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IEEE International Conference on Smart Energy Grid Engineering (SEGE)

作者： Mohsen Banaei Razgar Ebrahimy Henrik Madsen Department of Applied Mathematics and Computer Science Technical University of Denmark Lyngby Denmark

Demand-side flexibility as a new source of ancillary services is attracting growing attention. Aggregation and coordination mechanisms are needed to efficiently use the demand side flexibility. This paper proposes a new secure two-stage bottom-up coordination mechanism that ensures the quality of service (QoS) for customers and facilitates improved services for both distribution and transmission system operators. In the first stage of the proposed method, the interaction between aggregators and controllable loads is addressed. In the second stage, the interactions between the DSO and aggregators are addressed. Commitments of the aggregators to follow their scheduled power in the electricity market are also taken into account in the proposed framework. The proposed method is applied to a test system with two areas supplied by two transformers with some uncontrollable loads, 70 PV/battery setups, and 80 heating systems supplied by heat pumps (HP) that are in contract with two aggregators. Simulation results highlight the effectiveness of the proposed method in preventing transformers’ overload and reducing their loading by up to 27% while increasing the total electricity cost of customers with controllable devices by about 4.6%.

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From Obstacle Problems to Neural Insights: Feed Forward Neural Network Modeling of Ice Thickness

arXiv

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arXiv 2024年

作者： Chawla, Kapil Holmes, William Temam, Roger Department of Mathematics The Institute for Scientific Computing and Applied Mathematics Indiana University IN47405 United States Department of Mathematics and Cognitive Science Program Indiana University IN47405 United States

In this study, we integrate the established obstacle problem formulation from ice sheet modeling [12, 20] with cutting-edge deep learning methodologies to enhance ice thickness predictions, specifically targeting the Greenland ice sheet. By harmonizing the mathematical structure with an energy minimization framework tailored for neural network approximations, our method’s efficacy is confirmed through both 1D and 2D numerical simulations. Utilizing the NSIDC-0092 dataset for Greenland [1] and incorporating bedrock topography for model pre-training, we register notable advances in prediction accuracy. Our research underscores the potent combination of traditional mathematical models and advanced computational techniques in delivering precise ice thickness estimations. © 2024, CC BY.

关键词： Ice

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Digital-Twin Enabled Time Ahead Resource Allocation for Integrated Fiber-Wireless Connected Vehicular Network

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Journal of Communications and Information Networks 2024年第3期9卷 296-308页

作者： Akshita Gupta Saurabh Jaiswal Martin Maier Vivek Ashok Bohara Anand Srivastava Wirocomm Research Group Department of Electronics&Communication EngineeringIndraprastha Institute of Information Technology Delhi(IIITD)New Delhi 110020India Department of Computer Science&Applied Mathematics Indraprastha Institute of Information Technology Delhi(IIITD)New Delhi 110020India Optical Zeitgeist Laboratory Institute National de la Recherche ScientifiqueMontreal H5A 1K6Canada

The digital twin(DT)is envisaged as a catalyst for pioneering ecosystems of service provision within an immersive environment born from the convergence of virtual and physical ***,DT could enhance the performance of edge-intelligent connected vehicular networks by allocating network resources efficiently based on the key performance indicators(KPIs)of vehicular data ***,this work addresses the key challenge of computation and spectrum resource allocation for vehicular *** allocate the optimal resource allocation,we subdivided the problem into:traffic classification,collective learning,and resource allocation *** order to do so,this paper concentrates on two crucial vehicular applications:brake application and lane-change *** utilize a random forest model to collectively learn vehicular data traffic in the upcoming time ***,a time-ahead resource allocation algorithm is proposed to improve the quality of service(QoS)by intelligently offloading vehicular data traffic to a DT-based integrated fiber-wireless(Fi-Wi)connected vehicular *** evaluate the performance of the resource allocation strategy in terms of resources required by the network alongside the packet loss *** was observed that there was a 44.74%increase in cost as the total computation resources increased from F=50 to 100 GHz,whereas the PLR of the network decreased by 71.43%.

关键词： connected vehicles digital twin edgeintelligence fiber-wireless machine learning resource allocation

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Modeling, scientific computing and optimal control for renewable energy systems with storage

Modeling, scientific computing and optimal control for renew...

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European Control Conference (ECC)

作者： Nicola Cantisani Tobias K. S. Ritschel Christian A. Thilker Henrik Madsen John Bagterp Jørgensen Department of Applied Mathematics and Computer Science Technical University of Denmark Lyngby Denmark

This paper presents models for renewable energy systems with storage, and considers its optimal operation. We model and simulate wind and solar power production using stochastic differential equations as well as storage of the produced power using batteries, thermal storage, and water electrolysis. We formulate an economic optimal control problem, with the scope of controlling the system in the most efficient way, while satisfying the power demand from the electric grid. Deploying multiple storage systems allows flexibility and higher reliability of the renewable energy system.

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An Almost Singularly Optimal Asynchronous Distributed MST Algorithm 36

An Almost Singularly Optimal Asynchronous Distributed MST Al...

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36th International Symposium on Distributed Computing, DISC 2022

作者： Dufoulon, Fabien Kutten, Shay Moses, William K. Pandurangan, Gopal Peleg, David Department of Computer Science University of Houston HoustonTX United States Faculty of Industrial Engineering and Management Technion - Israel Institute of Technology Haifa Israel Department of Computer Science and Applied Mathematics Weizmann Institute of Science Rehovot Israel

ISBN: (纸本)9783959772556

A singularly (near) optimal distributed algorithm is one that is (near) optimal in two criteria, namely, its time and message complexities. For synchronous CONGEST networks, such algorithms are known for fundamental distributed computing problems such as leader election [Kutten et al., JACM 2015] and Minimum Spanning Tree (MST) construction [Pandurangan et al., STOC 2017, Elkin, PODC 2017]. However, it is open whether a singularly (near) optimal bound can be obtained for the MST construction problem in general asynchronous CONGEST networks. In this paper, we present a randomized distributed MST algorithm that, with high probability, computes an MST in asynchronous CONGEST networks and takes Õ(D1+Ε + √n) time and Õ(m) messages1, where n is the number of nodes, m the number of edges, D is the diameter of the network, and Ε > 0 is an arbitrarily small constant (both time and message bounds hold with high probability). Since (Equation presented)(D + √n) and Ω(m) are respective time and message lower bounds for distributed MST construction in the standard KT0 model, our algorithm is message optimal (up to a polylog(n) factor) and almost time optimal (except for a DΕ factor). Our result answers an open question raised in Mashregi and King [DISC 2019] by giving the first known asynchronous MST algorithm that has sublinear time (for all D = O(n1-Ε)) and uses Õ(m) messages. Using a result of Mashregi and King [DISC 2019], this also yields the first asynchronous MST algorithm that is sublinear in both time and messages in the KT1 CONGEST model. A key tool in our algorithm is the construction of a low diameter rooted spanning tree in asynchronous CONGEST that has depth Õ(D1+Ε) (for an arbitrarily small constant Ε > 0) in Õ(D1+Ε) time and Õ(m) messages. To the best of our knowledge, this is the first such construction that is almost singularly optimal in the asynchronous setting. This tree construction may be of independent interest as it can also be used for efficiently perfor

关键词： Distributed computer systems

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Direct System Identification of Dynamical Networks with Partial Measurements: A Maximum Likelihood Approach

Direct System Identification of Dynamical Networks with Part...

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European Control Conference (ECC)

作者： João Victor Galvão Da Mata Anders Hansson Martin S. Andersen Department of Applied Mathematics and Computer Science Technical University of Denmark Department of Electrical Engineering Linköping University.

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

This paper introduces a novel direct approach to system identification of dynamic networks with missing data based on maximum likelihood estimation. Dynamic networks generally present a singular probability density function, which poses a challenge in the estimation of their parameters. By leveraging knowledge about the network's interconnections, we show that it is possible to transform the problem into a more tractable form by applying linear transformations. This results in a nonsingular probability density function, enabling the application of maximum likelihood estimation techniques. Our preliminary numerical results suggest that when combined with global optimization algorithms or a suitable initialization strategy, we are able to obtain a good estimate of the dynamics of the internal systems.

关键词： Maximum likelihood estimation Sensitivity Heuristic algorithms Transfer functions Optimization methods Transforms Probability density function

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A Data Security Technique Combining Asymmetric Cryptography and Compressive Sensing for IoT Enabled Wireless Sensor Networks 22nd

A Data Security Technique Combining Asymmetric Cryptography ...

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22nd International Conference on Next Generation Teletraffic and Wired/Wireless Advanced Networks and Systems, NEW2AN 2022

作者： Aziz, Ahmed Khedr, Ahmed M. Salim, Ahmed Osamy, Walid Computer Science Department Faculty of Computers and Artificial Intelligence Benha University Benha Egypt Mathematics Department Zagazig University Zagazig Egypt Computer Science Department University of Sharjah Sharjah27272 United Arab Emirates Department of Computer Science College of Sciences and Arts Al-methnab Qassim University Buraydah Saudi Arabia Department of Applied Science College of Community in Unaizah Qassim University Buraydah Saudi Arabia Tashkent State University of Economics Tashkent Uzbekistan

ISBN: (纸本)9783031302572

Reducing the amount of data transmitted and protecting devices from the adversary environment are the major challenges faced in the development of the Internet of Things (IoT) network. Compressive sensing (CS) offers the major advantage of performing lightweight encryption and compression at the same time, making it energy efficient. Like any private key algorithm, the CS encryption method has problems with key distribution and management. Public key algorithms, on the other hand, do not have these problems and provide a high level of security. However, public key algorithms increase the cost of communication that leads to a decrease in network lifetime. In this paper, we propose an efficient technique that achieves a high level of security with minimum energy consumption. The proposed technique utilizes the advantage of public-key algorithms to provide a high level of security and reduces communication costs by using the CS method. The simulation results indicate that the proposed security approach is effective in achieving better performance in security with minimal communication cost, along with prolonging network lifetime. In addition, the proposed technique makes it possible to use public-key algorithms for securing the IoT network efficiently. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Wireless sensor networks

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GeoBeeDashboard: An Intelligent Geospatial Platform for Enhancing Waste Management in Tangerang City

GeoBeeDashboard: An Intelligent Geospatial Platform for Enha...

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IEEE International Conference on Communication, Networks and Satellite (ComNetSat)

作者： Richie Muljana Syauqi Akmal Deffansyah Hari Andrew Alexander Agung Santoso Gunawan Edy Irwansyah Fabian Surya Pramudya Muhamad Keenan Ario Muhammad Edo Syahputra Said Achmad Computer Science Department Data Science Program School of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Mathematics Department School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350368086

ISBN: (纸本)9798350368093

In this study, we created an Intelligent Geospatial Platform called GeoBeeDashboard. The GeoBeeDashboard combines advanced geospatial technologies and artificial intelligence (AI), allowing real-time data visualization and optimized decision-making across multiple sectors. The system architecture consists of a ***-based front end, a FastAPI-driven back end, and PostGIS for geospatial data management. One of the GeoBeeDashboard’s primary use cases is addressing waste management issues in Tangerang City, Indonesia. As rapid urbanization increases waste generation, effective management becomes critical. The dashboard identifies critical trends and inefficiencies in Tangerang’s districts by K-Means clustering waste management data from 2020 to 2023. Our findings identify distinct clusters, highlighting areas with effective waste management and those that require targeted interventions. The benefits that local government can get from GeoBeeDashboard by utilising insights based on clustering analysis of data per each district in Tangerang to optimise waste collection, allocate resources efficiently, and improve the policy-making process for each district in Tangerang. The GeoBeeDashboard improves local government capabilities by providing a scalable model for other cities facing similar urban challenges. In conclusion, GeoBeeDashboard provides local governments with a powerful tool for addressing waste management inefficiencies and fostering sustainable urban development.

关键词： Waste management Satellites Local government Urban areas Data visualization Systems architecture Production Real-time systems Geospatial analysis Artificial intelligence

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WAVELET COMPRESSED, MODIFIED HILBERT TRANSFORM IN THE SPACE-TIME DISCRETIZATION OF THE HEAT EQUATION

arXiv

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arXiv 2024年

作者： Harbrecht, Helmut Schwab, Christoph Zank, Marco Department of Mathematics and Computer Science University of Basel Basel Switzerland Seminar for Applied Mathematics ETH Zürich Zürich Switzerland Institute of Applied Mathematics TU Graz Graz Austria

On a finite time interval (0,T), we consider the multiresolution Galerkin discretization of a modified Hilbert transform HT which arises in the space-time Galerkin discretization of the linear diffusion equation. To this end, we design spline-wavelet systems in (0, T) consisting of piecewise polynomials of degree ≥ 1 with sufficiently many vanishing moments which constitute Riesz bases in the Sobolev spaces (formula presented) and (formula presented). These bases provide multilevel splittings of the temporal discretization spaces into "increment" or "detail" spaces of direct sum type. Via algebraic tensor-products of these temporal multilevel discretizations with standard, hierarchic finite element spaces in the spatial domain (with standard Lagrangian FE bases), sparse space-time tensor-product spaces are obtained, which afford a substantial reduction in the number of the degrees of freedom as compared to time-marching discretizations. In addition, temporal spline-wavelet bases allow to compress certain nonlocal integrodifferential operators which appear in stable space-time variational formulations of initial-boundary value problems, such as the heat equation and the acoustic wave equation. An efficient preconditioner is proposed that affords linear complexity solves of the linear system of equations which results from the sparse space-time Galerkin *** Codes 65N30, 65J15 Copyright © 2024, The Authors. All rights reserved.

关键词： Sobolev spaces

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Threat Hunting Using Elastic Stack: An Evaluation 15

Threat Hunting Using Elastic Stack: An Evaluation

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15th IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2021

作者： Subramanian, Kiruthiga Meng, Weizhi Technical University of Denmark Department of Applied Mathematics and Computer Science Denmark

ISBN: (纸本)9781665467223

Information Technology (IT) is now widely adopted in current business and organizations, which refers to the usage of any computers, networking and physical devices to help create, exchange and handle electronic data. While cyber-attacks are one major threat to IT based systems and networks. A successful attack can cause a major business loss, thus every organisation has their own information security measures. Among them, logging and monitoring is one important security measure to prevent an organization from threats. In particular, threat hunting is a significant approach to identify intruders. In this paper, our purpose is to study how well the Elastic stack tool can be used in threat hunting and compare it with four similar tools. It is found that Elastic Stack tool can be effective in detecting the threats/security events as well as cost-efficient while implementing on a large-scale environment. © 2021 IEEE.

关键词： Cybersecurity

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