Search

Your search keyword '"Danyal Mahmood"' showing total 8 results
Start Over Author "Danyal Mahmood"
8 results on '"Danyal Mahmood"'

1. The Effect of Music Listening on EEG Functional Connectivity of Brain: A Short-Duration and Long-Duration Study

Author

Danyal Mahmood, Humaira Nisar, Vooi Voon Yap, and Chi-Yi Tsai

Subjects
functional connectivity, electroencephalography, music stimuli, graph theory, network-based statistics, Inter-Site Phase Clustering, Mathematics, QA1-939
Abstract

Music is considered a powerful brain stimulus, as listening to it can activate several brain networks. Music of different kinds and genres may have a different effect on the human brain. The goal of this study is to investigate the change in the brain’s functional connectivity (FC) when music is used as a stimulus. Secondly, the effect of listening to the subject’s favorite music is compared with listening to specifically formulated relaxing music with alpha binaural beats. Finally, the effect of the duration of music listening is studied. Subjects’ electroencephalographic (EEG) signals were captured as they listened to favorite and relaxing music. After preprocessing and artifact removal, the EEG recordings were decomposed into the delta, theta, alpha, and beta frequency bands, and the grand-averaged connectivity matrices were generated using Inter-Site Phase Clustering (ISPC) for each frequency band and each type of music. Furthermore, each lobe of the brain was analyzed separately to understand the effect of music on specific regions of the brain. EEG-FC among different channels was accessed by using graph theory and Network-based Statistics (NBS). To determine the significance of the changes in brain networks after listening to music, statistical analysis was conducted using Analysis of Variance (ANOVA) and t-test. The study of listening to music for a short duration verifies that either favorite or preferred music can affect the FC of the subject and induce a relaxation state. The short duration study also verifies a significant (ANOVA and t-test: p < 0.05) effectiveness of relaxing music over favorite music to induce relaxation and alertness in the subject. In the study of long duration, it is concluded that listening to relaxing music can increase functional connectivity and connections strength in the frontal lobe of the subject. A significant increase (ANOVA and t-test: p < 0.05) in FC in alpha and theta band and a significant decrease (ANOVA and t-test: p < 0.05) in FC in beta band in the frontal and parietal lobe of the brain verifies the hypothesis that the relaxing music can help the subject to achieve relaxation, activeness, and alertness.

Published
2022
Full Text
View/download PDF

8. Comparison of Segmentation Performance of Activated Sludge Flocs Using Bright-Field and Phase-Contrast Microscopy at Different Magnifications

Author

Der Sheng Tan, Danyal Mahmood, Humaira Nisar, Kim Ho Yeap, Veerendra Dakulagi, and Ahmed Elaraby

Abstract

Activated sludge (AS) is a type of process which is commonly used for the treatment of sewage and industrial wastewater. In this treatment process, the settling of the sludge flocs is important to ensure the normal functioning of the system, while sludge bulking has become a common and long-term problem that greatly affects floc settleability. Thus, methods based on image processing and analysis are introduced for monitoring AS wastewater treatment plants. However, the effectiveness of using image processing methods heavily depends on the performance of segmentation algorithms. The AS wastewater plant can be monitored through microscopic images of the flocs and filaments. Water samples are taken from the aeration tank of the wastewater plants and then observed using bright field and phase-contrast microscopy to compare the segmentation accuracy at different magnifications i.e., 4x, 10x, 20x, 40x. In this paper, three methods to segment and quantify the flocs in bright field and phase-contrast microscopy images have been analyzed. The first method is image segmentation using Bradley local thresholding method, the second method is texture segmentation using range filtering and Otsu’s thresholding and the third method is Gaussian Mixture Method based segmentation. The experimental results show that Gaussian Mixture Model Method gives the best segmentation accuracy for bright-field microscopy and 10x magnification gives the best results.

Published
2021

Catalog

Books, media, physical & digital resources
See catalog results