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Depth Completion With Super-Resolution and Cross-Modality Optimization

IEEE Robotics and Automation Letters 2025年第6期10卷 5585-5592页

作者： Zhong, Ju Jiang, Aimin Liu, Chang Xu, Ning Zhu, Yanping Hohai University College of Information Science and Engineering Changzhou210098 China Changzhou University School of Microelectronics and Control Engineering Changzhou213164 China

Depth completion, the process of generating dense depth maps from sparse or incomplete data, is inherently challenging due to the variability in sensor types, environmental conditions, and the differences between data modalities. In this letter, we propose a novel framework for depth completion. First, we introduce an efficient depth estimation network capable of predicting relative depth from a single RGB image. Next, we design a depth super-resolution network that refines the predicted depth by using Fast Fourier Convolution (FFC) and Gradient-weighted Symmetric Feature Transmission (GSFT) modules. These modules upsample the depth map using high-resolution RGB guidance, effectively mitigating the cross-modality gap. Finally, a global optimization step fuses the upsampled depth with sparse ground truth to produce high-quality dense depth maps. Our unified approach enhances generalization across diverse datasets while avoiding overfitting to specific depth corruption patterns. The enhancement in depth resolution and accuracy are critical for robotic applications requiring precise spatial perception, such as localization and manipulation. Experimental results on NYU-Depth V2 and SUN RGB-D benchmarks demonstrate the superiority of our approach compared to state-of-the-art approaches. © 2016 IEEE.

关键词： Penetration depth (superconductivity)

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A Novel Three-Stage Filtering Identification Algorithm for the Exponential Autoregressive Time-Series Model

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IEEE Signal Processing Letters 2025年 32卷 2089-2093页

作者： Xu, Huan Xu, Ling Shen, Bingbing Changzhou University School of Microelectronics and Control Engineering Changzhou213159 China Hangzhou Normal University School of Mathematics Hangzhou311121 China

This letter studies the identification of a typical nonlinear time-series model, i.e., the exponential autoregressive model with unknown time-delay and colored noise. To deal with the identification difficulties caused by the time-delay, the identification model is transformed into an augmented one according to the redundant rule. Then, by means of the data filtering technique and the hierarchical principle, a novel three-stage filtering identification frame is presented to decrease the effect of the colored noise and complex nonlinearity. Moreover, a multi-innovation identification algorithm is proposed to improve the data utilization and estimation accuracy, and to jointly estimate the unknown model parameters and time-delay. The effectiveness of the proposed algorithm is evaluated by a numerical example. © 1994-2012 IEEE.

关键词： Time of arrival

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Research on Motion Target Positioning Using Smartphone Inertial Measurement Units 24

Research on Motion Target Positioning Using Smartphone Inert...

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8th International Conference on Electronic Information Technology and Computer engineering, EITCE 2024

作者： Ma, Weize Zhang, Jianqiang Tang, Yixuan Zhu, Yanping School of Microelectronics and Control Engineering Changzhou University Jiangsu Changzhou China

ISBN: (纸本)9798400710094

This study has developed a motion target positioning method leveraging the Inertial Measurement Unit (IMU) data embedded in smartphones, addressing the challenges of indoor positioning services such as complex deployment, high costs, and limited accessibility. The research integrates an attention mechanism with a Long Short-Term Memory (LSTM) model to analyze the relationship between the accelerometer and gyroscope data from smartphones and the velocity of moving targets, enabling precise regression and prediction of motion trajectories. By incorporating the attention mechanism into the RoNIN network model, the model’s capability to process complex and nonlinear data is significantly enhanced, thereby improving the accuracy and generalization of predictions. The study designed an enhanced LSTM module with integrated attention mechanisms within the RoNIN algorithm, which includes a position embedding layer, feature extraction layer, and trajectory output layer. This design not only optimizes the feature extraction process but also enhances the capture of contextual features related to pedestrian movement. The conclusion of this paper provides a detailed account of the evaluation results, demonstrating the model’s superiority in time series prediction tasks. © 2024 Copyright held by the owner/author(s).

关键词： Accelerometers

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Reconfigurable Janus metasurface with chiral meta-atoms for multi-channel vortex beams and holography multiplexing

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Optics Express 2025年第1期33卷 309-321页

作者： Gao, Peng Chen, Cong Dai, Yaowei Wang, Xinyan Cui, Hongzhong Zhu, Xiaojun Liu, Hai Engineering Research Center of Intelligent Control for Underground Space Ministry of Education China University of Mining and Technology Xuzhou221116 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China School of Microelectronics School of Integrated Circuits Nantong University Nantong226019 China

Multi-channel multiplexing metasurfaces have attracted considerable interest with the growing demand for multifunctional integration and enhanced communication capabilities. Dynamic tuning of electromagnetic waves with multiple degrees of freedom is a key approach to improving information processing capabilities. Metasurfaces with chiral meta-atoms and Janus metasurfaces with asymmetric transmission properties introduce new degrees of freedom for multiplexing technologies. It is a challenge to combine these two methods to achieve more degrees of freedom of multi-channel multiplexed metasurface. In this study, we present reconfigurable Janus metasurfaces with chiral meta-atoms based on vanadium dioxide (VO2). Our results demonstrate that chiral meta-atoms enable dynamic switching between asymmetric transmission and reflection at varying temperatures. In the design of multi-channel vortex beams, this reconfigurable Janus metasurface can generate vortex beams with different spins by active control of propagation direction or temperature. In multi-channel metasurface holography designs, this chiral unit-based reconfigurable Janus metasurface can actively produce eight-channel metasurface holograms by manipulating chiral characteristics, propagation direction, or temperature. Additionally, in the design of metasurfaces for information encryption, four distinct metasurface holograms have been generated, which can be synthesized into a unique decrypted image. This research not only offers a novel approach for the design of multi-path multiplexing metasurfaces but also paves the way for applications in multi-channel structured light and promoting high-capacity and high-secure holographic applications. Consequently, it provides new possibilities for terahertz optical information encryption, data storage, and intelligent information processing. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Holograms

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Kaon-induced production of strange hidden-charm molecular pentaquarks PψsΛ from proton

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European Physical Journal C 2025年第5期85卷 1-12页

作者： Chen, Shu Zhu, Jun-Tao Kong, Shu-Yi He, Jun School of Physics and Technology Nanjing Normal University Nanjing210097 China School of Microelectronics and Control Engineering Changzhou University Changzhou213164 China

In this work, we investigate the kaon-induced production of strange hidden-charm pentaquark PψsΛ states, including the PψsΛ(4459) and PψsΛ(4338) observed by the LHCb collaboration. Coupled-channel interactions involving the channels K¯N, Ξc(∗)D¯(∗), Ξc′D¯(∗), ΛcD¯s(∗), and ΛJ/ψ are studied using effective Lagrangians to describe these interactions. The potential kernels are constructed within the one-boson-exchange model and implemented into the quasipotential Bethe–Salpeter equation to calculate the scattering amplitudes. From these amplitudes, the partial-wave cross sections for kaon-induced production are predicted alongside the poles corresponding to strange hidden-charm molecular pentaquarks. The analysis reveals complex structures in the cross sections due to molecular states. A structure near the ΞcD¯ threshold is predicted in the ΛcD¯s channel, corresponding to PψsΛ(4338). Both molecular states near the ΞcD¯∗ threshold with JP=1/2- and JP=3/2-, associated with PψsΛ(4459), produce peaks in the Ξc′D¯ channel, which vary significantly with the cutoff. Additionally, a molecular state with JP=3/2- near the Ξc∗D¯ threshold gives rise to a peak in the ΞcD¯∗ channel. In the higher energy region, from 4350 to 4550 MeV, although the cross sections in the ΛcD¯s(∗) channels are substantial, no distinct structures corresponding to strange hidden-charm pentaquarks are identified, apart from some threshold-related cusps. These results provide valuable theoretical insights and serve as a foundation for future experimental studies of strange hidden-charm pentaquarks using kaon beams at J-PARC and JLab. © The Author(s) 2025.

关键词： Lagrange multipliers

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Exploring brain dysfunction in IBD: A study of EEG-fMRI source imaging based on empirical mode diagram decomposition

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Mathematical Biosciences and engineering 2025年第4期22卷 962-987页

作者： Kang, Yujie Li, Wenjie Lv, Jidong Zou, Ling Shi, Haifeng Liu, Wenjia School of Microelectronics and Control Engineering Changzhou University Changzhou213164 China School of Medical and Health Engineering Changzhou University Changzhou213164 China The Third Affiliated Hospital of Nanjing Medical University Department of Radiology Changzhou213003 China

Patients with inflammatory bowel disease (IBD) often suffer from mood disorders and cognitive decline, which has prompted research into abnormalities in emotional brain regions and their functional analysis. However, most IBD studies only focus on single-modality neuroimaging technologies. Due to a limited spatiotemporal resolution, it is unfeasible to fully explore deep brain source activities and accurately evaluate the brain functional connectivity. Therefore, we propose an electroencephalography (EEG)-functional magnetic resonance imaging (fMRI)source imaging method based on an empirical mode diagram decomposition (EMDD) and performed a synchronous EEG-fMRI source imaging analysis on 21 IBD patients and 11 healthy subjects. The high-frequency spatial components of the fMRI were extracted through EMDD as prior constraints and compared with the EEG source imaging based on the entire fMRI spatial prior. Then, the cortical source time series were reconstructed according to the Desikan-Killiany atlas for an effective connectivity analysis. The results showed that the EEG-fMRI source imaging based on EMDD had a better performance, with the average log model evidence increased by 29.60% and the average explained variance increased by 19.12%. There were significant differences in the activation intensity of a series of abnormal brain regions between IBD patients and healthy controls, some of which were newly discovered: the uncus, claustrum, lentiform nucleus, and lingual gyrus. Moreover, the findings from the effective connectivity analysis of cortical source signals revealed that IBD patients had information flow loss in the frontal lobes, central areas, left parietal lobe, and right temporal lobe, and the information flow intensity of the right lingual gyrus was enhanced. ©2025 the Author(s), licensee AIMS Press.

关键词： Empirical mode decomposition

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Enhanced Performance of ZnO-Based Deep Red Perovskite Light-Emitting Diodes through Polyethylenimine Ethoxylated/1- Aminopyridinium Iodide Dual-Function Modification Layer

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Journal of Physical Chemistry Letters 2025年第18期16卷 4515-4521页

作者： Wang, Ruoyan Liu, Kaiming Jiang, Luman Li, Mengmeng Zhang, Diwei Lin, Yuan Li, Xiaozhen Cao, Yu Wang, Jianpu Fujian Normal University Fujian Fuzhou350117 China Nanjing Tech University Jiangsu Nanjing211816 China School of Materials Science and Engineering School of Microelectronics and Control Engineering Changzhou University Jiangsu Changzhou213164 China

Deep red perovskite light-emitting diodes (LEDs) based on a zinc oxide (ZnO) electron transporting layer (ETL) have achieved great improvement in recent years. Polyethylenimine ethoxylated (PEIE) is widely employed as a modification layer for ZnO in deep red perovskite LEDs to address the interfacial reaction between ZnO and perovskites. However, there is a lack of research on the regulation of the PEIE properties. In this work, we design a dual-function modification layer of PEIE doped with 1-aminopyridinium iodide (PyNI) to achieve improved energy level alignment and enhanced perovskite film quality. As a result, the deep red perovskite LEDs with a PEIE/PyNI dual-function modification layer exhibit a peak external quantum efficiency of 17.5%, a brightness of 1644 cd m-2, and extended operational stability (T50 = 8.3 h at 20 mA cm-2). These advancements highlight the critical role of ZnO surface modification in achieving high-performance ZnO-based deep red perovskite LEDs. © 2025 American Chemical Society.

关键词： Fluorescence

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A Novel Multisource-Domain Adaptation Framework for Bearing Fault Diagnosis Based on Adversarial Network and Feature Enhancement

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Li, Zhixin Shen, Shiyi Liu, Zhijun Chen, Ying Changzhou University School of Microelectronics and Control Engineering Jiangsu Changzhou213164 China

Data-driven fault diagnosis methods have received extensive attention, and the existing diagnostic methods usually require sufficient supervised data. However, developing effective diagnostic methods with insufficient training data remains challenging, which is highly demanding in real industrial scenarios since collecting high-quality fault data is often difficult and expensive. Considering the potential similarity of rotating machinery, collecting bearing fault data from different but related equipment may benefit the diagnostic performance of the target machinery. This article proposes a novel multisource-domain adaptation framework for bearing fault diagnosis methods based on adversarial network and feature enhancement. This method reduces the feature distribution discrepancy between the target domain and each source domain through domain adversarial training and transfers the fault diagnosis knowledge learned from multiple labeled source domains to a single unlabeled target domain. Considering the problem of scarce fault data, this method uses multilinear mapping to fuse the class information (Class Inf.) with high-level features and introduces AlignMixup to enhance the real fault signal features. To evaluate the model, experimental validation was performed on the Case Western Reserve University (CWRU) and KAT datasets. The results show that the proposed method is promising to address the bearing fault diagnosis tasks from different places of machines, further improving the applicability of data-driven methods in real industries. © 1963-2012 IEEE.

关键词： Adversarial machine learning

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A novel active-passive protection strategy endows carbonyl iron with excellent intelligent anti-corrosion and microwave absorption dual functional characteristics

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Nano Research 2025年第1期18卷 487-500页

作者： Wei Tian Quanyuan Feng Linbo Zhang Yinfan Liu Xian Jian Longjiang Deng Institute of Microelectronics School of Information Science and TechnologySouthwest Jiaotong UniversityChengdu 611756China National Engineering Researching Centre of Electromagnetic Radiation Control Materials Key Laboratory of Multi-Spectral Absorbing Materials and Structures of Ministry of EducationState Key Laboratory of Electronic Thin Films and Integrated DevicesSchool of Electronic Science and EngineeringUniversity of Electronic Science and Technology of ChinaChengdu 611731China School of Materials and Energy University of Electronic Science and Technology of ChinaChengdu 611731China The Yangtze Delta Region Institute(Huzhou)&School of Electronic Science and Engineering University of Electronic Science and Technology of ChinaHuzhou 313001China

Carbonyl iron absorbers(CI)face significant challenges in practical applications,such as corrosion,interface bonding failure,detachment,and high maintenance ***,we have developed intelligent self-healing technology based on proactive/passive mechanisms via in situ synthesis of self-healing factors(polydopamine/benzotriazole(PDA/BTA))and physical barrier layers(SiO_(2)/1,1,1,3,3,3-hexamethyl disilazane,SiO_(2)/HMDS)to enhance corrosion resistance,while also being compatible with efficient microwave absorption *** unique multiscale structure gives full play to the utilization of the roles of each functional layer,including the intelligent self-healing features of PDA/BTA,physical shielding and spatial confinement characteristics of SiO_(2)/HMDS,and magnetic-dielectric synergistic mechanism resulted from the good impedance matching characteristics,the conduction loss,the interfacial polarization loss and natural *** asfabricated composites achieved an exceptional minimum reflection loss value of-55.4 dB at 10.7 GHz and the effective absorption band of 7.6 ***,it still exhibits obvious self-healing and corrosion resistance characteristics after 360 h corrosion treatment,ascribed to the self-healing mechanism of PDA/BTA and the blocking intervention effect of SiO_(2)/*** work is considered to pave the way for the synthesis of high-performance magnetic absorbers,especially in enhancing their intelligent self-healing ability in corrosive environments.

关键词： microwave absorption intelligent self-healing technology carbonyl iron multiscale structure magneticdielectric synergistic mechanism

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Hierarchical Multimodal Decoupling-Fusion Framework for offline Multiple Appropriate Facial Reaction Generation

Hierarchical Multimodal Decoupling-Fusion Framework for offl...

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2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Lv, Qincheng Liu, Xiaofeng Li, Jie Ni, Rongrong Xue, Pujun Song, Siyang College of Information Science and Engineering Hohai University Changzhou China College of Artificial Intelligence and Automation Hohai University Changzhou China School of Biomedical Engineering and Informatics Nanjing Medical University Nanjing China School of Microelectronics and Control Engineering Changzhou University Changzhou China School of Computer Science University of Exeter Exeter United Kingdom

ISBN: (纸本)9798350368741

Facial reactions convey crucial emotional information and coordinating interpersonal relationships in human dyadic interactions. While existing Multiple Appropriate Facial Reaction Generation (MAFRG) methods focus on generating multiple reasonable facial reactions, none of these approaches combines 2D and 3D facial behaviour information nor account for the influence of individuals' facial identities, leading to inconsistencies in the generated facial reactions and limited capability in capturing subtle variations in facial depth and expression dynamics. This paper proposes a novel Hierarchical Multimodal Decoupling-Fusion (HMDF) framework that decouples 3D facial identity from expression behaviors, eliminating identity-based interference in the reaction generation process, which are integrated with audio-visual features through a cross-attention mechanism. Experiments show that our framework achieved the enhanced diversity and synchrony in the generated facial reactions. © 2025 IEEE.

关键词： 2D 3D facial behaviour fusion Facial identity decoupling Multiple Appropriate Facial Reaction Generation

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