Search Results (282)

Optical networks serve as the backbone of modern communication, requiring statistical analysis and modeling to optimize performance, reliability, and scalability. This review paper explores statistical methodologies for analyzing network characteristics, dimensioning, parameter estimation, and cost prediction of optical networks, and provides a generalized framework based on the idea of convex areas, and link length and shortest path length distributions. Accurate dimensioning and cost estimation are crucial for optical network planning, especially during early-stage design, network upgrades, and optimization. However, detailed information is often unavailable or too complex to compute. Basic parameters like coverage area and node count, along with statistical insights such as distribution patterns and moments, aid in determining the appropriate modulation schemes, compensation techniques, repeater placement, and in estimating the fiber length. Statistical models also help predict link lengths and shortest path lengths, ensuring efficiency in design. Probability distributions, stochastic processes, and machine learning improve network optimization and fault prediction. Metrics like bit error rate, quality of service, and spectral efficiency can be statistically assessed to enhance data transmission. This paper provides a review on statistical analysis and modeling of optical networks, which supports intelligent optical network management, dimensioning of optical networks, performance prediction, and estimation of important optical network parameters with partial information. Full article

To address the issues of decreased accuracy and poor stability in distributed transfer alignment caused by factors such as wing deflection and deformation in complex flight environments, this paper proposes a wing-distributed transfer alignment method based on Fiber Bragg Grating (FBG). This paper establishes a flexural deformation model based on FBGs, establishes a coupling angle model and a dynamic lever arm model, derives the motion parameter relationship model between the main and the sub-nodes, establishes the corresponding transfer alignment filter, and proposes a federated adaptive filter based on allocation coefficients and an updated federated adaptive filter. The results show that the federated adaptive filtering algorithm based on allocation coefficients improved the pitch angle accuracy of the Inertial Measurement Unit (IMU) by 66.38% and the position estimation accuracy by 75.67%, compared to traditional algorithms. The arm estimation accuracy was also improved in the east and sky directions. Compared with traditional algorithms, the updated federated adaptive filtering algorithm improved the pitch angle accuracy of the sub IMU by 76.72%, the position estimation accuracy by 63.51%, and the lever arm estimation accuracy. Full article

This paper introduces the record-based transmuted Rayleigh distribution of order 3 (rbt-R), a three-parameter extension of the classical Rayleigh model designed to address data characterized by high skewness and heavy tails. While traditional generalizations of the Rayleigh distribution enhance model flexibility, they often lack sufficient adaptability to capture the complexity of empirical distributions encountered in applied statistics. The rbt-R model incorporates two additional shape parameters, a and b, enabling it to represent a wider range of distributional shapes. Parameter estimation for the rbt-R model is performed using the maximum likelihood method. Simulation studies are conducted to evaluate the asymptotic properties of the estimators, including bias and mean squared error. The performance of the rbt-R model is assessed through empirical applications to four datasets: nicotine yields and carbon monoxide emissions from cigarette data, as well as breaking stress measurements from carbon-fiber materials. Model fit is evaluated using standard goodness-of-fit criteria, including AIC, AIC_c, BIC, and the Kolmogorov–Smirnov statistic. In all cases, the rbt-R model demonstrates a superior fit compared to existing Rayleigh-based models, indicating its effectiveness in modeling highly skewed and heavy-tailed data. Full article

In complex reliability applications, it is common for the failure of an individual or an item to be attributed to multiple causes known as competing risks. This paper explores the estimation of the Hjorth competing risks model based on an adaptive progressive Type II censoring scheme via a binomial removal mechanism. For parameter and reliability metric estimation, both frequentist and Bayesian methodologies are developed. Maximum likelihood estimates for the Hjorth parameters are computed numerically due to their intricate form, while the binomial removal parameter is derived explicitly. Confidence intervals are constructed using asymptotic approximations. Within the Bayesian paradigm, gamma priors are assigned to the Hjorth parameters and a beta prior for the binomial parameter, facilitating posterior analysis. Markov Chain Monte Carlo techniques yield Bayesian estimates and credible intervals for parameters and reliability measures. The performance of the proposed methods is compared using Monte Carlo simulations. Finally, to illustrate the practical applicability of the proposed methodology, two real-world competing risk data sets are analyzed: one representing the breaking strength of jute fibers and the other representing the failure modes of electrical appliances. Full article

This paper presents a three-degrees-of-freedom origami parallel robot that is free from parasitic motion. This robot is designed to achieve one translational and two rotational motions within its workspace, enabling precise orientation about a fixed point—a capability unattainable for parallel robots with parasitic motion. The elimination of parasitic motion is critical, allowing the use of this device in applications requiring high precision. The robot’s key kinematic features include a parasitic motion-free workspace, large orientational capability, compactness, decoupled motion, simplicity in manufacturing and control, mechanically pivoted rotation of the moving platform, and scalability. These characteristics make the robot particularly well-suited for micromanipulation tasks in both manufacturing and medical applications. In manufacturing, it can enable high-precision operations such as micro-assembly, optical fiber alignment, and semiconductor packaging. In medicine, it can support delicate procedures such as microsurgery and cell injection, where sub-micron accuracy, high stability, and precise motion decoupling are critical requirements. The use of nearly identical limbs simplifies the architecture, facilitating easier design, manufacture, and control. The kinematics of the robot is analyzed using reciprocal screw theory for an analytic constraint-embedded Jacobian. To further enhance operational accuracy and robustness, particularly in the presence of uncertainties or disturbances, a deep neural network (DNN)-based state estimation method is integrated, providing accurate forward kinematic predictions. The construction of the robot utilizes origami-inspired limbs and joints, enhancing miniaturization, manufacturing simplicity, and foldability. Although capable of being scaled up or further miniaturized, its current size is 66 mm × 68 mm × 100 mm. The robot’s moving platform is theoretically and experimentally proven to be free of parasitic motion and possesses a large orientation capability. Its unique features are demonstrated, and its potential for high-precision applications is thoroughly discussed. Full article

This paper presents the fatigue limit of flax/PLA composites with different fiber reinforcement architectures. The configurations of the analyzed flax/PLA composites are [0°]₈, [0°/90°]_s, [+45°/−45°]_s, [90°]₄, stacking sequences, and basket weave laminates. The methods used to estimate the fatigue limit are the fitting of stress versus number of cycles data using Weibull and Basquin equations, the surface thermographic technique with bilinear and exponential models to analyze the evolution of temperature increment, and volumetric dissipated energy. According to the results found, superficial temperature and the maximum strain reached stabilization over 2000 cycles for σ_max/σ_ut < 0.7, which was used to determine cyclic stress–strain curves and the fatigue limit. The cyclic stress–strain shows a nonlinear behavior for all laminates, having a good correlation to the Ramberg–Osgood model. Furthermore, having the stabilized temperature and volumetric dissipated energy, the exponential model was used to evaluate the fatigue limit and compared to the values found by Basquin and bilinear models. The fatigue limit found by Basquin and bilinear models shows conservative values compared to the exponential models. The results also show that temperature measurement using infrared thermography is quite sensitive to the environmental temperature variation, especially at low stress applied, and finally, the comparison of these methods on different reinforcement configurations provides a guide to select a proper technique in each case. Full article

This paper tackles the important issue of the flexural strength of continuous fiber-reinforced ceramic composite. Estimates of the flexural strength of 2D woven SiC/SiC composite are extracted from symmetric and asymmetric 3-point bending test results using three independent approaches: (1) the equations of elastic beam theory for homogeneous solids, (2) finite element analysis of the stress state, (3) stress–strain relations in the tensile outer surface of specimens. Furthermore, the flexural strength is predicted from the ultimate tensile strength using a bundle failure model based on the fracture of the critical filament. It is shown that the equation of elastic beam theory significantly overestimates the flexural strength of the 2D SiC/SiC (620 MPa), while the alternate approaches and the predictions from the ultimate tensile strength converged to ≈340 MPa. The variability of strength data was approached using the construction of p-quantile diagrams that provide an unbiased assessment of the normal distribution function. Pertinent Weibull parameters are derived using the first moment equations. Important trends in the effects of the size, stress gradient, tension–flexure relations, strength of critical filament in a tow, and populations of critical flaws are established and discussed. Full article

As terrestrial resources become increasingly scarce, the exploration and utilization of marine resources have become crucial for ensuring a stable resource supply. A maritime A-Frame is a specialized lifting mechanism mounted on the stern of a vessel, designed for deploying and retrieving heavy loads during subsea exploration. Real-time monitoring of the stress of A-Frames is essential for identifying potential failures and preventing accidents. This paper presents a stress-monitoring campaign conducted on a maritime A-Frame during a deep-sea mining project in the South China Sea. Fiber Bragg Grating (FBG) strain sensors were installed on the A-Frame to measure its stress responses throughout the deep-sea mining operation. The stress variations observed during the deployment and retrieval of a deep-sea mining vehicle were analyzed. The results indicate that the stress caused by the swinging motion of the A-Frame was significantly higher than that generated by the lifting and deployment of the mining equipment. Additionally, a finite element model (FEM) of the A-Frame was developed to estimate the stress of the hot spots by integrating the measured strain data. The analysis confirmed that the maximum stress experienced by the A-Frame was well below the allowable threshold, indicating that the structure had sufficient strength to withstand operational loads. In addition, the swing angle of the A-Frame significantly affects the stress value of the A-Frame, while lifting the mining vehicle has a very slight effect. Thus, it is advisable to accelerate the deployment and retrieval speeds of the mining vehicle and minimize the outward swing angle of the A-Frame. These findings provide valuable insights for optimizing the design and ensuring the safe operation of maritime A-Frames in deep-sea mining exploration. Full article

This paper presents the development of two solutions for sandwich panels composed of a thin-layer alkali-activated composite (AAc) layer and a thicker insulation layer, formed by extruded polystyrene foam or expanded cork agglomerate (panels named AP_XPS or AP_ICB, respectively). The AAc combined ceramic waste from clay bricks and roof tiles (75%) with ladle furnace slag (25%), activated with sodium silicate. The AAc layer was further reinforced with polyacrylonitrile (PAN) fibers (1% content). The mechanical behavior was assessed by measuring the uniaxial compressive strength of cubic AAc specimens, shear bond strength, pull-off strength between the AAc layer and the insulation material, and the flexural behavior of the sandwich panels. The thermal performance was characterized by heat flux, inner surface temperatures, the thermal transmission coefficient, thermal resistance, and thermal conductivity. Mechanical test results indicated clear differences between the two proposed solutions. Although AP_XPS panels exhibited higher tensile bond strength values, the AP_ICB panels demonstrated superior interlayer bond performance. Similar findings were observed for the shear bond strength, where the irregular surface of the ICB positively influenced the adhesion to the AAc layer. In terms of flexural behavior, after the initial peak load, the AP_XPS exhibited a deflection-hardening response, achieving greater load-bearing capacity and energy absorption capacity compared to the AP_ICB. Finally, thermal resistance values of 1.02 m² °C/W and 1.14 m² °C/W for AP_ICB and AP_XPS were estimated, respectively, showing promising results in comparison to currently available building materials. Full article

In this paper, based on the multimode interference structure fiber and the sensitive advantages of a zeolitic imidazolate framework-8/Polydimethylsiloxane (ZIF-8/PDMS)-sensitive film in methane detection, a methane sensor based on an interferometer induced by multimode interference is designed and built with the aid of modeling. The methane-sensitive single mode fiber (MS-SMF) is obtained by coating a ZIF-8/PDMS-sensitive film around the cladding of a thin-diameter SMF. The change in methane concentration leads to a change in the cladding mode of the MS-SMF, which causes a change in interference spectrum and realizes methane concentration sensing. The factors affecting the sensitivity of the methane sensor are analyzed. Methane sensors with various parameters are fabricated and tested on a methane sensor platform for performance estimation at methane concentrations of 0–4%. The experimental results show that the sensitivity of the sensor to methane reaches 2.364 nm/% when the length of the MS-SMF is 42 mm, the thickness of the sensitive film is 1.8 µm, and the diameter of the MS-SMF is 58 µm. The limit of detection is about 338 ppm. The average response time is 30 s and the recovery time is 45 s. The temperature sensitivity of the methane sensor is approximately 0.026 nm/°C. The experimental results verify the correctness of the methane sensor model. This study provides a new design idea for optical methane sensors, showing great application potential in the field of methane detection. Full article

The space-division multiplexed (SDM) transmission technique based on uncoupled multi-core fibers (MCF) shows great implementation potential due to its huge transmission capacity and compatibility with existing transceivers. In this paper, we demonstrate a real-time single-span 106 km field trial over deployed 4-core MCF cable using commercial 800 Gb/s optical transport network (OTN) transceivers. The transceivers achieved a modulation rate of 130 Gbaud with the optoelectronic multiple-chip module (OE-MCM) packaging technique, which enabled the adoption of a highly noise-tolerant probability constellation shaping a 16-array quadrature amplitude modulation (PCS-16QAM) modulation format for 800 Gb/s OTN transceivers, and could realize unrepeated long-span transmission. The 4-core 800 Gb/s transmission systems achieved a real-time transmission capacity of 256 Tb/s with fully loaded 80-wavelength channels over the C+L band. The performance of different kinds of 800 G OTN transceivers with different modulation formats under this long-span unrepeated optical transmission system is also estimated and discussed. This field trial demonstrates the feasibility of applying uncoupled MCF with 800 Gb/s OTN transceivers in unrepeated long-span transmission scenarios and promotes its field implementation in next-generation high-speed optical interconnection systems. Full article

Accurate and low-complexity phase estimation is crucial for optimal data recovery in coherent optical receivers, especially for applications in emerging scenarios such as low-margin optical networks, green networks, probabilistic-shaping modulation, the use of high-order modulation formats in hollow-core fibers, long-haul links operating at low signal-to-noise ratios, and free-space optical links in low-earth orbit satellites, among others. These new developments demand highly efficient and reliable data transmission methods, even under stringent conditions of minimal operational excess margin. This paper introduces an efficient pilot-assisted phase estimation strategy for coherent optical receivers, integrating robust interpolation techniques for quasi-optimal operation. Our approach significantly enhances phase estimation accuracy, addressing the unique challenges posed by these new scenarios. Through comprehensive simulations, we illustrate our method’s superiority over conventional methods, showcasing marked improvements in computational complexity and bit error rate. The results highlight the critical role of sophisticated interpolation in bolstering pilot-assisted phase estimation, offering a promising technique for optimizing performance in next-generation coherent optical receivers. Full article

Non-contact blade vibration measurement based on blade tip timing (BTT) is a signature method for health monitoring in large rotating machinery. Time of arrival (ToA), as the fundamental data in BTT, directly impacts the accuracy of subsequent vibration parameter identification, thereby affecting the effectiveness of real-time condition monitoring and fault detection. However, no direct calibration method currently exists for ToA, and BTT errors are typically assessed through indirect or relative measurements, resulting in imprecise accuracy evaluations. To address this gap, this paper proposes a method for evaluating BTT measurement accuracy through direct calibration of ToA. A ToA direct calibration model is developed, which equivalently transforms the ToA variation caused by blade vibration into the circumferential angle difference between the BTT sensor and the rotating blade disk. The associated errors are systematically analyzed, and the BTT measurement accuracy is assessed using the directly calibrated ToA. Additionally, a BTT accuracy evaluation device was developed to facilitate this assessment. The uncertainty of the device was evaluated using the Monte Carlo method, accounting for both systematic and random factors. At 0.5° and 1000 rpm, the device yielded an estimated ToA value of 83.3055 μs, with the standard uncertainty of 8.824 × 10⁻³ μs and the 95% confidence interval of [83.2881, 83.3233] μs. The accuracy evaluation tests performed with the developed device simulated various vibration displacement and rotational speed conditions to validate the optical fiber BTT measurement system. The results showed that the system achieved a relative accuracy better than 0.8% and a repeatability accuracy exceeding 0.5%. The proposed BTT accuracy evaluation method and device have been validated for assessing both the accuracy and stability of the BTT measurement system, providing a reliable and precise approach for its evaluation. Full article

Background/Aims: The pelvic floor muscles are important structures involved in pelvic floor tone, pelvic organ support, and continence. The aim of this study was to perform an update on the pelvic floor muscle structure and function alterations of women with pelvic floor dysfunctions. Methods: A systematic search was undertaken in two electronic databases, PubMed/Medline and Ovid Discovery to find manuscripts (in English), published between 1 January 2002 and 31 July 2022, including all clinical studies using the following search terms: “muscle” or “extracellular matrix *” and “pelvic floor dysfunction *”. All clinical trials, observational, or animal studies examining the muscle and reporting pelvic floor dysfunction as a primary outcome were included. Case reports, literature reviews, conference papers and theses, and unpublished data were excluded. To ensure that no eligible articles were overlooked, the reference lists of all included papers underwent manual scrutiny. The bias level was estimated using Newcastle–Ottawa Scale (NOS) for cohort and case-control studies. A qualitative synthesis was performed. Results: The significant qualitative and quantitative heterogeneity between the studies did not allow for a quantitative analysis. Of the 30 articles selected with a total of 5592 women, 15 referred to the analysis of structural muscle defects, which included 3365 participants with urinary incontinence, pelvic organ prolapse, fecal incontinence, cistocele, rectocele, and sexual dysfunction; 10 manuscripts referred to the study of pelvic floor muscle function with a population of 2042 women, such as urinary incontinence, pelvic organ prolapse, fecal incontinence, and sexual dysfunction; and 5 papers evaluated cellular and/or molecular changes affecting the pelvic floor muscles, like urinary incontinence, pelvic organ prolapse, and rectocele, which included a total of 185 participants. Women with pelvic floor muscle defects are at greater risk of pelvic floor dysfunctions, and inversely, women with pelvic floor dysfunctions have more pelvic floor muscle defects than women without pelvic floor dysfunctions. These patients demonstrate a reduction in muscle tone, contraction strength, and resistance, a compromised neuromuscular activity, and an alteration of the normal composition and organization of the muscle cells. Conclusions: Women with pelvic floor dysfunction have anatomical muscle defects, disturbance of muscle function and cellular changes involving muscle cells and nerve fibers. Full article

This paper proposes an accuracy enhancement method for fiber-longitudinal power profile estimation (PPE) based on convolutional neural networks (CNN). Two types of CNNs are designed. The first network treats different polarization streams identically and is denoted as CNN. The second network considers the difference between the contributions of different polarization streams to the nonlinear phase shift and is denoted as enhanced CNN (ECNN). The numerical simulation results confirm the effectiveness of the method for a 64 Gbaud/s quadrature phase-shift keying (QPSK) polarization-division-multiplexed (PDM) coherent optical communication system with a fiber length of 320 km. The effects of finite impulse response (FIR) filter length, power into the fiber, and polarization mode dispersion on the PPE accuracy are examined. Finally, the results of the proposed method are monitored in the presence of several simultaneous power attenuation anomalies in the fiber optic link. It is found that the accuracy of the PPE substantially improves after using the proposed method, achieving a relative gain of up to 71%. When the modulation format is changed from QPSK to 16-ary quadrature amplitude modulation (16-QAM), and the fiber length is increased from 360 km to 480 km, the proposed method is still effective. This work provides a feasible solution for implementing fiber-longitudinal PPE, enabling significantly improved estimation accuracy in practical applications. Full article