Strategic noise maps are typically prepared for large-scale areas, towns and cities. However, some comparatively smaller industries are given less importance during preparation of noise maps. Very few studies have been reported worldwide providing insight on industrial noise mapping, and similar reports from India are negligible. This study provides a noise map of a forging plant and also investigates noise distribution pattern within 2 km of surrounding area. The complete study is evaluated in two types of scenario; in the first scenario all individual noise sources of the plant were considered as point sources whereas in the second scenario complete plant was treated as an area source. Furthermore, a regression graph is generated between the predicted and measured values for both scenarios individually which gives coefficients of determination of 0.4689 and 0.6382. This study reveals that the second scenario provides more precise noise prediction map than the first scenario.
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http://dx.doi.org/10.4103/nah.NAH_7_17 | DOI Listing |
Front Psychol
January 2025
Music College, Shanghai Normal University, Shanghai, China.
Introduction: The significance of music might be attributed to its role in social bonding, a function that has likely influenced the evolution of human musicality. Although there is substantial evidence for the relationship between prosocial songs and prosocial behavior, it remains unclear whether music alone, independent of lyrics, can influence prosocial behaviors. This study investigates whether music and the emotions it induces can influence prosocial decision-making, utilizing the classical two-dimensional model of emotion (mood and arousal).
View Article and Find Full Text PDFBMJ Surg Interv Health Technol
January 2025
Department of Surgical Oncology, Kanazawa Medical University, Kahoku-gun, Japan.
Objectives: The advantages of indocyanine green (ICG) fluorescence cholangiography have been emphasized, but its disadvantages remain unclear. This study investigated the advantages and disadvantages of this modality, particularly the optimal timing of administration of ICG fluorescence.
Design: This was a retrospective analysis of prospectively collected patient data.
Conf Proc Int Conf Image Form Xray Comput Tomogr
August 2024
Department of Radiology, Perelman School of Medicine, Philadelphia, PA USA.
Despite the evident benefits of spectral computed tomography (CT) in delivering qualitative imaging superior to that of conventional CT in adults, its application in pediatric diagnostic imaging is still relatively limited due to various reasons, including design limitations and radiation dose considerations. The use of specialized K-edge filters, in conjunction with other spectral technologies, has been demonstrated to improve spectral quantification accuracy. X-ray flux limitations generally pose challenges in these concepts when applied to adults.
View Article and Find Full Text PDFFront Plant Sci
January 2025
Research Institute of Forest Policy and Information, Chinese Academy of Forestry, Beijing, China.
The processing of LiDAR point cloud data is of critical importance in the context of forest resource surveys, as well as representing a pivotal element in the realm of forest physiological and ecological studies.Nonetheless, conventional denoising algorithms frequently exhibit deficiencies with regard to adaptability and denoising efficacy, particularly when employed in relation to disparate datasets.To address these issues, this study introduces DEN4, an unsupervised, deep learning-based point cloud denoising algorithm designed to improve the accuracy of single tree segmentation in LiDAR point clouds.
View Article and Find Full Text PDFFront Hum Neurosci
January 2025
Student Affairs Office, Guilin Normal College, Guilin, China.
Introduction: Attention classification based on EEG signals is crucial for brain-computer interface (BCI) applications. However, noise interference and real-time signal fluctuations hinder accuracy, especially in portable single-channel devices. This study proposes a robust Kalman filtering method combined with a norm-constrained extreme learning machine (ELM) to address these challenges.
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