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JARVIS-Leaderboard:a large scale benchmark of materials design methods

npj computational Materials 2024年第1期10卷 2280-2296页

作者： Kamal Choudhary Daniel Wines Kangming Li Kevin F.Garrity Vishu Gupta Aldo H.Romero Jaron T.Krogel Kayahan Saritas Addis Fuhr Panchapakesan Ganesh Paul R.C.Kent Keqiang Yan Yuchao Lin Shuiwang Ji Ben Blaiszik Patrick Reiser Pascal Friederich Ankit Agrawal Pratyush Tiwary Eric Beyerle Peter Minch Trevor David Rhone Ichiro Takeuchi Robert B.Wexler Arun Mannodi-Kanakkithodi Elif Ertekin Avanish Mishra Nithin Mathew Mitchell Wood Andrew Dale Rohskopf Jason Hattrick-Simpers Shih-Han Wang Luke E.K.Achenie Hongliang Xin Maureen Williams Adam J.Biacchi Francesca Tavazza Material Measurement Laboratory National Institute of Standards and TechnologyGaithersburgMD20899USA Department of Materials Science and Engineering University of Toronto27 King’s College CirTorontoONCanada Department of Electrical and Computer Engineering Northwestern UniversityEvanstonIL 60208USA Lewis-Sigler Institute for Integrative Genomics Princeton UniversityPrincetonNJ 08544USA Ludwig Institute for Cancer Research Princeton UniversityPrincetonNJ 08544USA Department of Physics and Astronomy West Virginia UniversityMorgantownWV 26506USA Materials Science and Technology Division Oak Ridge National LaboratoryOak RidgeTN 37831USA Center for Nanophase Materials Science Oak Ridge National LaboratoryOak RidgeTN 37831USA Computational Sciences and Engineering Division Oak Ridge National LaboratoryOak RidgeTN 37831USA Department of Computer Science and Engineering Texas A&M UniversityCollege StationTX 77843USA Globus University of ChicagoChicagoIL 60637USA Data Science and Learning Division Argonne National LabLemontIL 60439USA Institute of Nanotechnology Karlsruhe Institute of TechnologyKaiserstraße 1276131 KarlsruheGermany Institute of Theoretical Informatics Karlsruhe Institute of TechnologyKaiserstraße 1276131 KarlsruheGermany Department of Chemistry and Biochemistry and Institute for Physical Science and Technology University of MarylandCollege ParkMD 20742USA Department of Physics Applied Physics and AstronomyRensselaer Polytechnic InstituteTroyNY12180USA Department of Materials Science and Engineering University of MarylandCollege ParkMD20742USA Department of Chemistry and Institute of Materials Science and Engineering Washington University in St.LouisSt.LouisMO63130USA School of Materials Engineering Purdue UniversityWest LafayetteIN47907USA Department of Mechanical Science and Engineering University of Illinois Urbana-ChampaignUrbanaIllinois 61801USA Materials Research Laboratory University of Illinois Urbana-ChampaignUrbanaIL 61801USA Theore

Lack of rigorous reproducibility and validation are significant hurdles for scientific development across many *** science,in particular,encompasses a variety of experimental and theoretical approaches that require careful *** efforts have been developed previously to mitigate these ***,a comprehensive comparison and benchmarking on an integrated platform with multiple data modalities with perfect and defect materials data is still *** work introduces JARVIS-Leaderboard,an open-source and community-driven platform that facilitates benchmarking and enhances *** platform allows users to set up benchmarks with customtasks and enables contributions in the form of dataset,code,and meta-data *** cover the following materials design categories:Artificial intelligence(AI),Electronic Structure(ES).

关键词： rigorous perfect enable

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A Coupled CS-DSG3/BEM Method for Hydroelastic Analysis of Pontoon-Type VLFS with Arbitrary Plan Shape 3rd

A Coupled CS-DSG3/BEM Method for Hydroelastic Analysis of Po...

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3rd International Conference on Sustainable Civil engineering and Architecture, ICSCEA 2023

作者： Luong, Van Hai Nguyen, H.P. Nguyen-Thoi, T. 268 Ly Thuong Kiet Street District 10 Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Linh Trung Ward Thu Duc District Ho Chi Minh City Viet Nam School of Civil Engineering The University of Queensland St LuciaQLD4072 Australia Laboratory for Applied and Industrial Mathematics Institute for Computational Science and Artificial Intelligence Van Lang University Ho Chi Minh City Viet Nam Faculty of Mechanical-Electrical and Computer Engineering Van Lang University Ho Chi Minh City Viet Nam

ISBN: (纸本)9789819974337

The cell-based smoothed discrete shear gap method (CS-DSG3) was introduced for analysing Mindlin plates. This method employs three-node triangular elements and can produce solutions with high accuracy. This research aims to combine CS-DSG3 with the Boundary Element Method (BEM) to perform hydroelastic analyses on pontoon-type Very Large Floating Structures (VLFS) with varying plan shapes. In this study, the VLFS is conceptualized as a Mindlin plate resting on an ideal fluid. The structural and fluid domains are discretized using three-node triangular elements. The structural equation is formulated using CS-DSG3, while the water equation is established using BEM. The hydroelastic analysis is conducted within the frequency domain. To validate the accuracy of the CS-DSG3/BEM approach, its results are compared with available published solutions. The proposed method is then employed in parametric investigations involving various VLFS plan shapes to explore how the shape influences hydroelastic responses. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Boundary element method

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Intelligent evaluation system for new energy vehicles based on sentiment analysis: An MG-PL-3WD method

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engineering Applications of Artificial intelligence 2024年 133卷

作者： Zhang, Chao Wen, Qifei Li, Deyu Sangaiah, Arun Kumar Lin, Mingwei School of Computer and Information Technology Shanxi University Taiyuan030006 China Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education Shanxi University Taiyuan030006 China International Graduate Institute of Artificial Intelligence National Yunlin University of Science and Technology Yunlin64002 Taiwan Department of Electrical and Computer Engineering Lebanese American University Byblos1102-2801 Lebanon College of Computer and Cyber Security Fujian Normal University Fuzhou350117 China

As a critical strategic tool within the framework of the digital economy (DE), artificial intelligence (AI) plays a crucial role in realizing an AI-assisted economy. This novel paradigm has gained widespread acceptance from governments globally, positioning itself as a cornerstone in the practical implementation of the DE. The increasing reliance on digital means for economic transformation, the treatment of data as a critical resource, and the integration of information technologies highlight the synergy between AI and the DE. Against this backdrop, online reviews and SA play a pivotal role, offering rich data streams continually emerging on various platforms. Therefore, this article utilizes a probabilistic linguistic term set (PLTS) to establish a multi-granularity probabilistic linguistic (MG-PL) information system. This approach, through sentiment analysis (SA), enables quantitative analysis of user emotional expressions. The integration of these technological aspects holds the promise of enhancing decision-making processes, facilitating the intellectualization of economic activities, and addressing existing challenges in the application of AI within the DE domain. Initially, SA is conducted on text-based online comment data, forming a probabilistic linguistic incomplete information system. The maximum similarity method is employed to establish a probabilistic linguistic complete information system. Subsequently, an adjustable MG-PL decision-theoretic rough set (DTRS) is developed, followed by the establishment of a three-way group decision model using three-way decisions (3WD) and a directed graph. The model's applicability, stability, and feasibility are demonstrated via a case study centered on the acquisition of new energy vehicles (NEVs). © 2024 Elsevier Ltd

关键词： Sentiment analysis

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Fast and accurate sparse-view CBCT reconstruction using meta-learned neural attenuation field and hash-encoding regularization

arXiv

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arXiv 2023年

作者： Shin, Heejun Kim, Taehee Lee, Jongho Chun, Se Young Cho, Seungryong Shin, Dongmyung Artificial Intelligence Engineering Division Radisen Co. Ltd. Seoul Korea Republic of Laboratory for Imaging Science and Technology Department of Electrical and Computer Engineering Seoul National University Seoul Korea Republic of Intelligent Computational Imaging Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul Korea Republic of Medical Imaging and Radiotherapy Laboratory Department of Nuclear and Quantum Engineering Korea Advanced Institute of Science and Technology Daejeon Korea Republic of

Cone beam computed tomography (CBCT) is an emerging medical imaging technique to visualize the internal anatomical structures of patients. During a CBCT scan, several projection images of different angles or views are collectively utilized to reconstruct a tomographic image. However, reducing the number of projections in a CBCT scan while preserving the quality of a reconstructed image is challenging due to the nature of an ill-posed inverse problem. Recently, a neural attenuation field (NAF) method was proposed by adopting a neural radiance field algorithm as a new way for CBCT reconstruction, demonstrating fast and promising results using only 50 views. However, decreasing the number of projections is still preferable to reduce potential radiation exposure, and a faster reconstruction time is required considering a typical scan time. In this work, we propose a fast and accurate sparse-view CBCT reconstruction (FACT) method to provide better reconstruction quality and faster optimization speed in the minimal number of view acquisitions ( Copyright © 2023, The Authors. All rights reserved.

关键词： Image reconstruction

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Quantum Circuit for Non-Unitary Linear Transformation of Basis Sets

arXiv

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arXiv 2025年

作者： Zhu, Guorui Bierman, Joel Lu, Jianfeng Li, Yingzhou School of Mathematical Sciences Fudan University China Electrical and Computer Engineering North Carolina State University United States Department of Mathematics Department of Physics Department of Chemistry Duke University United States School of Mathematical Sciences Shanghai Key Laboratory for Contemporary Applied Mathematics Fudan University Key Laboratory of Computational Physical Sciences Ministry of Education China

This paper introduces a novel approach to implementing non-unitary linear transformations of basis on quantum computational platforms, a significant leap beyond the conventional unitary methods. By integrating Singular Value Decomposition (SVD) into the process, the method achieves an operational depth of O(n) with about n ancilla qubits, enhancing the computational capabilities for analyzing fermionic systems. The non-unitarity of the transformation allows us to transform a wave function from one basis to another, which can span different spaces. By this trick, we can calculate the overlap of two wavefunctions that live in different (but non-distinct Hilbert subspaces) with different basis representations. This provides the opportunity to use state specific ansatzes to calculate different energy eigenstates under orbital-optimized settings and may improve the accuracy when computing the energies of multiple eigenstates simultaneously in VQE or other framework. It allows for a deeper exploration of complex quantum states and phenomena, expanding the practical applications of quantum computing in physics and chemistry. © 2025, CC BY.

关键词： Wave functions

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IA-LSTM: Interaction-Aware LSTM for Pedestrian Trajectory Prediction

arXiv

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arXiv 2023年

作者： Yang, Jing Chen, Yuehai Du, Shaoyi Chen, Badong Principe, Jose C. School of Automation Science and Engineering Faculty of Electronic and Information Engineering Xi'an Jiaotong Xi'An710049 China Institute of Articial Intelligence and Robotics College of Articial Intelligence Xi'an Jiaotong University Shanxi Xi'An710049 China The Computational NeuroEngineering Laboratory Department of Electrical and Computer Engineering University of Florida GainesvilleFL32611 United States

Predicting the trajectory of pedestrians in crowd scenarios is indispensable in self-driving or autonomous mobile robot field because estimating the future locations of pedestrians around is beneficial for policy decision to avoid collision. It is a challenging issue because humans have different walking motions, and the interactions between humans and objects in the current environment, especially between humans themselves, are complex. Previous researchers focused on how to model human-human interactions but neglected the relative importance of interactions. To address this issue, a novel mechanism based on correntropy is introduced. The proposed mechanism not only can measure the relative importance of human-human interactions but also can build personal space for each pedestrian. An interaction module including this data-driven mechanism is further proposed. In the proposed module, the data-driven mechanism can effectively extract the feature representations of dynamic human-human interactions in the scene and calculate the corresponding weights to represent the importance of different interactions. To share such social messages among pedestrians, an interaction-aware architecture based on long short-term memory network for trajectory prediction is designed. Experiments are conducted on two public datasets. Experimental results demonstrate that our model can achieve better performance than several latest methods with good performance. © 2023, CC BY-NC-ND.

关键词： Long short-term memory

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Parametric amplification of an optomechanical quantum interconnect

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Physical Review Research 2022年第4期4卷 043119-043119页

作者： Huo Chen Marti Vives Mekena Metcalf Applied Mathematics and Computational Research Division Lawrence Berkeley National Laboratory Berkeley California 94720 USA Department of Electrical and Computer Engineering Princeton University Princeton New Jersey 08544 USA

Connecting superconducting qubits to optical fiber necessitates the conversion of microwave photons to optical photons. Modern experimental demonstrations exhibit strong coupling between a microwave resonator and an optical cavity mediated through phononic modes in a mechanical oscillator. This paradigmatic transduction experiment is bounded by a theoretical efficiency with constant driving amplitudes on electromagnetic resonators. By adding a parametric drive to the microwave resonator and optical cavity, we discover the converted signal through the quantum transducer is amplified, while maintaining a lower level of the added noise. We propose a theoretical framework for time-dependent control of the driving lasers based on the input-output formalism of quantum optics and solve analytically the transduction efficiency and added noise when the control signals parametrically drive the system. Our results show better transduction efficiency and lower added noise in varying parameter regimes relevant to current transduction experiments.

关键词： Hybrid quantum systems Optomechanics Quantum cavities Perturbative methods Quantum theory

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Augmented weighted K-means grey wolf optimizer: An enhanced metaheuristic algorithm for data clustering problems (vol 14, 5434, 2024)

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SCIENTIFIC REPORTS 2024年第1期14卷 1-33页

作者： Premkumar, Manoharan Sinha, Garima Ramasamy, Manjula Devi Sahu, Santhoshini Subramanyam, Chithirala Bala Sowmya, Ravichandran Abualigah, Laith Derebew, Bizuwork Department of Electrical & Electronics Engineering Dayananda Sagar College of Engineering Kumaraswamy Layout Bengaluru Karnataka 560078 India Department of Computer Science and Engineering Jain University Ramanagaram Bengaluru Karnataka India Department of Computer Science and Engineering KPR Institute of Engineering and Technology Coimbatore Tamil Nadu India Department of Computer Science & Engineering GMR Institute of Technology Rajam Srikakulam Andhra Pradesh India Department of Electrical and Electronics Engineering Manipal Institute of Technology Manipal Academy of Higher Education Manipal Karnataka India Computer Science Department Al al-Bayt University Mafraq 25113 Jordan Artificial Intelligence and Sensing Technologies (AIST) Research Center University of Tabuk 71491 Tabuk Saudi Arabia Hourani Center for Applied Scientific Research Al-Ahliyya Amman University Amman 19328 Jordan MEU Research Unit Middle East University Amman 11831 Jordan Department of Electrical and Computer Engineering Lebanese American University Byblos 13-5053 Lebanon School of Engineering and Technology Sunway University Malaysia 27500 Petaling Jaya Malaysia College of Engineering Yuan Ze University Taoyuan Taiwan Department of Statistics College of Natural and Computational Science Mizan-Tepi University Tepi Bushira Ethiopia Applied science research center Applied science private university Amman 11931 Jordan Department of Computer Science and Engineering Vardhaman College of Engineering Hyderabad India

This study presents the K-means clustering-based grey wolf optimizer, a new algorithm intended to improve the optimization capabilities of the conventional grey wolf optimizer in order to address the problem of data clustering. The process that groups similar items within a dataset into non-overlapping groups. Grey wolf hunting behaviour served as the model for grey wolf optimizer, however, it frequently lacks the exploration and exploitation capabilities that are essential for efficient data clustering. This work mainly focuses on enhancing the grey wolf optimizer using a new weight factor and the K-means algorithm concepts in order to increase variety and avoid premature convergence. Using a partitional clustering-inspired fitness function, the K-means clustering-based grey wolf optimizer was extensively evaluated on ten numerical functions and multiple real-world datasets with varying levels of complexity and dimensionality. The methodology is based on incorporating the K-means algorithm concept for the purpose of refining initial solutions and adding a weight factor to increase the diversity of solutions during the optimization phase. The results show that the K-means clustering-based grey wolf optimizer performs much better than the standard grey wolf optimizer in discovering optimal clustering solutions, indicating a higher capacity for effective exploration and exploitation of the solution space. The study found that the K-means clustering-based grey wolf optimizer was able to produce high-quality cluster centres in fewer iterations, demonstrating its efficacy and efficiency on various datasets. Finally, the study demonstrates the robustness and dependability of the K-means clustering-based grey wolf optimizer in resolving data clustering issues, which represents a significant advancement over conventional techniques. In addition to addressing the shortcomings of the initial algorithm, the incorporation of K-means and the innovative weight factor into the gre

关键词： computational intelligence Data mining Grey wolf optimizer K-means clustering Optimization algorithm

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Mechatronic Design for Multi Robots-Insect Swarms Interactions

Mechatronic Design for Multi Robots-Insect Swarms Interactio...

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2023 IEEE International Conference on Mechatronics (ICM)

作者： Fatemeh Rekabi-Bana Martin Stefanec Jiří Ulrich Erhan E. Keyvan Tomáš Rouček George Broughton Bilal Y. Gündeǧer Ömer Sahin Ali E. Turgut Erol Şahin Tomáš Krajník Thomas Schmickl Farshad Arvin Department of Computer Science Swarm & Computational Intelligence Laboratory (SwaCIL) Durham University UK Artificial Life Lab University of Graz Austria Faculty of Electrical Engineering Czech Technical University Czechia Middle East Technical University Türkiye

This paper presents the concept of a robotic system collaborating with a swarm of social insects inside their hive. This robot consists of a micro-and macro-manipulator and a tracking system. The micro-manipulator uses bio-mimetic agents to interact with an individual specimen. The macromanipulator positions and keeps the micro-manipulator’s base around the given individual while moving in the hive. This individual is tracked by a fiducial marker-based visual detection and localisation system, which also provides positions of the biomimetic agents. The base of the system was experimentally verified in a honeybee observation hive, where it flawlessly tracked the honeybee queen for several hours, gathering sufficient data to extract the behaviours of honeybee workers in the queen’s vicinity. These data were then used in simulation to verify if the micro-manipulator’s bio-mimetic agents could mimic some of the honeybee workers’ behaviours.

关键词： Visualization Mechatronics Tracking Databases Machine vision Insects Data models

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Gradient and non-gradient-based first order reliability method for robust and accurate structural reliability analysis

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Procedia Structural Integrity 2023年 48卷 348-355页

作者： Behrooz Keshtegar Mohamed El Amine Ben Seghier José A.F.O. Correia Department of Civil Engineering Faculty of Engineering University of Zabol P.B. *** Zabol Iran Laboratory for Computational Mechanics Institute for Computational Science and Artificial Intelligence Van Lang University Ho Chi Minh City Vietnam Faculty of Mechanical - Electrical and Computer Engineering School of Technology Van Lang University Ho Chi Minh City Vietnam INEGI Faculty of Engineering University of Porto Rua Dr. Roberto Frias 4200-465 Porto Portugal

The first order reliability method (FORM) may provide unstable and inaccurate results for gray/ highly nonlinear performance functions. In this study, FORM approaches based on gradient and non-gradient methods are compared for both accuracy and robustness of results in nonlinear/complex reliability problems. Two gradient based sensitivity vectors using steepest descent search direction as (HL-RF) and directional stability transformation method (DSTM) are compared to two non-gradient approaches of harmony search optimization (HS) and particle swarm optimization (PSO). A refined probabilistic model using FORM is used for non-gradient optimization methods. The accuracy and robustness of FORM-based gradient formulations and refined FORM-based non-gradient approaches are compared on nonlinear/complex performance functions. The comparative results demonstrate that the PSO-based refined FORM provides accurate and robust results compared to FORM using HL-RF and DSTM. In addition to that, PSO shows superior performances compared to HS and gradient-FORM in complex engineering structures applications.

关键词： Type your keywords here separated by semicolons

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