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arXiv 2024年

作者： Varotto, Matteo Valentin, Stefan Tomasin, Stefano Dep. of Computer Science Darmstadt University of Applied Sciences Germany Dep. of Information Engineering Dep. of Mathematics University of Padova Italy

Cellular networks are potential targets of jamming attacks to disrupt wireless communications. Since the fifth generation (5G) of cellular networks enables mission-critical applications, such as autonomous driving or smart manufacturing, the resulting malfunctions can cause serious damage. This paper proposes to detect broadband jammers by an online classification of spectrograms. These spectrograms are computed from a stream of in-phase and quadrature (IQ) samples of 5G radio signals. We obtain these signals experimentally and describe how to design a suitable dataset for training. Based on this data, we compare two classification methods: a supervised learning model built on a basic convolutional neural network (CNN) and an unsupervised learning model based on a convolutional autoencoder (CAE). After comparing the structure of these models, their performance is assessed in terms of accuracy and computational complexity. © 2024, CC BY.

关键词： Convolution

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Short-Term Wireless Connectivity Prediction for Connected Agricultural Vehicles

Short-Term Wireless Connectivity Prediction for Connected Ag...

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International Conference on Intelligent Transportation

作者： Brynjar Örn Grétarsson Charalampos Orfanidis Letizia Marchegiani Xenofon Fafoutis Department of Applied Mathematics and Computer Science Technical University of Denmark Denmark Department of Engineering and Architecture University of Parma Italy

Robots and autonomous vehicles have been integrated in our life and utilized in a plethora of application scenarios, including intelligent transportation, industrial automation and smart agriculture. Several of the these applications might be functioning in environments where cellular network coverage is low or non-existent. In a case like this, lower bandwidth networks and vehicle-to-vehicle communication can be used to keep the application operating safely, even with less active features. In such settings, disconnection events can be avoided if deteriorating communication links are detected early so that prevention measures can be taken. In this paper we investigate how we can predict if a communication link will be terminated in the near future based on the recent trend of the signal. We propose a deep neural network framework which is executed onboard and we evaluate its performance based on simulation and real word data. The results show that we can predict the termination of a link up to 7 seconds into the future with 72.38% accuracy and 86.38% recall.

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Efficient Diabetes Detection using Hybrid Machine Learning Model

Efficient Diabetes Detection using Hybrid Machine Learning M...

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2024 International Conference on Distributed Systems, computer Networks and Cybersecurity, ICDSCNC 2024

作者： Gowri, A.S. Jose, P. Karthik, S.M. Shaheema, S Berlin Karuppasway, K.M. Balamurugan, R. School of Computing Srm Institute of Science and Technology Department of Networking and Communications Kattankulathur India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai India Department for Applied Research Gandhigram India Stella Mary's College of Engineering Department of Artificial Intelligence and Data Science Azhikal India Bharath Institute of Higher Education and Research Department of Mathematics and Statistics Chennai India Dmi College of Engineering Department of Information Technology Chennai India

ISBN: (纸本)9798350375442

Diabetes is a metabolic disease that affects a large number of the global population and is incurable. The primary causes of death symptoms are kidney failure, heart attacks, strokes, and blindness. In this paper Principal component analysis used for pre-processing the data to extract features and The Efficient Hybrid Machine Learning Model Convolution Neural Network-Support Vector Machine is used to categorize the Pima Indian dataset. CNN and non-linear SVM used in a hybrid model to classify the diabetes data from the Pima Indians. To identify positive classes of pima Indians diabetes, the HCNN-SVM extract the features from the original data expression and learns diabetes data through a novel convolution network environment to the SVM classifier with RBF function and achieve the accuracy as 98,04%. © 2024 IEEE.

关键词： Adversarial machine learning

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MATLAB Simulation of 500 W Direct Methanol Fuel Cell Stack 2nd

MATLAB Simulation of 500 W Direct Methanol Fuel Cell Stack

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2nd International Conference on Materials, Design and Manufacturing for Sustainable Environment, ICMDMSE 2022

作者： Babu, S. Prem Kumar, T. Divya, V.V. Paulinga Prakash, R. Jeriel, D. Department of Mechanical Engineering PSG College of Technology Coimbatore641004 India Department of Mechanical Engineering PSG Institute of Technology and Applied Research Coimbatore641062 India Department of Mathematics With Computer Applications PSG College of Arts & Science Coimbatore641014 India Department of Mechanical Engineering VEL Tech Multitech Chennai600062 India

ISBN: (纸本)9789811930522

This paper aims about the mathematical model analysis of 500 W direct methanol fuel cell (DMFC) using MATLAB SIMULINK. Three dynamic models, Input I-stdy-ideal, Input I-stdy, InputI-dynshrt4, were included with simulation time of 4900 ms, 3900 ms and 2040 ms, respectively. Ideal cell load with steady state, real fuel cell load with steady and real fuel cell load with transient state had been studied in detail. Pattern of output voltage, current density, power density and temperature distribution with respect to time has been found. Decreasing voltage pattern and increasing current density pattern are in line with typical VI (Voltage-Current density) curve. The optimum cell conditions obtained at 3100 ms are 25 V, 23 A/cm2 which gives the maximum power density of 575 W/cm2 at the operating temperature of 315 K. One of the major advantages of DMFC is obtaining maximum efficiency at the operating temperature which is closed to ambient conditions unlike proton exchange membrane fuel cell (PEMFC). © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Current density

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Neural Bayes estimators for censored inference with peaks-over-threshold models

The Journal of Machine Learning Research

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The Journal of Machine Learning Research 2024年第1期25卷 19070-19118页

作者： Jordan Richards Matthew Sainsbury-Dale Andrew Zammit-Mangion Raphaël Huser School of Mathematics and Maxwell Institute for Mathematical Sciences University of Edinburgh Edinburgh UK and Statistics Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia Statistics Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia and School of Mathematics and Applied Statistics University of Wollongong Wollongong Australia School of Mathematics and Applied Statistics University of Wollongong Wollongong Australia Statistics Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

Making inference with spatial extremal dependence models can be computationally burdensome since they involve intractable and/or censored likelihoods. Building on recent advances in likelihood-free inference with neural Bayes estimators, that is, neural networks that approximate Bayes estimators, we develop highly efficient estimators for censored peaks-over-threshold models that use augmented data to encode censoring information in the neural network input. Our new method provides a paradigm shift that challenges traditional censored likelihood-based inference methods for spatial extremal dependence models. Our simulation studies highlight significant gains in both computational and statistical efficiency, relative to competing likelihood-based approaches, when applying our novel estimators to make inference with popular extremal dependence models, such as max-stable, r-Pareto, and random scale mixture process models. We also illustrate that it is possible to train a single neural Bayes estimator for a general censoring level, precluding the need to retrain the network when the censoring level is changed. We illustrate the efficacy of our estimators by making fast inference on hundreds-of-thousands of high-dimensional spatial extremal dependence models to assess extreme particulate matter 2.5 microns or less in diameter (PM2:5) concentration over the whole of Saudi Arabia.

关键词： censored data convolutional neural network likelihood-free inference neural estimation spatial extremes threshold exceedance

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Two-Way Communication Retrial Queue with Markov Modulated Poisson Input and Multiple Types of Outgoing Calls 25th

Two-Way Communication Retrial Queue with Markov Modulated P...

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25th International Conference on Distributed computer and Communication Networks, DCCN 2022

作者： Nazarov, Anatoly Phung-Duc, Tuan Paul, Svetlana Lizyura, Olga Institute of Applied Mathematics and Computer Science National Research Tomsk State University 36 Lenina ave. Tomsk634050 Russia Faculty of Engineering Information and Systems University of Tsukuba 1-1-1 Tennodai Ibaraki Tsukuba305-8573 Japan

ISBN: (纸本)9783031306471

In this paper, we consider single server two-way communication retrial queue with Markov modulated Poisson input. Such system serves two types of calls: incoming and outgoing. We assume that incoming calls arrive according to the input process and retry in case the server is busy upon arrival. If the server is occupied upon arrival, the incoming call joins the orbit and waits for some time before making the next try to receive service. On the other hand, outgoing calls are initiated by server and do not make redial. We present the analysis of the queue using asymptotic diffusion method. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Queueing theory

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Electricity Market Equilibria Analysis on the Value of Demand-Side Flexibility Portfolios’ Mix and the Strategic Demand Aggregators’ Market Power

SSRN

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SSRN 2024年

作者： Khaksari, Alireza Steriotis, Konstantinos Makris, Prodromos Tsaousoglou, Georgios Efthymiopoulos, Nikolaos Varvarigos, Emmanouel School of Electrical and Computer Engineering National Technical University of Athens Iroon Polytechneiou 9 Athens15780 Greece Department of Applied Mathematics and Computer Science Technical University of Denmark Denmark

Electricity market equilibrium analysis is becoming increasingly important within the today's liberalized electricity market and regulatory context for both market participants and policy makers. The former ones want to make informed business decisions to optimize their market position, while the latter need to promote efficient equilibria that satisfy both supply and demand-side requirements and optimize social welfare. In this paper, we focus on modeling the strategic demand aggregators' (DA) behavior via an Equilibrium Problem with Equilibrium Constraints (EPEC) formulation. We model typical demand flexibility portfolios that comprise of several types of distributed flexibility assets and renewable energy resources. We then quantify the value of demand flexibility portfolios' mix and respective value of market power that a strategic DA may exercise with respect to each DA's cost decrease and social welfare as a function of time for a day-ahead market use case. Simulation results show that: i) there is an optimal equilibrium point where overall DAs' costs decrease, while social welfare's deteriorates negligibly, ii) there may be a trade-off between the rate of a certain DA’scost decrease and the rate of market power (or else \% share of total demand flexibility) that this DA possesses, so the strategic DA should take this into account in order to find its optimal CAPEX/OPEX balance for its portfolio, iii) competition among strategic DAs at the demand-side can mitigate grid congestion problems and serve as a counter-balance to the strategic behavior of the supply-side market participants. © 2024, The Authors. All rights reserved.

关键词： Renewable energy resources

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On the Computational Determination of the Third Focus of the Cartesian Oval 32

On the Computational Determination of the Third Focus of the...

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32nd Telecommunications Forum, TELFOR 2024

作者： Malesevic, Branko Rosic, Aleksandra Banjac, Bojan Micovic, Milos University of Belgrade School of Electrical Engineering Department of Applied Mathematics Bulevar kralja Aleksandra 73 Belgrade11000 Serbia University of Belgrade Faculty of Mathematics Department of Algebra and Mathematical Logic Studentski trg 16 Belgrade11000 Serbia University of Novi Sad Computer Graphics Chair Faculty of Technical Sciences Trg Dositeja Obradovica 16 Novi Sad21000 Serbia Intens Doo Bulevar Evrope 28 Novi Sad21000 Serbia School of Electrical Engineering University of Belgrade Science and Research Centre Department of Applied Mathematics Bulevar kralja Aleksandra 73 Belgrade11000 Serbia

ISBN: (纸本)9798350391053

In this paper, the correctness of the algebraic determination of the coordinate of the third focus of the Cartesian oval is examined and analysed. This analysis is necessary because the process includes solving systems with a large number of multivariate polynomial equations using the computer algebra system Maple. The paper also considers the difficulties and limitations of using computers in determining the coordinate of the third focus. © 2024 IEEE.

关键词： Polynomials

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CLASSICAL SOLUTIONS TO THE THIN-FILM EQUATION WITH GENERAL MOBILITY IN THE PERFECT-WETTING REGIME

arXiv

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arXiv 2023年

作者： Gnann, Manuel V. Wisse, Anouk C. Delft Institute of Applied Mathematics Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Mekelweg 4 Delft2628 CD Netherlands

We prove well-posedness, partial regularity, and stability of the thin-film equation ht+(m(h)hzzz)z = 0 with general mobility m(h) = hn and mobility exponent (formula presented) in the regime of perfect wetting (zero contact angle). After a suitable coordinate transformation to fix the free boundary (the contact line where liquid, air, and solid coalesce), the thin-film equation is rewritten as an abstract Cauchy problem and we obtain maximal Lpt-regularity for the linearized evolution. Partial regularity close to the free boundary is obtained by studying the elliptic regularity of the spatial part of the linearization. This yields solutions that are non-smooth in the distance to the free boundary, in line with previous findings for source-type self-similar solutions. In a scaling-wise quasi-minimal norm for the initial data, we obtain a well-posedness and asymptotic stability result for perturbations of traveling waves. The novelty of this work lies in the usage of Lp-estimates in time, where 1 2t-estimates, well-posedness, and stability for (formula presented), our functional-analytic approach is significantly shorter while at the same time giving a more general *** Codes 35K65, 35K25, 35R35, 76A20, 76D08 Copyright © 2023, The Authors. All rights reserved.

关键词： Asymptotic stability

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WEIERSTRASS SEMIGROUPS AND AUTOMORPHISM GROUP OF A MAXIMAL FUNCTION FIELD WITH THE THIRD LARGEST POSSIBLE GENUS, q ≡ 0 (mod 3)

arXiv

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arXiv 2025年

作者： Beelen, Peter Montanucci, Maria Vicino, Lara Department of Applied Mathematics and Computer Science Technical University of Denmark Kongens Lyngby2800 Denmark Faculty of Science and Engineering Bernoulli Institute University of Groningen Groningen9747AG Netherlands

In this article we complete the work started in [3] and [4], explicitly determining the Weierstrass semigroup at any place and the full automorphism group of a known Fq2-maximal function field Z3 having the third largest genus, for q ≡ 0 (mod 3). The cases q ≡ 2 (mod 3) and q ≡ 1 (mod 3) have been in fact analyzed in [3] and [4], respectively. As in the other two cases, the function field Z3 arises as a Galois subfield of the Hermitian function field, and its uniqueness (with respect to the value of its genus) is a well-known open problem. Knowing the Weierstrass semigroups may provide a key towards solving this problem. Surprisingly enough, Z3 has many different types of Weierstrass semigroups and the set of its Weierstrass places is much richer than its set of Fq2-rational places. We show that a similar exceptional behaviour does not occur in terms of automorphisms, that is, Aut(Z3) is exactly the automorphism group inherited from the Hermitian function field, apart from the case q = *** Codes 14H37, 14H05 Copyright © 2025, The Authors. All rights reserved.

关键词： Algebra

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