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arXiv 2021年

作者： Griggs, David A. Gibbs, Jonathan S. Baker, Stuart P. Penny, Ryan W. Feldmann, Martin C. Hart, A. John Department of Mechanical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Naval Architecture and Ocean Engineering U.S. Naval Academy AnnapolisMD United States Materials and Manufacturing Directorate Air Force Research Laboratory DaytonOH United States

Metal additive manufacturing (AM) by laser powder bed fusion (L-PBF) builds upon fundamentals established in the field of laser welding which include the influence of gas and plume dynamics on weld depth and quality. L-PBF demands a thorough investigation of the complex thermophysical phenomena that occur where the laser interacts with the metal powder bed. In particular, melt pool turbulence and evaporation are influenced by the ambient gas chemistry and pressure. This paper presents the design and validation of high pressure laser melting (HPLM) testbed;this accommodates bare metal plate samples as well as manually-coated single powder layers, and operates at up to 300 psig. The open architecture of this testbed allows for full control of all relevant laser parameters in addition to ambient gas pressure and gas flow over the build area. Representative melt tracks and rasters on bare plate and powder are examined in order to validate system performance, and preliminary analysis concludes that pressure has a significant impact on melt pool aspect ratio. The HPLM system thus enables careful study pressure effects on processing of common L-PBF materials, and can be applied in the future to materials that are challenging to process under ambient pressure, such as those with high vapor pressures. © 2021, CC BY.

关键词： Lakes

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Artistic Style in Robotic Painting;a Machine Learning Approach to Learning Brushstroke from Human Artists

Artistic Style in Robotic Painting;a Machine Learning Approa...

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IEEE International Workshop on Robot and Human Communication (ROMAN)

作者： Ardavan Bidgoli Manuel Ladron De Guevara Cinnie Hsiung Jean Oh Eunsu Kang School of Architecture Carnegie Mellon University Pittsburgh PA USA School of Computer Science Carnegie Mellon University Pittsburgh PA USA Robotics Institute Carnegie Mellon University Pittsburgh PA USA

ISBN: (数字)9781728160757

ISBN: (纸本)9781728160764

Robotic painting has been a subject of interest among both artists and roboticists since the 1970s. Researchers and interdisciplinary artists have employed various painting techniques and human-robot collaboration models to create visual mediums on canvas. One of the challenges of robotic painting is to apply a desired artistic style to the painting. Style transfer techniques with machine learning models have helped us address this challenge with the visual style of a specific painting. However, other manual elements of style, i.e., painting techniques and brushstrokes of an artist, have not been fully *** propose a method to integrate an artistic style to the brushstrokes and the painting process through collaboration with a human artist. In this paper, we describe our approach to 1) collect brushstrokes and hand-brush motion samples from an artist, and 2) train a generative model to generate brushstrokes that pertains to the artist's style, and 3) fine tune a stroke-based rendering model to work with our robotic painting setup. We will report on the integration of these three steps in a separate publication. In a preliminary study, 71% of human evaluators find our reconstructed brushstrokes are pertaining to the characteristics of the artist's style. Moreover, 58% of participants could not distinguish a painting made by our method from a visually similar painting created by a human artist.

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Aerodynamic and LPV Modeling of a Distributed Propulsion Morphing Wing Aircraft

Aerodynamic and LPV Modeling of a Distributed Propulsion Mor...

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IEEE International Conference on Gridding and Polytope Based Modeling and Control

作者： Béla Takarics Réka Dóra Mocsányi Bálint Vanek Dávid Sziroczák Dániel Rohács Institute for Computer Science and Control 1111 Budapest Hungary Naval Architecture and Railway Vehicles Budapest University of Technology and Economics 1111 Budapest Hungary Budapest University of Technology and Economics 1111 Budapest Hungary

ISBN: (数字)9781728182193

ISBN: (纸本)9781728182209

Hybrid-electric, unconventional aircraft solutions can possibly be the solutions for the ambitious emission reduction targets set by regulators, based on society's demands. One such disruptive solution is a morphing wing cargo UAV, with distributed propulsion. This paper investigates the aerodynamics, flight dynamics and control of a scaled down technology demonstrator UAV, built to validate the feasibility of the morphing wing concept. Several types of analyses are run to gain knowledge on the performance, stability and control properties of the aircraft. The flight mechanical effects of the distributed propulsion system are taken into account based on the integral momentum theorem. The increased flow speed behind propellers increases the local lift forces. Therefore, the distributed propulsion can be used to control the roll, pitch and yaw motion of the morphing wing aircraft. The nonlinear 6 degrees of freedom, distributed propulsion aircraft model is constructed utilizing the stability and control derivatives obtained from the aerodynamic analysis. Grid and Tensor Product (TP) type linear parameter-varying (LPV) models of the morphing wing aircraft are generated via Jacobian linearization and TP model transformation. The LPV models capture the parameter varying dynamics arising from the airspeed, morphing wing and payload weight variations. Gain scheduled lateral and longitudinal baseline controllers are synthesized using the grid-based LPV model of the aircraft.

关键词： Atmospheric modeling Aerodynamics Stability analysis Aircraft manufacture Aircraft propulsion Aircraft Aerospace control

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On the potential of Stommel’s perpetual salt fountain for artificial upwelling

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Environmental Research Letters 2025年第7期20卷 074047-074047页

作者： Jost Kemper Jan Mense Jörn Kröger Thomas Slawig Kai Graf Ulf Riebesell Department of Computer Science Kiel University Christian-Albrechts-Platz 4 24118 Kiel Germany Institute for Naval Architecture and Maritime Engineering Kiel University of Applied Sciences Grenzstraße 3 24149 Kiel Germany Biological Oceanography GEOMAR Helmholtz Centre for Ocean Research Kiel Wischhofstraße 1-3 24148 Kiel Germany Kiel Marine Science (KMS)—Centre for Interdisciplinary Marine Science Christian-Albrechts-Platz 4 24118 Kiel Germany

Artificial upwelling (AU) of nutrient-rich deep ocean water to the surface ocean has been proposed to increase ecosystem productivity and enhance CO2 uptake. AU is thus considered a marine carbon dioxide removal optio...

Artificial upwelling (AU) of nutrient-rich deep ocean water to the surface ocean has been proposed to increase ecosystem productivity and enhance CO₂ uptake. AU is thus considered a marine carbon dioxide removal option among other potential uses. Due to the typical temperature and salinity depth profiles in wide parts of the oceans, a self-sustaining up or downflow within a vertical pipe can be established. This concept was introduced by Stommel et al (1956 Deep Sea Res. 3 152–3) as the perpetual salt fountain. Using a one-dimensional numerical performance prediction method for Stommel upwelling pipe (SUP) systems, previously developed and verified by Kemper et al (2025 Appl. Ocean Res. 160 104624), several studies on the potential of the SUP concept for AU are reported in the present work. A global assessment of the AU potential of SUP systems is presented, and the spatial and temporal variability of their performance is discussed. Additionally, an overview of upscaling and optimization design considerations for SUP systems is given based on a parametric study. Our results show that considerable parts of the global oceans are suitable for SUP-based AU of nutrients. The highest potential is found in the subtropical ocean gyres. We further find a significant seasonal pattern in the upwelling velocity. Upscaling of SUP systems to achieve practically significant flow rates for AU is found possible.

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Beyond game environments: Evolutionary algorithms with parameter space noise for task-oriented dialogue policy exploration

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Neurocomputing 2025年 648卷

作者： Qingxin Xiao Yangyang Zhao Lingwei Dang Yun Hao Le Che Qingyao Wu South China University of Technology School of Software Engineering Guangzhou 510006 Guangdong PR China Institute for Super Robotics(Huangpu) Guangzhou 510700 Guangdong PR China Changsha University of Science and Technology School of Computer and Communication Engineering Changsha 410114 Hunan PR China South China University of Technology School of Architecture Guangzhou 510006 Guangdong PR China

Reinforcement learning (RL) has achieved significant success in task-oriented dialogue (TOD) policy learning. Nevertheless, training dialogue policy through RL faces a critical challenge: insufficient exploration, which leads to the policy getting trapped in local optima. Evolutionary algorithms (EAs) enhance exploration breadth by maintaining and selecting diverse individuals, and they often add parameter space noise among different individuals to simulate mutation, thereby increasing exploration depth. This approach has proven to be an effective method for enhancing RL exploration and has shown promising results in game domains. However, previous research has not analyzed its effectiveness in TOD dialogue policy. Given the substantial differences between gaming contexts and TOD dialogue policy, this paper explores and validates the efficacy of EAs in TOD dialogue policy, investigating the effects of different evolutionary cycles and various noise strategies across different dialogue tasks to determine which combination of evolutionary cycle and noise strategy is most suitable for TOD dialogue policy. Additionally, we propose an adaptive noise evolution method that dynamically adjusts noise scales to improve exploration efficiency. Experiments on the MultiWOZ dataset demonstrate significant performance improvements, achieving state-of-the-art results in both on-policy and off-policy settings.

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Irreversibility analysis of magnetized flow of engine oil hybrid nanofluid (Ti6Al4V-ZnO/EO) over a stretching surface

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Alexandria Engineering Journal 2025年 127卷 214-227页

作者： Hussain, Syed M. Faridi, Aftab Ahmed Ahmad, Hijaz Ali, Kashif Iqbal, Muhammad Rashid Jamshed, Wasim Guedri, Kamel Almaliki, Abdulrazak H. Department of Mathematics Faculty of Science Islamic University of Madinah Madinah42351 Saudi Arabia Department of Mathematics The Islamia University of Bahawalpur Bahawalpur63100 Pakistan Near East University Operational Research Center in Healthcare TRNC Mersin 10 Nicosia99138 Turkey Department of Technical Sciences Western Caspian University Baku1001 Azerbaijan Department of Mathematics College of Science Korea University 145 Anam-ro Seongbuk-gu Seoul02841 Korea Republic of Department of Basic Sciences and Humanities Muhammad Nawaz Sharif University of Engineering and Technology Multan60000 Pakistan Department of Mathematics and Statistics Institute of Southern Punjab Multan32100 Pakistan Islamabad44000 Pakistan College of Engineering Al-Ayen Iraqi University An Nasiriyah64001 Iraq Department of Computer Engineering Biruni University Topkapi Istanbul Turkey Mechanical Engineering Department College of Engineering and Architecture Umm Al-Qura University P. O. Box 5555 Makkah21955 Saudi Arabia Department of Civil Engineering college of Engineering Taif University Taif21944 Saudi Arabia

This article analyzes the irreversibility of hydro-magnetic dynamics of hybridized nanofluid comprising of titanium alloy (Ti6Al4V) and zinc-oxide (ZnO) submerged into engine oil (used as a fuel) through a porous stretching sheet with multipart effects of viscous dissipation and non-uniform heat source. An induced magnetic field exists in the flow field due to the conducting nature of the hybrid nanofluid. The equations of the flow model are transformed by the similarity transformations and then simulated through a numerical scheme constructed with a formulation of central differences that adopts successive over-relaxation methodology. In this thermodynamic system, entropy and Bejan number profiles corresponding to the prominent parameters are simultaneously analysed for both the nanofluid case and hybrid nanofluid case in the Cartesian coordinates. A comparison table is constructed to validate the numerical results with existing literature. The impacts of various parameters on Nusselt number and skin friction coefficient are graphed with reference to the magnetic field parameter. A significant reduction in irreversibility and a remarkable improvement in thermal characteristics of engine oil are observed due to induced magnetism effects. The engine oil hybrid nanofluid (Ti6Al4V-ZnO/EO) exhibits a 13.89 % higher heat transfer rate over a porous stretching surface compared to the engine oil nanofluid (Ti6Al4V/EO). © 2025 The Authors

关键词： Magnetic levitation

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Predictive analytics in quality assurance for assembly processes: lessons learned from a case study at an industry 4.0 demonstration cell

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Procedia CIRP 2021年 104卷 641-646页

作者： Peter Burggräf Johannes Wagner Benjamin Heinbach Fabian Steinberg Alejandro R. Pérez M. Lennart Schmallenbach Jochen Garcke Daniela Steffes-lai Moritz Wolter Chair of International Production Engineering and Management (IPEM) Universität Siegen Paul-Bonatz-Straße 9-11 57076 Siegen Germany Fraunhofer Institute for Algorithms and Scientific Computing (SCAI) Schloss Birlinghoven 1 53757 Sankt Augustin Germany Fraunhofer Center for Machine Learning Schloss Birlinghoven 1 53757 Sankt Augustin Germany Institute for Numerical Simulation Universität Bonn Endenicher Allee 19b 53115 Bonn Germany Institute for Computer Science Universität Bonn Endenicher Allee 19a 53115 Bonn Germany

Quality assurance (QA) is an important task in manufacturing to assess whether products meet their specifications. However, QA might be expensive, time-consuming, or incomplete. This paper presents a solution for predictive analytics in QA based on machine sensor values during production while employing specialized machine-learning models for classification in a controlled environment. Furthermore, we present lessons learned while implementing this model, which helps to reduce complexity in further industrial applications. The paper’s outcome proves that the developed model was able to predict product quality, as well as to identify the correlation between machine-status and faulty product occurrence.

关键词： Machine-Learning Predictive Quality Production Quality Assurance Classification

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Dynamic Resilient Network Games with Applications to Multi-Agent Consensus

arXiv

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arXiv 2020年

作者： Nugraha, Yurid Cetinkaya, Ahmet Hayakawa, Tomohisa Ishii, Hideaki Zhu, Quanyan Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo152-8552 Japan Information Systems Architecture Science Research Division National Institute of Informatics Tokyo101-8430 Japan Department of Computer Science Tokyo Insitute of Technology Yokohama226-8502 Japan Department of Electrical and Computer Engineering New York University BrooklynNY11201 United States

A cyber security problem in a networked system formulated as a resilient graph problem based on a game-theoretic approach is considered. The connectivity of the underlying graph of the network system is reduced by an attacker who removes some of the edges whereas the defender attempts to recover them. Both players are subject to energy constraints so that their actions are restricted and cannot be performed continuously. For this two-stage game, which is played repeatedly over time, we characterize the optimal strategies for the attacker and the defender in terms of edge connectivity and the number of connected components of the graph. The resilient graph game is then applied to a multi-agent consensus problem. We study how the attacks and the recovery on the edges affect the consensus process. Finally, we also provide numerical simulation to illustrate the results. Copyright © 2020, The Authors. All rights reserved.

关键词： Multi agent systems

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Evaluation of OpenAI o1: Opportunities and Challenges of AGI

arXiv

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arXiv 2024年

作者： Zhong, Tianyang Liu, Zhengliang Pan, Yi Zhang, Yutong Zhou, Yifan Liang, Shizhe Wu, Zihao Lyu, Yanjun Shu, Peng Yu, Xiaowei Cao, Chao Jiang, Hanqi Chen, Hanxu Li, Yiwei Chen, Junhao Hu, Huawen Liu, Yihen Zhao, Huaqin Xu, Shaochen Dai, Haixing Zhao, Lin Zhang, Ruidong Zhao, Wei Yang, Zhenyuan Chen, Jingyuan Wang, Peilong Ruan, Wei Wang, Hui Zhao, Huan Zhang, Jing Ren, Yiming Qin, Shihuan Chen, Tong Li, Jiaxi Zidan, Arif Hassan Jahin, Afrar Chen, Minheng Xia, Sichen Holmes, Jason Zhuang, Yan Wang, Jiaqi Xu, Bochen Xia, Weiran Yu, Jichao Tang, Kaibo Yang, Yaxuan Sun, Bolun Yang, Tao Lu, Guoyu Wang, Xianqiao Chai, Lilong Li, He Lu, Jin Sun, Lichao Zhang, Xin Ge, Bao Hu, Xintao Zhang, Lian Zhou, Hua Zhang, Lu Zhang, Shu Liu, Ninghao Jiang, Bei Kong, Linglong Xiang, Zhen Ren, Yudan Liu, Jun Jiang, Xi Bao, Yu Zhang, Wei Li, Xiang Li, Gang Liu, Wei Shen, Dinggang Sikora, Andrea Zhai, Xiaoming Zhu, Dajiang Zhang, Tuo Liu, Tianming Department of Mathematical and Statistical Sciences University of Alberta Edmonton Canada School of Computing University of Georgia GA United States Institute of Medical Research Northwestern Polytechnical University Xi'An China College of Arts and Sciences University of Georgia Athens United States Institute of Plant Breeding Genetics & Genomics University of Georgia AthensGA United States Department of Computer Science and Engineering University of Texas ArlingtonTX United States The Lamar Dodd School of Art University of Georgia GA United States School of Computer Science Northwestern Polytechnical University Xi'An China School of Automation Northwestern Polytechnical University Xi'An China University of California Los AngelesCA United States Department of Radiology The Second Xiangya Hospital Central South University Changsha China Clinical Research Center for Medical Imaging in Hunan Province Changsha China Institute of Biomedical and Health Engineering Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China Guanghua School of Management Peking University Beijing China Department of Radiation Oncology Mayo Clinic PhoenixAZ United States Second Language Acquisition and Teaching University of Arizona TucsonAZ United States School of Life Science and Technology University of Electronic Science and Technology of China Chengdu China The First Hospital of Hebei Medical University Hebei Shijiazhuang China School of Computer and Cyber Sciences Augusta University AugustaGA United States School of Physics and Information Technology Shaanxi Normal University Xi'An China School of Future Technology South China University of Technology Guangzhou China Department of Radiology and BRIC University of North Carolina Chapel HillNC United States Department of Educational Psychology University of Georgia AthensGA United States Johns Hopkins University BaltimoreMD United States School of Architecture Tsinghua Universit

This comprehensive study evaluates the performance of OpenAI's o1-preview large language model across a diverse array of complex reasoning tasks, spanning multiple domains, including computer science, mathematics, natural sciences, medicine, linguistics, and social sciences. Through rigorous testing, o1-preview demonstrated remarkable capabilities, often achieving human-level or superior performance in areas ranging from coding challenges to scientific reasoning and from language processing to creative problem-solving. Key findings include: • 83.3% success rate in solving complex competitive programming problems, surpassing many human experts. • Superior ability in generating coherent and accurate radiology reports, outperforming other evaluated models. • 100% accuracy in high school-level mathematical reasoning tasks, providing detailed step-by-step solutions. • Advanced natural language inference capabilities across general and specialized domains like medicine. • Impressive performance in chip design tasks, outperforming specialized models in areas such as EDA script generation and bug analysis. • Remarkable proficiency in anthropology and geology, demonstrating deep understanding and reasoning in these specialized fields. • Strong capabilities in quantitative investing. O1 has comprehensive financial knowledge and statistical modeling skills. • Effective performance in social media analysis, including sentiment analysis and emotion recognition. The model excelled particularly in tasks requiring intricate reasoning and knowledge integration across various fields. While some limitations were observed, including occasional errors on simpler problems and challenges with certain highly specialized concepts, the overall results indicate significant progress towards artificial general intelligence. This evaluation not only highlights o1-preview's current strengths and limitations but also identifies crucial areas for future development, including multi-modal integratio

关键词： Emotion Recognition

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Efficient Cross-Level Testing for Processor Verification: A RISC- V Case-Study

Efficient Cross-Level Testing for Processor Verification: A ...

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Forum on Specification, Verification and Design Languages, FDL

作者： Vladimir Herdt Daniel Große Eyck Jentzsch Rolf Drechsler Cyber-Physical Systems DFKI GmbH Bremen Germany Chair of Complex Systems Johannes Kepler University Linz Austria MINRES® Technologies GmbH Munich Germany Institute of Computer Science University of Bremen Bremen Germany

ISBN: (数字)9781728189284

ISBN: (纸本)9781728189291

Extensive processor verification at the Register-Transfer Level (RTL) is crucial to avoid bugs. Therefore, simulation-based approaches are prevalent but they require efficient test generation methods to achieve a thorough verification. In this paper we propose an efficient cross-level testing approach for processor verification targeting the RISC- V Instruction Set architecture (ISA). We generate an endless instruction stream without restrictions on the generated instructions by evolving the instruction stream on-the-fly during simulation. An Instruction Set Simulator (ISS) is leveraged as reference model for the RTL core under test in a tightly coupled cross-level co-simulation setting. This enables a very efficient and comprehensive testing process. As a case-study we present results on the verification of the 32 bit pipelined RISC- V core of MINRES The Good Folk (TGF) Series Our approach has been very effective in finding several serious bugs.

关键词： Testing Test pattern generators Time-varying systems Time-domain analysis Registers Instruction sets Standards

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