• Title/Summary/Keyword: periodic noise

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Comparative analysis of linear model and deep learning algorithm for water usage prediction (물 사용량 예측을 위한 선형 모형과 딥러닝 알고리즘의 비교 분석)

  • Kim, Jongsung;Kim, DongHyun;Wang, Wonjoon;Lee, Haneul;Lee, Myungjin;Kim, Hung Soo
    • Journal of Korea Water Resources Association
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    • v.54 no.spc1
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    • pp.1083-1093
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    • 2021
  • It is an essential to predict water usage for establishing an optimal supply operation plan and reducing power consumption. However, the water usage by consumer has a non-linear characteristics due to various factors such as user type, usage pattern, and weather condition. Therefore, in order to predict the water consumption, we proposed the methodology linking various techniques that can consider non-linear characteristics of water use and we called it as KWD framework. Say, K-means (K) cluster analysis was performed to classify similar patterns according to usage of each individual consumer; then Wavelet (W) transform was applied to derive main periodic pattern of the usage by removing noise components; also, Deep (D) learning algorithm was used for trying to do learning of non-linear characteristics of water usage. The performance of a proposed framework or model was analyzed by comparing with the ARMA model, which is a linear time series model. As a result, the proposed model showed the correlation of 92% and ARMA model showed about 39%. Therefore, we had known that the performance of the proposed model was better than a linear time series model and KWD framework could be used for other nonlinear time series which has similar pattern with water usage. Therefore, if the KWD framework is used, it will be possible to accurately predict water usage and establish an optimal supply plan every the various event.

Preliminary Study on GIS Mapping-based Fine Dust Measurement in Complex Construction Site (단지조성공사 내 드론을 활용한 GIS 맵핑 기반 미세먼지 측정 시스템 기초 연구)

  • Lee, Jaeho;Han, Jae Goo;Kim, Young Hyun
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.22 no.2
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    • pp.319-325
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    • 2021
  • A fine dust measurement using drones is becoming an increasingly common technology, and air pollutants can be identified through dust monitoring in partial industrial areas. A station for measuring fine dust provides information at large construction site offices. On the other hand, it was difficult to check the fine dust in the pollutant source accurately. Therefore, the drone took measurements directly after been placed at the site. While measuring fine dust, monitoring noise occurred due to the influence of the drone's down-wind during landing, but the measurements were similar to the numerical value of the grounded pollution source on the height of 30 m. The field applicability to the study area has limitations in periodic updates using satellite images because the terrain was constantly changing due to considerable flattening fieldwork. Therefore, this study implemented a system that can reflect real-time field information through GIS mapping using drones.

Development of Preliminary Quality Assurance Software for $GafChromic^{(R)}$ EBT2 Film Dosimetry ($GafChromic^{(R)}$ EBT2 Film Dosimetry를 위한 품질 관리용 초기 프로그램 개발)

  • Park, Ji-Yeon;Lee, Jeong-Woo;Choi, Kyoung-Sik;Hong, Semie;Park, Byung-Moon;Bae, Yong-Ki;Jung, Won-Gyun;Suh, Tae-Suk
    • Progress in Medical Physics
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    • v.21 no.1
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    • pp.113-119
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    • 2010
  • Software for GafChromic EBT2 film dosimetry was developed in this study. The software provides film calibration functions based on color channels, which are categorized depending on the colors red, green, blue, and gray. Evaluations of the correction effects for light scattering of a flat-bed scanner and thickness differences of the active layer are available. Dosimetric results from EBT2 films can be compared with those from the treatment planning system ECLIPSE or the two-dimensional ionization chamber array MatriXX. Dose verification using EBT2 films is implemented by carrying out the following procedures: file import, noise filtering, background correction and active layer correction, dose calculation, and evaluation. The relative and absolute background corrections are selectively applied. The calibration results and fitting equation for the sensitometric curve are exported to files. After two different types of dose matrixes are aligned through the interpolation of spatial pixel spacing, interactive translation, and rotation, profiles and isodose curves are compared. In addition, the gamma index and gamma histogram are analyzed according to the determined criteria of distance-to-agreement and dose difference. The performance evaluations were achieved by dose verification in the $60^{\circ}$-enhanced dynamic wedged field and intensity-modulated (IM) beams for prostate cancer. All pass ratios for the two types of tests showed more than 99% in the evaluation, and a gamma histogram with 3 mm and 3% criteria was used. The software was developed for use in routine periodic quality assurance and complex IM beam verification. It can also be used as a dedicated radiochromic film software tool for analyzing dose distribution.