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Topology-optimized thermal metamaterials traversing full-parameter anisotropic space

npj Computational Materials 2022年第1期8卷 1717-1726页

作者： Wei Sha Run Hu Mi Xiao Sheng Chu Zhan Zhu Cheng-Wei Qiu Liang Gao State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan430074China State Key Laboratory of Coal Combustion School of Energy and Power EngineeringHuazhong University of Science and TechnologyWuhan430074China School of Engineering Cardiff UniversityCardiffCF243AAUnited Kingdom Department of Electrical and Computer Engineering National University of SingaporeKent Ridge117583Republic of Singapore

It is widely adopted in thermal metamaterials that mixing different materials could conveniently result in effective thermal conductivities(ETCs)beyond naturally-occurring *** multiple materials are isotropically mixed,the ETC is a direct average governed by their filling fractions and given bulk *** could lead to an inhomogeneous and anisotropic value within the maximal and minimal thermal conductivities of constituent *** thermal metadevices rely on anisotropic thermal conductivity tensor,whose tensorial elements are frequently inter-dependent and confined within a limited parametric *** is thus nontrivial to establish a design recipe for advanced thermal metamaterials whose ETCs could cover full-parameter anisotropic *** demonstrate topological functional cells(TFCs)with copper and polydimethylsiloxane,and show that the anisotropic ETCs traverse their full-parameter *** robust scheme based on topology-optimized TFCs unlocks unexplored opportunities for functional thermal metadevices whose parameters may not be reached in previous mixing *** study also sheds light on the developments in emerging acoustic,mechanical and electromagnetic composite materials.

关键词： parameter mixing thermal

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Automation 5.0: The Key to systems Intelligence and Industry 5.0

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1723-1727页

作者： Ljubo Vlacic Hailong Huang Mariagrazia Dotoli Yutong Wang Petros A.Ioannou Lili Fan Xingxia Wang Raffaele Carli Chen Lv Lingxi Li Xiaoxiang Na Qing-Long Han Fei-Yue Wang Institute of Intelligent and Integrated Systems and the School of Engineering and Built Environment Griffith UniversityNathanQLD 4111Australia Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic UniversityHong KongChina Department of Electrical and Information Engineering Polytechnic of Bari70126 BariItaly State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190and also with the Qingdao Academy of Intelligent IndustriesQingdao 266114China Department of Electrical Engineering-Systems University of Southern CaliforniaLos AngelesCA 90007 USA School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049 Beijing Huairou Academy of Parallel Sensing Beijing 101499China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University IndianapolisIndianapolisIN 46202 USA Department of Engineering University of CambridgeCB21TN CambridgeU.K. School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Dazhou Artificial Intelligence Institute Dazhouand the Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China

AUTOMATION has come a long way since the early days of mechanization,i.e.,the process of working exclusively by hand or using animals to work with *** rise of steam engines and water wheels represented the first generation of industry,which is now called Industry Citation:***,***,***,***,***,***,***,***,***,***,***,Q.-***,and F.-***,“Automation 5.0:The key to systems intelligence and Industry 5.0,”IEEE/CAA ***,vol.11,no.8,pp.1723-1727,Aug.2024.

关键词： Automation machinery intelligence

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Arbitrarily polarized bound states in the continuum with twisted photonic crystal slabs

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Light(science & Applications) 2023年第4期12卷 542-550页

作者： Haoye Qin Zengping Su Mengqi Liu Yixuan Zeng Man-Chung Tang Mengyao Li Yuzhi Shi Wei Huang Cheng-Wei Qiu Qinghua Song Tsinghua Shenzhen International Graduate School Tsinghua UniversityShenzhen 518055China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore Institute of Precision Optical Engineering School of Physics Science and EngineeringTongji UniversityShanghai 200092China Key Laboratory of Multifunctional Nanomaterials and Smart Systems Suzhou institute of Nano-Tech and Nano-Bionics(SINANO)Chinese Academy of Sciences(CAS)Suzhou 215123China

Arbitrary polarized vortex beam induced by polarization singularity offers a new platform for both classical optics and quantum entanglement *** states in the continuum(BICs)have been demonstrated to be associated with topological charge and vortex polarization singularities in momentum *** conventional symmetric photonic crystal slabs(PhCSs),BIC is enclosed by linearly polarized far fields with winding angle of 2π,which is unfavorable for high-capacity and multi-functionality integration-optics ***,we show that by breakingσz-symmetry of the PhCS,asymmetry in upward and downward directions and arbitrarily polarized BIC can be realized with a bilayer-twisted *** exhibits elliptical polarization states with constant ellipticity angle at every point in momentum space within the vicinity of *** topological nature of BIC reflects on the orientation angle of polarization state,with a topological charge of 1 for any value of ellipticity *** coverage of Poincarésphere(i.e.,-π/4≤X≤4 and-π/2≤ψ≤π/2)and higher-order Poincarésphere can be realized by tailoring the twist *** findings may open up new avenues for applications in structured light,quantum optics,and twistronics for photons.

关键词： Poincaré polarized twisted

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Self-Supervised Reflective Learning Through Self-Distillation and Online Clustering for Speaker Representation Learning

IEEE Transactions on Audio, Speech and Language Processing

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IEEE Transactions on Audio, Speech and Language Processing 2025年 33卷 1535-1550页

作者： Danwei Cai Zexin Cai Ze Li Ming Li Department of Electrical and Computer Engineering Duke University Durham NC USA Suzhou Municipal Key Laboratory of Multimodal Intelligent Systems Digital Innovation Research Center Duke Kunshan University Kunshan China School of Computer Science Wuhan University Wuhan China

Speaker representation learning is crucial for voice recognition systems, with recent advances in self-supervised approaches reducing dependency on labeled data. Current two-stage iterative frameworks, while effective, suffer from significant computational overhead due to repeated rounds of clustering and training. They also struggle with noisy pseudo labels that can impair model learning. This paper introduces self-supervised reflective learning (SSRL), an improved framework that addresses these limitations by enabling continuous refinement of pseudo labels during training. Through a teacher-student architecture and online clustering mechanism, SSRL eliminates the need for iterative training rounds. To handle label noise, we incorporate noisy label modeling and pseudo label queues that maintain temporal consistency. Experiments on VoxCeleb show SSRL's superiority over current two-stage iterative approaches, surpassing the performance of a 5-round method in just a single training round. Ablation studies validate the contributions of key components like noisy label modeling and pseudo label queues. Moreover, consistent improvements in pseudo labeling and the convergence of cluster counts demonstrate SSRL's effectiveness in deciphering unlabeled data. This work marks an important advancement in efficient and accurate self-supervised speaker representation learning through the novel reflective learning paradigm.

关键词： Training Representation learning Iterative methods Noise Adaptation models Noise measurement Predictive models Speech processing Robustness Convergence

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Dynamics of self-hybridized exciton–polaritons in 2D halide perovskites

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Light(science & Applications) 2024年第1期13卷 13-22页

作者： Surendra B.Anantharaman Jason Lynch Christopher E.Stevens Christopher Munley Chentao Li Jin Hou Hao Zhang Andrew Torma Thomas Darlington Francis Coen Kevin Li Arka Majumdar PJames Schuck Aditya Mohite Hayk Harutyunyan Joshua R.Hendrickson Deep Jariwala Department of Electrical and Systems Engineering University of PennsylvaniaPhiladelphiaPA19104USA KBR Inc. BeavercreekOH45431USA Air Force Research Laboratory Sensors DirectorateWright-Patterson Air Force BaseOH45433USA Department of Physics University of WashingtonSeattleWA98195USA Department of Physics Emory UniversityAtlantaGA30322USA Department of Chemical and Biomolecular Engineering Rice UniversityHoustonTX77005USA Department of Materials Science and Nanoengineering Rice UniversityHoustonTX77005USA Applied Physics Program Smalley‐Curl InstituteRice UniversityHoustonTX77005USA Department of Mechanical Engineering Columbia UniversityNew YorkNY10027USA Department of Electrical and Computer Engineering University of WashingtonSeattleWA98195USA

Excitons,bound electron–hole pairs,in two-dimensional hybrid organic inorganic perovskites(2D HOIPs)are capable of forming hybrid light-matter states known as exciton-polaritons(E–Ps)when the excitonic medium is confined in an optical *** the case of 2D HOIPs,they can self-hybridize into E–Ps at specific thicknesses of the HOIP crystals that form a resonant optical cavity with the ***,the fundamental properties of these self-hybridized E–Ps in 2D HOIPs,including their role in ultrafast energy and/or charge transfer at interfaces,remain ***,we demonstrate that>0.5µm thick 2D HOIP crystals on Au substrates are capable of supporting multiple-orders of self-hybridized E–P *** E–Ps have high Q factors(>100)and modulate the optical dispersion for the crystal to enhance sub-gap absorption and *** varying excitation energy and ultrafast measurements,we also confirm energy transfer from higher energy E–Ps to lower energy E–***,we also demonstrate that E–Ps are capable of charge transport and transfer at *** findings provide new insights into charge and energy transfer in E–Ps opening new opportunities towards their manipulation for polaritonic devices.

关键词： charge polar excitation

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Stability of the distributed Kalman filter using general random coefficients

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science China(Information sciences) 2021年第7期64卷 66-79页

作者： Die GAN Siyu XIE Zhixin LIU Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences The Department of Electrical and Computer Engineering Wayne State University

In this paper, we propose a distributed Kalman filter(DKF) for the dynamical system with general random coefficients. In the proposed method, each estimator shares local innovation pairs with its neighbors to collectively complete the estimation task. Further, we introduce a collective random observability condition by which the Lp-stability of the covariance matrix and the Lp-exponential stability of the homogeneous part of the estimation error equation can be established. In contrast, the stringent conditions on the coefficient matrices, such as independency and stationarity are not required. Besides, the stability of the DKF, i.e., the boundedness of the filtering errors, can be established. Finally, from the simulation result,we demonstrate the cooperative effect of the sensors.

关键词： distributed Kalman filter collective random observability $L_p$-stable $L_p$-exponentially stable state estimation

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Binary Bleed: Fast Distributed and Parallel Method for Automatic Model Selection

Binary Bleed: Fast Distributed and Parallel Method for Autom...

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2024 IEEE High Performance Extreme Computing Conference, HPEC 2024

作者： Barron, Ryan Eren, Maksim E. Bhattarai, Manish Boureima, Ismael Matuszek, Cynthia Alexandrov, Boian S. Theoretical Division Los Alamos National Laboratory Los Alamos United States University of Maryland Baltimore County Department of Computer Science and Electrical Engineering MD United States Advanced Research in Cyber Systems Los Alamos National Laboratory Los Alamos United States

ISBN: (纸本)9798350387131

In several Machine Learning (ML) clustering and dimensionality reduction approaches, such as nonnegative matrix factorization (NMF), RESCAL, and K-Means clustering, users must select a hyper-parameter k to define the number of clusters or components that yield an ideal separation of samples or clean clusters. This selection, while difficult, is crucial to avoid overfitting or underfitting the data. Several ML applications use scoring methods (e.g., Silhouette and Davies Boulding scores) to evaluate the cluster pattern stability for a specific k. The score is calculated for different trials over a range of k, and the ideal k is heuristically selected as the value before the model starts overfitting, indicated by a drop or increase in the score resembling an elbow curve plot. While the grid-search method can be used to accurately find a good k value, visiting a range of k can become time-consuming and computationally resource-intensive. In this paper, we introduce the Binary Bleed method based on binary search, which significantly reduces the k search space for these grid-search ML algorithms by truncating the target k values from the search space using a heuristic with thresholding over the scores. Binary Bleed is designed to work with single-node serial, single-node multi-processing, and distributed computing resources. In our experiments, we demonstrate the reduced search space gain over a naive sequential search of the ideal k and the accuracy of the Binary Bleed in identifying the correct k for NMFk, K-Means pyDNMFk, and pyDRESCALk with Silhouette and Davies Boulding scores. We make our implementation of Binary Bleed for the NMF algorithm available on GitHub. © 2024 IEEE.

关键词： Dimensionality reduction

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Marine Predators Algorithm with Deep Learning-Based Leukemia Cancer Classification on Medical Images

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computer Modeling in engineering & sciences 2024年第10期141卷 893-916页

作者： Sonali Das Saroja Kumar Rout Sujit Kumar Panda Pradyumna Kumar Mohapatra Abdulaziz S.Almazyad Muhammed Basheer Jasser Guojiang Xiong Ali Wagdy Mohamed Department of Computer Science&Engineering Gandhi Institute for TechnologyBPUTBhubaneswar752054India Department of Information Technology Vardhaman College of Engineering(Autonomous)Hyderabad501218TelanganaIndia Department of Electronic&Communication Engineering Vedang Institute of TechnologyBhubaneswar752010India Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computing and Information Systems School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Research Centre for Human-Machine Collaboration(HUMAC) School of Engineering and TechnologySunway UniversityJalan UniversitiBandar SunwaySelangor Darul Ehsan47500Malaysia Guizhou Key Laboratory of Intelligent Technology in Power System College of Electrical EngineeringGuizhou UniversityGuiyang550025China Operations Research Department Faculty of Graduate Studies for Statistical ResearchCairo UniversityGiza12613Egypt Applied Science Research Center Applied Science Private UniversityAmman11931Jordan

In blood or bone marrow,leukemia is a form of cancer.A person with leukemia has an expansion of white blood cells(WBCs).It primarily affects children and rarely affects *** depends on the type of leukemia and the extent to which cancer has established throughout the *** leukemia in the initial stage is vital to providing timely patient *** image-analysis-related approaches grant safer,quicker,and less costly solutions while ignoring the difficulties of these invasive *** can be simple to generalize computer vision(CV)-based and image-processing techniques and eradicate human *** researchers have implemented computer-aided diagnosticmethods andmachine learning(ML)for laboratory image analysis,hopefully overcoming the limitations of late leukemia detection and determining its *** study establishes a Marine Predators Algorithm with Deep Learning Leukemia Cancer Classification(MPADL-LCC)algorithm onMedical *** projectedMPADL-LCC system uses a bilateral filtering(BF)technique to pre-process medical *** MPADL-LCC system uses Faster SqueezeNet withMarine Predators Algorithm(MPA)as a hyperparameter optimizer for feature ***,the denoising autoencoder(DAE)methodology can be executed to accurately detect and classify leukemia *** hyperparameter tuning process using MPA helps enhance leukemia cancer classification *** results are compared with other recent approaches concerning various measurements and the MPADL-LCC algorithm exhibits the best results over other recent approaches.

关键词： Leukemia cancer medical imaging image classification deep learning marine predators algorithm

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Cyber-Security Knowledge Graph Generation by Hierarchical Nonnegative Matrix Factorization 12

Cyber-Security Knowledge Graph Generation by Hierarchical No...

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12th International Symposium on digital Forensics and Security, ISDFS 2024

作者： Barron, Ryan Eren, Maksim E. Bhattarai, Manish Wanna, Selma Solovyev, Nicholas Rasmussen, Kim Alexandrov, Boian S. Nicholas, Charles Matuszek, Cynthia Los Alamos National Laboratory Theoretical Division Los Alamos United States Los Alamos National Laboratory Advanced Research in Cyber Systems Los Alamos United States University of Maryland Department of Computer Science and Electrical Engineering Baltimore CountyMD United States

ISBN: (纸本)9798350330366

Much of human knowledge in cybersecurity is encapsulated within the ever-growing volume of scientific papers. As this textual data continues to expand, the importance of document organization methods becomes increasingly crucial for extracting actionable insights hidden within large text datasets. Knowledge Graphs (KGs) serve as a means to store factual information in a structured manner, providing explicit, interpretable knowledge that includes domain-specific information from the cybersecurity scientific literature. One of the challenges in constructing a KG from scientific literature is the extraction of ontology from unstructured text. In this paper, we address this topic and introduce a method for building a multi-modal KG by extracting structured ontology from scientific papers. We demonstrate this concept in the cybersecurity domain. One modality of the KG represents observable information from the papers, such as the categories in which they were published or the authors. The second modality uncovers latent (hidden) patterns of text extracted through hierarchical and semantic non-negative matrix factorization (NMF), such as named entities, topics or clusters, and keywords. We illustrate this concept by consolidating more than two million scientific papers uploaded to arXiv into the cyber-domain, using hierarchical and semantic NMF, and by building a cyber-domain-specific KG. © 2024 IEEE.

关键词： Cybersecurity

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Low-cost contact-free screen control based on machine vision 4

Low-cost contact-free screen control based on machine vision

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4th Optics Frontier Conference, OFS 2024

作者： Lin, Yangbing Wang, Teng Yan, Wei Peng, Xiao Zhang, Xinhai Department of Electrical and Electronic Engineering Southern University of Science and Technology Shenzhen518055 China College of Physics and Optoelectronic Engineering Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province Shenzhen University Shenzhen518060 China School of Computer Science and Engineering South China University of Technology Guangzhou510641 China

ISBN: (纸本)9781510682269

Contact-free manipulation technology represents a novel approach that offers a fresh possibility for human-machine interaction, aiming to meet the evolving demands of this interface. In this paper, we introduce a contact-free planar display control technique based on imaging. In our research, we employ cameras as sensors and integrate infrared lasers with image processing techniques to detect and localize input signals. By establishing a coordinate mapping relationship between the operational plane and the display plane, we achieved contact-free control over the planar display. Our paper introduces two methods for establishing this coordinate mapping. The first involves constructing mapping functions between the rectified and transformed camera imagery and the display plane, thereby creating a point-to-point correspondence. The second method entails dividing both the camera imagery and the display plane into segments, establishing a one-to-one relationship between regions. We analyze the strengths and limitations of these two approaches. While the former boasts higher theoretical precision, it is more susceptible to equipment factors and exhibits slower response speeds. Conversely, the latter, despite its lower theoretical precision, offers faster response times. Through the setup of an experimental platform, we demonstrate the feasibility of our proposed. © 2024 SPIE.

关键词： Machine vision

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