Objective
The effect of acute noise on cognitive function has long been a topic of study, yet these effects remain a serious problem for learning performance in school children.
Methods
From November 15, 2010 to December 8, 2010, we enrolled 268 students from three elementary schools (135 boys and 133 girls, 10–12 years old) in Ulsan, Korea. The study subjects were divided into two groups according to their test conditions (background versus additional noise), and tests were conducted using psychological examination tools. Chi-square tests and general linear models were used to assess the differences of impacts on cognition between the two groups.
Results
After adjusting for socio-demographic covariates, the noise significantly affected the results of full-scale IQ, verbal IQ, Continuous Performance Test scores, and Children’s Color Trails Test and Stroop test scores. The groups at high risk of learning difficulties were more affected by noise than low-risk groups.
Conclusion
These findings suggest that noise is hazardous to the attention and performance of elementary school students, particularly for groups at greater risk for poor academic achievement. Additional studies are needed to identify subject-specific levels of noise that can affect attention and cognitive function.
Combining aluminum and steel is a major goal of automobile manufacturers and other industries because the hybrid material reduces the weight of components. However, differences in chemical properties, thermal expansion, and physical characteristics of aluminum and steel are barriers to achieving this goal. In this article, selective laser melting (SLM), which is widely used in industrial fields, was applied to join dissimilar materials by printing aluminum on a steel substrate. Defects of joining during the SLM process, characteristics of the intermetallic reaction layer, and the effects of the process parameters were investigated. The analysis indicates that flake behavior could affect the quality of joining. The phases of the intermetallic layer found in this study were in agreement with other research, but the morphology of the layer was much different. A formula to estimate the join quality in terms of density energy is proposed. The results indicate that the SLM process is a promising method to manufacture a hybrid material.
Environmental noise is known to cause noise annoyance. Since noise annoyance is a subjective indicator, other mediators—such as noise sensitivity—may influence its perception. However, few studies have thus far been conducted on noise annoyance in South Korea that consider noise sensitivity and noise level simultaneously. The aim of this study was to evaluate the correlations between noise sensitivity or noise level and noise annoyance on a large scale in South Korea. This study estimated the level of noise exposure based on a noise map created in 2014; identified and surveyed 1836 subjects using a questionnaire; and assessed the impact of transportation noise and noise sensitivity on noise annoyance. The result showed that noise exposure level and noise sensitivity simultaneously affect noise annoyance, and noise sensitivity has a relatively larger impact on noise annoyance. In conclusion, when study subjects were exposed to a similar level of noise, the level of noise annoyance differed depending on the noise sensitivity of the individual.
Fault characteristic extraction is attracting a great deal of attention from researchers for the fault diagnosis of rotating machinery. Generally, when a gearbox is damaged, accurate identification of the side-band features can be used to detect the condition of the machinery equipment to reduce financial losses. However, the side-band feature of damaged gears that are constantly disturbed by strong jamming is embedded in the background noise. In this paper, a hybrid signal-processing method is proposed based on a spectral subtraction (SS) denoising algorithm combined with an empirical wavelet transform (EWT) to extract the side-band feature of gear faults. Firstly, SS is used to estimate the real-time noise information, which is used to enhance the fault signal of the helical gearbox from a vibration signal with strong noise disturbance. The empirical wavelet transform can extract amplitude-modulated/frequency-modulated (AM-FM) components of a signal using different filter bands that are designed in accordance with the signal properties. The fault signal is obtained by building a flexible gear for a helical gearbox with ADAMS software. The experiment shows the feasibility and availability of the multi-body dynamics model. The spectral subtraction-based adaptive empirical wavelet transform (SS-AEWT) method was applied to estimate the gear side-band feature for different tooth breakages and the strong background noise. The verification results show that the proposed method gives a clearer indication of gear fault characteristics with different tooth breakages and the different signal-noise ratio (SNR) than the conventional EMD and LMD methods. Finally, the fault characteristic frequency of a damaged gear suggests that the proposed SS-AEWT method can accurately and reliably diagnose faults of a gearbox.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.