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Modelling and Simulation of Lily flowers using PDE Surfaces

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Modelling and Simulation of Lily flowers using PDE Surfaces

International Conference on Software, Knowledge Information, Industrial Management and Applications (SKIMA)

作者： Ehtzaz Chaudhry Jian Chang Hassan Ugail Alexander Malyshev Alfonso Carriazo Andres Iglesias Zulfiqar Habib Allah Bux Sargano Habibollah Haron Algirdas Noreika Lihua You Jian Jun Zhang NCCA Bournemouth University Poole UK Center for Visual Computing University of Bradford Bradford UK Department of Mathematics University of Bergen Bergen Norway Faculty of Mathematics University of Seville Sevilla Spain Department of Applied Mathematics and Computational Sciences University of Cantabria Spain Department of Computer Science COMSATS University Islamabad Lahore Pakistan Faculty of Computing Universiti Teknologi Malaysia Johor Bahru Malaysia Indeform Ltd Kaunas Lithuania

This paper presents a partial differential equation (PDE)-based surface modelling and simulation framework for lily flowers. We use a PDE-based surface modelling technique to represent shape of a lily flower and PDE-based dynamic simulation to animate blossom and decay processes of lily flowers. To this aim, we first automatically construct the geometry of lily flowers from photos to obtain feature curves. Second, we apply a PDE-based surface modelling technique to generate sweeping surfaces to obtain geometric models of the flowers. Then, we use a physics-driven and data-based method and introduce the flower shapes at the initial and final positions into our proposed dynamic deformation model to generate a realistic deformation of flower blossom and decay. The results demonstrate that our proposed technique can create realistic flower models and their movements and shape changes against time efficiently with a small data size.

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Optimal planning of slow-ramping power production in energy systems with renewables forecasts and limited storage

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Optimal planning of slow-ramping power production in energy ...

International Conference on Probabilistic Methods applied to Power Systems (PMAPS)

作者： Nathaniel Richmond Peter Jacko Armand M. Makowski BCAM — Basque Center for Applied Mathematics Bilbao Basque Country Spain Applied Mathematical & Computational Sciences University of Iowa USA Lancaster University Management School Lancaster UK Department of Electrical & Computer Engineering University of Maryland College Park USA

We address the cost-efficient operation of an energy production system under renewables uncertainty. We develop an MDP model for an idealized system with the following features: (1) perfectly predictable power demand, (2) a renewable power source subject to uncertain forecast, (3) limited energy storage, (4) an unlimited fast-ramping power source, and (5) a slow-ramping power source which requires (optimal) planning. A finite-horizon stochastic optimization problem is introduced to minimize the overall cost of operating the system, and then solved numerically using standard approaches (based on backward induction) and available data. In contrast with the unit commitment problem which is traditionally optimized for a single planning frame, we show in simple scenarios that it may be beneficial to optimize over a few planning frames, and that there is no benefit to considering longer (e.g., infinite) horizons. We discretize the state space in an attempt to mitigate the curse of dimensionality usually associated with numerically solving MDPs. We note that few discretization states already yield a significant decrease in the total cost.

关键词： Production Planning Wind forecasting computational modeling Energy storage Wind power generation

Optimal Algorithms for Differentially Private Stochastic Monotone Variational Inequalities and Saddle-Point Problems

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arXiv 2021年

作者： Boob, Digvijay Guzmán, Cristóbal Engineering Management Information and Systems Southern Methodist University United States Department of Applied Mathematics University of Twente Institute for Mathematical and Computational Eng. Pontificia Universidad Católica de Chile Netherlands

In this work, we conduct the first systematic study of stochastic variational inequality (SVI) and stochastic saddle point (SSP) problems under the constraint of differential privacy (DP). We propose two algorithms: Noisy Stochastic Extragradient (NSEG) and Noisy Inexact Stochastic Proximal Point (NISPP). We show that a stochastic approximation variant of these algorithms attains risk bounds vanishing as a function of the dataset size, with respect to the strong gap function;and a sampling with replacement variant achieves optimal risk bounds with respect to a weak gap function. We also show lower bounds of the same order on weak gap function. Hence, our algorithms are optimal. Key to our analysis is the investigation of algorithmic stability bounds, both of which are new even in the nonprivate case. The dependence of the running time of the sampling with replacement algorithms, with respect to the dataset size n, is n2 for NSEG and (Equation presented) for *** Codes 65K10, 49M37, 68T09 © 2021, CC BY.

关键词： Stochastic systems

A Dynamic Pyramidal Relaxation Method of AC OPF

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A Dynamic Pyramidal Relaxation Method of AC OPF

Power and Electrical Engineering (ACPEE), 5th Asia Conference on

作者： Yu-Yang Tang Liang Chen Hongbo Du Sheng-Jie Chen Caixia Kou Xiaomeng Ai Bo Zhou Academy of Mathematics and Systems Science Chinese Academy of Sciences Institute of Computational Mathematics and Scientific/Engineering Computing Beijing China College of Sciences Beijing University of Posts and Telecommunications Beijing China Academy of Mathematics and Systems Science Chinese Academy of Sciences Institute of Applied Mathematics Beijing China School of Electrical and Electronic Engineering Huazhong University of Science and Technology Wuhan China Department of Industrial and Operations Engineering University of Michigan Ann Arbor United States

ISBN: (数字)9798350309638

ISBN: (纸本)9798350309645

The Alternating Current Optimal Power Flow (AC OPF) is crucial for power system analysis, yet existing algorithms face challenges in meeting the diverse requirements of practical applications. This paper presents a Pyramidal Relaxation (PR) formulation of the Branch Flow Model (BFM) for AC OPF, where surface conical constraints are approximated through a union of tetrahedrons in a Mixed Integer Linear programming (MILP) relaxation. To reduce problem size and to enhance computational efficiency, we proposed a Dynamic Pyramidal Relaxation (DPR) method, where the cuts (inner approximation and outer approximation) are adaptively added. In practice, the DPR method is embedded into a MILP commercial solver based on the branch-and-cut framework. Case studies in different test systems validate the effectiveness in terms of feasibility, accuracy, and efficiency of our proposed method.

关键词： Electrical engineering computational modeling Power system dynamics Asia Linear approximation Relaxation methods Mixed integer linear programming

An enhanced SDR based global algorithm for nonconvex complex quadratic programs with signal processing applications

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arXiv 2019年

作者： Lu, Cheng Liu, Ya-Feng Zhou, Jing School of Economics and Management North China Electric Power University Beijing102206 China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Department of Applied Mathematics College of Science Zhejiang University of Technology Hangzhou310023 China

In this paper, we consider a class of nonconvex complex quadratic programming (CQP) problems, which find a broad spectrum of signal processing applications. By using the polar coordinate representations of the complex variables, we first derive a new enhanced semidefinite relaxation (SDR) for problem (CQP). Based on the newly derived SDR, we further propose an efficient branch-and-bound algorithm for solving problem (CQP). Key features of our proposed algorithm are: (1) it is guaranteed to find the global solution of the problem (within any given error tolerance);(2) it is computationally efficient because it carefully utilizes the special structure of the problem. We apply our proposed algorithm to solve the multiinput multi-output (MIMO) detection problem, the unimodular radar code design problem, and the virtual beamforming design problem. Simulation results show that our proposed enhanced SDR, when applied to the above problems, is generally much tighter than the conventional SDR and our proposed global algorithm can efficiently solve these problems. In particular, our proposed algorithm significantly outperforms the state-of-the-art sphere decode algorithm for solving the MIMO detection problem in the hard cases (where the number of inputs and outputs is equal or the SNR is low) and a state-of-the-art general-purpose global optimization solver called Baron for solving the virtual beamforming design problem. Copyright © 2019, The Authors. All rights reserved.

关键词： Beamforming

High-Rate Phase Association with Travel Time Neural Fields

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arXiv 2023年

作者： Shi, Cheng Poggiali, Giulio Marone, Chris de Hoop, Maarten V. Dokmanić, Ivan Departement of Mathematics and Computer Science University of Basel Switzerland Department of Earth Sciences La Sapienza Università di Roma Italy Simons Chair in Computational and Applied Mathematics and Earth Science Rice University United States Department of ECE University of Illinois at Urbana–Champaign United States Department of Geosciences Pennsylvania State University United States

Earthquake science and seismology rely on the ability to associate seismic waves with their originating earthquakes. Earthquake detection algorithms based on deep learning have progressed rapidly and now routinely detect microearthquakes with unprecedented clarity, providing information about fault dynamics on increasingly finer spatiotemporal scales. However, this densification of detections can overwhelm existing techniques for phase association which rely on fixed wave speed models and associate events one by one. These methods fail when the event rates become high or where the 4D complexity of elastic wave speeds cannot be ignored. Here, we introduce Harpa, a deep learning solution to this problem. Harpa is a high-rate association framework which incorporates wave physics by leveraging deep generative models and travel time neural fields. Instead of associating events one by one, it lifts arrival sequences to probability distributions and compares them using an optimal transport metric. The generative travel time neural fields are used to estimate the wave speed simultaneously with association. Harpa outperforms state-of-the-art association methods for both real seismic data and complex synthetic models and paves the way for improved understanding of seismicity while establishing a new seismic data analysis paradigm. Copyright © 2023, The Authors. All rights reserved.

关键词： Travel time

A Visual Attention-Based Model for Bengali Image Captioning

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SN Computer Science 2023年第2期4卷 208页

作者： Das, Bidyut Pal, Ratnabali Majumder, Mukta Phadikar, Santanu Sekh, Arif Ahmed Department of Information Technology Haldia Institute of Technology West Bengal Haldia 721657 India Department of Applied Mathematics NIT Durgapur West Bengal Durgapur 713213 India Department of Computational Science Brainware University West Bengal Kolkata 700125 India Department of Computer Science and Technology University of North Bengal West Bengal Siliguri 734014 India Department of Computer Science and Engineering Maulana Abul Kalam Azad University of Technology W.B. West Bengal Haringhata 741249 India School of Computer Science and Engineering XIM University Odisha Bhubaneswar 752050 India

Image caption or description generation is a fundamental task that involves computer vision (CV) and natural language processing (NLP) ideas to recognize an image-context and produces description(s) using a natural language. Bengali is one of the world’s most commonly spoken languages, ranking fifth. For this reason, large research achievements have been recognized to image captioning, i.e. explaining images with grammatically correct and semantically meaningful Bengali sentences. Many established datasets exist for image caption generation in English, but no standard dataset is available for Bengali. This paper proposes a model for generating automatic image captions in the Bengali language. This study uses only two initial available Bengali datasets to train the encoder-decoder neural network model. We have curated the human errors available in the datasets and benchmarked. Experimental results of this proposed model performs better than other baseline models using these datasets. It achieved 0.67 and 0.65 BLEU-1, and 0.26 and 0.24 BLEU-4 respectively. We expect that our research will take attentions to more researchers from regional language understanding and accelerate Bengali vision-language understanding. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Attention mechanism Bengali image caption Bengali NLP Deep learning Image description

HOMOGENIZATION OF HIGH-CONTRAST DIELECTRIC ELASTOMER COMPOSITES

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arXiv 2024年

作者： Dang, Thuyen Gorb, Yuliya Bolaños, Silvia Jiménez Department of Statistics/Committee on Computational and Applied Mathematics University of Chicago 5747 S. Ellis Avenue ChicagoIL60637 United States National Science Foundation 2415 Eisenhower Avenue AlexandriaVA22314 United States Department of Mathematics Colgate University 13 Oak Drive HamiltonNY13346 United States

This paper focuses on the homogenization of high-contrast dielectric elastomer composites, which are materials that deform in response to electrical stimulation. The considered heterogeneous material, consisting of an ambient material with inserted particles, is described by a weakly coupled system of an electrostatic equation with an elastic equation enriched with electrostriction. It is assumed that particles gradually become rigid as the fine-scale parameter approaches zero. This study demonstrates that the effective response of this system entails a homogeneous dielectric elastomer, described by a system of PDEs whose equations are fully decoupled. The coefficients of the homogenized equations depend on various factors, including the geometry of the composite, the periodicity of the original microstructure, and the coefficients characterizing the initial heterogeneous material. In particular, these coefficients are significantly influenced by the high-contrast nature of the coefficients of the fine-scale *** Codes 35B27, 35J47, 74A40, 74F15 © 2024, CC BY.

关键词： Electrostriction

The effect of synaptic plasticity on the stability of place fields under graded environmental perturbations

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BMC Neuroscience 2010年第1期11卷 1-2页

作者： Kathryn Ward Steve Cox Anthony Kellems Horatiu Voitu James Knierim Department of Computational and Applied Mathematics Rice University Houston TX 77005 USA Department of Neurobiology and Anatomy University of Texas Medical School at Houston Houston TX 77030 USA Department of Neuroscience and Krieger Mind/Brain Institute Johns Hopkins University Baltimore MD 21218 USA