Search Results (3,438)

Background/Objectives: This research focuses on the increasing presence of older workers in the labor market, a group particularly vulnerable to hearing problems due to age-related changes and prolonged noise exposure. Methods: The research combines theoretical and empirical approaches to investigate the impact of noise on the workplaces of older employees. The empirical component is based on two primary methods: a survey and audiometric testing to assess participants’ hearing abilities. The study included a sample of 50 older workers, all with diagnosed hearing loss. Results: The results of the survey showed that most older workers are regularly exposed to noise at work, which has long-term negative effects on their hearing. This highlights the need to introduce appropriate protective measures such as personal protective equipment, insulation of noise sources, and raising awareness about the dangers of noise. In addition to the questionnaire survey, the analysis of hearing measurements revealed that all respondents had significant bilateral hearing loss, with sensorineural hearing loss being the most prevalent type. Conclusions: This study highlights the negative impact of chronic noise exposure in the workplace on the hearing, communication and productivity of older workers and emphasizes the importance of combining preventive measures, hearing protection and workplace adaptations to promote their well-being and performance. Full article

The multi-wing centrifugal fan is an important part of air conditioning systems, particularly in the automotive domain. Due to the compact structure and short blade passage of the fan, it may reduce the aerodynamic performance and generate noise. As a key part of the multi-wing centrifugal fan, the volute tongue has an important impact on the aerodynamic performance and noise of the multi-wing centrifugal fan. In this paper, the volute tongue of a multi-wing centrifugal fan is modified for air conditioning systems, and a novel gradient-radius volute tongue is designed. Specifically, a simulation calculation model for the multi-wing centrifugal fan is developed based on the Realizable $k-\epsilon$ turbulence model and the Ffowcs Williams–Hawkings (FW-H) equation. The simulation results are analyzed, and the reliability of the proposed method is assessed by comparing the total pressure efficiency and noise levels with the corresponding experimental measurements. Subsequently, the aerodynamic performance and noise characteristics of the gradient-radius volute tongue are investigated, with particular attention given to variations in the flow field, pressure pulsation, and noise before and after the modification. The results indicate that the gradient-radius volute tongue effectively attenuates the pressure pulsations arising from the interaction between the volute and the airflow, thereby reducing the tongue-region noise. Compared with the original fan, a noise reduction of 3.5 dB is achieved through the implementation of the gradient-radius volute tongue. Full article

Micro and small wind turbines (MAWTs) are increasingly integrated into residential and prosumer hybrid energy systems. However, their real-world performance often falls short of catalog specifications due to mismatched wind resources, siting limitations, and insufficient attention to human comfort. This paper presents a comprehensive decision-support framework for selecting the type and scale of MAWTs under actual local conditions. The energy assessment module combines aerodynamic performance scaling, wind speed-frequency modeling based on Weibull distributions, turbulence intensity adjustments, and component-level efficiency factors for both horizontal and vertical axis turbines. The framework addresses three key design objectives: efficiency—aligning turbine geometry and control strategies with local wind regimes to maximize energy yield; comfort—evaluating candidate designs for noise emissions, shadow flicker, and visual impact near buildings; and climate adaptation—linking turbine siting, hub height, and rotor type to terrain roughness, turbulence, and built environment characteristics. Case studies from low and moderate wind locations in Central Europe demonstrate how multi-criteria filtering avoids oversizing, improves the autonomy of hybrid PV–wind systems, and identifies configurations that may exceed permissible limits for noise or flicker. The proposed methodology enables evidence-based deployment of MAWTs in decentralized energy systems that balance technical performance, resilience, and occupant well-being. Full article

In Global Navigation Satellite System (GNSS)-denied environments, navigation using signals of opportunity (SOP) from Low Earth Orbit (LEO) satellites is considered a feasible alternative. Compared with single-constellation systems, multiple-constellation LEO systems offer improved satellite visibility and geometric diversity, which enhances positioning continuity and accuracy. To allocate weights among heterogeneous observations, prior studies have employed the Helmert variance component estimation (HVCE) method, which iteratively determines relative weight ratios of different observation types through posterior variance estimation. HVCE enables error modeling and weight adjustment without prior noise information but is highly sensitive to outliers, making it vulnerable to their impact. This study proposes a Robust HVCE-based dual-constellation weighted positioning method. The approach integrates prior weighting based on satellite elevation, observation screening based on characteristic slopes, HVCE, and IGG-III robust estimation to achieve dynamic weight adjustment and suppress outliers. Experimental results over a 33.9 km baseline demonstrate that the proposed method attains Two-Dimensional (2D) and Three-Dimensional (3D) positioning accuracies of 12.824 m and 23.230 m, corresponding to improvements of 29% and 16% over conventional HVCE weighting, respectively. It also outperforms single-constellation positioning and equal-weighted fusion, confirming the effectiveness of the proposed approach. Full article

Space–time adaptive processing (STAP) based on sparse recovery (SR-STAP) has demonstrated remarkable clutter suppression performance under insufficient sample conditions. However, the main aim of sparse recovery is to solve the norm minimization problem. To this end, this study proposes a weighted STAP algorithm based on a greedy block coordinate descent method to address the problems of slow convergence speed and insufficient estimation accuracy in the existing l_2,1-norm minimization methods. First, the weights are estimated using the multiple signal classification (MUSIC) algorithm. Then, a greedy block selection rule that favors sparsity is used, prioritizing the update of the weighted block that has the greatest impact on sparsity. Although the proposed algorithm in this paper is greedy in nature, it is globally convergent. Finally, the accuracy of clutter covariance matrix estimation and the convergence speed of the SR-STAP algorithm are enhanced by reasonably estimating the noise power and selecting appropriate regularization parameters. The results of simulation experiments indicate that the proposed algorithm can effectively suppress clutter ridge expansion, achieving excellent clutter suppression and target detection performance compared with the existing methods, as well as satisfactory convergence properties. Full article

The flexible DC transmission project of renewable energy has become an inevitable development trend for large-scale renewable energy grid connection. A two-terminal weak feed (TTWF) AC system is often composed of 100% power electronic equipment. The traditional fault control strategy adopted after a fault in the converter at both terminals of the line limits the fault current and controls the phase, resulting in a decrease in the time-domain distance protection performance. This paper first analyzes the adaptability challenges of time-domain distance protection in TTWF. Based on detailed fault characteristic studies, two improvement approaches are proposed: (1) accounting for phase control effects by equivalently modeling the fault impedance as a series combination of fault resistance and inductance; and (2) incorporating distributed capacitance effects through fault differential equation derivation based on π-type line equivalent models. A novel time-domain distance protection method is subsequently developed, comprehensively considering control strategy impacts and distributed capacitive currents. Simulation tests verify that the proposed method maintains reliable operation under severe conditions, including 300 Ω fault resistance and 30 dB white noise interference, demonstrating significantly improved resistance to fault impedance and noise compared to conventional solutions. Full article

The ground small-loop transient electromagnetism (TEM) provides a basis for detecting shallow underground space. However, the strong primary field interference from the transmitting coil to the receiving coil, along with the transition process of the receiving coil, can cause serious distortion of the early secondary field signals. This leads to the loss of effective shallow underground information. In this paper, we utilize the eccentric self-compensating structure to weaken the primary field interference. Aiming at the current position sensitivity of the eccentric structure, we propose a statistical method to realize the robustness analysis of the eccentric structure and find the optimal eccentric position where the primary field coupling between the transmitting and receiving coil is approximated to be zero. To address the impact of the coil transition process, a double receiving coils structure is proposed. This ensures that the number of turns, the secondary field flux and the secondary field response strength in the single receiving coil structure remain unchanged. Compared with the conventional eccentric structure of a single receiving coil, the bandwidth of the receiving coil sensor was increased from 103.5 kHz to 218.3 kHz, and the Signal-to-Noise Ratio (SNR) of the measured early secondary field signals improved from 18.5 to 27.9, representing a 50.81% increase in SNR. This study not only reduces primary field interference but also reduces the impact of the coil transition process, thereby capturing more early secondary field signals and enhancing the shallow detection resolution of the ground TEM. Full article

Lubricants are useful for reducing the negative impacts of friction. An engine that is not properly lubricated will easily wear out, make noise, and produce excessive heat. The use of conventional petroleum-based lubricants still dominates, but the sustainability of fossil resources and the environmental impacts they have are major concerns. Therefore, the development of lubricants based on natural materials, or bio lubricants, is increasingly gaining attention. This paper aims to analyze various studies that have been conducted related to bio lubricants, especially those based on Indonesian natural resources. With the plant resources available in Indonesia, this research can be developed by utilizing the local wealth that is available, especially in abundance in Sukabumi City or Regency. Full article

Global navigation satellite systems (GNSSs) are an integral part of modern society and are used in various industries, providing users with positioning, navigation, and timing (PNT). However, their effectiveness is vulnerable to signal interference, since GNSSs are based on received satellite signals from space, and that can severely impact applications that rely on continuous and accurate data. Interference can pose significant risks to sectors dependent on GNSSs, including transportation, telecommunications, finance, geodesy, and others. For this reason, in parallel with the development of GNSSs, various interference protection techniques are being developed to enable users to receive GNSS signals without the risk of interference, which can cause various effects, such as reducing the accuracy of positioning, as well as completely blocking signal reception and making it impossible to obtain positioning. There are various sources and methods of interfering with GNSS signals, and the greatest consequences are caused by intentional interference, which includes jamming, spoofing, and meaconing. This study investigates the effects of jamming devices on static GNSS observations using high-accuracy devices through multiple controlled experiments using both single-frequency (SF) and multi-frequency (MF) jammers. The aim was to identify the distances within which signal interference devices disrupt GNSS signal reception and position accuracy. The research conducted herein was divided into several phases where zones within which the jammer completely blocked the reception of the GNSS signal were determined (blackout zones), as were zones within which it was possible to obtain the position (but the influence of the jammer was present) and the influence of the jammer from different directions/azimuths in relation to the GNSS receiver. Various statistical indicators of the jammer’s influence, such as DOP (dilution of precision), SNR (signal-to-noise-ratio), RMS (root mean square), and others, were obtained through research. The results of this study indicate that commercially available, low-cost jamming devices, when operated within manufacturer-specified distances, completely disrupt the reception of GNSS signals. Their impact is also evident at greater distances, where they significantly reduce SNR values, increase DOP, and decrease the number of visible satellites, leading to reduced measurement reliability and integrity. These results underline the necessity of developing effective protection mechanisms against GNSS interference and strategies to ensure reliable signal reception in GNSS-dependent applications, particularly as the use of jamming devices becomes more prevalent. Full article

Noise barriers are commonly used to reduce the adverse effects of traffic noise in both urban and suburban settings. While conventional systems constructed from concrete and steel provide reliable acoustic and structural performance, they raise sustainability concerns due to high embodied energy and carbon emissions. Glued-laminated (glulam) timber has emerged as a sustainable alternative, offering a reduced carbon footprint, aesthetic appeal, and effective acoustic performance. However, the crashworthiness of timber-based noise wall systems remains under investigated, particularly with respect to the safety criteria established in the 2016 edition of the American Association of State Highway and Transportation Officials (AASHTO) Manual for Assessing Safety Hardware (MASH). This study presents the full-scale crash testing and evaluation of glulam rubrail and noise wall systems under MASH Test Level 3 (TL-3) impact conditions. Building on a previously tested system compliant with National Cooperative Highway Research Program (NCHRP) Report 350, modifications were made to increase rubrail dimensions to meet higher lateral design loads. Three full-scale vehicle crash tests were conducted using 1100C and 2270P vehicles at 100 km/h and 25 degrees, covering both front- and back-mounted wall configurations. All tested systems demonstrated acceptable structural performance, effective vehicle redirection, and compliance with MASH 2016 occupant risk criteria. There was no penetration or potential for debris intrusion into the occupant compartment, and all measured occupant risk values remained well below allowable thresholds. Minimal damage to structural components was observed. The results confirm that the modified glulam noise wall system meets current impact safety standards and is suitable for use along high-speed roadways. This work supports the integration of sustainable materials into roadside safety infrastructure without compromising crash performance. Full article

Geothermal power generation offers a high availability factor and independence from weather conditions, yet steam production in geothermal wells often declines over time due to factors such as pressure depletion and scale deposition. To enable early detection of production anomalies and optimize maintenance, this paper proposes an anomaly detection framework based on Singular Spectrum Analysis (SSA). First, a Butterworth low-pass filter reduces high-frequency noise; then, SSA decomposes the time series, focusing on the largest singular value’s corresponding vectors. An anomaly score measures the deviation between current and historical singular vectors, and Non-Maximum Suppression (NMS) aggregates consecutive peaks to reduce false positives. We apply this method to 14 years of data from nine geothermal wells, comparing two threshold strategies: a unified threshold and well-specific thresholds. Results show that while a unified threshold simplifies deployment, individual thresholds can improve detection in certain wells, underscoring the impact of well characteristics and class imbalance. Our findings demonstrate that SSA-based anomaly detection, combined with NMS and threshold optimization, can effectively support maintenance decisions in geothermal power plants. Full article

Efficient and explainable vehicle damage inspection is essential due to the increasing complexity and volume of vehicular incidents. Traditional manual inspection approaches are not time-effective, prone to human error, and lead to inefficiencies in insurance claims and repair workflows. Existing deep learning methods, such as CNNs, often struggle with generalization, require large annotated datasets, and lack interpretability. This study presents a robust and interpretable deep learning framework for vehicle damage classification, integrating Vision Transformers (ViTs) and ensemble detection strategies. The proposed architecture employs a RetinaNet backbone with a ViT-enhanced detection head, implemented in PyTorch using the Detectron2 object detection technique. It is pretrained on COCO weights and fine-tuned through focal loss and aggressive augmentation techniques to improve generalization under real-world damage variability. The proposed system applies the Weighted Box Fusion (WBF) ensemble strategy to refine detection outputs from multiple models, offering improved spatial precision. To ensure interpretability and transparency, we adopt numerous explainability techniques—Grad-CAM, Grad-CAM++, and SHAP—offering semantic and visual insights into model decisions. A custom vehicle damage dataset with 4500 images has been built, consisting of approximately 60% curated images collected through targeted web scraping and crawling covering various damage types (such as bumper dents, panel scratches, and frontal impacts), along with 40% COCO dataset images to support model generalization. Comparative evaluations show that Hybrid ViT-RetinaNet achieves superior performance with an F1-score of 84.6%, mAP of 87.2%, and 22 FPS inference speed. In an ablation analysis, WBF, augmentation, transfer learning, and focal loss significantly improve performance, with focal loss increasing F1 by 6.3% for underrepresented classes and COCO pretraining boosting mAP by 8.7%. Additional architectural comparisons demonstrate that our full hybrid configuration not only maintains competitive accuracy but also achieves up to 150 FPS, making it well suited for real-time use cases. Robustness tests under challenging conditions, including real-world visual disturbances (smoke, fire, motion blur, varying lighting, and occlusions) and artificial noise (Gaussian; salt-and-pepper), confirm the model’s generalization ability. This work contributes a scalable, explainable, and high-performance solution for real-world vehicle damage diagnostics. Full article

Control point detection is a critical initial step in camera calibration. For checkerboard corner points, detection is based on inferences about local gradients in the image. Infrared (IR) imaging, however, poses challenges due to its low resolution and low signal-to-noise ratio, hindering the identification of clear local features. This study proposes a physics-informed neural network (PINN) based on the YOLO target detection model to detect checkerboard corner points in infrared images, aiming to enhance the calibration accuracy of infrared thermal cameras. This method first optimizes the YOLO model used for corner detection based on the idea of enhancing image gradient information extraction and then incorporates camera physical information into the training process so that the model can learn the intrinsic constraints between corner coordinates. Camera physical information is applied to the loss calculation process during training, avoiding the impact of label errors on the model and further improving detection accuracy. Compared with the baselines, the proposed method reduces the root mean square error (RMSE) by at least 30% on average across five test sets, indicating that the PINN-based corner detection method can effectively handle low-quality infrared images and achieve more accurate camera calibration. Full article

As contemporary society and the global economy become increasingly dependent on satellite-based systems, the need for reliable and resilient positioning, navigation, and timing (PNT) services has never been more critical. This study investigates the impact of the geomagnetic storm that occurred in May 2024 on the performance of global navigation satellite system (GNSS) low-cost permanent stations. The research evaluates the influence of ionospheric disturbances on both positioning performance and raw GNSS observations. Two days were analyzed: 8 May 2024 (DOY 129), representing quiet ionospheric conditions, and 11 May 2024 (DOY 132), coinciding with the peak of the geomagnetic storm. Precise Point Positioning (PPP) and static relative positioning techniques were applied to data from a low-cost GNSS station (DYVA), supported by comparative analysis using a nearby geodetic-grade station (TRDS00NOR). The results showed that while RMS positioning errors remained relatively stable over 24 h, the maximum errors increased significantly during the storm, with the 3D positioning error nearly doubling on DOY 132. Short-term analysis revealed even larger disturbances, particularly in the vertical component, which reached up to 3.39 m. Relative positioning analysis confirmed the vulnerability of single-frequency (L1) solutions to ionospheric disturbances, whereas dual-frequency (L1+L2) configurations substantially mitigated errors, highlighting the effectiveness of ionosphere-free combinations during storm events. In the second phase, raw GNSS observation quality was assessed using detrended GPS L1 carrier-phase residuals and signal strength metrics. The analysis revealed increased phase instability and signal degradation on DOY 132, with visible cycle slips occurring between epochs 19 and 21. Furthermore, the average signal-to-noise ratio (SNR) decreased by approximately 13% for satellites in the northwest sky sector, and a 5% rise in total cycle slips was recorded compared with the quiet day. These indicators confirm the elevated measurement noise and signal disruption associated with geomagnetic activity. These findings provide a quantitative assessment of low-cost GNSS receiver performance under geomagnetic storm conditions. This study emphasizes their utility for densifying GNSS infrastructure, particularly in regions lacking access to geodetic-grade equipment, while also outlining the challenges posed by space weather. Full article

People’s perceptions of architectural spaces are shaped by multiple senses, including vision and hearing. While vision has received extensive attention, hearing is often overlooked in architectural design, with a primary focus on sound insulation and noise reduction rather than on using acoustics to enhance spatial experience. Therefore, this study aims to investigate the impact of acoustic environments on two key spatial perceptions: Spaciousness and transparency. Two laboratory experiments were conducted with 60 participants. Thirty subjects evaluated 96 audiovisual stimuli for perceived spaciousness, and another 30 subjects assessed 128 audiovisual stimuli for perceived transparency. The results indicate that sound type significantly affects perceived spaciousness, while sound type and sound pressure level (SPL) significantly influence perceived transparency. Reverberation time (RT, T60) had no effect on either spatial perception. Interaction analysis further revealed that sound type affects transparency across different space sizes and window proportions, while SPL only influences small spaces and standard window proportions, with transparency decreasing as SPL increases. Mediation analysis showed that the effects of sound type on both spaciousness and transparency are partially mediated by subjective spatial perceptions, such as building environment preference and alignment with the outdoor environment. These findings emphasize the importance of integrating acoustic considerations into architectural design, which can enhance spatial experiences and provide valuable insights for future design practices. Full article