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Digital Signal Processing and its Applications (DSPA), International Conference on

作者： Pavel S. Izyumov Alexander V. Ivchenko Department of Multimedia Technologies and Telecommunications Moscow Institute of Physics and Technology Dolgoprudny Russia Laboratory of Big Data and Information Systems Keldysh Institute of Applied Mathematics Moscow Russia

The paper describes the issues of setting up an experiment, limitations, and features of the platform, primarily focusing on the influence of hardware and software versions of probes, network types, and cross-traffic. The impact of new versions of software and hardware requires analysis and con-sideration in further data work. Additionally, the nature of the global network is evolving over time due to technological ad-vancements. The outcome of this work includes recommendations for calibrating measurements and reducing systematic sampling errors.

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Improving DL-Learner on a Malware Detection Use Case 36

Improving DL-Learner on a Malware Detection Use Case

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36th International Workshop on Description Logics, DL 2023

作者： Bisták, Tomáš Švec, Peter Kluka, Ján Šimko, Alexander Balogh, Štefan Homola, Martin Department of Applied Informatics Faculty of Mathematics Physics and Informatics Comenius University Mlynská dolina Bratislava842 48 Slovakia Institute of Computer Science and Mathematics Faculty of Electrical Engineering and Information Technology Slovak University of Technology Ilkovicova 3 Bratislava812 19 Slovakia

Automation of malware characterization has become increasingly important for early malware detection over the past decades. Since it is crucial to be able to perform malware detection transparently, explainable machine-learning methods may be considered particularly suitable for this application. In our previous work, we thus employed algorithms for learning description-logics concept expressions to obtain structured characterizations of malicious software. The results of our initial experiments, however, lead us to several inconsistencies in the behaviour of the studied algorithms included in DL-Learner, a widely adopted framework for concept learning. Hence, in this work, we make a couple of corrections to DL-Learner, along with a few further enhancements, and repeat the experiments to empirically assess the effects of our changes. The outcomes show that the modified algorithms can mark an improvement in terms of the predictability of their behaviour as well as evaluation metrics. © 2023 CEUR-WS. All rights reserved.

关键词： Malware

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ACSLs for Large-Scale Bounded Single Depot Multiple Travelling Salesman Problem

ACSLs for Large-Scale Bounded Single Depot Multiple Travelli...

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Congress on Evolutionary Computation

作者： Shanu Verma Millie Pant Department of Applied Mathematics & Scientific Computing Indian Institute of Technology Roorkee Roorkee Uttarakhand India Department of Applied Mathematics & Scientific Computing Mehta Family School of Data Science & Artificial Intelligence Indian Institute of Technology Roorkee Roorkee Uttarakhand India

ISBN: (数字)9798350308365

ISBN: (纸本)9798350308372

Bounded single depot multiple travelling salesman problem (BSD-MTSP) optimizes salesmen tours with constraints on the number of cities visiting per salesman, which ensures balanced routes. BSD-MTSP presents challenges due to its combinatorial nature and additional complexities arising from multiple salesmen and depot-related constraints. Exact solutions for BSD-MTSP via classical methods are computationally expensive, prompting the use of heuristics and metaheuristics for practical solutions. This paper presents ACSLs, a hybrid algorithm combining initialization heuristic, Ant colony system, and Local search operators. ACSLs efficiently tackles large-scale BSD-MTSPs, demonstrating a superiority of up to 9.964% over the most advanced algorithms through comparative analysis.

关键词： Heuristic algorithms Urban areas Metaheuristics Evolutionary computation Benchmark testing Approximation algorithms Space exploration

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Composite metamorphic relations for integration testing 22

Composite metamorphic relations for integration testing

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8th International Conference on Computer Technology Applications, ICCTA 2022

作者： Iakusheva, Sofia Khritankov, Anton Phystech School of Applied Mathematics and Informatics Moscow Institute of Physics and Technology Russia Faculty of Computer Science Dept. of Software Engineering Hse University Russia

ISBN: (纸本)9781450396226

Metamorphic testing is a testing method for problems without test oracles. Integration testing allows for detecting errors in complex systems that may not be found during the testing of their components. In this paper, we propose a novel approach that applies metamorphic testing in integration testing. The main idea is to develop a composite metamorphic relation for the system represented as an acyclic graph. This relation is a logical function of metamorphic relations for the parts of the system (vertices of the graph). It takes into account the features of the parts. Also, it can simplify the search for failure by identifying the subsystem with error. In this paper's theoretical part, we describe an algorithm of relation design. Then, we apply our method to a bioinformatics system for comparative genetic analysis of tissues using production tools. This experiment proves our method can be applied to real-life pipelines and find errors in them. © 2022 ACM.

关键词： Integration testing

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LSTM new gate for computing the efficiency on inputdata

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Knowledge-Based Systems 2025年 322卷

作者： García Cabello, Julia Carbó-García, Santiago Department of Applied Mathematics Andalusian Research Institute in Data Science and Computational Intelligence University of Granada Granada Spain Department of Computer Science and Artificial Intelligence Andalusian Research Institute in Data Science and Computational Intelligence University of Granada Granada Spain

The recognized learning ability of neural networks (NNs) is determined by their training process. The NN data-dependent nature makes that their success depends to a large extent on the quality of the training data sets. This paper addresses the selection of the best training sets for Long Short Time Models (LSTMs) in real-life contexts. If such selection from a theoretical standpoint is already complex, it becomes challenging when addressed for real scenarios, where effectiveness should be replaced by efficiency (i.e., effectiveness in the shortest possible time and without increasing the computational cost). Our proposal revolves around the introduction, definition and structuring of a new LSTM gate: the efficiency gate, that applies to those inputs that have passed the forget gate. The efficiency gate is responsible for ensuring that training advances only with the best inputs in the sense that the corresponding outputs match as closely as possible with a target value (best estimators). For this purpose, new mathematical results will be demonstrated here in order to prove that our efficiency gate is mathematically feasible. We also fully describe how the new gate joins the LSTM operation, blending in with it. The consequence of such natural integration is that the computational effort is practically unchanged. Our methodology also allows the user to set the admissible error thresholds (which are different in each real scenario) as part of the setting options. © 2025 The Authors

关键词： Efficiency gate New LSTM gate Selection of training data sets Real-life contexts

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Day-Ahead Forecasting of Solar Irradiance & PV Power Output Through Statistical Machine Learning Methods

Day-Ahead Forecasting of Solar Irradiance & PV Power Output ...

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2022 Saudi Arabia Smart Grid Conference, SASG 2022

作者： Kamarianakis, Yiannis Pantazis, Yannis Kalligiannaki, Evangelia Katsaounis, Theodoros D. Kotsovos, Konstantinos Gereige, Issam Abdullah, Marwan Jamal, Aqil Tzavaras, Athanasios Foundation for Research and Technology-Hellas Institute of Applied and Computational Mathematics Data Science Group Greece University of Crete Dept. of Mathematics and Applied Mathematics Greece Saudi Aramco RandD Center Carbon Management Division Dhahran Saudi Arabia Computer Electrical and Mathematical Sciences and Engineering Division Thuwal Saudi Arabia

ISBN: (纸本)9781665475891

Energy production from solar photovoltaic (PV) plants is unpredictable, mainly due to the stochastic formation and movement of clouds or aerosol - dust particles which scatter or disperse solar radiation. Accurate forecasts of PV output are essential to Distribution and Transportation System Operators as they assist efficient solar energy trading and management of electricity grids. This work evaluates an autoregressive, computationally-light KNN-regression scheme (TSFKNN) for hourly, day-ahead forecasts of solar irradiance and energy yield of various PV technologies. The model is being tested and validated using data measured in Thuwal, Saudi Arabia. The available measured records span a 60-month period. The developed forecasting models are designed for online systems and provide increased levels of accuracy and low computational cost. Several parametric and nonparametric specifications, coupled with conventional versus outlier-robust estimation procedures are tested, in order to derive an optimal month-specific daily profile (MDP). Current results demonstrate that including intraday variability to the monthly-based irradiance models achieve improved predictive accuracy between 10% and 25% on average. © 2022 IEEE.

关键词： Forecasting

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Consensus-based Optimal Control Strategy for Multi-microgrid Systems with Battery Degradation Consideration

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CSEE Journal of Power and Energy Systems 2024年第5期10卷 1911-1924页

作者： Tonghe Wang Hong Liang Bo He Haochen Hua Yuchao Qin Junwei Cao Institute of Energy Conversion Chinese Academy of SciencesGuangzhou 510640China Meihua Holdings Group Co. Ltd.Langfang 065001China. Department of Astronautical Science and Technology Space Engineering UniversityBeijing 101416China College of Energy and Electrical Engineering Hohai UniversityNanjing211100China Department of Applied Mathematics and Theoretical Physics University of CambridgeCambridgeCB30WAUK. Beijing National Research Center for Information Science and Technology Tsinghua UniversityBeijing 100084China

Consensus has been widely used in distributed control,where distributed individuals need to share their states with their neighbors through communication links to achieve a common ***,the objectives of existing consensus-based control strategies for energy systems seldom address battery degradation cost,which is an important performance indicator to assess the performance and sustainability of battery energy storage(BES)*** this paper,we propose a consensusbased optimal control strategy for multi-microgrid systems,aiming at multiple control objectives including minimizing battery degradation *** consensus is used to synchronize the ratio of BES output power to BES state-of-charge(SoC)among all microgrids while each microgrid is trying to reach its individual *** order to reduce the pressure of communication links and prevent excessive exposure of local information,this ratio is the only state variable shared between *** our complex nonlinear problem might be difficult to solve by traditional methods,we design a compressive sensing-based gradient descent(CSGD)method to solve the control *** simulation results show that our control strategy results in a 74.24%reduction in battery degradation cost on average compared to the control method without considering battery *** addition,the compressive sensing method causes an 89.12%reduction in computation time cost compared to the traditional Monte Carlo(MC)method in solving the control problem.

关键词： Battery degradation compressive sensing consensus distributed control multi-microgrid

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Holes in Convex and Simple Drawings 32

Holes in Convex and Simple Drawings

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32nd International Symposium on Graph Drawing and Network Visualization, GD 2024

作者： Bergold, Helena Orthaber, Joachim Scheucher, Manfred Schröder, Felix Institute of Computer Science Freie Universität Berlin Germany TUM School of Computation Information and Technology Technische Universität München Germany Institute of Software Technology Graz University of Technology Austria Institut Für Mathematik Technische Universität Berlin Germany Department of Applied Mathematics Faculty of Mathematics and Physics Charles University Prague Czech Republic Institute of Mathematics Technische Universität Berlin Germany

ISBN: (纸本)9783959773430

Gons and holes in point sets have been extensively studied in the literature. For simple drawings of the complete graph a generalization of the Erdos-Szekeres theorem is known and empty triangles have been investigated. We introduce a notion of k-holes for simple drawings and study their existence with respect to the convexity hierarchy. We present a family of simple drawings without 4-holes and prove a generalization of Gerken's empty hexagon theorem for convex drawings. A crucial intermediate step will be the structural investigation of pseudolinear subdrawings in convex drawings. © Helena Bergold, Joachim Orthaber, Manfred Scheucher, and Felix Schröder.

关键词： Geometry

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Dispersive blow-up for solutions to three dimensional generalized Zakharov-Kuznetsov equations

arXiv

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arXiv 2024年

作者： Ban, Yingzhe Shan, Minjie Institute of Applied Physics and Computational Mathematics Beijing100088 China College of Science Minzu University of China Beijing100081 China

We illustrate the dispersive blow up phenomena of the solutions of three dimensional generalized Zakharov-Kuznetsov equations. In particular, we construct smooth initial data such that, the associated global solutions fail to be C1 at time t in a null set containing all rational numbers, but are C1 at all times t which are generic irrational numbers. The key ingredient are to construct linear solutions which exhibit such phenomena and to prove nonlinear smoothing estimates for the full nonlinear *** Codes 35Q53, 35B44 Copyright © 2024, The Authors. All rights reserved.

关键词： Sobolev spaces

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Delayed interactions in the noisy voter model through the periodic polling mechanism

arXiv

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arXiv 2024年

作者： Kononovicius, Aleksejus Astrauskas, Rokas Radavičius, Marijus Ivanauskas, Feliksas Institute of Theoretical Physics and Astronomy Vilnius University Lithuania Institute of Computer Science Vilnius University Lithuania Institute of Applied Mathematics Vilnius University Lithuania

We investigate the effects of delayed interactions on the stationary distribution of the noisy voter model. We assume that the delayed interactions occur through the periodic polling mechanism and replace the original instantaneous two-agent interactions. In our analysis, we require that the polling period aligns with the delay in announcing poll outcomes. As expected, when the polling period is relatively short, the model with delayed interactions is almost equivalent to the original model. As the polling period increases, oscillatory behavior emerges, but the model with delayed interactions still converges to stationary distribution. The stationary distribution resembles a Beta-binomial distribution, with its shape parameters scaling with the polling period. The observed scaling behavior is non-monotonic. Namely, the shape parameters peak at some intermediate polling period. Copyright © 2024, The Authors. All rights reserved.

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