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35th International Conference on Power Electronics and Electrical Drives, EDPE 2021

作者： Stojanović, Željko Pelin, Denis Department of Electrical Engineering Zagreb University of Applied Sciences Zagreb Croatia Faculty of Electrical Engineering Computer Science and Information Technology Osijek University of Osijek Osijek Croatia

The paper deals with the harmonic content of the input current of the voltage mode controlled boost converter in quasiperiodicity. By decrease of the input voltage the converter exhibits quasiperiodicity caused by Hopf bifurcation and border collision bifurcation. In the area of these bifurcations mode locking, quasiperiodic steady-states and chaotic steady-states alternate. Characteristic waveforms, trajectories and harmonic contents of the input currrent in the area of Hopf bifurcation and border collision bifurcation are presented. The quasiperiodicity caused by both bifurcations has so far not been recorded in the boost converter. Additional harmonics in the input current of the converter are introduced by the quasiperiodicity. These harmonics are spread to the area of frequencies lower than the switching frequency as well as between the multiple integers of the switching frequency. Low frequency AC components in quasiperiodicity caused by border collision bifurcation are higher than low frequency AC components caused by Hopf bifurcation. These low frequency harmonics can be harmful to the source of the input voltage. ©2021 IEEE.

关键词： Boost converter Border collision bifurcation Harmonic content Hopf bifurcation Quasiperiodicity

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Nonreciprocal Dissipation engineering via Strong Coupling with a Continuum of Modes

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Physical Review X 2024年第2期14卷 021002-021002页

作者： Yishu Zhou Freek Ruesink Shai Gertler Haotian Cheng Margaret Pavlovich Eric Kittlaus Andrew L. Starbuck Andrew J. Leenheer Andrew T. Pomerene Douglas C. Trotter Christina Dallo Katherine M. Musick Eduardo Garcia Robert Reyna Andrew L. Holterhoff Michael Gehl Ashok Kodigala John Bowers Matt Eichenfield Nils T. Otterstrom Anthony L. Lentine Peter Rakich Department of Applied Physics Yale University New Haven Connecticut USA Jet Propulsion Laboratory California Institute of Technology Pasadena California USA Microsystems Engineering Science and Applications Sandia National Laboratories Albuquerque New Mexico USA Department of Electrical and Computer Engineering University of California Santa Barbara California USA James C. Wyant College of Optical Sciences University of Arizona Tucson Arizona USA

Optical nonreciprocity plays a key role in almost every optical system, directing light flow and protecting optical components from backscattered light. Controllable forms of on-chip nonreciprocity are needed for the robust operation of increasingly sophisticated photonic integrated circuits (PICs) in the context of classical and quantum computation, networking, communications, and sensing. However, it has been challenging to achieve wideband, low-loss optical nonreciprocity on-chip. In this paper, we demonstrate strong coupling and Rabi-like energy exchange between photonic bands, possessing a continuum of modes, to unlock nonreciprocity and frequency translation over wide optical bandwidths in silicon. Using a traveling-wave phonon field to drive indirect interband photonic transitions, we demonstrate band hybridization that enables an intriguing form of nonreciprocal dissipation engineering. Using the converted mode to create a nonreciprocal dissipation channel, we demonstrate a frequency-neutral, low-loss (less than 1 dB) isolator with high nonreciprocal contrast (more than 14 dB) and broad operating bandwidth (more than 59 GHz). Additionally, through the implementation of complete interband conversion, we demonstrate a high extinction (more than 55 dB) optical frequency translation operation with near-unity efficiency.

关键词： Integrated optics Optomechanics Phonons Optical isolators Rabi model

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High-Dimensional Quantum Conference Key Agreement

High-Dimensional Quantum Conference Key Agreement

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IEEE International Symposium on Information Theory

作者： Omar Amer Walter O. Krawec Future Lab for Applied Research and Engineering JPMorgan Chase Bank N.A New York NY USA Computer Science &amp Engineering Department University of Connecticut Storrs CT

ISBN: (数字)9781665421591

ISBN: (纸本)9781665421607

Quantum Conference Key Agreement (QCKA) protocols are designed to allow multiple parties to agree on a shared secret key, secure against computationally unbounded adversaries. In this paper, we consider a high-dimensional QCKA protocol and prove its information theoretic security against arbitrary, general, attacks in the finite-key scenario. Our proof technique may be useful for other high-dimensional multiparty quantum cryptographic protocols. Finally, we evaluate the protocol in a variety of settings, showing that high-dimensional states can greatly benefit QCKA protocols.

关键词： Quantum computing Conferences Quantum mechanics Security Information theory Cryptographic protocols

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An Efficient Mechanism for Product Data Extraction from E-Commerce Websites

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computers, Materials & Continua 2020年第12期65卷 2639-2663页

作者： Malik Javed Akhtar Zahur Ahmad Rashid Amin Sultan H.Almotiri Mohammed A.Al Ghamdi Hamza Aldabbas University of Engineering and Technology TaxilaPakistan Computer Science Department Umm Al-Qura UniversityMakkah CitySaudi Arabia Al-Balqa Applied University Al-SaltJordan

A large amount of data is present on the web which can be used for useful purposes like a product recommendation,price comparison and demand forecasting for a particular *** are designed for human understanding and not for ***,to make data machine-readable,it requires techniques to grab data from web *** have addressed the problem using two approaches,i.e.,knowledge engineering and machine *** of the art knowledge engineering approaches use the structure of documents,visual cues,clustering of attributes of data records and text processing techniques to identify data records on a web *** learning approaches use annotated pages to learn *** rules are used to extract data from unseen web *** structure of web documents is continuously ***,new techniques are needed to handle the emerging requirements of web data *** this paper,we have presented a novel,simple and efficient technique to extract data from web pages using visual styles and structure of *** proposed technique detects Rich Data Region(RDR)using query and correlative words of the *** is then divided into data records using style *** elements are removed using a Common Tag Sequence(CTS)and formatting *** system is implemented using JAVA and runs on the dataset of real-world working *** effectiveness of results is evaluated using precision,recall,and F-measure and compared with five existing systems.A comparison of the proposed technique to existing systems has shown encouraging results.

关键词： Document object model rich data region common tag sequence web data extraction deep web mining

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Deep neural networks for smooth approximation of physics with higher order and continuity B-spline base functions

arXiv

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arXiv 2022年

作者： Doleglo, Kamil Paszyńska, Anna Paszyński, Maciej Demkowicz, Leszek Institute of Computer Science AGH University of Science and Technology Kraków Poland Faculty of Physics Astronomy and Applied Computer Science Jagiellonian University Kraków Poland Oden Institute for Computational and Engineering Sciences The University of Texas at Austin United States

This paper deals with the following important research question. Traditionally, the neural network employs non-linear activation functions concatenated with linear operators to approximate a given physical phenomenon. They "fill the space" with the concatenations of the activation functions and linear operators and adjust their coefficients to approximate the physical phenomena. We claim that it is better to "fill the space" with linear combinations of smooth higher-order B-splines base functions as employed by isogeometric analysis and utilize the neural networks to adjust the coefficients of linear combinations. In other words, the possibilities of using neural networks for approximating the B-spline base functions' coefficients and by approximating the solution directly are evaluated. Solving differential equations with neural networks has been proposed by Maziar Raissi et al. in 2017 [16] by introducing Physics-informed Neural Networks (PINN), which naturally encode underlying physical laws as prior information. Approximation of coefficients using a function as an input leverages the well-known capability of neural networks being universal function approximators [6]. In essence, in the PINN approach the network approximates the value of the given field at a given point. We present an alternative approach, where the physcial quantity is approximated as a linear combination of smooth B-spline basis functions, and the neural network approximates the coefficients of B-splines. This research compares results from the DNN approximating the coefficients of the linear combination of B-spline basis functions, with the DNN approximating the solution directly. We show that our approach is cheaper and more accurate when approximating smooth physical fields. © 2022, CC BY.

关键词： Deep neural networks

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Modeling and Simulation of a Single Catalytic Fixed Bed in an Ammonia Reactor

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IFAC-PapersOnLine 2023年第2期56卷 6906-6912页

作者： Emil Skov Martinsen Joachim Weel Rosbo Anders H.D. Andersen Tobias K.S. Ritschel Steen Hørsholt Jakob Kjøbsted Huusom John Bagterp Jørgensen Department of Applied Mathematics and Computer Science Technical University of Denmark DK-2800 Kgs. Lyngby Denmark Department of Chemical Engineering Technical University of Denmark DK-2800 Kgs. Lyngby Denmark 2-control ApS DK-7400 Herning Denmark

We present a dynamical model of a single catalytic fixed bed in a quench-type ammonia reactor. This model consists of thermodynamics, kinetics, pressure loss, and mass and energy balances, which upon spatial discretisation results in a set of differential-algebraic equations. Compared to similar models in the literature, the main novelties in the model are: 1) a rigorous thermodynamic model using a thermodynamic software library; and 2) a correlation between the gas velocity and the pressure gradient throughout the bed, i.e. the pressure loss is included in the model and used to compute the gas velocity. We investigate steady state solutions and dynamical simulations to understand the behaviour of the single catalytic fixed bed. We determine the optimal steady state operational area and inverse response dynamics are observed. The model can be used to develop model-based control, which is relevant for dynamic and flexible operation of ammonia reactors in a Power-to-Ammonia plant.

关键词： Mathematical modeling Dynamical simulation Ammonia reactor Power-to-X

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Orchestrating Apache NiFi/MiNiFi within a Spatial Data Pipeline

Orchestrating Apache NiFi/MiNiFi within a Spatial Data Pipel...

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International Conference on Software engineering Research, Management and Applications (SERA)

作者： Chase Carthen Araam Zaremehrjardi Vinh Le Carlos Cardillo Scotty Strachan Alireza Tavakkoli Frederick C. Harris Sergiu M. Dascalu Computer Science and Engineering University of Nevada Reno Reno Nevada Nevada Center for Applied Research University of Nevada Reno Reno Nevada System Computing Services Nevada System of Higher Education Reno Nevada

In many smart city projects, a common choice to capture spatial information is the inclusion of LiDAR data, but this decision will often invoke severe growing pains within the existing infrastructure. In this paper, we introduce a data pipeline that orchestrates Apache NiFi (NiFi), Apache MiNiFi (MiNiFi), and several other tools as an automated solution in order to relay and archive LiDAR data captured by deployed edge devices. The LiDAR sensors utilized within this workflow are Velodyne Ultra Pucks sensors that capture at a rate of 10 frames per second and produces 6-7 GB packet capture (PCAP) files per hour. By both compressing the file after capturing it and compressing the file in real-time, we discovered that gzip produced a file of 5 GB and saved about 5 minutes in transmission time to NiFi, as well as saving considerable CPU time when compressing the file in real-time. Alternatively, we chose XZ as the compression algorithm for the ingestion of LiDAR data onto an institution compute cluster due to its high compression ratio. In order to evaluate the capabilities of our system design, the features of this data pipeline were compared against existing third-party services, namely Globus and RSync.

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Neural Injective Functions for Multisets, Measures and Graphs via a Finite Witness Theorem

arXiv

引用

arXiv 2023年

作者： Amir, Tal Gortler, Steven J. Avni, Ilai Ravina, Ravina Dym, Nadav Faculty of Mathematics Technion – Israel Institute of Technology Haifa Israel School of Engineering and Applied Sciences Harvard University Cambridge United States Faculty of Computer Science Technion – Israel Institute of Technology Haifa Israel

Injective multiset functions have a key role in the theoretical study of machine learning on multisets and graphs. Yet, there remains a gap between the provably injective multiset functions considered in theory, which typically rely on polynomial moments, and the multiset functions used in practice, which rely on neural moments — whose injectivity on multisets has not been studied to date. In this paper, we bridge this gap by showing that moments of neural networks do define injective multiset functions, provided that an analytic non-polynomial activation is used. The number of moments required by our theory is optimal essentially up to a multiplicative factor of two. To prove this result, we state and prove a finite witness theorem, which is of independent interest. As a corollary to our main theorem, we derive new approximation results for functions on multisets and measures, and new separation results for graph neural networks. We also provide two negative results: (1) moments of piecewise-linear neural networks cannot be injective multiset functions;and (2) even when moment-based multiset functions are injective, they can never be bi-Lipschitz. Copyright © 2023, The Authors. All rights reserved.

关键词： Graph neural networks

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Analyzing Generalized Pólya Urn Models using Martingales, with an Application to Viral Evolution

arXiv

引用

arXiv 2023年

作者： Specht, Ivan Mitzenmacher, Michael Harvard College Faculty of Arts and Sciences Harvard University CambridgeMA02138 United States Department of Computer Science School of Engineering and Applied Sciences Harvard University CambridgeMA02138 United States

The randomized play-the-winner (RPW) model is a generalized Pólya Urn process with broad applications ranging from clinical trials to molecular evolution. We derive an exact expression for the variance of the RPW model by transforming the Pólya Urn process into a martingale, correcting an earlier result of Matthews and Rosenberger (1997). We then use this result to approximate the full probability mass function of the RPW model for certain parameter values relevant to genetic applications. Finally, we fit our model to genomic sequencing data of SARS-CoV-2, demonstrating a novel method of estimating the viral mutation rate that delivers comparable results to existing scientific literature. © 2023, CC BY.

关键词： Coronavirus

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Design and Development of Power Management Framework for Electrical Vehicles in Smart City Grid

Design and Development of Power Management Framework for Ele...

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International Conference for Convergence of Technology (I2CT)

作者： D. Sagar Harishankar Singh Hari Krishna S. M Computer science and Engineering Ramaiah University of Applied Sciences Bangalore Karnataka India

Electric Vehicles are the future of mobility, which are dependent on battery technology, and as estimated, 70% of the two-wheeler and 50% of the EV's, price is estimated to be of batteries. In this dissertation work, power management framework model has been designed and developed for electric vehicles in smart city grid and the proof of concept has been disclosed. After an intense literature review, to design the framework for power management in EV's, three layered architecture is selected and the layers are divided as organisation layer, business logic layer, and analysis layer. The organisation is front layer for various electric vehicles sellers, developers and will act as a connecting layer for the user end and the proposed framework. The organisation layer is divided into three subfunctions namely: data segregation, data evaluation function, and data marshalling function. Where, data segregation is done w.r.t., core, luxury, and safety parameters function. Second layer has been divide into four sub-functions namely: data acquisition function, data un-marshalling function, data representation function, and data marshalling function. Third layer has been divided into four sub-functions namely: data acquisition function, data un-marshalling function, data segregation with respect to core, luxury, and safety parameters function and data analysis function. The proof of concept is given using the NetBeans software and framework designed has three layers which will be represented as three different server stations and the results obtain gives a very clear acceptance confirmation of the designed framework.

关键词： Power demand Smart cities Power system management Roads Data acquisition Electric vehicles Software

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