Search Results (1,021)

Elastic optical networks (EONs) must allocate resources dynamically to accommodate heterogeneous, high-bandwidth demands. However, the continuous setup and teardown of connections with different bit rates can fragment the spectrum and lead to blocking. The blocking predictors enable proactive defragmentation and resource reallocation within network controllers. In this paper, we propose two novel deep learning models (based on CNN–BiLSTM and CNN–LSTM) to predict blocking in EONs by combining spatial feature extraction from spectrum snapshots using 2D convolutional layers with temporal sequence modeling. This hybrid spatio-temporal design learns how local fragmentation patterns evolve over time, allowing it to detect impending blocking scenarios more accurately than conventional methods. We evaluate our model on the simulated NSFNET topology and compare it against multiple baselines, namely 1D CNN, 2D CNN, k-nearest neighbors (KNN), and support vector machines (SVMs). The results show that the proposed CNN–BiLSTM/LSTM models consistently achieve higher performance. The CNN–BiLSTM model achieved the highest accuracy in blocking prediction, while the CNN–LSTM model shows slightly lower accuracy; however, it has much lower complexity and a faster learning time. Full article

High-precision angular positioning mechanisms are essential across diverse scientific and industrial applications, from optical instrumentation to automated mechanical systems. Conventional bronze–steel gear reduction units, while reliable, are often heavy, costly, and unsuitable for chemically aggressive or vacuum environments, limiting their use in advanced research setups. This work introduces a novel 1:360 gear reduction system manufactured by resin-based additive manufacturing, designed to overcome these limitations. The compact worm–gear assembly translates a single crank rotation into a precise one-degree indicator displacement, enabling fine and repeatable angular control. A primary application is the alignment of parabolic mirrors in schlieren systems, where accurate tilt adjustment is critical to correct optical alignment; however, the design is broadly adaptable to other precision positioning tasks in laboratory and industrial contexts. Compared with conventional assemblies, the resin-based reducer offers reduced weight, chemical and vacuum compatibility, and lower production cost. Its three-stage reduction design further enhances load-bearing capacity, achieving approximately double the theoretical torque transfer of equivalent commercial systems. These features establish the device as a robust, scalable, and automation-ready solution for high-accuracy angular adjustment, contributing both to specialized optical research and general-purpose precision engineering. Full article

Stimulated Brillouin scattering (SBS) suppression and phase demodulation are two fundamental issues in remote interferometric fiber sensing systems. A method is proposed for achieving simultaneous SBS suppression and phase-generated carrier (PGC) demodulation in remote interferometric fiber sensing systems, with only the use of an electro-optic phase modulator (PM). A single-frequency laser is phase-modulated by a PM to generate multi-sideband light, which can suppress SBS in long-haul fibers and generate PGC combined with the optical fiber interferometer. Then, the phase signal of the optical fiber interferometer can be demodulated by the PGC demodulation method. A detailed theoretical analysis and the experimental results are presented to confirm the feasibility of the method. The results show that the proposed method can achieve high-performance PGC demodulation with much higher bandwidth and larger dynamic range than the conventional method. Meanwhile, the SBS and its induced phase noise can be suppressed effectively. This work presents a simple setup for SBS suppression and PGC demodulation in a remote interferometric fiber sensing system. The proposed method shows great potential for application in remote and large-scale interferometric fiber sensing systems. Full article

A two-photon fluorescence microscope employing line-shaped illumination is presented. This type of excitation is commonly expected to bring about the degradation of axial resolution because of the weaker focusing of the illuminating beam in just one direction. On the basis of a detailed theoretical investigation of the beam shaping performed by cylindrical lenses when inserted in conventional point-scanning systems, we design and implement a microscope set-up making use of readily available optical components. The experimental results show that the proper choice and arrangement of the cylindrical lenses that we have devised is able to preserve the optical-sectioning capability at the video-rate acquisition speed. Full article

Background: To assess the agreement among prediction models for the functional classification of intraocular lenses (IOLs) and discuss their limitations in evaluating pupil dependency of a sinusoidal IOL. Methods: An ISO-compliant optical bench setup with modifications to characterize the modulation transfer function area (MTFa) across pupil diameters from 1.5 to 5.5 mm was used to measure the Acriva Trinova Pro C Pupil Adaptive IOL. Six prediction models (Vega et al., 2018, Fernández et al., 2019, Alarcón et al., 2016, Armengol et al., 2020 were applied to estimate visual acuity defocus curves from MTFa and functional classification based on the depth-of-field (DOFi) and the increase in visual acuity (ΔVA) from intermediate to near. Results: Defocus curves for all prediction models consistently demonstrated a Full-DOFi response (>2.3 D at 0.2 logMAR), with differences in ΔVA emerging across pupil diameters. Continuous decreases (ΔVA < 0.05 logMAR) were observed at pupil diameters <2.5 mm, while Smooth transitions (ΔVA from 0.05 to 0.14 logMAR) occurred between 2.5–3.0 mm for all models except for Vega. At pupil diameters >3.5 mm, most models transitioned to a Steep classification (ΔVA ≥ 0.14 logMAR), except Fernández, which remained Smooth, and Armengol 2020a, which shifted to Steep at 4.0 mm. Conclusions: Visual acuity prediction models provide useful means of reporting optical bench data in clinically familiar metrics. However, outcomes should be interpreted with caution as functional classifications can vary depending on the optical bench setup and prediction model used. Full article

The modeling of light propagation in scattering media is an important topic that has attracted considerable attention in recent decades. Coupling microscopic parameters such as particle concentration, particle size, and the refractive index of the medium can broaden the applicability of the model and improve simulation accuracy. In this work, these parameters are used to regulate the anisotropy factor and the mean free path. They are then integrated into a random phase screen model constructed using the Monte Carlo and the Gerchberg–Saxton algorithm. An optical experimental setup was established, in which a Laguerre–Gaussian beam was employed as the incident light source and diffusers with mesh numbers of 1500, 600, and 220 were used as the scattering media. The model was validated through comparative analysis between simulated and experimental results. Correlation coefficients between the simulated and experimental beam profiles exceeded 0.73, and the maximum relative error in power-in-the-bucket was only 4.9%, confirming the model’s accuracy and reliability. Numerical simulations were performed based on the established model to investigate beam propagation behavior. The results indicate that increasing particle concentration and particle size both lead to enhanced beam centroid shift and beam broadening. This modeling method provides a useful tool for analyzing beam propagation in complex scattering media and holds potential applications in wavefront correction and structured beam recognition. Full article

In ocean engineering, the demand for fiber-optic vector hydrophones (FOVHs) is increasing. The performance of a FOVH depends on phase consistency between its pressure and acceleration channels, which should match the acoustic field’s properties. Phase polarity, which refers to the alignment of the output signal with the acoustic field direction, is critical. Incorrect phase polarity during sensor assembly can disrupt phase consistency and invalidate directional measurements. This study investigates phase polarity in mandrel FOVHs that use the Phase Generated Carrier (PGC) technique. We develop a theoretical model combining the PGC algorithm with elastic mechanics to analyze the response of acoustic signals. Our model shows that correct demodulated signal polarity requires a specific physical setup: the pressure sensor’s long arm should be on the inner mandrel and the short arm on the outer, while the accelerometer’s positive axis should follow the vector from the long to its short arm. These results are validated through standing wave tube experiments and lake tests. This research provides practical guidelines for the installation and calibration of FOVHs, ensuring phase consistency in underwater acoustic sensing. Full article

Mechanical vibrations induced by electromagnetic forces during transformer operation can lead to winding deformation or failure, an issue responsible for over 12% of all transformer faults. While previous studies have predominantly relied on accelerometers for vibration monitoring, this study explores the use of an optical sensor for real-time vibration measurement in a dry-type transformer. Experiments were conducted using a custom-designed single-phase transformer model specifically developed for laboratory testing. This experimental setup offers a unique advantage: it allows for the interchangeable simulation of healthy and deformed winding sections without causing permanent damage, enabling controlled and repeatable testing scenarios. The transformer’s secondary winding was short-circuited, and three levels of current (low, intermediate, and high) were applied to simulate varying stress conditions. Vibration displacement data were collected under load to assess mechanical responses. The primary goal was to classify this vibration data to localize potential winding deformation faults. Five supervised learning algorithms were evaluated: Random Forest, Support Vector Machine, K-Nearest Neighbors, Logistic Regression, and Decision Tree classifiers. Hyperparameter tuning was applied, and a comparative analysis among the top four models yielded average prediction accuracies of approximately 60%. These results, achieved under controlled laboratory conditions, highlight the promise of this approach for further development and future real-world applications. Overall, the combination of optical sensing and machine learning classification offers a promising pathway for proactive monitoring and localization of winding deformations, supporting early fault detection and enhanced reliability in power transformers. Full article

Modern ophthalmic imaging methods such as optical coherence tomography (OCT) typically require expensive scanner components to direct the light beam across the retina while the patient’s gaze remains fixed. This proof-of-concept experiment investigates whether the patient’s natural eye movements can replace mechanical scanning by guiding the gaze along predefined patterns. An infrared fundus camera setup was used with nine healthy adults (aged 20–57) who completed tasks comparing passive viewing of moving patterns to actively tracing them by drawing using a touchpad interface. The active task involved participant-controlled target movement with real-time color feedback for accurate pattern tracing. Results showed that active tracing significantly increased pupil diameter by an average of 17.8% (range 8.9–43.6%; p < 0.001) and reduced blink frequency compared to passive viewing. More complex patterns led to greater pupil dilation, confirming the link between cognitive load and physiological response. These findings demonstrate that patient driven gaze guidance can stabilize gaze, reduce blinking, and naturally dilate the pupil. These conditions might enhance the quality of scannerless OCT or other imaging techniques benefiting from guided gaze and larger pupils. There could be benefits for children and people with compliance issues, although further research is needed to consider cognitive load. Full article

Synechocystis sp. PCC 6803 is a photosynthetic microbe with high potential for capturing excessive atmospheric carbon while generating valuable bioproducts, like glucose. Current cultivation technologies remain expensive, closed-source, and poorly suited for downstream processing. This study presents a low-cost, open-source bioreactor platform with integrated modules for Synechocystis cultivation and glucose extraction. The system incorporates a photobioreactor, a lysis module, and a pressure-driven filtration setup. Optical density was continuously monitored using a custom-built module, and glucose was quantified using high-performance liquid chromatography (HPLC). Under an incident light intensity of approximately 400 $\mathsf{\mu }\mathrm{m}\mathrm{o}\mathrm{l}$${\mathrm{m}}^{-2}$${\mathrm{s}}^{-1}$, cultures reached a biomass productivity of 90 mg ${\mathrm{L}}^{-1}{\mathrm{day}}^{-1}$, with a specific growth rate of $0.166{\mathrm{day}}^{-1}$ and glucose concentrations up to $5.08$$\mathrm{m}\mathrm{g}{\mathrm{L}}^{-1}$. A model was developed to predict the growth based on measured environmental parameters, achieving a strong predictive accuracy with a mean absolute error and variance of $0.0009\pm 0.0003$. The system demonstrates up to 65% reduction in cost compared to commercial alternatives. This modular platform provides an accessible solution for biomanufacturing research and serves as a template for sustainable cyanobacteria-derived glucose production. Full article

This study describes the design and validation of an experimental setup for testing photoplethysmographic (PPG) devices intended for the non-invasive monitoring of vascular accesses in hemodialysis patients. Continuous assessment of arteriovenous fistulas is essential to detect pathological conditions such as stenosis, which can compromise patient safety and dialysis efficacy. While PPG-based sensors are capable of detecting such anomalies, their clinical applicability must be supported by controlled in vitro validation. The developed system replicates the anatomical, mechanical, optical, and hemodynamic features of vascular accesses. A 3D fistula model was designed and fabricated via 3D printing and silicone casting. The hydraulic circuit used red India ink and a PWM-controlled pump to simulate physiological blood flow, including stenotic conditions. Quantitative validation confirmed anatomical accuracy within 0.1 mm tolerance. The phantom exhibited an average Shore A hardness of 20.3 ± 1.1, a Young’s modulus of 10.4 ± 0.9 MPa, and a compression modulus of 105 MPa—values consistent with soft tissue behavior. Burst pressure exceeded 2000 mmHg, meeting ISO 7198:2016 standards. Flow rates (400–700 mL/min) showed <1% error. Compliance was 2.4 ± 0.2, and simulated blood viscosity was 3.9 ± 0.3 mPa·s. Systolic and diastolic pressures fell within physiological ranges. Photoplethysmographic signals acquired using a MAX30102 sensor (Analog devices Inc., Wilmington, MA, USA) reproduced key components of in vivo waveforms, confirming the system’s suitability for device testing. Full article

We present some numerical results on piston and tilt detection by using the Young experiment with Genetic Algorithms (GAs). We have simulated the cophasing of a flat surface by following the experimental setup and the mathematical model for Optical Path Difference (OPD) in the Young experiment to characterize piston and tip–tilt misalignment images in the order of a few nanometers, considering diffraction effects and random noise of 5%. Thus, the best fitness obtained by the genetic algorithm is considered as a determining factor to decide a complete error measurement because the proposed algorithm is capable of extracting the values of piston and tilt separately, regardless of which error is present or both. As a result, we have developed a study on piston detection from (0.001, 10) mm with a tilt present in the same pattern from (0, $\lambda /2$) by using GAs embedded in a computational application. Full article

We present a comprehensive study of LED-based optical sensing systems for the classification of waste materials, analyzing recent developments in the field. Accurate identification of materials such as plastics, glass, aluminum, and paper is a crucial yet challenging task in waste management for recycling. The first approach uses short-wave infrared reflectance spectroscopy with commercial Germanium photodetectors and selected LEDs to keep data complexity and cost at a minimum while achieving classification accuracies up to 98% with machine learning algorithms. The second system employes a voltage-tunable Germanium-on-Silicon photodetector that operates across a broader spectral range (400–1600 nm), in combination with three LEDs in both the visible and short-wave infrared bands. This configuration enables an adaptive spectral response and simplifies the optical setup, supporting energy-efficient and scalable integration. Accuracies up to 99% were obtained with the aid of machine learning algorithms. Across all systems, the strategic use of low-cost LEDs as light sources and compact optical sensors demonstrates the potential of light-emitting devices in the implementation of compact, intelligent, and sustainable solutions for real-time material recognition. This article explores the design, characterization, and performance of such systems, providing insights into the way light-emitting and optoelectronic components can be leveraged for advanced sensing in waste classification applications. Full article

Monitoring of laser-based processes is essential for ensuring the quality of produced surface structures and for maintaining the process stability and reproducibility. Optical methods based on scatterometry are attractive for industrial monitoring as they are fast, non-contact, non-destructive, and can resolve features down to the sub-microscale. Here, Laser-Induced Periodic Surface Structures (LIPSS) are produced on stainless steel using ultrashort laser pulses in combination with a polygon scanning system. After the process, the fabricated LIPSS features are characterized by microscopy methods and with an optical setup based on scatterometry. Images of the diffraction patterns are collected and the intensity distribution analyzed and compared to the microscopy results in order to estimate the LIPSS height, spatial period, and regularity. The resulting analysis allows us to study LIPSS formation development, even when its characteristic diffraction pattern gradually changes from a double-sickle shape to a diffuse cloud. The scatterometry setup could be used to infer LIPSS height up to 420 nm, with an estimated average error of 7.7% for the highest structures and 11.4% in the whole working range. Periods estimation presents an average error of ~5% in the range where LIPSS are well-defined. In addition, the opening angle of the LIPSS was monitored and compared with regularity measurements, indicating that angles exceeding a certain threshold correspond to surfaces where sub-structures dominate over LIPSS. Full article

This study explores the integration of reduced graphene oxide (rGO) into an optoelectronic XOR logic gate to enhance BB84 protocol encryption in quantum communication systems. The research leverages the nonlinear optical properties of rGO, specifically its nonlinear refraction characteristics, in combination with a Michelson interferometer to implement an optoelectronic XOR gate. rGO samples were deposited using the Langmuir–Blodgett technique and characterized in morphology and structure. The optical setup utilized a frequency-modulated laser signal for the interferometer and a pulsed laser system that generates the quantum information carrier. This integration of quantum encryption with nonlinear optical materials offers enhanced security against classical attacks while providing adaptability for various applications from secure communications to quantum AI. Full article