• The Journal of the Korea Contents Association
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• v.17 no.5
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• pp.491-498
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• 2017

This study is to determine the significant effect of white and pink noise on brain. The brain synchronization has been analyzed under the condition of non-noise, white nose and pink noise(male 10, female 10, mean age $23.3{\pm}2.14$). As a result of analysis, pink noise stimulus, alpha, low beta band, and high beta band were significantly decreased than non-noise and white noise. In addition, these brain response pattern significantly increased at frontal lobe and temporal lobe, and dominated on the right hemisphere. This result is considered to be useful of sound design in driving quality of human life on the basis of neuroscience.

• Science of Emotion and Sensibility
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• v.16 no.4
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• pp.481-492
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• 2013

This study sorted scores of individual characteristics and multiple intelligence by sex, handle, blood type and age through previous questionnaire with 462 adult males and females. Then electrode was attached to prefrontal lobes Fp1 and Fp2 with EEG measuring system and changes of concentration between no stimulation state and pure pink noise stimulation and their relations to multiple intelligence were examined. As a result of analysis of covariance, the mean concentration of all subjects was significantly higher in the pink noise stimulation compared to no stimulation. According to individual characteristics, concentration was significantly higher in left-hander, type A blood, and group in their thirties except for gender. Concentration in pink noise state strengthened the relation to spatial intelligence and made negative correlations with musical intelligence compared to no stimulation state. These results suggested that individual characteristics should be reflected on using pink noise for improving concentration.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.2197-2204
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• 2015

In recent years, medical image diagnosis has growing significant momentous in the medicinal field. Brain and lung image of patient are distorted with salt and pepper noise is caused by moving the head and chest during scanning process of patients. Reconstruction of these images is a most significant field of diagnostic evaluation and is produced clearly through techniques such as linear or non-linear filtering. However, restored images are produced with smaller amount of noise reduction in the presence of huge magnitude of salt and pepper noises. To eliminate the high density of salt and pepper noises from the reproduction of images, a new efficient fuzzy based median filtering algorithm with a moderate elapsed time is proposed in this paper. Reproduction image results show enhanced performance for the proposed algorithm over other available noise reduction filtering techniques in terms of peak signal -to -noise ratio (PSNR), mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), image enhancement factor (IMF) and structural similarity (SSIM) value when tested on different medical images like magnetic resonance imaging (MRI) and computer tomography (CT) scan brain image and CT scan lung image. The introduced algorithm is switching filter that recognize the noise pixels and then corrects them by using median filter with fuzzy two-sided π- membership function for extracting the local information.

• Progress in Superconductivity
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• v.11 no.2
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• pp.152-157
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• 2010

We have fabricated the low noise liquid helium(LHe) dewar with a different shape of thermal shield to apply the 64-channel SQUID(Superconducting Quantum Interference Device) gradiometer. The first shape of thermal shield was made of an aluminum plate with a wide width of 100 mm slit and the other shape was modified with a narrow width of 20 mm slit. The two types of dewars were estimated by comparing the thermal noise and the signal-to-noise ratio(SNR) of magnetocardiography(MCG) using the $1^{st}$ order SQUID gradiometer system cooled each dewar. The white noise was different as a point of the dewar. The noise was increased as close as the edge of dewar, and also increased at the thermal shield with the more wide width slit. The white noise of the dewar with thermal shield of 100 mm slit was 6.5 fT/$Hz^{1/2}$ at the center of dewar and 25 fT/$Hz^{1/2}$ at the edge, and the white noise of the other one was 3.5 - 7 fT/$Hz^{1/2}$. We measured the MCG using 64-channel SQUID gradiometer cooled at each LHe dewar and compared the SNR of MCG signal. The SNR was improved of 10 times at the LHe dewar with a modified thermal shield.

• Nuclear Engineering and Technology
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• v.55 no.5
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• pp.1527-1532
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• 2023

The noise reduction algorithm using the non-local means (NLM) approach is very efficient in nuclear medicine imaging. In this study, the applicability of the NLM noise reduction algorithm in single-photon emission computed tomography (SPECT) images with a brain phantom and the optimization of the NLM algorithm by changing the smoothing factors according to various reconstruction methods are investigated. Brain phantom images were reconstructed using filtered back projection (FBP) and ordered subset expectation maximization (OSEM). The smoothing factor of the NLM noise reduction algorithm determined the optimal coefficient of variation (COV) and contrast-to-noise ratio (CNR) results at a value of 0.020 in the FBP and OSEM reconstruction methods. We confirmed that the FBP- and OSEM-based SPECT images using the algorithm applied with the optimal smoothing factor improved the COV and CNR by 66.94% and 8.00% on average, respectively, compared to those of the original image. In conclusion, an optimized smoothing factor was derived from the NLM approach-based algorithm in brain SPECT images and may be applicable to various nuclear medicine imaging techniques in the future.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.1.1-5
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• 1994

In the single sweep record of event-related potential (ERP), the peak latency of P300, which is one of the most prominent positive peaks in the ERP record, might fluctuate according to the recording conditions. The fluctuation of the peak latency (measurement fluctuation) is the summation of the fluctuation caused by physiological factor (physiological fluctuation) and one by noise of background EEG (noise fluctuation). We propsed a method for estimating the interval of the physiological fluctuation based on a limited number of single sweep records. The noise fluctuation was estimated by using the relationship between the signal-to-noise (SN) ratio and the noise fluctuation based on the P300 model and the background EEG model. The interval estimate of the physiological fluctuation were obtained by subtracting the interval estimate of the noise fluctuation from that of the measurement fluctuation. The proposed method was tested by using simulation data of ERP and applied to actual ERP and data of normal subjects, and gave satisfactory results.

• Proceedings of the KOSOMBE Conference
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• v.1997 no.11
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• pp.71-74
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• 1997

MR acoustic sound or noise due to gradient pulsings has been one of the problems in MRI, both in patient scanning as well as in many areas of psychiatric and neuroscience research, such as brain fMRI. Especially in brain fMRI, sound noise is one of the serious noise sources which obscures the small signals obtainable from the subtle changes occurring in oxygenation status in the cortex and blood capillaries. Therefore, we have studied the effects of acoustic or sound noise arising in fMR imaging of the auditory, motor and visual cortices. The results show that the acoustical noise effects on motor and visual responses are opposite. That is, for the motor activity, it shows an increased total motor activation while for the visual stimulation, corresponding (visual) cortical activity has diminished substantially when the subject is exposed to a loud acoustic sound. Although the current observations are preliminary and require more experimental confirmation, it appears that the observed acoustic-noise effects on brain unctions, such as in the motor and visual cortices, are new observations and could have significant consequences in data observation and interpretation in future fMRI studies.

• Korean Journal of Radiology
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• v.22 no.6
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• pp.951-958
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• 2021

Objective: To evaluate the usefulness of virtual monochromatic images (VMIs) obtained using dual-layer dual-energy CT (DL-DECT) for evaluating brain tumors. Materials and Methods: This retrospective study included 32 patients with brain tumors who had undergone non-contrast head CT using DL-DECT. Among them, 15 had glioblastoma (GBM), 7 had malignant lymphoma, 5 had high-grade glioma other than GBM, 3 had low-grade glioma, and 2 had metastatic tumors. Conventional polychromatic images and VMIs (40-200 keV at 10 keV intervals) were generated. We compared CT attenuation, image noise, contrast, and contrast-to-noise ratio (CNR) between tumor and white matter (WM) or grey matter (GM) between VMIs showing the highest CNR (optimized VMI) and conventional CT images using the paired t test. Two radiologists subjectively assessed the contrast, margin, noise, artifact, and diagnostic confidence of optimized VMIs and conventional images on a 4-point scale. Results: The image noise of VMIs at all energy levels tested was significantly lower than that of conventional CT images (p < 0.05). The 40-keV VMIs yielded the best CNR. Furthermore, both contrast and CNR between the tumor and WM were significantly higher in the 40 keV images than in the conventional CT images (p < 0.001); however, the contrast and CNR between tumor and GM were not significantly different (p = 0.47 and p = 0.31, respectively). The subjective scores assigned to contrast, margin, and diagnostic confidence were significantly higher for 40 keV images than for conventional CT images (p < 0.01). Conclusion: In head CT for patients with brain tumors, compared with conventional CT images, 40 keV VMIs from DL-DECT yielded superior tumor contrast and diagnostic confidence, especially for brain tumors located in the WM.

• International conference on construction engineering and project management
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• 2020.12a
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• pp.237-242
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• 2020

Construction noise is among the most critical stressors that adversely affect the quality of life of the people residing near construction sites. Many countries strictly regulate construction noise based on sound pressure levels, as well as timeslots and type of construction equipment. However, individuals react differently to noise, and their tolerance to noise levels varies, which should be considered when regulating construction noise. Although studies have attempted to analyze individuals' stress responses to construction noise, the lack of quantitative methods to measure stress has limited our understanding of individuals' stress responses to noise. Therefore, the authors proposed a quantitative stress measurement framework with a wearable electroencephalogram (EEG) sensor to decipher human brain wave patterns caused by diverse construction stressors (e.g., worksite hazards). This present study extends this framework to investigate the feasibility of using the wearable EEG sensor to measure individuals' emotional stress responses to construction noise in a laboratory setting. EEG data were collected from three subjects exposed to different construction noises (e.g., tonal vs. impulsive noises, different sound pressure levels) recorded at real construction sites. Simultaneously, the subjects' perceived stress levels against these noises were measured. The results indicate that the wearable EEG sensor can help understand diverse individuals' stress responses to nearby construction noises. This research provides a more quantitative means for measuring the impact of the noise generated at a construction site on neighboring communities, which can help frame more reasonable construction noise regulations that consider various types of residents in urban areas.

• Journal of radiological science and technology
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• v.40 no.4
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• pp.589-594
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• 2017

The objective of this study was to evaluate the enhancement effects of the quantum denoising system (QDS) on brain CT images. This retrospective study was conducted with 45 adults who visited G Radiology located in Gyungbuk for having brain CT tests between Jul 2017 and Oct 2017 after receiving consents. Subjects were divided into a control group (A group; no QDS(-) application during the brain CT test) and a treatment group (B Group; QDS(+) application during the brain CT test). The following conclusions were obtained from the study. The noise values at the Pons part and the Vermis part were significantly (p<0.05) lower in B Group ($Pons=5.41{\pm}1.05HU$; $Vermis=5.28{\pm}0.73HU$) than A Group ($Pons=6.92{\pm}0.98HU$; Vermis=6.72). The SNR values at the Pons part and the Vermis part were significantly (p<0.05) higher in B Group ($Pons=7.28{\pm}2.56$; $Vermis=8.63{\pm}3.04$) than A Group ($Pons=5.21{\pm}1.28$; $Vermis=6.23{\pm}1.49$). In conclusion, the results of this study suggested that the application of QDS to the brain CT test would enhance the signal to noise ratio (SNR) and the contrast to noise ratio (CNR) to provide an image more appropriate for diagnosis.