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Reliability of electric vehicle charging infrastructure:A cross-lingual deep learning approach

Communications in Transportation Research 2023年第1期3卷 81-91页

作者： Yifan Liu Azell Francis Catharina Hollauer M.Cade Lawson Omar Shaikh Ashley Cotsman Khushi Bhardwaj Aline Banboukian Mimi Li Anne Web Omar Isaac Asensio School of Public Policy Georgia Institute of TechnologyAtlanta30332USA Sam Nunn School of International Affairs Georgia Institute of TechnologyAtlanta30332USA School of Civil&Environmental Engineering Georgia Institute of TechnologyAtlanta30332USA H.Milton Stewart School of Industrial and Systems Engineering Georgia Institute of TechnologyAtlanta30332USA School of Computer Science Georgia Institute of TechnologyAtlanta30332USA School of Computer Science Stanford UniversityPalo Alto94305USA School of Economics Georgia Institute of TechnologyAtlanta30332USA Institute for Data Engineering&Science(IDEaS) Georgia Institute of TechnologyAtlanta30332USA

Vehicle electrification has emerged as a global strategy to address climate change and emissions externalities from the transportation *** of charging infrastructure is needed to accelerate technology adoption;however,managers and policymakers have had limited evidence on the use of public charging stations due to poor data sharing and decentralized ownership across *** this article,we use machine learning based classifiers to reveal insights about consumer charging behavior in 72 detected languages including *** investigate 10 years of consumer reviews in East and Southeast Asia from 2011 to 2021 to enable infrastructure evaluation at a larger geographic scale than previously *** find evidence that charging stations at government locations result in higher failure rates with consumers compared to charging stations at private points of *** evidence contrasts with predictions in the *** European markets,where the performance is closer to *** also find that networked stations with communication protocols provide a relatively higher quality of charging services,which favors policy support for connectivity,particularly for underserved or remote areas.

关键词： Electric vehicles Consumer behavior Charging infrastructure Public policy Machine learning Natural language processing Transformer algorithms

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Toward a Framework for Virtual Testing of Complex Machine Tools 3rd

Toward a Framework for Virtual Testing of Complex Machine To...

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3rd International Conference on Design Tools and Methods in Industrial engineering, ADM 2023

作者： Rega, Andrea Genua, Alessandro Vitolo, Ferdinando Patalano, Stanislao Sanseverino, Giuseppe Penter, Lars Arnold, Frank Ihlenfeldt, Steffen Lanzotti, Antonio Fraunhofer J-Lab IDEAS Department of Industrial Engineering University of Naples Federico II Naples Italy Chair of Machine Tool Development and Adaptive Controls Technische Universität Dresden Dresden Germany Department of Sports Equipment and Technology Chemnitz University of Technology Chemnitz Germany

ISBN: (纸本)9783031520747

Virtual prototyping is a strategic practice in the research and development of innovative products and machine tools. Virtual prototyping allows the integration of multidomain simulations into the designing process to replicate and analyze the impact of design choices on the overall system performance, reducing time-to-market while simultaneously improving quality. The current paper provided a methodological approach to model complex machine tools and perform virtual testing. As a use case for this study, a parallel kinematic machine (Pentapod P800, METROM Mechatronische Maschinen GmbH, Germany) is investigated. The adoption of these complex machine tools within the industrial context and the design of parallel kinematic machines can be eased by the implementation of methodologies capable of reducing efforts and risks during the analysis and the testing phases, prior to actual commissioning. In this scenario, virtual testing guarantees generality, completeness, and quick response. Therefore, the multibody model of the Pentapod P800 was developed following the proposed framework. Then, the simulation of a test trajectory was successfully carried out. The results show that this approach might lead to the design and implementation of a parallel kinematics machine reducing risks, time, and costs. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Virtual prototyping

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D-MiSo: Editing Dynamic 3D Scenes using Multi-Gaussians Soup 38

D-MiSo: Editing Dynamic 3D Scenes using Multi-Gaussians Soup

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Waczyńska, Joanna Borycki, Piotr Kaleta, Joanna Tadeja, Slawomir Spurek, Przemyslaw Doctoral School of Exact Natural Sciences Jagiellonian University Poland Faculty of Mathematics and Computer Science Jagiellonian University Poland Warsaw University of Technology Sano Centre for Computational Medicine Poland Department of Engineering University of Cambridge United Kingdom Jagiellonian University IDEAS NCBR Poland

Over the past years, we have observed an abundance of approaches for modeling dynamic 3D scenes using Gaussian Splatting (GS). These solutions use GS to represent the scene's structure and the neural network to model dynamics. Such approaches allow fast rendering and extracting each element of such a dynamic scene. However, modifying such objects over time is challenging. SC-GS (Sparse Controlled Gaussian Splatting) enhanced with Deformed Control Points partially solves this issue. However, this approach necessitates selecting elements that need to be kept fixed, as well as centroids that should be adjusted throughout editing. Moreover, this task poses additional difficulties regarding the re-productivity of such editing. To address this, we propose Dynamic Multi-Gaussian Soup (D-MiSo), which allows us to model the mesh-inspired representation of dynamic GS. Additionally, we propose a strategy of linking parameterized Gaussian splats, forming a Triangle Soup with the estimated mesh. Consequently, we can separately construct new trajectories for the 3D objects composing the scene. Thus, we can make the scene's dynamic editable over time or while maintaining partial dynamics. © 2024 Neural information processing systems foundation. All rights reserved.

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Automatic Outcomes in Minnesota Dexterity Test Using a System of Multiple Depth Cameras

Automatic Outcomes in Minnesota Dexterity Test Using a Sys...

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International Joint Conference on Mechanics, Design engineering and Advanced Manufacturing, JCM 2022

作者： Caporaso, Teodorico Sanseverino, Giuseppe Krumm, Dominik Grazioso, Stanislao D’Angelo, Raffaele Di Gironimo, Giuseppe Odenwald, Stephan Lanzotti, Antonio Fraunhofer Joint Lab IDEAS Department of Industrial Engineering University of Naples Federico II Naples80125 Italy Department of Sports Equipment and Technology Chemnitz University of Technology Reichenhainer Str. 70 Chemnitz09126 Germany Direzione Regionale INAIL - CONTARP Naples Italy

ISBN: (纸本)9783031159275

Objective and reliable assessment of motor functions, such as dexterity, is a key point for evaluating worker’s abilities. In this context, the proposed work presents a tool for objective automatic assessment of the Minnesota Dexterity Test using cameras with depth sensors. Typical performance measurements (i.e., total time and associated percentiles) were estimated using custom algorithms. In addition, the possibility to identify the qualifiers for the code d440 of the International Classification of Functioning, Disability and Health was implemented in the developed algorithms. The proposed tool can also identify the mistakes most frequently committed by the subjects. To prove the capabilities of the proposed method, a series of experimental trials was conducted with 10 healthy young volunteers. Results showed that the developed tool helps clinicians to obtain performance feedback and evaluate patients’ dexterity quickly without bias. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Cameras

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The Same Only Different: On Information Modality for Configuration Performance Analysis

arXiv

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arXiv 2025年

作者： Liang, Hongyuan Huang, Yue Chen, Tao School of Computer Science and Engineering University of Electronic Science and Technology of China China IDEAS Lab School of Computer Science University of Birmingham United Kingdom

Configuration in software systems helps to ensure efficient operation and meet diverse user needs. Yet, some, if not all, configuration options have profound implications for the system’s performance. Configuration performance analysis, wherein the key is to understand (or infer) the configuration options’ relations and their impacts on performance, is crucial. Two major modalities exist that serve as the source information in the analysis: either the manual or source code. However, it remains unclear what roles they play in configuration performance analysis. Much work that relies on manuals claims their benefits of information richness and naturalness;while work that trusts the source code more prefers the structural information provided therein and criticizes the timeliness of manuals. To fill such a gap, in this paper, we conduct an extensive empirical study over 10 systems, covering 1,694 options, 106,798 words in the manual, and 22,859,552 lines-of-code for investigating the usefulness of manual and code in two important tasks of configuration performance analysis, namely performance-sensitive options identification and the associated dependencies extraction. We reveal several new findings and insights, such as it is beneficial to fuse the manual and code modalities for both tasks;the current automated tools that rely on a single modality are far from being practically useful and generally remain incomparable to human analysis. All those pave the way for further advancing configuration performance analysis. Copyright © 2025, The Authors. All rights reserved.

关键词： Codes (symbols)

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An analysis of the processes, kinetics and equilibrium of iron's biosorption on immobilized green microalgae

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South African Journal of Chemical engineering 2023年 45卷 210-220页

作者： Diale, P.P. Hildebrandt, D. Glasser, D. Matambo, T.S. Makgato, S.S. University of the Witwatersrand School of Chemical and Metallurgical Engineering Private Bag 3 Wits 2050 South Africa African Leadership Centre WITS Business School Molecular Science Institute School of Chemistry University of the Witwatersrand Johannesburg 2050 South Africa Institute for the Development of Energy for African Sustainability (IDEAS) University of South Africa College of Science Engineering and Technology Florida Roodepoort 1709 South Africa Department of Chemical Engineering College of Science Engineering and Technology University of South Africa (UNISA) c/o Christiaan de Wet & Pioneer Avenue Florida Campus Johannesburg 1710 South Africa

Metals including Cu, Cd, Ni, Pb, Zn, Hg, Fe and Cr can be found in significant concentrations in acid mine drainage effluent from previous gold mining operations. Even at very low levels, heavy metals and their compounds are very toxic, carcinogenic, mutagenic and teratogenic. Acid mine drainage discharge must therefore be properly treated before disposal. In this study, iron removal from acid mine drainage effluent using immobilized green microalgae is explored. The impact of pH on iron metal concentrations was studied at multiple pH values between 2 and 12 using 0.1 M HCl or NaOH solutions. At pH 6, the optimal value, 82% and 90% of Fe (II) were removed from Ca-alginate beads and immobilized Desmodesmus sp., respectively. It was shown that Fe (II) ions were biosorbed by immobilized microalgae cells in a pseudo-second-order manner. This study demonstrated how immobilized green microalgae showed potential to remove iron from acid mine drainage effluent. © 2023

关键词： Biosorption Ca-alginate Desmodesmus sp. Iron Remediation

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Faster Configuration Performance Bug Testing with Neural Dual-level Prioritization

arXiv

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arXiv 2025年

作者： Ma, Youpeng Chen, Tao Li, Ke School of Computer Science and Engineering University of Electronic Science and Technology of China China IDEAS Lab School of Computer Science University of Birmingham United Kingdom Department of Computer Science University of Exeter United Kingdom

As software systems become more complex and configurable, more performance problems tend to arise from the configuration designs. This has caused some configuration options to unexpectedly degrade performance which deviates from their original expectations designed by the developers. Such discrepancies, namely configuration performance bugs (CPBugs), are devastating and can be deeply hidden in the source code. Yet, efficiently testing CPBugs is difficult, not only due to the test oracle is hard to set, but also because the configuration measurement is expensive and there are simply too many possible configurations to test. As such, existing testing tools suffer from lengthy runtime or have been ineffective in detecting CPBugs when the budget is limited, compounded by inaccurate test oracle. In this paper, we seek to achieve significantly faster CPBug testing by neurally prioritizing the testing at both the configuration option and value range levels with automated oracle estimation. Our proposed tool, dubbed NDP, is a general framework that works with different heuristic generators. The idea is to leverage two neural language models: one to estimate the CPBug types that serve as the oracle while, more vitally, the other to infer the probabilities of an option being CPBug-related, based on which the options and the value ranges to be searched can be prioritized. Experiments on several widely-used systems of different versions reveal that NDP can, in general, better predict CPBug type in 87% cases and find more CPBugs with up to 88.88× testing efficiency speedup over the state-of-the-art tools. Copyright © 2025, The Authors. All rights reserved.

关键词： Program debugging

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No Task Left Behind: Isotropic Model Merging with Common and Task-Specific Subspaces

arXiv

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arXiv 2025年

作者： Marczak, Daniel Magistri, Simone Cygert, Sebastian Twardowski, Bartlomiej Bagdanov, Andrew D. van de Weijer, Joost Warsaw University of Technology Poland IDEAS NCBR Warsaw Poland Department of Information Engineering University of Florence Italy Gdańsk University of Technology Poland Computer Vision Center Barcelona Spain Department of Computer Science Universitat Autonoma de Barcelona Spain

Model merging integrates the weights of multiple task-specific models into a single multi-task model. Despite recent interest in the problem, a significant performance gap between the combined and single-task models remains. In this paper, we investigate the key characteristics of task matrices – weight update matrices applied to a pre-trained model – that enable effective merging. We show that alignment between singular components of task-specific and merged matrices strongly correlates with performance improvement over the pre-trained model. Based on this, we propose an isotropic merging framework that flattens the singular value spectrum of task matrices, enhances alignment, and reduces the performance gap. Additionally, we incorporate both common and task-specific subspaces to further improve alignment and performance. Our proposed approach achieves state-of-the-art performance across multiple scenarios, including various sets of tasks and model scales. This work advances the understanding of model merging dynamics, offering an effective methodology to merge models without requiring additional training. Code is available at https://***/danielm1405/iso-merging. © 2025, CC BY.

关键词： Matrix algebra

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Towards Economically Viable Anti-Soiling Coatings: A Target Costing Analysis

Towards Economically Viable Anti-Soiling Coatings: A Target ...

引用

IEEE Conference Photovoltaic Specialists (PVSC)

作者： Leonardo Micheli Greg P. Smestad Diego L. Talavera Department of Astronautical Electrical and Energy Engineering (DIAEE) Sapienza University of Rome Rome Italy Sol Ideas Technology Development San Jose CA United States Advances in Photovoltaic Technology (AdPVTech) University of JaA©n JaÃ©n Spain

ISBN: (数字)9781665464260

ISBN: (纸本)9781665475822

This abstract outlines initial findings of an investigation on the maximum allowable costs of anti-soiling coatings (ASCs )-a preventive solution to reduce soiling deposition. These can increase the profitability of a photovoltaic system if the additional revenues made through the reduced losses are higher than the coating fabrication/deposition costs. The target costs to make anti-soiling coatings cost-effective are calculated for different effectiveness and degradation conditions in several European and Eurasian countries. The target costs represent the maximum allowable costs for ASC fabrication and deposition that would not increase the Levelized Cost of Electricity (LCOE) or not decrease the Net Present Value (NPV). It is shown that the target costs vary depending upon the considered economic index (NPV or LCOE), and that ASC degradation has the highest impact on these targets, followed by soiling loss and coating effectiveness.

关键词： Photovoltaic systems Degradation Fabrication Costs Profitability Costing Electricity Europe Coatings Indexes

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Particle identification with machine learning in ALICE Run 3

arXiv

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arXiv 2023年

作者： Karwowska, Maja Jakubowska, Monika Graczykowski, Lukasz Deja, Kamil Kasak, Milosz CERN – European Organization for Nuclear Research Switzerland Faculty of Physics Warsaw University of Technology Poland Faculty of Electrical Engineering Warsaw University of Technology Poland Faculty of Electronics and Information Technology Warsaw University of Technology Poland IDEAS NCBR Poland

The main focus of the ALICE experiment, quark–gluon plasma measurements, requires accurate particle identification (PID). The ALICE sub-detectors allow identifying particles over a broad momentum interval ranging from about 100 MeV/c up to 20 GeV/c. However, a machine learning (ML) model can explore more detector information. During LHC Run 2, preliminary studies with Random Forests obtained much higher efficiencies and purities for selected particles than standard techniques. For Run 3, we investigate Domain Adaptation Neural Networks that account for the discrepancies between the Monte Carlo simulations and the experimental data. Preliminary studies show that domain adaptation improves particle classification. Moreover, the solution is extended with Feature Set Embedding and attention to give the network more flexibility to train on data with various sets of detector signals. PID ML is already integrated with the ALICE Run 3 Analysis Framework. Preliminary results for the PID of selected particle species, including real-world analyzes, are discussed as well as the possible optimizations. © 2023, CC BY.

关键词： Machine learning

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