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检索条件"任意字段=Conference on Multiscale Optimization Methods and Applications"

共 64 条记录，以下是1-10 订阅

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Nonlinear Schwarz Preconditioning for Nonlinear optimization Problems with Bound Constraints 27th

Nonlinear Schwarz Preconditioning for Nonlinear Optimization...

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27th International conference on Domain Decomposition methods in Science and Engineering, DD 2022

作者： Kothari, Hardik Kopanicáková, Alena Krause, Rolf Università della Svizzera italiana Lugano Switzerland Brown University Providence United States

ISBN: (纸本)9783031507687

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multiscale Structure Prompted Diffusion Models for Scene Text Image Super-Resolution 19

Multiscale Structure Prompted Diffusion Models for Scene Tex...

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19th ACM SIGGRAPH International conference on Virtual-Reality Continuum and its applications in Industry, VRCAI 2024

作者： Xie, Huilong Fan Fan, Wanshu Zhou, Dongsheng Dalian University Dalian China School of Software Engineering Dalian University Dalian China

ISBN: (纸本)9798400713484

Scene Text Image Super-Resolution (STISR), which aims to enhance the resolution and legibility of text in low-resolution images, is crucial for accurate text recognition in real-world scenarios, especially in virtual reality (VR) environments where clarity is essential for immersive experiences. However, existing STISR methods often fall short of capturing detailed structural information, limiting the quality of reconstructed images. While diffusion models offer robust generative abilities, they can still result in structural inconsistencies, particularly when handling highly blurred or distorted text. To address these challenges, we introduce MSPDiff, a multiscale Structure Prompted Diffusion Model designed specifically for STISR. MSPDiff integrates two main components: the multiscale Structure Generation Model (MSGM) and the Prompted Diffusion Model (PDM). The MSGM captures multiscale structural features from text data, generating structural priors that guide the PDM. In this setup, the PDM leverages both the low-resolution images and the multiscale structures from the MSGM to enhance text clarity. Training both components simultaneously presents optimization challenges, as the MSGM is constrained by text data limitations while the PDM is optimized using noise. To address this, we implement a two-stage training approach: the MSGM is trained initially, after which the PDM is trained with the MSGM frozen. Experiments on the widely-used TextZoom benchmark demonstrate that MSPDiff outperforms state-of-the-art methods in both text recognition accuracy and image quality, establishing it as a promising approach for enhancing text clarity in virtual reality applications. © 2024 ACM.

关键词： Virtual reality

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Evaluation of Heuristic optimization Algorithms for Model Predictive Ventilation Control and Reducing Energy Consumption 9th

Evaluation of Heuristic Optimization Algorithms for Model Pr...

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9th International Building Physics conference

作者： Bielenda, Ryan Tariku, Fitsum BCIT Bldg Sci Ctr Excellence Burnaby BC V5G 3H2 Canada Now Stantec Morrison Hershfield Burnaby BC V5C 6S7 Canada

ISBN: (纸本)9789819783199;9789819783175;9789819783168

Research shows that heuristic optimization algorithms can find solutions for complex problems in the physical world. Pairing these algorithms with machine learning models for predictive building control applications has been widely explored. This study investigates the efficacy of determining optimal ventilation rates using a particle swarm optimization (PSO) algorithm, a genetic algorithm (GA), and a hybridized genetic particle swarm optimization (GPSO) algorithm developed using MATLAB within an EnergyPlus building energy simulation model. Weather data from Vancouver is used to exemplify a marine climate, where free-cooling opportunities are relatively abundant. The algorithm performance results are collected for both the heating and cooling seasons and are compared against each other for run times, energy savings, and indoor air quality performance. The results are compared against simulation results using a conventional demand control ventilation (DCV) system. Results indicate that when compared to the DCV controller with an economizer mode, heuristic optimization control methods are capable of reducing HVAC energy consumption during a cooling season with free-cooling opportunities by up to 14.1%. Additionally, all three optimization algorithms are capable of minimizing HVAC energy consumption with zero unmet hours for the indoor carbon dioxide concentration setpoint.

关键词： Particle Swarm optimization Genetic Algorithm Predictive Control Ventilation Rates Free-Cooling Artificial Neural Networks Marine Climate Energy Efficiency Indoor Air Quality

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A NOVEL CONNECTIVITY INDEX FOR MICROSTRUCTURES IMPERFECTION DETECTION AND RECTIFICATION IN multiscale STRUCTURE DESIGN

A NOVEL CONNECTIVITY INDEX FOR MICROSTRUCTURES IMPERFECTION ...

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ASME 2024 International Design Engineering Technical conferences and Computers and Information in Engineering conference, IDETC-CIE 2024

作者： Rastegarzadeh, Sina Huang, Jida Department of Mechanical and Industrial Engineering University of Illinois Chicago ChicagoIL60607 United States

ISBN: (纸本)9780791888346

Inspired by natural designs, microstructures exhibit remarkable properties, which drive interest in creating metamaterials with extraordinary traits. However, imperfections within microstructures and poor connectivity at the microscale level can significantly impact their performance and reliability. Achieving proper connectivity between microstructural elements and detecting structural imperfections within the microstructures pose challenges in multiscale design optimization. While using a connectivity index (CI) to quantify the topological connectivity between microstructures has been explored previously, prior approaches have limitations in identifying microstructures with complex curved geometries between adjacent units. To alleviate this issue, we present a novel CI in this study. The proposed CI goes beyond conventional methods by focusing on surface interfaces and internal microstructural irregularities. Through numerical investigations, we successfully connected distinct types of microstructures well by integrating the introduced CI with the functional-gradation scheme. We also demonstrate that the presented CI can serve as a metric to identify sharp changes or imperfections within microstructures. We evaluate the performance of the introduced index against other connectivity indices using diverse microstructural examples. Experimental findings provide valuable insights into the fundamental aspects of imperfection detection and rectification in microstructures within the multiscale design, paving the way for developing more robust and reliable materials in engineering applications. © 2024 by ASME.

关键词： Electric rectifiers

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SVR-AVT: Scale Variation Robust Active Visual Tracking

SVR-AVT: Scale Variation Robust Active Visual Tracking

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International Joint conference on Neural Networks (IJCNN)

作者： Zhang, Biao Jin, Songchang Ouyang, Qianying Yang, Huanhuan Zheng, Yuxi Fu, Chunlian Shi, Dianxi Natl Univ Def Technol Coll Comp Changsha Peoples R China Intelligent Game & Decis Lab Beijing Peoples R China Tianjin Artificial Intelligence Innovat Ctr Tianjin Peoples R China

ISBN: (纸本)9798350359329;9798350359312

Active Visual Tracking (AVT) is a significant research area with extensive applications in fields such as drones and autonomous driving. AVT involves controlling camera motion based on visual observations to track target object(s). In dynamic environments, especially with the presence of distractors, AVT faces the challenge of scale variation. Existing methods struggle to effectively handle these scale changes. To address this problem, this paper proposes a novel Scale Variation Robust Active Visual Tracking method (SVR-AVT). We first introduce a multiscale multi-stage curriculum learning approach. By progressively increasing the complexity of tracking tasks, the tracker adapts to target of various scales. Secondly, we design a scale attention network, which adaptively extracts important scale features through multiple convolutional branches with different receptive fields and a scale attention mechanism. Moreover, we employ maximum position entropy learning to encourage the target to explore the environment more extensively. Experimental results in 3D environments demonstrate that SVR-AVT significantly outperforms existing methods in handling distraction and scale variation, and exhibits strong generalization capability in unseen environments.

关键词： active visual tracking reinforcement learning scale attention entropy based policy optimization

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Lightweight Human Motion Recognition Method with multiscale Temporal Features 5

Lightweight Human Motion Recognition Method with Multiscale ...

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2023 5th International conference on Artificial Intelligence Technologies and applications, ICAITA 2023

作者： Liu, Ying Luan, Tian School of Electronic and Information Engineering Liaoning Technical University Huludao China

To address the problems of the large size of human motion recognition models based on deep learning and insufficient mining of data features and thus low recognition accuracy, a lightweight human motion recognition algorithm based on multi-scale temporal features is proposed, the algorithm automatically extracted features through a multiscale feature fusion model. After, the integrated features are modeled by an improved time convolution network (TCN). In the TCN network structure, In the TCN network structure, the depthwise separable convolution is used instead of the normal convolutional layer to reduce the computational complexity, and the Leaky ReLU activation function is used instead of the ReLU function to improve the training efficiency. The experiments are based on the WISDM public dataset. finally achieve fast real-time recognition of actions, and structural and parametric optimization is performed through experiments to effectively improve the accuracy of results, and the final accuracy rate reaches 99.06%. In comparison with other methods, this method can reduce the model volume while maintaining a high accuracy rate. © Published under licence by IOP Publishing Ltd.

关键词： Convolution

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Accelerating NZEB Design optimization Through LLM-Based Standardization and Compliance Checking 9th

Accelerating NZEB Design Optimization Through LLM-Based Stan...

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9th International Building Physics conference

作者： Guo, Hongshan Coleman, James Gullapalli, Ishawn Univ Hong Kong Hong Kong Peoples R China Princeton Univ Princeton NJ USA

ISBN: (纸本)9789819783113;9789819783090;9789819783083

For building practitioners, staying current with guidelines and regulations has always been crucial. Traditional methods relies predominantly on researchers reviewing and comparing international building standards and is known to be time consuming. Leveraging recent advancements in large language models (LLMs), which have enabled more efficient information retrieval/comparison techniques on various tasks, we propose a novel framework in this paper that extracts, compares and varies design briefs/inputs for NZEB designs, in particular when new guidelines and requirements arise from new international building codes/requirements. To extract requirements from building codes and standards, we rely on unsupervised Named Entity Recognition (NER) techniques. However, the state-of-the-art approach in extracting relationships established in papers can be challenging, especially before the emergence of more generalized LLMs. To address this challenge, we use kor, a tool that enables the definition of various free text and/or numbered extraction based on description and definition, and few examples that the model can learn from. The instruction is passed as a JSON object to the LLM, which analyzes specific traits from the model following a tailored recipe. For a proof of concept, we will be comparing three versions of ASHRAE Standard 55, using the LLM to assess specific sections related to clothing factor determination within each standard. While larger-scale applications may present challenges in splitting and retrieving the overall standard as a text corpus, our proposed framework offers evidence that systematic information extraction from building standards using LLMs is feasible. By adapting to evolving requirements in real-time, our proposed approach ensures compliance with new standards while providing a scalable solution for building practitioners. The use of LLMs offers a promising path forward in managing complex building codes and standards, enabling NZEB designs in a

关键词： NZEB building standard large language model

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Bearing Fault Diagnosis Based on the Combination of Attention Entropy and Bayesian Network

Bearing Fault Diagnosis Based on the Combination of Attentio...

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Power Electronics, Computer applications (ICPECA), IEEE International conference on

作者： Zhaojing Tong Yongkui Fan Lina Tang School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo China School of Training Office Zhengzhou Industry Technicians College Zhengzhou China

ISBN: (数字)9798331533694

ISBN: (纸本)9798331533700

In order to improve the accuracy of bearing fault identification, this paper proposes a bearing fault diagnosis method that combines the Improved Refined Composite multiscale Attention Entropy (IRCMATE) with Bayesian networks. The method uses Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) to decompose the original signal, obtain multiple intrinsic modal functions (IMFs), calculate the Pearson correlation coefficient (PCC) between each IMF and the original signal, and select the IMFs with PCC greater than 0.3 to reconstruct the signal. Aiming at the problem that the multiscale attention entropy depends on the data length and is easily affected by the outliers in the sample, the improved refined composite multiscale attention entropy is proposed. The paper calculates the IRCMATE of the reconstructed signals, and select the IRCMATE under the appropriate scale as the new feature vector, so as to realize the fault feature extraction of the bearings. Improved Crown Porcupine Optimizer (ICPO) is proposed. ICPO solves the variable conflict problem of Crown Porcupine Optimizer (CPO) by realizing binary conversion through Sigmoid function. The dynamic strategy selection factor is introduced into the CPO, which improves the global exploration ability of the algorithm early in the iteration. After each iteration, the local optimization operations of increasing edge, decreasing edge and reversing edge are implemented on the current global optimal solution, so as to avoid falling into the local optimal solution. Using ICPO to get Bayesian network structure, and the bearing fault diagnosis model is obtained after training using the training set. It is shown through experiments that the fault features extracted using IRCMATE are more obvious. The comparison with other methods shows that IRCMATE-ICPO-BN has a higher fault diagnosis recognition rate.

关键词： Fault diagnosis Training Correlation coefficient Accuracy Heuristic algorithms Feature extraction Entropy Vectors Bayes methods optimization

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Multifractal Approach for Engineering of Piezoelectric and Multiferroic Bioresorbable Scaffolds: Information Extracted by D(q) and f(α) in Box Counting methods 4

Multifractal Approach for Engineering of Piezoelectric and M...

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4th International conference on Applied Mathematics, Modeling and Computer Simulation, AMMCS 2024

作者： Burianskaya, E.L. Gradov, Oleg V. Gradova, M.A. Iordanskii, A.L. Maklakova, I.A. Olkhov, A.A. Kosygina 4 Moscow119991 Russia 2nd Bauman street 5-1 Moscow105005 Russia Kosygina 4 Moscow119334 Russia

ISBN: (纸本)9781643685519

The porosity of fibrillar scaffolds plays a pivotal role in the regeneration of living tissue, significantly influencing cell spreading, proliferation, and differentiation, thereby impacting the overall efficiency of regenerative processes. A genuine fibrillar scaffold comprises fibers and pores of diverse sizes and scales. The interconnectivity of the fiber network is intrinsically linked to its mechanical properties. When the scaffold material exhibits piezoelectric characteristics, the application of an electric field to enhance regeneration induces microelectromechanical movement among the fibers, both in relation to one another and in alignment with the applied field. This results in alterations to the connectivity parameters of the network, with notable fluctuations in the distances between electroactive fibers and pore sizes. Consequently, the pathways for signal transduction within the piezoelectric scaffold adapt according to changes in the equivalent circuits of the network. Therefore, a straightforward mathematical approach (time-resolved) is essential for assessing field-induced variations in interfilament distances, network connectivity parameters, and the orientation of fiber ensembles composed of various filaments. This extends to the formation of multiscale networks and tree-like structures with lateral branches for signal routing, which is critical for the engineering and optimization of electroactive scaffolds. We propose employing multifractal analysis for this purpose. We recommend utilizing the multifractal spectra parameters D(q) and f(α), while advising against direct analysis of the scaling behavior for the dynamics of fiber structures for scaffold engineering applications. © 2024 The Authors.

关键词： Piezoelectricity

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multiscale Computational Roughness Analysis of InGaAs Growth Process for Solar Cell applications

Multiscale Computational Roughness Analysis of InGaAs Growth...

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International conference on Electrical Engineering, Computing Science and Automatic Control (CCE)

作者： C. Rodríguez C. Camas D. Valencia I. Zúñiga H. Vilchis Instituto de Investigación e Innovación en Energías Renovables UNICACH Tuxtla Gutiérrez México Ingeniería en Energía Universidad Politécnica de Chiapas Suchiapa México

ISBN: (数字)9798350377545

ISBN: (纸本)9798350377552

In this work, we analyzed the interactions between indium gallium arsenide (In-Ga-As) atoms via Molecular Dynamics (MD) for the growth of thin films through evaporation methods with applications in tandem solar cells. In addition, film roughness and its influence on device performance were determined using the Silvaco ATLAS software. To optimize the growth conditions, we used the MD method with the open-access code LAMMPS to reproduce the thermodynamic phenomena that occur during deposition. We built different models in agreement with the information found in repositories for the interatomic Tersoff potentials of As, Ga, and In. Subsequently, we obtained the film roughness at different stages of the process and performed an electrical stimulation of the tandem solar cell. As part of the results, we obtained long deposition interactions at different temperatures and density flux. In the electrical simulation using Silvaco Atlas, the rms (root-mean-square roughness) values of film growth for models 1 and 2 revealing that Model 2 achieved an efficiency of 19.84%, higher than the 16.79% efficiency of Model 1.

关键词： Performance evaluation Photovoltaic cells Computational modeling Process control Atoms Indium gallium arsenide Surface roughness Numerical models Rough surfaces optimization

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