithms converges globally to a critical point of the function at hand. Numerical experiments on a number of challenging non-convex problems in image processing and machine learning were conducted and show the power of combining inertial step and double backtracking strategy in achieving improved *** Codes 90C25, 26B25, 49M27, 52A41, 65K05 Copyright © 2019, The Authors. All rights reserved.

关键词： Extrapolation

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New multi-wave solutions of the conformable LPD model with nonlinear wave phenomena arise in mathematical physics

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Journal of Ocean Engineering and science 2022年

作者： Tripathy, Ananya Sahoo, Subhadarshan Rezazadeh, Hadi Ahmad, Hijaz Inc, Mustafa Kalinga Institute of Industrial Technology Deemed to be University Odisha Bhubaneswar 751024 India Faculty of Modern Technologies Engineering Amol University of Special Modern Technologies Amol Iran Section of Mathematics International Telematic University Uninettuno Corso Vittorio Emanuele II Roma 3900186 Italy Department of Computer Engineering Biruni University Istanbul Turkey Firat University Science Faculty Department of Mathematics Elazig 23119 Turkey Department of Medical Research China Medical University Hospital China Medical University Taichung Taiwan

In this paper, the conformable Lakshmanan–Porsezian–Daniel equation with parabolic law nonlinearity is solved and the newly acquired optical solutions are analysed. To achieve this, two robust analytical techniques are implemented namely, the three-wave method and the interaction phenomena form. The newly obtained solutions are in the form of dark, w-shaped, periodic, peakon, bright and three-soliton solutions and their interaction solution in a kinky base. These characteristics are analysed by the graphical representation which demonstrates the reliability and virtue of the proposed methods. The most fascinating part of the reported solutions is their use in science and engineering. The novel aspect of this study is the obtained solutions, which were not before achieved and demonstrate a good balance between the nonlinear physical components. Furthermore, the solutions can facilitate estimating the performance of wave patterns in fibers when needed in a design. © 2022

关键词： 02.30.Hq 02.30.Jr 42.65.Wi 42.81.Dp Fractional derivative Lakshmanan–Porsezian–Daniel equation Optical fibers Optical solutions Three-wave method

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Medical deep learning-A systematic meta-review

arXiv

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arXiv 2020年

作者： Egger, Jan Gsaxner, Christina Pepe, Antonio Pomykala, Kelsey L. Jonske, Frederic Kurz, Manuel Li, Jianning Kleesiek, Jens Institute of Computer Graphics and Vision Faculty of Computer Science and Biomedical Engineering Graz University of Technology Inffeldgasse 16 Styria Graz8010 Austria Department of Oral & Maxillofacial Surgery Medical University of Graz Auenbruggerplatz 5/1 Styria Graz8036 Austria Computer Algorithms for Medicine Laboratory Styria Graz Austria University Medicine Essen Girardetstraße 2 Essen45131 Germany University Medicine Essen Hufelandstraße 55 Essen45147 Germany Partner Site Essen Hufelandstraße 55 Essen45147 Germany

Deep learning has remarkably impacted several different scientific disciplines over the last few years. For example, in image processing and analysis, deep learning algorithms were able to outperform other cutting-edge methods. Additionally, deep learning has delivered state-of-the-art results in tasks like autonomous driving, outclassing previous attempts. There are even instances where deep learning outperformed humans, for example with object recognition and gaming. Deep learning is also showing vast potential in the medical domain. With the collection of large quantities of patient records and data, and a trend towards personalized treatments, there is a great need for automated and reliable processing and analysis of health information. Patient data is not only collected in clinical centers, like hospitals and private practices, but also by mobile healthcare apps or online websites. The abundance of collected patient data and the recent growth in the deep learning field has resulted in a large increase in research effort s. In Q2/2020, the search engine PubMed returned already over 11,000 results for the search term 'deep learning', and around 90% of these publications are from the last three years. However, even though PubMed represents the largest search engine in the medical field, it does not cover all medical-related publications. Hence, a complete overview of the field of 'medical deep learning' is almost impossible to obtain and acquiring a full overview of medical sub-fields is becoming increasingly more difficult. Nevertheless, several review and survey articles about medical deep learning have been published within the last few years. They focus, in general, on specific medical scenarios, like the analysis of medical images containing specific pathologies. With these surveys as a foundation, the aim of this article is to provide the first high-level, systematic meta-review of medical deep learning surveys. Copyright © 2020, The Authors. All rights res

关键词： Generative adversarial networks

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ConceptExplorer: Visual Analysis of Concept Driftsin Multi-source Time-series Data

arXiv

引用

arXiv 2020年

作者： Wang, Xumeng Xu, Dongshi Chen, Wei Wu, Xiangyang Xia, Jiazhi Xu, Mingliang Chen, Zexian Schreck, Tobias State Key Lab of CAD&CG Zhejiang University China College of Information Engineering China Jiliang University China Institute of Graphics and Image Hangzhou Dianzi University China School of Computer Science and Engineering Central South University China Zhengzhou University China Graz University of Technology Austria

Time-series data is widely studied in various scenarios, like weather forecast, stock market, customer behavior analysis. To comprehensively learn about the dynamic environments, it is necessary to comprehend features from multiple data sources. This paper proposes a novel visual analysis approach for detecting and analyzing concept drifts from multi-sourced time-series. We propose a visual detection scheme for discovering concept drifts from multiple sourced time-series based on prediction models. We design a drift level index to depict the dynamics, and a consistency judgment model to justify whether the concept drifts from various sources are consistent. Our integrated visual interface, ConceptExplorer, facilitates visual exploration, extraction, understanding, and comparison of concepts and concept drifts from multi-source time-series data. We conduct three case studies and expert interviews to verify the effectiveness of our approach. Copyright © 2020, The Authors. All rights reserved.

关键词： Time series

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Inferring IGM parameters from the redshifted 21-cm Power Spectrum using Artificial Neural Networks

arXiv

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arXiv 2024年

作者： Choudhury, Madhurima Ghara, Raghunath Zaroubi, Saleem Ciardi, Benedetta Koopmans, Leon V.E. Mellema, Garrelt Shaw, Abinash Kumar Acharya, Anshuman Iliev, I.T. Ma, Qing-Bo Giri, Sambit K. Astrophysics Research Centre of the Open University of Israel Ra'anana4353701 Israel Center for Fundamental Physics of the Universe Department of Physics Brown University ProvidenceRI02914 United States Department of Physics and Astronomy Haverford College 370 Lancaster Ave HaverfordPA19041 United States Center for Particle Cosmology Department of Physics and Astronomy University of Pennsylvania PhiladelphiaPA19104 United States Department of Natural Sciences The Open University of Israel 1 University Road Ra'anana4353701 Israel Kapteyn Astronomical Institute University of Groningen PO Box 800 Groningen9700AV Netherlands Max-Planck Institute for Astrophysics Karl-Schwarzschild-Straße 1 Garching85748 Germany The Oskar Klein Centre Department of Astronomy Stockholm University AlbaNova StockholmSE-10691 Sweden Department of Computer Science University of Nevada Las VegasNV89154 United States Astronomy Centre Department of Physics and Astronomy University of Sussex Pevensey II Building BrightonBN1 9QH United Kingdom School of Physics and Electronic Science Guizhou Normal University Guiyang550001 China Nordita KTH Royal Institute of Technology Stockholm University Hannes Alfvéns väg 12 StockholmSE-106 91 Sweden

The high redshift 21-cm signal promises to be a crucial probe of the state of the intergalactic medium (IGM). Understanding the connection between the observed 21-cm power spectrum and the physical quantities intricately associated with the IGM is crucial to fully understand the evolution of our Universe. In this study, we develop an emulator using artificial neural network (ANN) to predict the 21-cm power spectrum from a given set of IGM properties, namely, the bubble size distribution and the volume averaged ionization fraction. This emulator is implemented within a standard Bayesian framework to constrain the IGM parameters from a given 21-cm power spectrum. We compare the performance of the Bayesian method to an alternate method using ANN to predict the IGM parameters from a given input power spectrum, and find that both methods yield similar levels of accuracy, while the ANN is significantly faster. We also use this ANN method of parameter estimation to predict the IGM parameters from a test set contaminated with noise levels expected from the SKA-LOW instrument after 1000 hours of observation. Finally, we train a separate ANN to predict the source parameters from the IGM parameters directly, at a redshift of z = 9.1, demonstrating the possibility of a non-analytic inference of the source parameters from the IGM parameters for the first time. We achieve high accuracies, with R2-scores ranging between 0.898 − 0.978 for the ANN emulator and between 0.966 − 0.986 and 0.817 − 0.981 for the predictions of IGM parameters from 21-cm power spectrum and source parameters from IGM parameters, respectively. The predictions of the IGM parameters from the Bayesian method incorporating the ANN emulator leads to tight constraints with error bars around ±0.14 on the IGM parameters. © 2024, CC BY.

关键词： Machine learning

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Slow Heat-Based Hybrid Simulated Annealing Algorithm in Vehicular Ad Hoc Network

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Computational intelligence and neuroscience 2023年第1期2023卷 9918748页

作者： Pavan Kumar Pagadala P Lalitha Surya Kumari Deepak Thakur Vivek Bhardwaj Mohammad Shahid Abdulrajak Buradi Abdul Razak Abiot Ketema Computer Science and Engineering Koneru Lakshmaiah Educational Foundation Hyderabad Telangana India. Chitkara University Institute of Engineering and Technology Chitkara University Punjab India. School of Computer Science and Engineering Lovely Professional University Jalandhar 144411 India. Department of Electrical Engineering Galgotias College of Engineering and Technology 1 Knowledge Park Phase II Noida 201306 UP India. Department of Mechanical Engineering Nitte Meenakshi Institute of Technology Bangalore India. Department of Mechanical Engineering P. A. College of Engineering (Affiliated to Visvesvaraya Technological University Belagavi) Mangaluru 574153 India. Department of Biosystems Engineering Institute of Technology Hawassa University Hawassa Ethiopia.

Vehicular ad hoc networks (VANETs) using reliable protocols of routing have become crucial in identifying the changes to topology on a continuous basis for a large collection of vehicles. For this purpose, it becomes important to identify an optimal configuration of these protocols. There are several possible configurations that have been preventing the configuration of efficient protocols that do not make use of automatic and intelligent design tools. It can further motivate using the techniques of metaheuristics like the tools, which are well-suited to be able to solve these problems. The glowworm swarm optimization (GSO), simulated annealing (SA), and slow heat-based SA-GSO algorithms have been proposed in this work. The SA is a method of optimization, which imitates the manner in which the thermal system has been frozen down to its lowest state of energy. In the GSO, there is guidance to the rules of feasibility, where the swarm converges to its feasible regions very fast. Additionally, for overcoming any premature convergence, there is a local search strategy that is based on the SA and is used for making a search that is near to its true optimum solutions. Finally, this sluggish temperature-based SA-GSO algorithm will be employed to solve routing problems and problems of heat transfer. There is a hybrid slow heat SA-GSO algorithm with a faster speed of convergence and higher precision of computation that is more effective in solving problems of constrained engineering.

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