Sensors最新文献

{"title":"PIABC: Point Spread Function Interpolative Aberration Correction.","authors":"Chanhyeong Cho, Chanyoung Kim, Sanghoon Sull","doi":"10.3390/s25123773","DOIUrl":"https://doi.org/10.3390/s25123773","url":null,"abstract":"<p><p>Image quality in high-resolution digital single-lens reflex (DSLR) systems is degraded by Complementary Metal-Oxide-Semiconductor (CMOS) sensor noise and optical imperfections. Sensor noise becomes pronounced under high-ISO (International Organization for Standardization) settings, while optical aberrations such as blur and chromatic fringing distort the signal. Optical and sensor-level noise are distinct and hard to separate, but prior studies suggest that improving optical fidelity can suppress or mask sensor noise. Upon this understanding, we introduce a framework that utilizes densely interpolated Point Spread Functions (PSFs) to recover high-fidelity images. The process begins by simulating Gaussian-based PSFs as pixel-wise chromatic and spatial distortions derived from real degraded images. These PSFs are then encoded into a latent space to enhance their features and used to generate refined PSFs via similarity-weighted interpolation at each target position. The interpolated PSFs are applied through Wiener filtering, followed by residual correction, to restore images with improved structural fidelity and perceptual quality. We compare our method-based on pixel-wise, physical correction, and densely interpolated PSF at pre-processing-with post-processing networks, including deformable convolutional neural networks (CNNs) that enhance image quality without modeling degradation. Evaluations on DIV2K and RealSR-V3 confirm that our strategy not only enhances structural restoration but also more effectively suppresses sensor-induced artifacts, demonstrating the benefit of explicit physical priors for perceptual fidelity.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 12","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144508245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Research on Bearing Fault Diagnosis Method for Varying Operating Conditions Based on Spatiotemporal Feature Fusion.","authors":"Jin Wang, Yan Wang, Junhui Yu, Qingping Li, Hailin Wang, Xinzhi Zhou","doi":"10.3390/s25123789","DOIUrl":"https://doi.org/10.3390/s25123789","url":null,"abstract":"<p><p>In real-world scenarios, the rotational speed of bearings is variable. Due to changes in operating conditions, the feature distribution of bearing vibration data becomes inconsistent, which leads to the inability to directly apply the training model built under one operating condition (source domain) to another condition (target domain). Furthermore, the lack of sufficient labeled data in the target domain further complicates fault diagnosis under varying operating conditions. To address this issue, this paper proposes a spatiotemporal feature fusion domain-adaptive network (STFDAN) framework for bearing fault diagnosis under varying operating conditions. The framework constructs a feature extraction and domain adaptation network based on a parallel architecture, designed to capture the complex dynamic characteristics of vibration signals. First, the Fast Fourier Transform (FFT) and Variational Mode Decomposition (VMD) are used to extract the spectral and modal features of the signals, generating a joint representation with multi-level information. Then, a parallel processing mechanism of the Convolutional Neural Network (SECNN) based on the Squeeze-and-Excitation module and the Bidirectional Long Short-Term Memory network (BiLSTM) is employed to dynamically adjust weights, capturing high-dimensional spatiotemporal features. The cross-attention mechanism enables the interaction and fusion of spatial and temporal features, significantly enhancing the complementarity and coupling of the feature representations. Finally, a Multi-Kernel Maximum Mean Discrepancy (MKMMD) is introduced to align the feature distributions between the source and target domains, enabling efficient fault diagnosis under varying bearing conditions. The proposed STFDAN framework is evaluated using bearing datasets from Case Western Reserve University (CWRU), Jiangnan University (JNU), and Southeast University (SEU). Experimental results demonstrate that STFDAN achieves high diagnostic accuracy across different load conditions and effectively solves the bearing fault diagnosis problem under varying operating conditions.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 12","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144508259","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Signal Processing Method and Evaluation Method for Weak Doppler Signal Detection.","authors":"Chongbin Xi, Jian Zhou, Xiaoming Nie, Shilong Jin","doi":"10.3390/s25123775","DOIUrl":"https://doi.org/10.3390/s25123775","url":null,"abstract":"<p><p>When the amplitude of the laser Doppler signal is less than that of the noise amplitude, the speed information cannot be identified. In this paper, the recognition of weak Doppler signals is accomplished by superimposing multiple-frame Doppler signals in the frequency domain and eliminating the base noise. Meanwhile, the relative prominence is defined to assess the quality of Doppler signals. The theoretical analysis and experimental results demonstrate that the relative prominence can be enhanced by more than two orders of magnitude through the stacking of 10,000 frames of Doppler signals. Moreover, this paper establishes a foundation for determining the threshold of relative prominence in practical measurements. When the relative prominence at a specific point on the spectrum is 3, there is at least a 99.08% probability that this point corresponds to the target signal.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 12","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144508298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Modified Differential Evolution for Source Localization Using RSS Measurements.","authors":"Yunjie Tao, Lincan Li, Shengming Chang","doi":"10.3390/s25123787","DOIUrl":"https://doi.org/10.3390/s25123787","url":null,"abstract":"<p><p>In wireless sensor networks, evolutionary algorithms have emerged as pivotal tools for addressing complex localization challenges inherent in non-convex and nonlinear maximum likelihood estimation problems associated with received signal strength (RSS) measurements. While differential evolution (DE) has demonstrated notable efficacy in optimizing multimodal cost functions, conventional implementations often grapple with suboptimal convergence rates and susceptibility to local optima. To overcome these limitations, this paper proposes a novel enhancement of DE by integrating opposition-based learning (OBL) principles. The proposed method introduces an adaptive scaling factor that dynamically balances global exploration and local exploitation during the evolutionary process, coupled with a penalty-augmented cost function to effectively utilize boundary information while eliminating explicit constraint handling. Comparative evaluations against state-of-the-art techniques-including semidefinite programming, linear least squares, and simulated annealing-reveal significant improvements in both convergence speed and positioning precision. Experimental results under diverse noise conditions and network configurations further validate the robustness and superiority of the proposed approach, particularly in scenarios characterized by high environmental uncertainty or sparse anchor node deployments.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 12","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144508107","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CAs-Net: A Channel-Aware Speech Network for Uyghur Speech Recognition.","authors":"Jiang Zhang, Miaomiao Xu, Lianghui Xu, Yajing Ma","doi":"10.3390/s25123783","DOIUrl":"https://doi.org/10.3390/s25123783","url":null,"abstract":"<p><p>This paper proposes a Channel-Aware Speech Network (CAs-Net) for low-resource speech recognition tasks, aiming to improve recognition performance for languages such as Uyghur under complex noisy conditions. The proposed model consists of two key components: (1) the Channel Rotation Module (CIM), which reconstructs each frame's channel vector into a spatial structure and applies a rotation operation to explicitly model the local structural relationships within the channel dimension, thereby enhancing the encoder's contextual modeling capability; and (2) the Multi-Scale Depthwise Convolution Module (MSDCM), integrated within the Transformer framework, which leverages multi-branch depthwise separable convolutions and a lightweight self-attention mechanism to jointly capture multi-scale temporal patterns, thus improving the model's perception of compact articulation and complex rhythmic structures. Experiments conducted on a real Uyghur speech recognition dataset demonstrate that CAs-Net achieves the best performance across multiple subsets, with an average Word Error Rate (WER) of 5.72%, significantly outperforming existing approaches. These results validate the robustness and effectiveness of the proposed model under low-resource and noisy conditions.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 12","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144508141","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Coherent DOA Estimation of Multi-Beam Frequency Beam-Scanning LWAs Based on Maximum Likelihood Algorithm.","authors":"Yifan Yang, Rihui Zeng, Qingqing Zhu, Weijin Fang, Biyun Ma, Yide Wang","doi":"10.3390/s25123791","DOIUrl":"https://doi.org/10.3390/s25123791","url":null,"abstract":"<p><p>Multi-Beam frequency scanning leaky-wave antennas (FBS-LWAs) offer a viable solution for hardware miniaturization in direction-of-arrival (DOA) estimation systems. However, the presence of multiple spatial harmonics results in responses in multiple directions for a given incident source, introducing estimation ambiguity and significantly challenging accurate DOA estimation. Moreover, due to the nonlinear frequency response of the FBS-LWA, its response matrix does not satisfy the Vandermonde structure, which renders common rank-recovery techniques ineffective for processing coherent signals. As a result, the DOA estimation of coherent sources using multi-beam FBS-LWAs remains an open and challenging problem. To address this issue, this paper proposes a novel DOA estimation method for coherent signals based on multi-beam frequency scanning leaky-wave antennas. First, the received signals are transformed into the frequency domain via fast Fourier transform (FFT) to construct the signal data matrix from which the covariance matrix is computed.Then, conventional beamforming (CBF) is employed to obtain an initial estimate of the angle set, which will be further refined by a smaller grid to form a candidate angle set. Finally, a maximum likelihood algorithm based on the stochastic principle (Sto-ML) is used to suppress the interference of the parasitic directions and select the final DOA estimates from the candidate angle set. Simulation results show that the proposed method effectively mitigates the impact of parasitic directions and achieves an accurate DOA estimation of multiple coherent sources, even under both low and medium-to-high signal-to-noise ratio (SNR) conditions.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 12","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144508145","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Survey of Performance Metrics for Spectrum Sensing and Spectrum Hole Geolocation for Wireless Spectrum Access.","authors":"Dayan Adionel Guimarães","doi":"10.3390/s25123770","DOIUrl":"https://doi.org/10.3390/s25123770","url":null,"abstract":"<p><p>This paper presents a survey of performance metrics applicable to spectrum sensing and spectrum hole geolocation within the context of dynamic spectrum access (DSA) in cognitive radio networks. While grounded in binary hypothesis testing, the review emphasizes metrics specialized for sensing reliability, interference risk, spatial accuracy, and network efficiency. The work also highlights trade-offs among metrics and provides guidelines for their practical application. A key contribution of this work is to provide researchers and practitioners with a comprehensive set of evaluation tools, extending well beyond the applicability of the conventional probabilities of detection and false alarm.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 12","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144508073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Self-Sensing of Piezoelectric Micropumps: Gas Bubble Detection by Artificial Intelligence Methods on Limited Embedded Systems.","authors":"Kristjan Axelsson, Mohammadhossien Sheikhsarraf, Christoph Kutter, Martin Richter","doi":"10.3390/s25123784","DOIUrl":"https://doi.org/10.3390/s25123784","url":null,"abstract":"<p><p>Gas bubbles are one of the main disturbances encountered when dispensing drugs of microliter volumes using portable miniaturized systems based on piezoelectric diaphragm micropumps. The presence of a gas bubble in the pump chamber leads to the inaccurate administration of the required dose due to its impact on the flowrate. This is particularly important for highly concentrated drugs such as insulin. Different types of sensors are used to detect gas bubbles: inline on the fluidic channels or inside the pump chamber itself. These solutions increase the complexity, size, and cost of the microdosing system. To address these problems, a radically new approach is taken by utilizing the sensing capability of the piezoelectric diaphragm during micropump actuation. This work demonstrates the workflow to build a self-sensing micropump based on artificial intelligence methods on an embedded system. This is completed by the implementation of an electronic circuit that amplifies and samples the loading current of the piezoelectric ceramic with a microcontroller STM32G491RE. Training datasets of 11 micropumps are generated at an automated testbench for gas bubble injections. The training and hyper-parameter optimization of artificial intelligence algorithms from the TensorFlow and scikit-learn libraries are conducted using a grid search approach. The classification accuracy is determined by a cross-training routine, and model deployment on STM32G491RE is conducted utilizing the STM32Cube.AI framework. The finally deployed model on the embedded system has a memory footprint of 15.23 kB, a runtime of 182 µs, and detects gas bubbles with an accuracy of 99.41%.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 12","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144508289","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine Learning-Based Identification of Plastic Types Using Handheld Spectrometers.","authors":"Hedde van Hoorn, Fahimeh Pourmohammadi, Arie-Willem de Leeuw, Amey Vasulkar, Jerry de Vos, Steven van den Berg","doi":"10.3390/s25123777","DOIUrl":"https://doi.org/10.3390/s25123777","url":null,"abstract":"<p><p>Plastic waste and pollution is growing rapidly worldwide and most plastics end up in landfill or are incinerated because high-quality recycling is not possible. Plastic-type identification with a low-cost, handheld spectral approach could help in parts of the world where high-end spectral imaging systems on conveyor belts cannot be implemented. Here, we investigate how two fundamentally different handheld infrared spectral devices can identify plastic types by benchmarking the same analysis against a high-resolution bench-top spectral approach. We used the handheld Plastic Scanner, which measures a discrete infrared spectrum using LED illumination at different wavelengths, and the SpectraPod, which has an integrated photonics chip which has varying responsivity in different channels in the near-infrared. We employ machine learning using SVM, XGBoost, Random Forest and Gaussian Naïve Bayes models on a full dataset of plastic samples of PET, HDPE, PVC, LDPE, PP and PS, with samples of varying shape, color and opacity, as measured with three different experimental approaches. The high-resolution spectral approach can obtain an accuracy (mean ± standard deviation) of (0.97 ± 0.01), whereas we obtain (0.93 ± 0.01) for the SpectraPod and (0.70 ± 0.03) for the Plastic Scanner. Differences of reflectance at subsequent wavelengths prove to be the most important features in the plastic-type classification model when using high-resolution spectroscopy, which is not possible with the other two devices. Lower accuracy for the handheld devices is caused by their limitations, as the spectral range of both devices is limited-up to 1600 nm for the SpectraPod, while the Plastic Scanner has limited sensitivity to reflectance at wavelengths of 1100 and 1350 nm, where certain plastic types show characteristic absorbance bands. We suggest that combining selective sensitivity channels (as in the SpectraPod) and illuminating the sample with varying LEDs (as with the Plastic Scanner) could increase the accuracy in plastic-type identification with a handheld device.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 12","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144508230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Intraretinal Electrophysiology and Resistivity Profiles of WT and RCS Rat Retina.","authors":"Marie Jung, Antje Willuweit, Viviana Rincón Montes","doi":"10.3390/s25123765","DOIUrl":"https://doi.org/10.3390/s25123765","url":null,"abstract":"<p><p>Retinal prostheses have been utilized in the treatment of blindness resulting from retinal degeneration. However, they have not met patient expectations, leading to market withdrawals. As a result, research continues to focus on improving visual perception, such as by modeling retinal neural activation. The retina's electrical resistivity profile is key, as it influences the current spread during electrical stimulation. To advance efficient stimulation parameters, more data on the electrical properties of the retina in both its healthy and diseased state is needed. While this question has been addressed in mouse models, few data are available from rat models, whose bigger size is advantageous for many applications. To address this knowledge gap, we used flexible penetrating microelectrode arrays to measure intraretinal impedance and electrophysiological activity in retinas from both healthy (WT) and diseased RCS rats, an established model of retinal degeneration. Consequently, we calculated resistivity profiles, consistent with previous mouse retina findings, and correlated them with spontaneous spiking activity. Hence, both impedance and electrophysiological measurements across retinal depths are demonstrated as valuable tools to identify the optimal stimulation depth and simulate the electric field spread during electrical stimulation, which is particularly useful for the development of retinal prostheses. These findings demonstrate that resistivity changes in the degenerated retina significantly impact stimulation protocols and electric field propagation.</p>","PeriodicalId":21698,"journal":{"name":"Sensors","volume":"25 12","pages":""},"PeriodicalIF":3.4,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144508217","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}