Knowledge Discovery Of Noise Level In Lecture Rooms

The classroom acoustics is an important aspect of the lecturing and learning condition in university level to ensure the student able to receive the information and knowledge from the lecturer. Earlier works have reported on the room acoustic research by using the parameters like reverberation tim...

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Main Author: Tang, Jau Hoong
Format: Monograph
Language:English
Published: Universiti Sains Malaysia 2018
Subjects:
Online Access:http://eprints.usm.my/54302/
http://eprints.usm.my/54302/1/Knowledge%20Discovery%20Of%20Noise%20Level%20In%20Lecture%20Rooms_Tang%20Jau%20Hoong_M4_2018.pdf
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author Tang, Jau Hoong
author_facet Tang, Jau Hoong
author_sort Tang, Jau Hoong
building USM Institutional Repository
collection Online Access
description The classroom acoustics is an important aspect of the lecturing and learning condition in university level to ensure the student able to receive the information and knowledge from the lecturer. Earlier works have reported on the room acoustic research by using the parameters like reverberation time, background noise, clarity 50 and sound transmission index in the measurement. However, it was realized that no efforts were done on the lecture room physical attributes like the room sizes, geometry and shape, and frequency spectrum by data mining. Therefore, this study considers different lecture room sizes impact on the noise level. The objectives of this project are to differentiate the informative audio and background noise level from different lecture room sizes, to classify the noise level from audio quantitative measures and lecture room features and to identify the patterns of noise levels corresponding to the room physical attributes and the audio quantitative attributes. The audio data was collected from three different the lecture room sizes available at Engineering Campus, Universiti. The experimental audio recording will take place using 4 identical phones and camera tripod stand during lecture hours. Recorded audio data will go through data pre-processing for outlier and extreme value screening. Data classification was conducted in two phases; initially on 23 built-in classifier algorithms followed by a refinement of seven better-performed classifiers with selective attributes investigation using Weka tool. The pattern analysis and visualization will be applied to the data to identify the correlation between physical lecture room and audio quantitative measures. The study results showed 99.5918 % accuracy reflected on 6classifers which is the J48, REP Tree, Decision Table, JRip, OneR and PART. Findings show that the larger the room size, the lower will be the STI. Meanwhile, the smaller the room, the higher the noise produced specifically the first 10 minutes and the last 10 minutes of the lecture.
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spelling usm-543022022-08-25T00:13:18Z http://eprints.usm.my/54302/ Knowledge Discovery Of Noise Level In Lecture Rooms Tang, Jau Hoong T Technology TJ Mechanical engineering and machinery The classroom acoustics is an important aspect of the lecturing and learning condition in university level to ensure the student able to receive the information and knowledge from the lecturer. Earlier works have reported on the room acoustic research by using the parameters like reverberation time, background noise, clarity 50 and sound transmission index in the measurement. However, it was realized that no efforts were done on the lecture room physical attributes like the room sizes, geometry and shape, and frequency spectrum by data mining. Therefore, this study considers different lecture room sizes impact on the noise level. The objectives of this project are to differentiate the informative audio and background noise level from different lecture room sizes, to classify the noise level from audio quantitative measures and lecture room features and to identify the patterns of noise levels corresponding to the room physical attributes and the audio quantitative attributes. The audio data was collected from three different the lecture room sizes available at Engineering Campus, Universiti. The experimental audio recording will take place using 4 identical phones and camera tripod stand during lecture hours. Recorded audio data will go through data pre-processing for outlier and extreme value screening. Data classification was conducted in two phases; initially on 23 built-in classifier algorithms followed by a refinement of seven better-performed classifiers with selective attributes investigation using Weka tool. The pattern analysis and visualization will be applied to the data to identify the correlation between physical lecture room and audio quantitative measures. The study results showed 99.5918 % accuracy reflected on 6classifers which is the J48, REP Tree, Decision Table, JRip, OneR and PART. Findings show that the larger the room size, the lower will be the STI. Meanwhile, the smaller the room, the higher the noise produced specifically the first 10 minutes and the last 10 minutes of the lecture. Universiti Sains Malaysia 2018-05-01 Monograph NonPeerReviewed application/pdf en http://eprints.usm.my/54302/1/Knowledge%20Discovery%20Of%20Noise%20Level%20In%20Lecture%20Rooms_Tang%20Jau%20Hoong_M4_2018.pdf Tang, Jau Hoong (2018) Knowledge Discovery Of Noise Level In Lecture Rooms. Project Report. Universiti Sains Malaysia, Pusat Pengajian Kejuruteraan Mekanikal. (Submitted)
spellingShingle T Technology
TJ Mechanical engineering and machinery
Tang, Jau Hoong
Knowledge Discovery Of Noise Level In Lecture Rooms
title Knowledge Discovery Of Noise Level In Lecture Rooms
title_full Knowledge Discovery Of Noise Level In Lecture Rooms
title_fullStr Knowledge Discovery Of Noise Level In Lecture Rooms
title_full_unstemmed Knowledge Discovery Of Noise Level In Lecture Rooms
title_short Knowledge Discovery Of Noise Level In Lecture Rooms
title_sort knowledge discovery of noise level in lecture rooms
topic T Technology
TJ Mechanical engineering and machinery
url http://eprints.usm.my/54302/
http://eprints.usm.my/54302/1/Knowledge%20Discovery%20Of%20Noise%20Level%20In%20Lecture%20Rooms_Tang%20Jau%20Hoong_M4_2018.pdf