Search Results (4,546)

Deep learning-based data-driven methods have gained significant attention in underwater acoustic source localization. However, their performance is often constrained by environmental disturbances and the scarcity of real-world underwater acoustic data. To address these issues, this paper presents a novel network termed MTCL-Net, a multi-task learning network that incorporates contrastive learning as an auxiliary task for underwater acoustic source ranging. A standard dataset and a perturbed dataset to simulate real underwater interferences are constructed based on known environmental parameters in this method. A Siamese dual-branch architecture is employed, where a contrastive learning task enables the automatic extraction of position-related features. The network jointly optimizes three tasks: source localization in perturbed environments, localization on the standard dataset, and position similarity discrimination, which improves the robustness and generalization ability. The experimental results on simulated and sea trial data demonstrate that MTCL-Net outperforms traditional matched field processing (MFP), single-task learning (STL), and multi-task learning based on depth–range (MTL-DR) methods in terms of mean absolute error (MAE) and probability of credible localization (PCL-10%). Specifically, on SWellEx-96 sea trial data, MTCL-Net achieves an MAE of 0.17 km and a PCL-10% of 90.36%. Moreover, the proposed method only needs a few samples for fine-tuning and shows strong practicality in uncertain marine environments. Full article

Coal gangue is one of the most abundant solid wastes generated during coal mining. The use of coal gangue for underground backfilling is widely recognized as an effective approach to reducing waste accumulation and promoting sustainable utilization. To further investigate the bearing and deformation behavior of underground gangue filling materials, combined with the underground occurrence conditions of crushed gangue in goaf, a self-designed loading apparatus for crushed gangue was employed to perform lateral compression experiments on crushed gangue. The compaction deformation, fractal dimension, and acoustic emission evolution characteristics of crushed gangue under the influence of lithology, water content state, particle size distribution, and axial pressure were analyzed. The results indicate that higher rock strength, lower moisture content, smaller particle size range, and lower axial pressure significantly enhance the bearing capacity and reduce axial strain. The fractal dimension increases with decreasing rock strength, increasing moisture content, and increasing axial pressure, reflecting intensified particle fragmentation. The acoustic emission response exhibits three different stages, corresponding to void compaction, void filling, and structural adjustment. Axial pressure has been identified as the main factor controlling acoustic emission energy release, while water content significantly suppresses acoustic emission energy and event frequency. The key roles of particle sliding, rotation, and torque-driven rearrangement in controlling overall deformation were elucidated. These findings provide theoretical support for the mechanical behavior of gangue filling in the goaf and the sustainable disposal and resource utilization of mining waste. Full article

Continuous monitoring of pig behavior is essential for timely health management and welfare assessment in commercial production systems. Although vision-based methods have been widely studied, their practical application in commercial barns is often limited by variable lighting, frequent occlusion, and high stocking density. Acoustic sensing offers a non-contact alternative that is independent of lighting conditions; however, reliable behavior classification from pig vocalizations remains challenging in commercial environments because of background noise and temporal variability in sound patterns. In this study, an attention-guided acoustic framework, termed ATF-Conformer, was developed for pig vocalization classification under farm conditions. A five-class vocalization dataset was collected from finishing Landrace pigs and multiparous sows on a commercial farm, including cough, scream, estrus, feeding, and normal behavior sounds. The proposed framework combined spectrogram denoising with interactive attention to enhance behavior-related acoustic information, while a time-frequency-decoupled Conformer encoder was introduced to improve feature representation under noisy conditions. Final classification was performed using mask-based temporal pooling with an additive angular margin Softmax objective. In five-fold grouped cross-validation, ATF-Conformer achieved an accuracy of 97.34% ± 0.42 and outperformed several existing acoustic models across multiple evaluation metrics. A similar accuracy of 97.38% was obtained on an independent test set, indicating stable performance across datasets. These results suggest that the proposed method can support continuous, non-invasive pig vocalization-based behavior monitoring and may assist farm owners or workers in pen-level screening of frequent cough or abnormal vocal events, thereby supporting targeted on-site inspection in precision livestock farming. Full article

The work uses a comprehensive approach based on the information and communication concept of construction management templates to minimize information asymmetry between construction stakeholders when implementing innovative technologies. An analysis of the regulatory framework and patent research of existing analogs of wall structures was conducted. It was theoretically substantiated that the use of removable reusable formwork for monolithic walls made of expanded polystyrene concrete allows significant reduction in cost and logistics costs. A technology for erecting heat-insulating walls made of expanded polystyrene concrete (EPC) has been developed, which involves preliminary preparation of the insulation with the application of a protective reinforced layer. This allows avoiding performing labor-intensive and dangerous operations at height. A design of a noise-proof wall with sound-absorbing hollow-forming elements has been proposed, improving acoustic characteristics while saving materials. Thermophysical tests of fragments of walls made of expanded polystyrene concrete with a density of D250 (thickness of 260 mm) confirmed the need for additional insulation for heat transfer resistance for regulatory compliance. Acoustic studies have proven the effectiveness of using hollow-forming elements to increase the airborne noise insulation index and to reduce material consumption. All this helped to develop and patent the polystyrene concrete wall technology. For the first time, the concept of implementing the technological process of expanded polystyrene concreting of monolithic walls into construction management and production using construction management templates was proposed. This allowed the transformation of technological operations into a flow of objective data to minimize information asymmetry between project participants. It was theoretically proven that the objectification of production indicators through construction management templates is a base for measuring the commercial value and investment attractiveness of the technology being implemented. Full article

The nonlinear dynamic response of aerospace thin-walled structures in a post-buckling state under thermo-acoustic loads is critical for their design. This study investigates this phenomenon through integrated experimental and numerical approaches. Acoustic tests on thermally stressed flat plates yielded results in close agreement with finite element and reduced-order modal (FEM/ROM) simulations, with first-order frequency deviations within ±2 Hz and strain values of the same order of magnitude (10.7 µε vs. 9.5 µε at 50 °C). A key observation is the non-monotonic variation in the thermal modal frequency, which initially decreases then increases with the buckling coefficient, while dynamic strain data further validate the computational model. Comparative analysis of three Haynes 188 alloy geometries—flat plates, cylindrical shells, and spherical shells—reveals distinct behaviors rooted in their critical buckling temperatures (68.46 °C, 151.20 °C, and 698.28 °C, respectively): flat plates exhibit softening–hardening transitions with a frequency range of 491–624 Hz; cylindrical shells show irregular responses with a dramatic frequency drop from 1120 Hz to 360 Hz; and spherical shells maintain the highest stability and frequency range (1913–2109 Hz), governed by the buckling coefficient’s linear effect. Time-domain and probability density function (PDF) analyses elucidate the snap-through phenomena and the modulating roles of the buckling coefficient and sound pressure level (SPL). These findings underscore that geometric configuration and inherent stiffness are critical to post-buckling performance, providing a theoretical basis for designing aerospace components in extreme environments. Full article

The purpose of this paper is to investigate the seismic damage performance levels of reinforced concrete (RC) external beam–column joints exhibiting beam flexural failure mode based on acoustic emission (AE) characteristics. To achieve this purpose, two specimens of RC external beam–column joints with beam flexural failure mode were tested under constant axial compression at the column and low-cyclic lateral loading at the end of the beam. During the tests, six AE-based indicators—namely AE hit ($H_{\mathrm{AE}}$), AE energy ($E_{\mathrm{AE}}$), AE count ($C_{\mathrm{AE}}$), amplitude ($A_{\mathrm{AE}}$), rise time (RT), and peak frequency ($f_{\mathrm{p}}$)—were measured using the PCI-2 Acoustic Emission System equipped with R6$\alpha$ piezoelectric sensors. In addition, five damage performance levels, i.e., no damage, minor damage, medium damage, serious damage, and collapse, were proposed based on the analysis of AE monitoring results. After calibration, the fiber finite element method was used to conduct a numerical simulation of 432 joints subjected to lateral loading. An empirical expression for the material parameter of the Park–Ang damage model was presented based on simulated results. Suggested five damage performance levels were used together with a response databank from the numerical analysis to obtain the limit damage values. This work provides a quantitative AE-based framework for seismic damage assessment of RC external beam–column joints with beam flexural failure mode, which can inform performance-based seismic design and post-earthquake safety evaluation. Full article

Room acoustics computer models based on geometrical acoustics usually handle the sound reflections by the assumption of plane waves. However, if the sound source is a point source, which is usually the case, the spherical wave reflection would be more correct. An approximate model for the spherical wave reflection is presented, starting with the assumption of an infinite plane. It was found that the errors caused due to the simplified plane wave assumption can be significant, especially for hard surfaces and near grazing incidence. As something new, the gradual transition from a spherical wave to a plane wave approximation was addressed. For sound propagation exceeding 50 times the wavelength, the plane wave approximation was found to be fully justified, but for shorter distances the spherical wave reflection model should be applied. In contrast to previous work on spherical wave reflection, the reflection from a finite-sized surface was studied. For the first time, the spherical wave reflection model was combined with the complex radiation impedance of a finite-sized surface. One interesting application example of the spherical reflection model is the attenuation of sound propagation above the audience area in a performance space. Finally, the extension of the spherical wave reflection model to higher order reflections was addressed. Full article

High-frequency transformer (HFT) noise is a pivotal indicator of equipment performance. To conduct a comprehensive evaluation, this study systematically performed testing and evaluation on the noise generated by a 70 kW HFT under no-load conditions. Acoustic data were collected using acoustic sensors and a head-and-torso simulator, followed by an analysis of noise characteristics focusing on the impacts of voltage levels and operating frequencies. A multi-dimensional evaluation of HFT noise was carried out using sound quality parameters to unravel its intrinsic attributes under electrical parameter excitation. The key findings are as follows: HFT noise exhibits steady-state time-domain behavior and distinct tonal frequency-domain features; the dominant frequency is twice the operating frequency, with prominent harmonics. The noise intensity increases with the voltage levels (~47.0 dB (A) at 200 V to ~72.0 dB (A) at 750 V at 5 kHz) but decreases with the operating frequencies (~82.0 dB (A) at 4 kHz to ~47.0 dB (A) at 10 kHz at 750 V). This study establishes correlations between the electrical parameters and sound quality metrics; the loudness, sharpness, tone-to-noise ratio and prominence ratio are sensitive to the electrical parameters of HFT. Single-frequency noise from HFT exhibits remarkable perceptual salience, exacerbating the perceived annoyance. Thus, HFT design should prioritize reducing single-frequency noise to alleviate such issues. Full article

Cement stabilized macadam (CSM) bases are prone to cracking and void damage under long-term traffic loading and environmental actions, which accelerates structural deterioration. Although grouting is an effective method for treating such concealed defects, laboratory-based evaluation of repair effectiveness remains limited. In this study, field-cored CSM specimens were recombined in a cylindrical mold to simulate four void conditions (1/4, 2/4, 3/4, and 4/4), and repaired using an inorganic cementitious composite grouting material based on ultra-fine cement and high-belite sulphoaluminate cement (HBSAC), and modified with ethylene-vinyl acetate (EVA) latex, wollastonite (WO) whiskers, and polyvinyl alcohol (PVA) fibers. The repair effectiveness was evaluated through ultrasonic testing, capacitance measurement, uniaxial compression with acoustic emission (AE) monitoring, and computed tomography (CT). The results show that the longitudinal wave velocity of all repaired groups increases continuously with curing time, with a maximum increase of 21.98% at 28 days. The normalized capacitance response exhibits clear time- and layer-dependent variation, with the 4/4 group showing the most pronounced spatial heterogeneity. In the uniaxial compression tests, the peak load increases from 181 kN in the control group to 201–286 kN in the repaired groups, while the tensile-related AE event proportion increases from 77.35% in the 1/4 group to 89.38% in the 4/4 group. CT analysis shows that the proportion of micropores smaller than 1 mm³ increases from 66.3% to 82.7%, whereas the proportion of pores larger than 100 mm³ decreases from 46.5% to 21.6% after repair. These results demonstrate that the composite grouting material provides effective filling, structural reconstruction, and mechanical enhancement for void-damaged CSM, and that the proposed multi-source characterization framework is suitable for evaluating grouting repair performance. Full article

This study proposes a noise-robust unsupervised acoustic anomaly detection framework for early identification of abnormal operating conditions in rotating machinery under submarine-like environments with severe data scarcity. In such environments, underwater background noise and onboard interference sources significantly degrade signal quality, while limited computing resources constrain the deployment of high-complexity deep learning models. To address the lack of labeled fault data, the publicly available MIMII dataset was adopted as a proxy platform, and representative submarine interference sources were physically modeled, including colored background noise, structure-borne resonance, band-limited auxiliary noise, tonal components, and sensor noise. These components were combined and scaled to predefined SNR levels (−6 to 6 dB) to generate realistic noise-augmented data. Three unsupervised approaches were compared under edge deployment constraints: (i) Gaussian Mixture Model (GMM) with statistical MFCC features, (ii) statistical-feature-based Ensemble Autoencoder, and (iii) Conv1D-based Ensemble Autoencoder using 1-s log Mel-spectrogram segments. Performance was evaluated in terms of AUC, F1-score, and computational cost. Results show that GMM provides competitive detection performance with minimal computational burden, whereas Conv1D achieves superior accuracy when temporal fault patterns dominate, at the expense of higher complexity. The study provides practical design guidelines for acoustic anomaly detection under multi-noise and resource-constrained conditions. Full article

Indoor Environmental Quality (IEQ) strongly influences health, comfort, and learning performance in academic buildings, yet assessment practices remain fragmented and rarely aligned with sustainability goals. This study conducted a PRISMA 2020-guided systematic literature review to identify, screen, and map IEQ indicators for educational facilities and to develop a sustainability-aligned framework for classroom evaluation. Searches of Google Scholar, Scopus, and Web of Science (2010–2025) yielded 365 records; after de-duplication and eligibility screening, 142 peer-reviewed studies were included. From these, 118 unique IEQ indicators were extracted and classified into six domains: thermal comfort, indoor air quality, acoustic quality, visual comfort, environmental quality, and spatial quality. Using sustainability-oriented screening criteria (measurability, relevance, reliability, data accessibility, understandability, and long-term applicability), 50 indicators (42%) were retained as methodologically robust, while 68 (58%) were excluded due to weak standardization or limited practical applicability. The retained indicators were systematically mapped to the environmental, social, and economic pillars and aligned with key SDGs (3, 4, 7, 11, and 13). The resulting Sustainability-Aligned IEQ Indicator Framework integrates quality-screened indicators with pillar/SDG alignment and a mixed-method pathway that combines objective monitoring and occupant perception, supporting context-sensitive evaluation, particularly for naturally ventilated and tropical learning environments. Full article

With the increasing demand for intelligent fault monitoring, acoustic-based diagnosis has emerged as a promising solution for industrial applications such as pipeline leakage and electrical equipment fault detection. However, complex working conditions and domain shifts significantly degrade model performance, especially when unseen target domain data is unavailable. To address this, we propose an amplitude-phase collaborative augmentation network named AP-CANet tailored for acoustic fault diagnosis. Specifically, the network adaptively aligns amplitude and phase features across multiple source domains and performs label-consistent sample augmentation to enrich data diversity while preserving semantic consistency. A frequency–spatial interaction module further integrates global spectral information with local temporal details to improve feature discriminability. Moreover, we introduce a manifold triplet loss that scales shortest path distances in the feature manifold, encouraging the model to better capture subtle distinctions among hard samples and improving intra-class compactness and inter-class separability. We evaluate the proposed method on two publicly available datasets: the Pipeline Leak Acoustic Dataset (GPLA-12) and the Electrical Sound Dataset (MIMII-DG). Experimental results demonstrate superior performance under domain-shift scenarios, highlighting the method’s potential for scalable and low-cost acoustic fault diagnosis in real-world industrial environments. Full article

Unlike reactive systems, mechanical ventilation controlled by CO₂ concentration operates at a target efficiency that dynamically increases whenever the target CO₂ level is exceeded. This approach eliminates the typical ‘dead-time’ and prevents air quality degradation by ensuring the system adjusts its performance immediately in response to concentration changes. In this work, the study focuses on the development and evaluation of data-driven predictive models for near-term indoor CO₂ forecasting that can be integrated into pre-occupancy ventilation strategies, rather than designing a complete control scheme. Experimental data were collected over four months in a 48 m² smart laboratory configured as an open-plan office, where a heterogeneous IoT sensing architecture logged synchronized time-series measurements of CO₂ and microclimate variables (temperature, relative humidity, PM_2.5, TVOCs), together with acoustic noise levels and appliance-level energy consumption used as indirect occupancy-related signals. Raw telemetry was transformed into a 22-feature state vector using a structured feature engineering method incorporating z-score standardization, cyclic time encodings, multi-horizon CO₂ lags, rolling statistics, momentum features, and non-linear interactions to represent temporal autocorrelation and daily periodicity. The study benchmarks multiple regression paradigms, including simple baselines and ensemble methods, and found that an automated multi-level stacked ensemble achieved the highest predictive fidelity for short-term forecasting, with an Mean Absolute Error (MAE) of 32.97 ppm across an observed CO₂ range of 403–2305 ppm, representing improvements of approximately 24% and 43% over Linear Regression and K-Nearest Neighbors (KNN), respectively. Temporal diagnostics showed strong phase alignment with observed CO₂ rises during occupancy transitions and statistically reliable prediction intervals. Five-fold walk-forward cross-validation confirmed the temporal stability of these results, with top models achieving consistent R² values of 0.93–0.95 across Folds 2–5. These results demonstrate that, within a single-room university laboratory setting, historical sensor data from low-cost IoT devices can support accurate short-term CO₂ forecasting, providing a predictive layer that could support future proactive ventilation scheduling aimed at reducing CO₂ lag at the start of occupancy while avoiding unnecessary ventilation runtime. Generalization to other building types and occupancy profiles requires further validation. Full article

The miniaturization of medical ultrasound imaging transducers is currently limited by the thick backing layers required to dissipate backward acoustic energy. To address this, a novel hybrid composite backing material was developed by interpenetrating a three-dimensional open-cell nickel foam skeleton with a traditional tungsten-powder/epoxy-resin matrix. Two groups of composite samples with varying pores per inch (PPI) were fabricated, and their acoustic properties were systematically characterized. Experimental results indicated that the 100 PPI composite achieved macroscopic acoustic attenuation coefficients of 62.6 dB/cm at 5 MHz and 84.2 dB/cm at 7.5 MHz. These values are roughly three times higher than conventional backing materials, while maintaining a suitable acoustic impedance of 10.81 MRayl. A 5 MHz transducer utilizing a 5.0 mm layer of this proposed backing achieved a −60 dB two-way pulse-echo insertion loss, effectively eliminating backside interference with performance comparable to a 16.5 mm conventional backing. This structural strategy successfully reduces the required backing axial dimension by over 60% without compromising transducer bandwidth, offering a viable material solution for miniaturized ultrasonic transducers. Full article

Indoor environmental quality (IEQ) is increasingly recognized as a critical factor in shaping employee well-being, satisfaction, and work performance, particularly in hybrid workplace settings. This mixed-methods study examined how integrated IEQ conditions influence employee experience in a public-sector hybrid workplace through a case study of the WorkHub, a technology-enabled flexible workspace embedded within a large municipal utility. Quantitative data were collected from 93 valid survey responses using the Workplace Environment Satisfaction and Performance Questionnaire (WESP-Q™), and qualitative insights were obtained from a 90-min participatory think tank session with 24 employees. Results showed that WorkHub users reported significantly higher satisfaction across 15 of 18 environmental and spatial dimensions, including layout, thermal comfort, air quality, lighting, furnishings, cleanliness, and overall building experience. They also reported significantly stronger outcomes in collaboration access, work transition, focus support, work efficiency, workspace productivity, pride in work, and job satisfaction. Qualitative findings reinforced these results, highlighting technology integration, daylight, and spatial flexibility as key strengths, while identifying acoustics, thermal discomfort, and limited privacy as persistent challenges. These findings support a systems-oriented, human-centered approach to workplace design, demonstrating that integrated IEQ can enhance employee experience, collaboration, and organizational performance in hybrid public-sector environments. Full article