• Title/Summary/Keyword: 미이용 에너지

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Clustering and classification of residential noise sources in apartment buildings based on machine learning using spectral and temporal characteristics (주파수 및 시간 특성을 활용한 머신러닝 기반 공동주택 주거소음의 군집화 및 분류)

  • Jeong-hun Kim;Song-mi Lee;Su-hong Kim;Eun-sung Song;Jong-kwan Ryu
    • The Journal of the Acoustical Society of Korea
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    • v.42 no.6
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    • pp.603-616
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    • 2023
  • In this study, machine learning-based clustering and classification of residential noise in apartment buildings was conducted using frequency and temporal characteristics. First, a residential noise source dataset was constructed . The residential noise source dataset was consisted of floor impact, airborne, plumbing and equipment noise, environmental, and construction noise. The clustering of residential noise was performed by K-Means clustering method. For frequency characteristics, Leq and Lmax values were derived for 1/1 and 1/3 octave band for each sound source. For temporal characteristics, Leq values were derived at every 6 ms through sound pressure level analysis for 5 s. The number of k in K-Means clustering method was determined through the silhouette coefficient and elbow method. The clustering of residential noise source by frequency characteristic resulted in three clusters for both Leq and Lmax analysis. Temporal characteristic clustered residential noise source into 9 clusters for Leq and 11 clusters for Lmax. Clustering by frequency characteristic clustered according to the proportion of low frequency band. Then, to utilize the clustering results, the residential noise source was classified using three kinds of machine learning. The results of the residential noise classification showed the highest accuracy and f1-score for data labeled with Leq values in 1/3 octave bands, and the highest accuracy and f1-score for classifying residential noise sources with an Artificial Neural Network (ANN) model using both frequency and temporal features, with 93 % accuracy and 92 % f1-score.

The Analysis of Radiation Exposure of Hospital Radiation Workers (병원 방사선 작업 종사자의 방사선 피폭 분석 현황)

  • Jeong Tae Sik;Shin Byung Chul;Moon Chang Woo;Cho Yeong Duk;Lee Yong Hwan;Yum Ha Yong
    • Radiation Oncology Journal
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    • v.18 no.2
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    • pp.157-166
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    • 2000
  • Purpose : This investigation was peformed in order to improve the health care of radiation workers, to predict a risk, to minimize the radiation exposure hazard to them and for them to realize radiation exposure danger when they work in radiation area in hospital. Methods and Materials : The documentations checked regularly for personal radiation exposure in four university hospitals in Pusan city in Korea between January 1, 1993 and December 31, 1997 were analyzed. There were 458 persons in this documented but 111 persons who worked less then one year were excluded and only 347 persons were included in this study. Results : The average of yearly radiation exposure of 347 persons was 1.52$\pm$1.35 mSv. Though it was less than 50mSv, the limitaion of radiation in law but 125 (36%) people received higher radiation exposure than non-radiation workers. Radiation workers under 30 year old have received radiation exposure of mean 1.87$\pm$1.01 mSv/year, mean 1.22$\pm$0.69 mSv between 31 and 40 year old and mean 0.97$\pm$0.43 mSv/year over 41year old (p<0.001). Men received mean 1.67$\pm$1.54 mSv/year were higher than women who received mean 1.13$\pm$0.61 mSv/year (p<0.01). Radiation exposure in the department of nuclear modicine department in spite of low energy sources is higher than other departments that use radiations in hospital (p<0.05). And the workers who received mean 3.59$\pm$1.81 msv/year in parts of management of radiation sources and injection of sources to patient receive high radiation exposure in nuclear medicine department (p<0.01). In department of diagnostic radiology high radiation exposure is in barium enema rooms where workers received mean 3.74$\pm$1.74 mSv/year and other parts where they all use fluoroscopy such as angiography room of mean 1.17$\pm$0.35 mSv/year and upper gastrointestinal room of mean 1.74$\pm$1.34 mSv/year represented higher radiation exposure than average radiation exposure in diagnostic radiology (p<0.01). Doctors and radiation technologists received higher radiation exposure of each mean 1.75$\pm$1.17 mSv/year and mean 1.50$\pm$1.39 mSv/year than other people who work in radiation area in hospital (p<0.05). Especially young doctors and technologists have the high opportunity to receive higher radiation exposure. Conclusions : The training and education of radiation workers for radiation exposure risks are important and it is necessary to rotate worker in short period in high risk area. The hospital management has to concern health of radiation workers more and to put an effort to reduce radiation exposure as low as possible in radiation areas in hospital.

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