Relevant bibliographies by topics / ENSEMBLE EMPIRIAL MODE DECOMPOSITION / Dissertations / Theses
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Dissertations / Theses on the topic 'ENSEMBLE EMPIRIAL MODE DECOMPOSITION'

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Published: 11 September 2023

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1

Furlaneto, Dennis Carnelossi. "An analysis of ensemble empirical mode decomposition applied to trend prediction on financial time series." reponame:Repositório Institucional da UFPR, 2017. http://hdl.handle.net/1884/49137.

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Orientador : Luiz Eduardo S. Oliveira<br>Coorientador : David Menotti<br>Dissertação (mestrado) - Universidade Federal do Paraná, Setor de Ciências Exatas, Programa de Pós-Graduação em Informática. Defesa: Curitiba, 20/07/2017<br>Inclui referências : f. 63-72<br>Resumo: As séries temporais financeiras são notoriamente difíceis de analisar e prever dada sua natureza não estacionária e altamente oscilatória. Nesta tese, a eficácia da técnica de decomposição não-paramétrica Ensemble Empirical Mode Decomposition (EEMD) é avaliada como uma técnica de extração de característica de séries temporais p
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2

Li, Zhendan. "An Ensemble Empirical Mode Decomposition Approach to Wear Particle Detection in Lubricating Oil Subject to Particle Overlap." Thèse, Université d'Ottawa / University of Ottawa, 2011. http://hdl.handle.net/10393/20313.

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With the development of mechanical fault diagnosis technology, complex mechanical systems do not need to be shut down periodically for the maintenance. The working condition of the mechanical systems can be monitored by analyzing the wear metal particles in the systems' lubricating oil. However, the output signals of the monitoring sensor are non-stationary. In some case the particle signals are overlapped with each other. The goal of this thesis is to find a method to decompose those overlapped particle signals, and then count the particle number in the lubricating oil. At the beginning EMD
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Alshahrani, Saeed Sultan. "Detection, classification and control of power quality disturbances based on complementary ensemble empirical mode decomposition and artificial neural networks." Thesis, Brunel University, 2017. http://bura.brunel.ac.uk/handle/2438/15872.

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4

Lozano, García Manuel. "Multichannel analysis of normal and continuous adventitious respiratory sounds for the assessment of pulmonary function in respiratory diseases." Doctoral thesis, Universitat Politècnica de Catalunya, 2015. http://hdl.handle.net/10803/397706.

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Respiratory sounds (RS) are produced by turbulent airflows through the airways and are inhomogeneously transmitted through different media to the chest surface, where they can be recorded in a non-invasive way. Due to their mechanical nature and airflow dependence, RS are affected by respiratory diseases that alter the mechanical properties of the respiratory system. Therefore, RS provide useful clinical information about the respiratory system structure and functioning. Recent advances in sensors and signal processing techniques have made RS analysis a more objective and sensitive tool
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Quinlan, John Mathew. "Investigation of driving mechanisms of combustion instabilities in liquid rocket engines via the dynamic mode decomposition." Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/54343.

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Combustion instability due to feedback coupling between unsteady heat release and natural acoustic modes can cause catastrophic failure in liquid rocket engines and to predict and prevent these instabilities the mechanisms that drive them must be further elucidated. With this goal in mind, the objective of this thesis was to develop techniques that improve the understanding of the specific underlying physical processes involved in these driving mechanisms. In particular, this work sought to develop a small-scale, optically accessible liquid rocket engine simulator and to apply modern, high-s
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Wei, Shao-Kuan, and 魏韶寬. "Ensemble Empirical Mode Decomposition with Clustering Analysis." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/82011189687957252619.

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碩士<br>國立臺灣師範大學<br>數學系<br>100<br>Ensemble Empirical Mode Decomposition (EEMD) is an adaptive time-frequency data analysis method. Time series or signals can be decomposed into a collection of intrinsic mode functions (IMFs). Nevertheless, there appears a multi-mode problem where signals with a similar time scale are decomposed into different IMFs. A possible solution to this problem is to combine the multi-modes into a proper single mode, but there is no general rule on how to combine IMFs in the literature. In this paper, we propose to modify EEMD algorithm using the statistical clustering an
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Sheng-MaoWang and 王晟懋. "Automated program of Ensemble Empirical Mode Decomposition." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/2yg4c2.

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碩士<br>國立成功大學<br>航空太空工程學系<br>107<br>The ensemble empirical mode decomposition (EEMD) method is applied for wind data analysis in the current research. However, calculations could take a very long time. Therefore, an attempt is made to accelerate the calculations. MATLAB and Python are used to explore the characteristics of different programming language operations, and a user-friendly graphical interface is also developed, and the execution process will be operated automatically and continuously. The wind data analyzed were collected by the wind turbines located on campus of Case Western R
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Yang, Sheng-Ning, and 楊勝寧. "Using Complementary Ensemble Empirical Mode Decomposition Method To Analyze Images." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/38533054079787149646.

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碩士<br>國立陽明大學<br>醫學工程研究所<br>99<br>In this study, by Huang NE, who proposed the complementary empirical mode decomposition method based on the empirical mode decomposition method. The algorithm inherits the empirical mode decomposition some of the benefits. For example it can solve nonlinear and nonstationary signals. Another Empirical mode decomposition method and the traditional numerical methods, the base need to know prior to analysis, the original signals can be based on the characteristics and nature of the original signal automatically a number of nature apart from the function and the re
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9

Chen-KuoChen and 陳振國. "The Study of Pile Integrity Test Using Ensemble Empirical Mode Decomposition." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/55168835560927508888.

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碩士<br>國立成功大學<br>土木工程學系<br>105<br>Non-destructive testing (NDT) has the advantages of economical, fast, and a wide range of applicability. Therefore it is a fairly effective testing method. The testing of piles without pile cap has been considered a well-developed technique. However, affected by complex boundaries conditions, testing of piles with pile cap is more difficult. This study use Impulse response (IR) method for the field test, then use ensemble empirical mode decomposition (EEMD) by Hilbert-Huang Transform to decompose the signals, finally use Fast Fourier Transform (FFT) to transfor
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10

Tsai, Shu-Yun, and 蔡舒韻. "A Novel Energy Detection Method Based on Ensemble Empirical Mode Decomposition." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/mu66ak.

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碩士<br>國立東華大學<br>電機工程學系<br>100<br>Cognitive radio(CR) is a novel smart wireless communication technology. To improve spectrum utilization efficiency, CR can detect the communication environment features to automatically adjust the transmitting and receiving parameters of a system, such as power, frequency, and modulation mode etc. The spectrum sensing is a key technology in the CR. In this thesis, we use energy detection for spectrum sensing. Many researches on energy detection are performed on the basis of a precise knowledge of noise power environment to set threshold. In this thesis we use e
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11

Chao, Yung-cheng, and 趙永誠. "Near-field Sound Source Imaging System Using Ensemble Empirical Mode Decomposition." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/e9cwzj.

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碩士<br>國立臺灣科技大學<br>電子工程系<br>99<br>The conventional microphone array near-field Fourier acoustic holography using Fast Fourier Transform (FFT) is able to efficiently reconstruct sound field and acquire an image of noise distribution. However, Fourier transform causes measuring error in practical applications, and people have to select primary frequency for observing sound field holography based on the spectrum of source signal. In this thesis, we use the ensemble empirical mode decomposition (EEMD) owing to its adaptive basis and low mode-mixing, which are able to decompose multiple sound source
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12

Wu, Xuan-Han, and 吳宣漢. "Using Ensemble Empirical Mode Decomposition for Fatigue Analysis of Surface Electromyogram." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/15841409940840012481.

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碩士<br>朝陽科技大學<br>資訊工程系碩士班<br>99<br>Muscular endurance is not only an indispensable part of physical fitness, but also an important indicator for people’s health. The purpose of this study was to detect the muscle fatigue with the change of the median frequency of the electromygram (EMG) signal measured in exercise. Ten healthy students (five males and five females) were selected as subjects. All of them went a one month sports. A self designed device was used to measure and analytics the EMG signal of vastus lateralis. Three signal decomposition technologies, Wavelet Decomposition, Empirical Mo
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Wang, Ying-Chung, and 王英仲. "A Study of Applying Ensemble Empirical Mode Decomposition to Signal Noise Reduction." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/09763432018627673470.

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碩士<br>國立臺灣大學<br>工程科學及海洋工程學研究所<br>99<br>A signal analyzing method, Hilbert-Huang Transform (HHT), was proposed by Norden E. Huang et al. in 1998. By using Emprical Mode Decomposition (EMD), signal could be decomposed into a finite number of intrinsic mode functions (IMFs) based on the local characteristic time-scale of the signal. Devoting these IMFs with Hilbert Transform could obtain meaningful instantaneous information about the signal. In this thesis, Ensemble Empirical Mode Decomposition (EEMD) and the post-processing of EEMD that were improved from the original EMD were involved to re
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14

Chu, Chia-Ping, and 朱嘉平. "Robust Speech Recognition by Ensemble Empirical Mode Decomposition and its Parallel Processing." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/11922507124572269812.

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碩士<br>國立高雄大學<br>資訊工程學系碩士班<br>100<br>The main purposes of this study were to enhance and improve the speech recognition rate of speech recognition systems subject to some environment noise. In our research, we used Ensemble Empirical Mode Decomposition (Ensemble EMD) to decompose the speech signals with noise to several IMFs, and then find the best weights for each IMF by using real-coded genetic algorithm. Thereafter, the speech signals were recovered by summing the weighted IMFs to reduce the effect of the noise. Since the Ensemble EMD will take much computation time, a parallel computation a
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15

SNEKHA. "GENETIC ALGORITHM BASED ECG SIGNAL DE-NOISING USING EEMD AND FUZZY THRESHOLDING." Thesis, 2016. http://dspace.dtu.ac.in:8080/jspui/handle/repository/15346.

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ElectroCardioGram (ECG) signal records electrical conduction activity of heart. These are very small signals in strength with narrow bandwidth of 0.05-120 Hz. Physicians especially cardiologist use these signals for diagnosis of the heart’s condition or heart diseases. ECG signal is contaminated with various artifacts such as Power Line Interference (PLI), Patient–electrode motion artifacts, Electrode-pop or contact noise, and Baseline Wandering and ElectroMyoGraphic (EMG) noise during acquisition. Analysis of ECG signals becomes difficult to inspect the cardiac activity in the presence
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16

Chang, Chung-Yu, and 張仲宇. "An Approach to Eliminating EMG noise from ECG using Ensemble Empirical Mode Decomposition." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/16381634943074798556.

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碩士<br>國立臺灣大學<br>電子工程學研究所<br>101<br>Cardiovascular disease has been listed as the second rank of the top ten leading causes of death. Electrocardiogram(ECG) has played an important role and has been widely used clinically because it is a non-invasive, real-time, quick and easy-to-implement technique. Cardiovascular disease was diagnosed traditionally by inspection from doctors. For doctors, ECG noise can be easily ignored by visual inspection. Nevertheless, with the advance of science and technology, remote monitoring and diagnosis have become important processes to automatically detecting card
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17

Lu, Guan-Hung, and 呂冠鴻. "Using 2-D Ensemble Empirical Mode Decomposition to Extract Characteristic Wind-wave Signatures." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/d9byxm.

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博士<br>國立臺灣大學<br>工程科學及海洋工程學研究所<br>107<br>An image processing technique, which is based on 2-D ensemble empirical mode decomposition, is developed to decompose the thermal images at wind-wave surfaces with various wind conditions. Four components attributed to different flow processes, including the gravity waves, parasitic capillary waves, Langmuir circulations, and the streamwisely elongated coherent vortices induced by wind shear, and the corresponding contribution fractions are derived. In the lowest wind speed case, coherent vortices contribute the most to the surface signatures, and Langmu
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Wang, Jyng-Siang, and 王俊祥. "Fast Ensemble Empirical Mode Decomposition for Speech-Like Signal Analysis Using Shaped Noise Addition." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/7b33hc.

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碩士<br>國立臺灣科技大學<br>電子工程系<br>99<br>In Signal Processing, Empirical mode decomposition (EMD) is one of the useful approaches for processing nonlinear and nonstationary signals. It is adaptive to input signal and could decompose signal straightly in time domain. However, its shortcomings include mode mixing and end effects that usually appear in the decomposed bands. Although a noise-assisted data analysis (NADA) called ensemble empirical mode decomposition (EEMD) has been proposed to circumvent this problem, doing so also results in an inevitably long computation for alleviating the mode mixing.
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Lin, Jheng-Hong, and 林政弘. "Financial Time Series Forecasting Using Ensemble Empirical Decomposition Mode, Genetic Algorithm and Extreme Learning Machine." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/mf36zg.

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碩士<br>國立臺北科技大學<br>商業自動化與管理研究所<br>99<br>Financial time series are inherently nonlinear and non-stationary, it is therefore difficult using statistical models to forecast. ANN(Artificial Neural Networks)does not require strict theoretical assumptions, so it has been widely applied for financial prediction. On ANN learning algorithms, the ELM(Extreme Learning Machine) overcomes the drawback of traditional Back-propagation. This study takes the closing price of Taiwan Capitalization Weighted Stock Index, Shanghai Stock Exchange Composite Index and Hong Kong Hang Seng Index as research subjects dur
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Chang, Chi-Ying, and 張琦英. "Intrinsic fluorescence feature extraction of excitation-emission matrix by using multi-dimensional ensemble empirical mode decomposition." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/r72caw.

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碩士<br>國立交通大學<br>生醫工程研究所<br>102<br>Excitation-emission matrix (EEM) fluorescence spectroscopy is a noninvasive method for tissue diagnosis and has become important in clinical use. However, the intrinsic characterization of EEM fluorescence remains unclear. Photobleaching and the complexity of the chemical compounds make it difficult to distinguish individual compounds due to overlapping features. Conventional studies use principal component analysis (PCA) for EEM fluorescence analysis, and the relationship between the EEM features extracted by PCA and diseases has been examined. The spectral f
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Chuang, Shang-Yi, and 莊上毅. "A System-on-Chip Design of Ensemble Empirical Mode Decomposition Processor for Photoplethysmography Signals Processing System." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/n2m6p6.

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碩士<br>國立交通大學<br>生醫工程研究所<br>104<br>According to statistics regarding the ten leading causes of death among the Taiwanese people, announced by the Department of Health, Executive Yuan, mortalities due to cardiovascular disease (CVDs) accounted for 40.6% of the total number of deaths in 2014. These health concerns may also induce disease and afflictions such as hypertension, stroke, and diabetes. Therefore, innovative health-care systems with high integrativity have become an important topic of research in recent years. This thesis presents Photoplethysmography (PPG) signal processing System-on-C
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Hong, Huei-Cheng, and 洪暉程. "Applications of Ensemble Empirical Mode Decomposition (EEMD) and Auto-Regressive (AR) Model for Diagnosing Looseness Faults of Rotating Machinery." Thesis, 2009. http://ndltd.ncl.edu.tw/handle/umbye9.

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碩士<br>國立中央大學<br>光機電工程研究所<br>97<br>Post processing of Ensemble Empirical Mode Decomposition (EEMD) can be utilized to decompose the vibration signals of rotating machinery into finite number of Intrinsic Mode Functions (IMFs) without mode mixing problem. The basis of the post processing of EEMD will satisfy the well-defined conditions of IMF. The Autoregressive (AR) model of information-contained IMFs can be used to predict the unmeasured vibration signal, and the coefficients of AR model represent the feature of systematic dynamic behavior. In this paper, the post-processing of EEMD comb
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23

Zhendan, Li. "An Ensemble Empirical Mode Decomposition Approach to Wear Particle Detection in Lubricating Oil Subject to Particle Overlap." Thèse, 2011. http://hdl.handle.net/10393/20313.

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With the development of mechanical fault diagnosis technology, complex mechanical systems do not need to be shut down periodically for the maintenance. The working condition of the mechanical systems can be monitored by analyzing the wear metal particles in the systems' lubricating oil. However, the output signals of the monitoring sensor are non-stationary. In some case the particle signals are overlapped with each other. The goal of this thesis is to find a method to decompose those overlapped particle signals, and then count the particle number in the lubricating oil. At the beginning EMD
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24

Chen, Chun-Erh, and 陳均爾. "Predicting Arterial Stiffness With The Aid of Ensemble Empirical Mode Decomposition(EEMD) Algorithm of the Wrist Pulse Sigmals." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/49706152693930296506.

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碩士<br>國立東華大學<br>電機工程學系<br>98<br>In this study, we propose an easy-to-use noninvasive arterial stiffness assessment instrument that can be used to record the radial arterial pressure signals from the wrist. The system combines the ensemble empirical mode decomposition (EEMD) algorithm with the signals to derive a modified reflection index (MRI) and modified stiffness index (MSI). The performance of MRI and MSI was verified based on 46 subjects (35 men and 11 women, 20 to 27 years of age). Early self-monitoring of cardiovascular dysfunction and arterial stiffness can be easily and effectively a
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25

Liao, Jia-Ju, and 廖家駒. "An Effective Photoplethysmography Signals Processing System Based on Ensemble Empirical Mode Decomposition Method for Acquiring the Multiple Physiological Parameters." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/a5wbqb.

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碩士<br>國立交通大學<br>電子工程學系 電子研究所<br>104<br>The heavily medical burden caused by population ageing will become a serious challenge for the current and next generation medical care system. There is an urgent need of low-cost disease prevention and home care programs to lower the possible medical burden in the future. The cardiovascular diseases have been on the list of leading cause of death for years in Taiwan. There is about seventeen million people pass away because of cardiovascular around the world. There is urgent need to get the early prevention tool to reduce the risk of cardiovascular disea
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Chen, I.-Wei, and 陳弈暐. "An Integrated Electrocardiography and Photoplethysmography Signal Processing System Based on Ensemble Empirical Mode Decomposition Method for Multimodal Physiological Data Monitoring." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/yk4fna.

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Chen, Tzu-Tung, and 陳姿彤. "300-year dendroclimatic reconstructions based on conventional methods and Ensemble Empirical Mode Decomposition using Picea morrisonicola tree rings from central Taiwan." Thesis, 2011. http://ndltd.ncl.edu.tw/handle/76399793270131758250.

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碩士<br>國立臺灣大學<br>地質科學研究所<br>99<br>Virtually very little dendrochronology data have been reported internationally from Taiwan, despite the existence of many dendrochronologically appropriate tree species. In this study, the potential for reconstruction of local paleoclimate was investigated using multi-century tree-ring chronologies developed from Picea morrisonicola (the endemic Taiwan Spruce). Significant correlations were found against the mean April-June diurnal temperature range (DTR) and against the mean July-September maximum temperature (Tmax). Both of these climate parameters were recons
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