最新刊期
卷 33 ， 期 20 ， 2025
- “在病理组织样本检测领域，专家提出了多因素跨模块误差校正模型，显著提升了Mueller矩阵偏振成像系统的检测精度和稳定性，为甲状腺癌辅助诊断提供了新方法，具有良好的应用前景。”摘要：In order to improve the accuracy and stability of the system in the detection of pathological tissue samples， and to explore its application potential in the auxiliary diagnosis of thyroid cancer， a multi-factor cross-module error correction model was proposed to improve the accuracy and stability of the system in the detection of pathological tissue samples. Firstly， the main sources of system errors are analyzed， the error transfer optical path model is established by analytical method and numerical reconstruction method， and a multi-factor cross-module error correction model with 16 calibration parameters is constructed. Secondly， the nonlinear least squares fitting method is used to calibrate 16 parameters. According to the error correction model， the Mueller matrix of the air and blank slices is detected to evaluate the detection accuracy. Then， using the unstained sections of papillary thyroid carcinoma and nodular goiter as samples， four vector parameters （Δ， P， D， R） were extracted by Mueller matrix polarization decomposition method， and the texture features of each vector parameter image were extracted， and two classification models of random forest and support vector machine were constructed to obtain confusion matrix and ROC curve. Finally， the classification effect was evaluated by calculating Precision， Recall， F1-score， and AUC. The experimental results show that the calibration accuracy is increased by 12%， the calibration stability is increased by 21.5%， and the detection accuracy is increased by 59%. The classification effect of random forest was better than that of support vector machine， and the classification effect of Δ parameter was the most significant in random forest classification， with F1-score and AUC reaching 0.96 and AUC， respectively. Combined with Mueller matrix polarization decomposition method and texture analysis， the proposed multivariate error correction model can effectively distinguish papillary thyroid carcinoma and nodular goiter samples， which provides a new method for early auxiliary diagnosis of cancer and has a good application prospect.关键词：polarization imaging;error correction;Mueller matrix vector parameters;texture features;random forest40|18|0更新时间：2025-12-02
- “据最新报道，研究人员开发了一种新型非接触式呼吸监测系统，通过混合式TOF传感技术，实现了高精度犬静态呼吸监测，为宠物医疗领域提供了小型化、低成本的生物光学测量新方案。”摘要：To address the clinical need for continuous respiratory rate monitoring in dogs with heart failure， this study developed a novel non-contact respiratory monitoring system based on Hybrid TOF （optical time-of-flight） sensing. A hybrid single-point/array TOF sensing architecture was proposed， incorporating a spatial adaptive monitoring model to accommodate varying pet postures. An STM32-embedded platform enabled sensor synchronization and raw signal preprocessing， while a LabVIEW-based host computer implemented real-time respiratory waveform analysis algorithms. Optical calibration tests optimized array TOF ranging parameters. Testing on small-sized dogs under static conditions demonstrates a respiratory rate measurement error of ≤ 2 breaths per minute （BPM）. The LabVIEW interface enables real-time visualization of respiratory waveforms and BPM values， confirming the feasibility of optical TOF sensing for vital sign monitoring. The hybrid TOF system achieves high-precision static respiratory monitoring in dogs through optical measurement optimization and spatial adaptive strategies， which provides a miniaturized， low-cost bionic optical solution for veterinary medical applications.关键词：TOF sensor;non-contact monitoring;pet respiration rate;Dogs with heart failure;LabVIEW30|17|0更新时间：2025-12-02
- “在食品安全领域，研究者提出了一种基于改进黑翅鸢算法优化XGBoost模型的可解释分类模型，为转基因棉籽油鉴别提供快速准确分析方法。”摘要：To achieve accurate classification and identification of genetically modified and non-genetically modified cottonseed oil， this study proposes an explainable classification model based on an improved black-winged kite algorithm optimized extreme gradient boosting （XGBoost） model. First， a terahertz time-domain spectroscopy （THz-TDS） system was used to collect terahertz absorption spectra of genetically modified and non-genetically modified cottonseed oil samples in the 0.3-1.8 THz frequency range. Then， the traditional Black-winged Kite algorithm （BKA） was improved by introducing a dual-objective fitness function optimization strategy， a reverse learning initial population strategy， and a Rayleigh distribution function to control the Lévy flight strategy. The improved Black-winged Kite algorithm （DLBKA） was used to perform dual-objective hyperparameter optimization of the tree depth， learning rate， and maximum iteration count of the XGBoost model， thereby constructing the DLBKA-XGBoost classification model. Finally， the model was applied to identify genetically modified cottonseed oil， and the model's identification results were analyzed for interpretability using the SHAP method. The results showed that the improved Black-winged Kite Algorithm-optimized XGBoost interpretable classification model not only improved the accuracy of identifying genetically modified and non-genetically modified cottonseed oil （with a test set accuracy as high as 97.78%， an improvement of 4.45% over the traditional Black-winged Kite algorithm-optimized model， an improvement of 14.45% over the traditional Whale Optimization Algorithm（WOA）-optimized model）， but also provided explanations for the model， clarifying the positive influence mechanism of key feature frequencies on the identification results， thereby enhancing the model's transparency and credibility. Therefore， this study provides a fast and accurate analytical method for the identification of genetically modified cottonseed oil and offers valuable references for the identification of other genetically modified substances.关键词：terahertz spectroscopy;genetically modified cottonseed oil;extreme gradient boosting;improved black-winged kite algorithm;explainability analysis34|18|0更新时间：2025-12-02
- “在机器视觉测量领域，专家建立了明暗场复合照明系统的照度分布模型，采用改进算法优化光源布置，有效提升目标区域光照均匀性。”摘要：In order to improve the image quality of machine vision inspection systems， this paper studies the problem of refining the arrangement of light sources for composite illumination in bright-dark fields. First， the illuminance distribution model of the bright and dark field composite lighting system was established based on Lambert radiation characteristics and linear superposition principle for the first time and then the optimization objective function including the coefficient of variation and the minimum maximum ratio was constructed. Next， an improved simulated annealing-particle swarm algorithm was used to solve for the optimal layout parameters. An experimental platform was constructed and the illuminance distribution in the target area was measured. Then， to evaluate the effectiveness of the refined scheme， images of the workpieces in the target area were collected， and the illuminance uniformity was calculated and compared with experimental measurements. The measured optimal illuminance uniformity reached 0.9219， showing a relative error of 2.59% compared to the AE-SAPSO optimized result. The maximum relative error between the measured illuminance uniformity of the workpiece surface and the experimental results is 3.42%. Finally， the performance of the proposed lighting scheme was analyzed by comparing defect visibility under three illumination modes from the perspectives of binarization quality and illuminance uniformity. The results demonstrate that the proposed light source layout method effectively enhances illumination uniformity in the target area.关键词：machine vision;composite illumination in bright-dark fields;illuminance uniformity;lighting design41|19|0更新时间：2025-12-02
Modern Applied Optics
- “在磁流变抛光领域，专家提出基于Halbach阵列的永磁体排列方式，有效提升加工性能。”摘要：To enhance the excitation performance and processing quality of magnetorheological polishing， a Halbach array-based permanent magnet arrangement is proposed， and the influence of process parameters on the polishing performance of K9 glass is investigated. Magnetic field simulations were conducted to compare the Halbach array， traditional N-S pole alternating array， and inner-outer alternating array in terms of magnetic field strength， magnetic flux density magnitude， gradient distribution， and the force acting on carbonyl iron particles. Combined with single-factor experiments， the effects of workpiece rotation speed， magnetic field rotation speed， working gap， and excitation gap on surface roughness and material removal rate were systematically studied. The results indicate that the Halbach array expands the effective acting area of the magnetic field， maintains good uniformity， and enhances both magnetic field strength and abrasive particle force， thereby exhibiting superior excitation performance. With increasing workpiece rotation speed， magnetic field rotation speed， and working gap， the surface roughness decreases initially and then increases， while the material removal rate increases at first and then decreases. As the excitation gap increases， the surface roughness keeps rising and the material removal rate declines. Under the conditions of a workpiece rotation speed of 650 r/min， magnetic field rotation speed of 70 r/min， working gap of 1.2 mm， excitation gap of 4 mm， and a polishing duration of 30 min， the surface roughness of K9 glass reaches 0.029 7 μm， and the material removal rate is 51.928 nm/min. The Halbach array excitation method and its corresponding polishing process effectively improve the performance of magnetorheological polishing.关键词：magnetorheological polishing;Halbach array;K9 glass;surface roughness;material removal rate44|16|0更新时间：2025-12-02
- “在提升Mini/Micro LED芯片流磁巨量转移效率领域，专家提出了阶梯式聚磁永磁定位磁针，优化了磁针结构，提升了磁密峰谷变化率和峰谷变化速率，为巨量转移技术发展提供了新方案。”摘要：To improve the magnetic density peak-to-valley effect of the permanent magnet positioning array magnetic needle in the fluid magnetic mass transfer of Mini/Micro LED chips， a stepped polymagnetic permanent magnet positioning magnetic needle was proposed. For this stepped polymagnetic permanent magnet needle structure， a multistage equivalent magnetic circuit model incorporating nonlinear demagnetization effects and magnetic circuit saturation characteristics， as well as a mechanical dynamic model considering chip motion characteristics and fluid-structure interaction， were established. Based on this， with the core objectives of improving the magnetic field peak-to-valley change rate and peak-to-valley change speed， the height and diameter parameters of each stage of the magnetic needle were subjected to step-by-step parametric simulation using finite element analysis software. This determined the optimal three-dimensional structural parameters for a high-performance magnetic needle under specific geometric scale and process constraints. A prototype magnetic needle was developed based on the optimization results， and the effectiveness of the optimization was verified through magnetic needle magnetic density measurement tests and mass transfer tests. The results show that the optimized magnetic needle achieved a magnetic density peak-to-valley change rate δ of 82.3% and a peak-to-valley change speed ζ of 44.8 mT/mm， representing improvements of 20.1% and 28.7%， respectively. A fluid magnetic mass transfer experiment involving 4 500 chips was conducted on a 180 mm×160 mm receiving substrate， with a transfer time of only 3 minutes， reducing the time by 40% compared to existing solutions.关键词：mass transfer;stepped structure;dynamic model;magnetic field optimization27|15|0更新时间：2025-12-02
- “在永磁同步电机控制领域，专家设计了基于模糊滑模控制及谐波电压补偿器的复合控制方法，有效提高了系统的动态响应性能、鲁棒性和转速控制精度。”摘要：In order to improve the anti-disturbance capability and steady-state control accuracy of permanent magnet synchronous motor control systems， this paper proposed a composite control method integrating fuzzy sliding mode control and a harmonic voltage compensator. To address the inherent chattering issue in sliding mode control， a fuzzy sliding mode convergence law was designed. This convergence law utilized the system states to define fuzzy rules that dynamically adjusted the gain of the exponential term. Concurrently， it replaced the fixed parameter in the switching term with an adaptive function， enabling dynamic adaptation. This design effectively suppressed sliding mode chattering while maintaining system robustness and dynamic response performance. To mitigate the pulsating harmonics issue in the motor control system， a harmonic voltage compensator based on a second-order generalized integral filter was developed. This compensator employed the second-order generalized integral filter to extract harmonic components present in the stator current signal. Subsequently， it implemented control and provided online compensation for these extracted harmonic components. Consequently， current pulsating harmonics within the system were significantly attenuated， leading to enhanced speed control accuracy. Experimental results demonstrate that， compared to the conventional PI control method， the implementation of the proposed composite control method yields a 44.36% improvement in the system's dynamic response speed， a 30.38% reduction in the maximum rotational speed fluctuation during sudden torque disturbance， and a reduction of the 6th harmonic pulsating component in the q-axis current to 0.77×10-3. These results confirm that the proposed composite control method effectively enhances the system's dynamic response performance， robustness， and rotational speed control accuracy.关键词：permanent magnet synchronous motor;fuzzy sliding mode control;harmonic voltage compensator;rotation speed control39|17|0更新时间：2025-12-02
- “在微纳电子制造领域，研究者提出了一种粘滑型压电驱动器，满足晶圆检测系统及扫描电子显微镜光学系统内部精密驱动需求。该驱动器具备宏-微-纳跨尺度驱动能力，最大空载速度20.3 mm/s，最大步进位移15.82 μm，定位分辨率70 nm，最大负载2.2 N。”摘要：To meet the precision driving requirements of wafer inspection systems and the internal optical systems of scanning electron microscopes （SEMs） in the field of micro-nano electronics manufacturing， a stick-slip piezoelectric actuator with Macro-Micro-Nano cross-scale drive was proposed in this study. First， the structural design of the slider and stator of the actuator and its driving principle were elaborated in detail， and the dimensional parameters of the stator structure were optimized by finite element simulation method. Then， the dynamic model of the actuator was constructed to analyze its stepping characteristics. The simulation results showed that the actuator was capable of micro-stepping displacement. Finally， the prototype of the actuator was fabricated， and the experimental system was built to evaluate its output performance. The experimental results indicate that the proposed actuator exhibits a maximum no-load speed of 20.3 mm/s， a maximum step displacement of 15.82 μm， a positioning resolution of 70 nm， and a maximum load of 2.2 N， which can meet the cross-scale driving requirements of macro large-stroke continuous movement， micro-scale step displacement， and nano-scale high-precision positioning. This study provides an essential theoretical and experimental basis for the application of stick-slip piezoelectric actuators in critical scenarios such as the alignment of aperture plates in SEM optical systems and wafer inspection platforms.关键词：stick-slip piezoelectric actuator;cross-scale;precision positioning;dynamic modeling35|15|0更新时间：2025-12-02
Micro/Nano Technology and Fine Mechanics
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Hand-object interaction pose estimation integrating multi-modal features and structure awareness AI导读
“在人手与物体交互行为研究领域，专家提出了一种三维姿态估计方法，有效降低了手部和交互物体的姿态误差，为手物交互研究提供了新方向。”摘要：In the real world， hands inevitably interact with objects. Understanding the interaction behaviors and intentions between human hands and objects is of great research significance. This paper tackled the low-accuracy pose-estimation issue during hand-object interaction， caused by mutual hand-object occlusion， hand self-occlusion， and complex backgrounds. A 3D pose-estimation method for hands and interacting objects， which combined multi-modal features and structure awareness， was proposed. This method exploited the multi-modal features of color and depth images for information complementarity， effectively addressing complex backgrounds， hand self-occlusion， and hand-object mutual occlusion. Second， graph-structure-based awareness modules for the hand， the object， and their interaction were designed to help estimate more reasonable and accurate 2D poses. Finally， the obtained 2D poses were merged with depth-image depth information， and texture features were used to optimize the merged 3D poses for the final hand-object interaction 3D pose. To verify the method’s effectiveness， experiments were conducted on datasets like FPHA and HO-3D. The hand and object pose errors are reduced to 9.62 mm and 14.37 mm， respectively. Results show the proposed method outperforms existing ones and has strong robustness and generalization.关键词：hand-object pose estimation;graph convolutional network;multi-modal features;structure awareness30|16|0更新时间：2025-12-02 - “在点云配准领域，研究人员设计了一种无监督算法，通过特征交互和点匹配增强，有效提升了配准精度和鲁棒性。”摘要：To address the issue of partial point mismatches in point cloud registration caused by outliers， partial overlap， and geometrically similar but non-corresponding points， this paper proposed an Unsupervised Point Cloud Registration Algorithm Integrating Feature Interaction and Point Matching Enhancement. First， a feature fusion module was developed to perform interactive integration between features of the source and target point clouds， and to fuse the resulting features with those extracted at the corresponding positions in the previous layer， thereby enhancing feature representation capability. Second， a graph Convolutional Network-Transformer fusion module was designed， in which graph convolution was employed to extract local geometric information， while the self-attention mechanism of the Transformer was used to capture global contextual information. A cross-attention mechanism was further incorporated to achieve effective feature interaction between point clouds. Finally， a point matching enhancement module was introduced， which established point correspondences by jointly considering the Euclidean distance of point features and the similarity of their local neighborhoods. The proposed algorithm was evaluated on the ModelNet40 （with noise）， 7Scenes， ICL-NUIM， KITTI， and ScanObjectNN datasets. Experimental results demonstrate that， compared with the IFNet algorithm， the proposed method achieves reductions in root mean square error RMSE（R） of 31.93%， 23.72%， 19.76%， 10.53%， and 21.05%， respectively， validating its superiority in both registration accuracy and robustness. Overall， the proposed algorithm exhibits excellent performance in registration accuracy， generalization capability， and noise resistance， showing strong potential for real-world applications.关键词：point cloud registration;feature interaction;cross-attention;point matching enhancement;unsupervised35|17|0更新时间：2025-12-02
- “在睑板腺图像分割领域，研究者设计了端到端多粒度分割算法，有效解决了边缘模糊和腺体粘连问题，为睑板腺功能障碍辅助诊断提供依据。”摘要：To address the multi-stage processing and edge blurring issues in meibomian gland image segmentation， this paper designed an end-to-end multi-granularity segmentation algorithm. During the encoding phase， the TransUNet encoder architecture was adopted to efficiently extract shared features of the eyelid and glandular regions. In the decoding phase， a dual decoding path was employed to set up different decoder branches for the unique features of the eyelid and glandular regions. Meanwhile， for the glandular region， a multi-scale feature fusion module was designed， and a channel attention mechanism was incorporated into the skip connections. These optimizations improved edge accuracy， texture clarity， and shape contour， thereby effectively solving the problems of edge blurring and glandular adhesion. For the eyelid region， a standard decoder structure was used for segmentation prediction. Through experimental comparison with existing advanced segmentation methods， the proposed algorithm exhibits excellent performance in terms of the average accuracy for the upper and lower meibomian glands. Especially on the key indicators of mean Intersection over Union （IoU） and Dice Similarity Coefficient， it reaches 79.9% and 76.5% respectively， which are 3.2% and 5.3% higher than those of TransUNet. The algorithm in this paper can accurately segment the target regions of meibomian gland images， which can provide a basis for the auxiliary diagnosis of meibomian gland dysfunction.关键词：meibomian gland image segmentation;multi-granularity segmentation;CNN;transformer;medical image processing28|16|0更新时间：2025-12-02
- “在三维重建领域，针对点云配准挑战，提出了自适应采样与几何-空间特征融合的配准算法，有效提高了匹配精度和鲁棒性。”摘要：Point cloud registration in 3D reconstruction scenarios faces significant challenges， as traditional local feature descriptors often fail due to insufficient keypoints， weak geometric descriptiveness， and poor matching robustness. To address these issues， this study proposed an adaptive sampling and geometry-spatial feature fusion algorithm. First， adaptive density-based voxelization followed by nearest-neighbor downsampling was proposed to address size and density imbalances between low-overlap point cloud pairs while achieving efficient data reduction. Next， surface normals were computed via KD-tree search， and a filtering mechanism incorporating neighborhood point count and linearity constraints was employed to identify salient keypoints. These selected points were subsequently encoded using fused geometry-spatial descriptors to overcome the redundancy and weak descriptiveness of conventional methods. Finally， a bidirectional correspondence approach based on histogram similarity identified reliable point matches， which were then refined through RANSAC to attain robust， high-precision registration under low-overlap conditions. The algorithm was validated on public benchmarks and real-world datasets. Experimental results demonstrate that our method reduces average matching error by 51.14%， 64.16%， and 78% compared to ISS+3DSC+K4PCS， ISS+FPFH+RANSAC， and TOLDI+RANSAC， respectively. Additionally， our approach achieves the highest runtime efficiency among all compared methods， evidencing superior accuracy， adaptability， and robustness.关键词：point cloud registration;low overlap;feature fusion;3D reconstruction36|15|0更新时间：2025-12-02
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