Current Issue : January-March Volume : 2026 Issue Number : 1 Articles : 5 Articles
The phase-sensitive optical time-domain reflectometry (Φ-OTDR) system has shown substantial potential in distributed acoustic sensing applications. Accurate event classification is crucial for effective deployment of Φ-OTDR systems, and various methods have been proposed for event classification in Φ-OTDR systems. However, most existing methods typically rely on sufficient labeled signal data for model training, which poses a major bottleneck in applying these methods due to the expensive and laborious process of labeling extensive data. To address this limitation, we propose CLWTNet, a novel contrastive representation learning method enhanced with wavelet transform convolution for event classification in Φ-OTDR systems. CLWTNet learns robust and discriminative representations directly from unlabeled signal data by transforming time-domain signals into STFT images and employing contrastive learning to maximize inter-class separation while preserving intra-class similarity. Furthermore, CLWTNet incorporates wavelet transform convolution to enhance its capacity to capture intricate features of event signals. The experimental results demonstrate that CLWTNet achieves competitive performance with the supervised representation learning methods and superior performance to unsupervised representation learning methods, even when training with unlabeled signal data. These findings highlight the effectiveness of CLWTNet in extracting discriminative representations without relying on labeled data, thereby enhancing data efficiency and reducing the costs and effort involved in extensive data labeling in practical Φ-OTDR system applications....
Detecting and alerting for falls is a crucial component of both healthcare and assistive technologies. Wearable devices are vulnerable to damage and require regular inspection and maintenance. Manned video surveillance avoids these problems, but it involves constant labor-intensive attention and, in most cases, may interfere with the privacy of the observed individuals. To address this issue, in this work we introduce and evaluate a novel approach for fully automated fall detection. The presented technique uses direct reconstruction of principal motion parameters, avoiding the computationally expensive full optical flow reconstruction and still providing relevant descriptors for accurate detections. Our method is systematically compared with state-of-the-art techniques. Comparisons of detection accuracy, computational efficiency, and suitability for real-time applications are presented. Experimental results demonstrate notable improvements in accuracy while maintaining a lower computational cost compared to traditional methods, making our approach highly adaptable for real-world deployment. The findings highlight the robustness and universality of our model, suggesting its potential for integration into broader surveillance technologies. Future directions for development will include optimization for resource-constrained environments and deep learning enhancements to refine detection precision....
This theoretical work investigates the linear (absorption and emission) and nonlinear (first hyperpolarizability and TPA) optical properties of donor–π–acceptor (D–π–A) molecular architectures based on functionalized benzoxazoles, with potential applications in optoelectronic technologies such as OLEDs and solar cells. Four π-conjugated compounds were studied in the gas phase and in polar (methanol) and nonpolar (toluene) solvents, employing DFT with the B3LYP and CAM-B3LYP functionals and the 6-311++G(d,p) basis set, as implemented in Gaussian and Dalton. The results reveal that the chemical environment induces spectral shifts and modulates the intensity of electronic transitions. In particular, the compound 2-((4-((5-nitro-2-oxo-1,3-benzoxazol-3(2H)-yl)amino)phenyl)methyl)-1,3-benzoxazole exhibited outstanding behavior in methanol, with a significant increase in dipole moment, polarizability, and first hyperpolarizability (static and dynamic at 1064 nm), reaching a TPA cross-section close to 150 GM. These findings highlight the key role of ionic substituents in tuning the optical response of π-conjugated systems and underscore their potential as functional materials for high-performance light-emitting and energy-conversion devices....
In recent years, with the continuous advancement of technology and the expansion of application scenarios, AR has become a highly regarded field. However, AR still faces several challenges in practical usage. Notable shortcomings include inadequate image uniformity, low diffraction efficiency. Among these, the insufficient image uniformity stands out as a significant issue directly affecting user experience. The analysis of uniformity improvement in this study is limited to the simulated scenario of monochromatic blue light (LED light source), aiming to optimize the insufficient uniformity of the image output of the diffractive optical waveguide-based AR technology scheme. We improve the details of the input grating in the waveguide, such as the morphological characteristics of the grating, the detail parameter, etc. In addition, we propose to incorporate a photonic crystal film in the waveguide as an innovative study and find that the incorporation of the photonic crystal thin film significantly improves the uniformity of the output image in the diffractive optical waveguide scheme. In order to further verify the effect of the photonic crystal film on the uniformity of its image output, we also compare different types of coupled gratings and find that they all have a positive effect. Thus, the photonic crystal film demonstrated effective control over the diffraction optical waveguide scheme. This research offers new insights and design approaches for enhancing the output image uniformity based on diffraction optical waveguide technology, providing a new path for improving image uniformity in AR displays....
Slope stability monitoring and evaluation are key means to ensure the safety of engineering projects. Firstly, the classification, principles, and characteristics of distributed fiber optic sensing technology for slope engineering are introduced, and the significant advantages of this technology in slope monitoring are analyzed. Secondly, taking the Three Gorges Reservoir landslide as a case study, laboratory experiments of slopes were conducted using spatiotemporally continuous fiber optic neural sensing technology. Through the slope physical model experiment under loading excavation and rainfall conditions, it is found that (1) the strain changes monitored by vertically laid sensing cables are more sensitive to loading (with a peak strain of about 1400 με), while horizontally laid optical cables are more sensitive to excavation processes (with a peak strain of about 8900 με). Specifically, the tension–compression strain transformation in horizontally laid sensing cables can be used to identify slope failure in advance. (2) Rainfall infiltration significantly weakens the strength of the slope soil. Only considering the loading situation, the slope experiences instability and failure under a load of 120 kg. Under the premise of the soil saturation caused by rainfall infiltration, the slope experienced instability and failure under a load of 20 kg. Therefore, compared to human engineering activities, rainfall has a more significant impact on the stability of the slope. This study sheds light on the slope failure mechanism and provides a scientific basis for early warning....
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