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Purpose Noise, an environmental stimulus, is especially important in the neurobehavioral development of newborns and brain development of infants at high risk. Conditions in the neonatal intensive care units (NICUs) may cause certain sensory stimuli that are not appropriate for the development of newborns, especially preterm infants. This study was conducted in order to determine noise levels in the NICU and to evaluate the effect of training provided for noise control. Design and Methods This study was conducted as a pretest-posttest quasiexperimental design between September and November 2014 in a 30-bed NICU of a tertiary hospital in Istanbul. A sample group consisting of 30 people (26 nurses, 4 care workers). Noise measurement devices were used in the Training Program of Noise Control. Results Of the health professionals, 96.7% were women, 86.7% were nurses, and 63.3% were university graduates. Some 36.7% of the health professionals had worked within the unit for more than 5 years. Noise measurements of full implementations were made over three 24-h periods. Noise measurements were taken before and after the training on Monday, Friday, and Sunday. Noise levels after training diminished in all three measurements, and the decrease was found statistically significant ( P < 0.01). Practice Implications Planned Noise Control Training for health professionals who work in NICUs is an effective way of reducing noise. We recommend that this training should be given to NICU health professionals and noise levels should be determined through measurements at specific times. [ABSTRACT FROM AUTHOR]

Edge detection methods based on derivatives of potential fields have been commonly utilizing to interpret the potential field data. Although these techniques are very useful tools for determining subsurface lineaments, they have some limitations such as sensitivity to noise, thick or diffuse detected boundaries and blurred edges. In this study, the Kuwahara filter, an edge enhancement operator which has smoothing, edge preserving and edge sharpening effects, is proposed to enhance the boundaries in the potential field data without above-mentioned limitations. Three synthetic model applications are made to demonstrate the mentioned advantages of the Kuwahara filter. The effect of the window size on the filter response has been studied and demonstrated in detail. After that, the total horizontal derivative, analytic signal and vertical gradient of the Kuwahara filter responses of the noisy synthetic gravity dataset have been calculated and compared with those calculated from the original data. In addition, it has been shown that the results can be further improved by applying the Gaussian smoothing to the Kuwahara filter responses. Finally, the Bouguer gravity dataset compiled from Konya-Beyşehir region in Turkey have been utilized to show the performance of the Kuwahara filter on real data. Both synthetic and real data applications have shown that more clearly edges and detailed results can be obtained from the datasets filtered by using the Kuwahara and Gaussian filters. [Display omitted] • Smoothing and edge preserving effects of the Kuwahara filter on potential field data. • The effect of the window size on the Kuwahara filter response. • Improvement the responses of derivative-based edge detection methods. [ABSTRACT FROM AUTHOR]