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Learning a Subspace and Clustering Simultaneously with Manifold Regularized Nonnegative Matrix Factorization

Guidance, Navigation and Control 2024年第3期4卷 147-165页

作者： Feiping Nie Huimin Chen Heng Huang Chris H.Q.Ding Xuelong Li School of Computer Science Northwestern Polytechnical University Xi'an 710072 P.R.China School of Artificial Intelligence Optics and Electronics(iOPEN)Northwestern Polytechnical University Xi'an 710072 P.R.China Key Laboratory of Intelligent Interaction and Applications(Northwestern Polytechnical University)Ministry of Industry and Information Technology Xi'an 710072 P.R.China Department of Electrical and Computer Engineering University of Pittsburgh PittsburghPA 15260USA Department of Computer Science and Engineering The Chinese University of Hong Kong Shenzhen 518172 P.R.China Institute of Artificial Intelligence(TeleAI)China Telecom Corporation Limited 31 Jinrong Street Beijing 100033P.R.China

With the incredible growth of high-dimensional data such as microarray gene expression data and web blogs from internet, the researchers are desirable to develop new clustering techniques to address the critical problem created by irrelevant dimensions. Properties of Nonnegative Matrix Factorization(NMF) as a clustering method were studied by relating its formulation to other methods such as K-means clustering. In this paper, by introducing clustering indicator constraints on NMF and incorporating manifold regularization to preserve geometric structures,we propose a novel manifold regularized NMF method that can simultaneously learn subspace and do clustering. As a result, our clustering results can directly assign cluster label to data points. Extensive experimental results show that our method outperforms related other methods.

关键词： Subspace learning clustering nonnegative matrix factorization manifold learning

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A Digital Twin-Driven Hybrid Estimate Method for Health Status of Train Braking System 25

A Digital Twin-Driven Hybrid Estimate Method for Health Stat...

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25th IEEE International Conference on computer Supported Cooperative Work in Design, CSCWD 2022

作者： Peng, Jun Zhao, Qin Gao, Dianzhu Yang, Yingze Zhou, Feng Rong, Jieqi Fan, Yunsheng Liu, Bowen Jiang, Fu Zhang, Xiaoyong Central South University School of Computer Science and Engineering Changsha China Central South University School of Automation Changsha China Changsha University of Science and Technology School of Electrical and Information Engineering Changsha China Hunan Engineering Laboratory of Rail Vehicles Braking Technology Changsha China

ISBN: (纸本)9781665405270

The braking system is the key part of trains, and its full life-cycle of health status is essential to ensure the safety of trains. How to accurately assess real-time health status throughout the full life-cycle of the train braking system is a challenge. In this paper, a digital twin-driven hybrid estimate method for health status of the braking system is proposed. Firstly, an equivalent model of the braking system is built in the digital twin platform. Then, a hybrid method of fusing model and data is proposed to assess the health status. Finally, a cloud digital twin experimental platform for health status assessment of the braking system is built, and the health status is shown by visualization framework. The experiments verify the effectiveness and practicality of the proposed scheme. © 2022 IEEE.

关键词： Life cycle

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Inspection of a helicopter blade using drone based active thermography 45

Inspection of a helicopter blade using drone based active th...

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Thermosense: Thermal Infrared Applications XLV 2023

作者： Pant, Shashank Genest, Marc Ibarra-Castanedo, Clemente Avdelidis, Nicolas P. Valdes, Julio Deane, Shakeb Zolotas, Argyrios Maldague, Xavier P. National Research Council Canada OttawaONK1A 0R6 Canada Computer Vision and Systems Laboratory Department of Electrical and Computer Engineering Laval University Quebec CityQCG1V 0A6 Canada School of Aerospace Transport and Manufacturing Cranfield University CranfieldMK43 0AL United Kingdom

ISBN: (纸本)9781510661868

A drone-based inspection system that can move "freely" around an aircraft to perform the inspection of all the areas of interest in a fast and effective manner can have significant impact in reducing inspection time and cost. However, active thermography inspection using drone is challenging because the drone carrying the optical and thermal cameras is subjected to vibration and undesired motion. Since active thermography relies on the pixel temperature evolution over time, an unstable thermal video from a flying drone can cause error in the output results as any movement between the acquired images will affect the pixel position in the successive frames and thus disrupt the monitoring of the temperature evolution. This paper presents the outcome of experimental runs, where a commercially available drone equipped with both thermal and optical cameras was used to inspect a helicopter Main Rotor Blade (MRB) in a laboratory environment. © 2023 SPIE.

关键词： Inspection

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Sequential generation of self-starting diverse operations in all-fiber laser based on thulium-doped fiber saturable absorber

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Chinese Physics B 2022年第6期31卷 87-90页

作者： Pei Zhang Kaharudin Dimyati Bilal Nizamani Mustafa M.Najm S.W.Harun School of Electrical and Information Engineering Huaihua UniversityHuaihua 418008China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua UniversityHuaihua 418008China Department of Electrical Engineering Faculty of EngineeringUniversity of MalayaKuala Lumpur 50603Malaysia Faculty of Advanced Technology and Multidiscipline Airlangga UniversitySurabaya 60115Indonesia Institute of Computer Science and Digital Innovation UCSI UniversityKuala LumpurMalaysia

Self-starting Q-switching,Q-switched mode-locking and mode-locking operation modes are achieved sequentially in an all-fiber erbium-doped fiber laser with thulium-doped fiber saturable absorber for the first *** central wavelengths of Q-switching,Q-switched mode-locking and mode-locking operation modes are 1569.7 nm,1570.9 nm,and 1572 nm,*** mode-locking operation of the proposed fiber laser generates stable dark soliton with a repetition rate of 0.99 MHz and signal-to-noise ratio of 65 *** results validate the capability of generating soliton pulse by doped fiber saturable ***,the proposed fiber laser is beneficial to the applications of optical communication and signal processing system.

关键词： all-fiber laser Q-switched mode-locking dark soliton fiber saturable absorber

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Annotating TSSs in Multiple Cell Types Based on DNA Sequence and RNA-seq Data via DeeReCT-TSS

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Genomics, Proteomics & Bioinformatics 2022年第5期20卷 959-973页

作者： Juexiao Zhou Bin Zhang Haoyang Li Longxi Zhou Zhongxiao Li Yongkang Long Wenkai Han Mengran Wang Huanhuan Cui Jingjing Li Wei Chen Xin Gao Computer Science Program ComputerElectrical and Mathematical Sciences and Engineering DivisionKing Abdullah University of Science and TechnologyThuwal 23955-6900Saudi Arabia Computational Bioscience Research Center King Abdullah University of Science and TechnologyThuwal 23955-6900Saudi Arabia Department of Biology School of Life SciencesSouthern University of Science and TechnologyShenzhen 518055China Shenzhen Key Laboratory of Gene Regulation and Systems Biology School of Life SciencesSouthern University of Science and TechnologyShenzhen 518055China Academy for Advanced Interdisciplinary Studies Southern University of Science and TechnologyShenzhen 518055China

The accurate annotation of transcription start sites(TSSs)and their usage are critical for the mechanistic understanding of gene regulation in different biological *** fulfill this,specific high-throughput experimental technologies have been developed to capture TSSs in a genome-wide manner,and various computational tools have also been developed for in silico prediction of TSSs solely based on genomic *** of these computational tools cast the problem as a binary classification task on a balanced dataset,thus resulting in drastic false positive predictions when applied on the genome ***,we present Dee Re CT-TSS,a deep learningbased method that is capable of identifying TSSs across the whole genome based on both DNA sequence and conventional RNA sequencing *** show that by effectively incorporating these two sources of information,Dee Re CT-TSS significantly outperforms other solely sequence-based methods on the precise annotation of TSSs used in different cell ***,we develop a meta-learning-based extension for simultaneous TSS annotations on 10 cell types,which enables the identification of cell type-specific ***,we demonstrate the high precision of DeeReCT-TSS on two independent datasets by correlating our predicted TSSs with experimentally defined TSS chromatin *** source code for Dee Re CT-TSS is available at https://github.-com/Joshua Chou2018/Dee Re CT-TSS_release and https://***/biocode/tools/BT007316.

关键词： Transcription start site Machine learning Deep learning Meta-learning RNA sequencing

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SEMI-CONTRANS: Semi-Supervised Medical Image Segmentation via Multi-Scale Feature Fusion and Cross Teaching of CNN and Transformer

SEMI-CONTRANS: Semi-Supervised Medical Image Segmentation vi...

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IEEE International Symposium on Biomedical Imaging

作者： Weiren Zhao Lanfeng Zhong Guotai Wang School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Mechanical and Electrical Engineering University of Electronic Science and Technology of China Chengdu China Shanghai Artificial Intelligence Laboratory China

ISBN: (数字)9798350313338

ISBN: (纸本)9798350313345

Convolutional Neural Networks (CNNs) and Transformers have achieved promising results in fully supervised medical image segmentation. However, acquiring high-quality annotations for medical images is prohibitively expensive, making semi-supervised learning a promising way to reduce the annotation cost by leveraging both labeled and unlabeled images for training. In this work, we propose a novel model named Semi-ConTrans that unifies the advantages of CNNs and Transformers through multi-scale feature fusion and cross teaching for semi-supervised segmentation. Specifically, to leverage localization capability from CNNs and global context modeling of self-attention in Transformers in a unified framework, we adaptively fuse them at multiple scales in the encoder. Furthermore, we use a CNN decoder and a Transformer decoder with different decision boundaries for cross teaching, obtaining more holistic pseudo labels for dealing with unlabeled images. Experiments on the ACDC dataset of cardiac images demonstrate that our approach greatly improves the performance with only 10% or 20% labeled images by exploiting unlabeled images, outperforming eight state-of-the-art semi-supervised segmentation methods.

关键词： Training Location awareness Image segmentation Annotations Fuses Semisupervised learning Transformers

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RoboFold: A platform for Protein-folding Inspired Robot Swarms ∗ 5

RoboFold: A platform for Protein-folding Inspired Robot Swar...

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5th World Robot Conference Symposium on Advanced Robotics and Automation, WRC SARA 2023

作者： Zhang, Feng Gu, Yuping Yuan, Shuai Yang, Yongliang Shenyang Jianzhu University School of Electrical and Control Engineering Liaoning Shenyang110168 China Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Liaoning Shenyang110016 China Shenyang Jianzhu University School of Computer Science and Engineering School of Electrical and Control Engineering Liaoning Shenyang110168 China

ISBN: (纸本)9798350307320

Natural swarms have inspired various controlling algorithms for swarm robotics, while few of them were programmed in a similar way as the natural swarms. Defining a reliable programming method is still a daunting challenge in swarm robotics. In nature, the information of 3D protein structure is programmed in the sequence of amino acids of the protein. To mimic the programming method of protein folding, we present a platform for investigating protein-folding inspired programming method for robot swarms. This platform includes three parts: a vibration machine, protein-like robot sequences, and recording devices. The preliminary results presented here demonstrated the effectiveness of this platform and the feasibility of protein-folding inspired programming method for robot swarms. © 2023 IEEE.

关键词： Protein folding

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Ultra-Thin ta-C Hermetic Seals for Electronics Packaging

Ultra-Thin ta-C Hermetic Seals for Electronics Packaging

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Electronics Packaging Technology Conference (EPTC)

作者： Eric JR Phua Tan Yik Kai Lum Ya Woon Li Ying Jacob Lim Tay Yu Shan Gan Chee Lip Shi Xu Nanofilm Technologies International Ltd Singapore NTI-NTU Corporate Laboratory Singapore School of Electrical and Electronic Engineering (NTU) Singapore School of Materials Science and Engineering (NTU) Singapore Department of Electrical and Computer Engineering (NUS) Singapore

ISBN: (数字)9798331522001

ISBN: (纸本)9798331522018

The increasing demand for compact high-performance electronic devices necessitates the development of advanced materials that are capable of providing effective hermetic sealing. Tetrahedral Amorphous Carbon (ta-C) deposited by Filtered Cathodic Vacuum Arc (FCVA) has garnered attention as a promising alternative because of its exceptional barrier characteristics, mechanical durability, and optical properties. This paper presents a comprehensive analysis of ta-C attributes as an encapsulating material [1], supported by empirical evidence, and investigates its potential application in protecting electronic components. The research demonstrated that ta-C coatings exhibited minimal changes in resistance under elevated humidity and temperature conditions (85% RH, 85°C) for up to 792 h, with Set 1 samples displaying less than 5% variation in electrical resistance. The ta-C films also achieved an adhesion rating of ASTM 5B on both silicon and glass substrates. Water contact angle measurements revealed hydrophilicity with an average angle of 73.84° on silicon, further corroborating the suitability of the material for hermetic sealing applications.

关键词： Optical filters Temperature measurement Encapsulation Silicon Mechanical factors Optical sensors Optical films Protection Thermal stability Immune system

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Low-Complexity Iterative Precoding Design for Near-field Multiuser Systems With Spatial Non-Stationarity

arXiv

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arXiv 2025年

作者： Liu, Mengyu Pan, Cunhua Zhi, Kangda Ren, Hong Wang, Cheng-Xiang Wang, Jiangzhou Eldar, Yonina C. National Mobile Communications Research Laboratory Southeast University Nanjing211189 China School of Electrical Engineering and Computer Science Technical University of Berlin Berlin10623 Germany Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot7610001 Israel

Extremely large antenna arrays (ELAA) are regarded as a promising technology for supporting sixth-generation (6G) networks. However, the large number of antennas significantly increases the computational complexity in precoding design, even for linearly regularized zero-forcing (RZF) precoding. To address this issue, a series of low-complexity iterative precoding are investigated. The main idea of these methods is to avoid matrix inversion of RZF precoding. Specifically, RZF precoding is equivalent to a system of linear equations that can be solved by fast iterative algorithms, such as random Kaczmarz (RK) algorithm. Yet, the performance of RK-based precoding algorithm is limited by the energy distributions of multiple users, which restricts its application in ELAA-assisted systems. To accelerate the RK-based precoding, we introduce the greedy random Kaczmarz (GRK)-based precoding by using the greedy criterion-based selection strategy. To further reduce the complexity of the GRK-based precoding, we propose a visibility region (VR)-based orthogonal GRK (VR-OGRK) precoding that leverages near-field spatial non-stationarity, which is characterized by the concept of VR. Next, by utilizing the information from multiple hyperplanes in each iteration, we extend the GRK-based precoding to the aggregation hyperplane Kaczmarz (AHK)-based pecoding algorithm, which further enhances the convergence rate. Building upon the AHK algorithm, we propose a VR-based orthogonal AHK (VR-OAHK) precoding to further reduce the computational complexity. Furthermore, the proposed iterative precoding algorithms are proven to converge to RZF globally at an exponential rate. Simulation results show that the proposed algorithms achieve faster convergence and lower computational complexity than benchmark algorithms, and yield very similar performance to the RZF precoding. Copyright © 2025, The Authors. All rights reserved.

关键词： Near field communication

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Localization of Image Splicing Under Segment Anything Model With Integrated Compression and Edge Artifacts

Localization of Image Splicing Under Segment Anything Model ...

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IEEE International Conference on Image Processing

作者： Ruhao Zhao Xian Zhong Liang Liao Wenxuan Liu Wenxin Huang Zheng Wang School of Computer Science and Artificial Intelligence Hubei Key Laboratory of Transportation Internet of Things Wuhan University of Technology School of Electrical and Electronic Engineering Rapid-Rich Object Search Lab Nanyang Technological University College of Computing and Data Science Nanyang Technological University School of Computer Science and Information Engineering Hubei University School of Computer Science National Engineering Research Center for Multimedia Software Wuhan University

ISBN: (数字)9798350349399

ISBN: (纸本)9798350349405

The localization of image splicing involves identifying pixels in an image that have been spliced from other images, necessitating the discernment of splicing features. Despite significant advancements driven by the rise of social media and deep learning, existing methods exhibit limitations, often neglecting the integration of coarse and precise features and lacking the ability to understand objects. This leads to erroneous predictions in identifying spliced regions. This paper proposes Segment Anything Model with Integrated Compression and Edge artifacts (SAM-ICE) for the localization of image splicing, addressing these limitations by fusing forged edge features and compression artifact features. Leveraging SAM’s object understanding ability, our method identifies spliced regions using the fused features as guidance. Specifically, we employ Edge Artifact Extractor (EAE) to extract fine high-frequency edge splicing features and Compression Artifact Extractor (CAE) to extract coarse compression artifact features. By combining these features, our method utilizes coarse-fine features to accurately pinpoint the spliced portions of the image. Experimental results demonstrate the superior accuracy, robustness, and generalizability of our method compared to the state-of-the-arts.

关键词： Location awareness Image segmentation Image coding Social networking (online) Image edge detection Splicing Feature extraction

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