Academic literature on the topic 'Long term average spectra'

The technique of �open throat� is a pedagogical concept transmitted through the oral tradition of singing. This thesis explored the pedagogical perceptions and practices of �open throat� using empirical methodologies to assess technical skill and associated vocal quality. In the first study (Mitchell, Kenny, Ryan, & Davis, 2003), we assessed the degree of consensus amongst singing pedagogues regarding the definition of, and use in the singing studio of the technique called �open throat.� Results indicated that all fifteen pedagogues described �open throat� technique as fundamental to singing training and were positive about the sound quality it achieved, especially in classical singing. It was described as a way of maximising pharyngeal space or abducting the false vocal folds. Hypotheses generated from pedagogical beliefs expressed in this first study were then tested acoustically (Mitchell & Kenny, 2004a, 2004b). Six advanced singing students sang in two conditions: �optimal� (O), using maximal open throat, �sub-optimal� (SO), using reduced open throat and loud sub-optimal (LSO) to control for the effect of loudness. From these recordings, acoustic characteristics of vibrato (Mitchell & Kenny, 2004b) and energy distribution (Mitchell & Kenny, 2004a) were examined. Subsequent investigations of the vibrato parameters of rate, extent and onset, revealed that extent was significantly reduced and onset increased when singers did not use the technique. As inconsistent vibrato is considered indicative of poor singing, it was hypothesized that testing the energy distribution in these singers� voices in each condition would identify the timbral changes associated with open throat. Visual inspection of long term average spectra (LTAS) confirmed differences between O and SO, but conventional measures applied to long term average spectra (LTAS), comparing energy peak height [singing power ratio (SPR)] and peak area [energy ratio (ER)] were not sensitive to the changes identified through visual inspection of the LTAS. These results were not consistent with the vibrato findings and suggest that conventional measures of SPR and ER are not sufficiently sensitive to evaluate LTAS. In the fourth study, fifteen expert listeners consistently and reliably identified the presence of open throat technique with 87% accuracy (Mitchell & Kenny, in press). In the fifth study, LTAS measurements were examined with respect to the perceptual ratings of singers. There was no relationship between perceptual rankings of vocal beauty and acoustic rankings of vocal quality (Kenny & Mitchell, 2004, in press). There is a vast literature of spectral energy definitions of good voice but the studies in this thesis have indicated that current acoustic methods are limited in defining vocal quality. They also suggest that current work in singing has not sufficiently incorporated perceptual ratings and descriptions of sound quality or the relationship between acoustic and perceptual factors with pedagogical practices.

Made available in DSpace on 2015-12-06T23:06:22Z (GMT). No. of bitstreams: 0 Previous issue date: 2005<br>Fundo de Auxílio aos Docentes e Alunos da UNIFESP (FADA)<br>O conhecimento das diferenças entre as vozes de atores e não atores, nos seus aspectos perceptivos e acústicos - especialmente por meio do Long-term average spectrum - podem contribuir para o re-direcionamento tanto da avaliação quanto da preparação vocal destes que buscam uma técnica vocal econômica e eficiente, os atores. Não há em nosso meio estudos da voz de atores utilizando o LTAS o objetivo do presente estudo é estabelecer as diferenças entre as vozes de atores e não atores nas loudness habitual, moderada e forte, por meio da análise acústica e perceptiva auditiva e verificar as correlações entre as diferentes variáveis Trata-se de um estudo de desenho transversal, do qual participaram 11 atores e 10 não atores do gênero masculino, tendo no português brasileiro a sua língua-mãe, sem queixas de voz, e com idade variando entre 20 e 60 anos para garantir uma voz madura, fora do período de muda vocal e não presbifônica As variáveis acústicas analisadas foram: nível de pressão sonora médio, proporção alpha, freqüência fundamental, nível de pressão sonora da freqüência fundamental, freqüência do primeiro formante, nível de pressão sonora do primeiro formante, diferença entre LI eLO. Para calcular o nível de pressão sonora médio, a proporção Alpha e a freqüência fundamental, usamos o sistema de análise computadorizada lntelligent Speech Analyser (Raimo Toivonen M. Se. Eng.). Os espectros do LTAS para cada indivíduo foram feitos por meio do Analisador de Sinal HewIlett-Packard 3561A. A extensão de freqüências analisada pelo programa foi de O-10kHz, janelamento Hanning, com resolução de janela de tempo de 40msec e largura de banda de 37.5Hz. Os sons não vozeados, sons fracos, sons da qualidade do /s/ e as pausas foram automaticamente cortados pelo programa. As variáveis perceptivo-auditivas analisadas foram: o grau de projeção, o grau de loudness, e o grau de tensão. Para fazer a avaliação perceptivo-auditiva, as 21 vozes foram gravadas de maneira aleatória em CDs, um para cada loudness. As vozes foram apresentadas para um grupo de 8 fonoaudiólogas especialistas em voz, com mais de 5 anos de profissão, e treino em avaliação perceptiva auditiva Os resultados da análise perceptiva auditiva mostraram diferenças estatisticamente significantes entre os dois grupos, em todas as loudness, na proporção alpha que foi menor para o grupo de atores (p < .001), e no nível de pressão sonora do "formante do ator" que foi maior para atores (p < .001). Na análise perceptiva auditiva, o grau de projeção e de loudness foi maior para atores que para não atores nas três loudness (p <.001). No LTAS, atores apresentaram o "formante do ator" nas três loudness e não atores, nas loudness moderada e forte. Os valores dos "fonnante do ator" para atores foram de -23,4dB, -19,3dB e -19,4dB respectivamente para loudness habitual, moderada e forte e para não atores, -25,4dB e - 24,5dB respectivamente para loudness moderada e forte. Para ambos os grupos, a freqüência central do "fonnante do ator" está em 3.4 kHz Podemos concluir que as vozes de atores e não atores se diferenciaram significativamente tanto na análise acústica quanto na perceptiva auditiva. Algumas variáveis acústicas, proporção alpha e "fonnante do ator", correlacionaram-se significativamente com o grau de loudness da análise perceptivo auditiva. No L T AS dos atores o "fonnante do ator" foi verificado em todas as loudness..<br>The knowledge about the differences between actors and non actors’ voices, regarding perceptual and acoustic parameters – especially through the Long-term average spectrum – could contribute for a better evaluation and vocal preparation of those who pursue an economic and efficient vocal technique like actors themselves. There are not studies, in our country, of the actors’ voices using LTAS. The objective of the present study is to establish the differences between actors and non actors’ voices in habitual, median and strong loudness through acoustic and perceptual analysis and verify the correlations between the different variables. It is a cross-sectional study with the participation of 11 actors and 10 non actors of the male gender, who had Brazilian Portuguese as their mother tongue, without voice complaints, and within the 20 to 60 age group to ensure a mature voice, out of the vocal mutational period and not yet presbifonic. The acoustic variables analyzed were: sound pressure level, alpha proportion, fundamental frequency, sound pressure level of the fundamental frequency, frequency of the first formant, sound pressure level of the first formant, difference between L1 and L0. To calculate the sound pressure level, alpha proportion and the fundamental frequency, it was used the system of computerized analysis Intelligent Speech Analyser. (Raimo Toivonen M. Sc. Eng.). The LTAS’ spectrums for each individual were done through the Hewllett-Packard 3561A signal analyzer. The frequency range analyzed by the program was 0-10kHz, Hanning window, which gives time window of 40 msec and bandwidth of 37.5 Hz. The program excluded the voiceless sounds, weak sounds, s-kind of sounds and pauses. The perceptual variables analyzed were: degree of projection, degree of loudness and degree of tightness. To allow the perceptual evaluation, the 21 voices were randomly recorded in CDs. The voices were presented to 8 speech therapists specialized in voice, with more than 5 years of experience and trained for perceptual evaluation. The results of the acoustic analysis showed statistically significant differences between the groups in all the loudness, for alpha proportion, that was smaller in the actors group (p <. 001), and the sound pressure level of the “actors formant”, that was greater for actors (p <. 001). In the perceptual analysis the degree of projection and loudness were greater among actors in the three loudness (p <. 001), In the LTAS, actors presented an “actor’s formant” in the three loudness and non-actors in the median and strong loudness. The mean values of the “actor’s formant” in the actors group was -23.4dB, -19.3dB, and -19,4dB in the habitual, median and strong loudness respectively, and in the non actors group, -25.4dB, -24.4dB in the median and strong loudness respectively. For both groups the central frequency of the “actor's formant” was 3.4 kHz. We can conclude that actors and non actor’s voices were significantly differentiated either in the acoustic or in the perceptual analysis. Some acoustic variables, as alpha proportion and “actor’s formant”, significantly correlated with the degree of loudness in the perceptual analysis. The “actor’s formant” in the LTAS was verified for actors in all the three loudness.<br>BV UNIFESP: Teses e dissertações

Through the analysis of the spectral characteristics of thousands of mastered (or remastered) commercial recordings from a variety of genres over the history of popular music, researchers have studied stylistic trends and spectral conventions. The aim of this study was to further explore, analyse and compare the spectral characteristics of two broad but distinct popular music genres: rock and vocal-based electronic music. The main reason for this choice of genres being that rock generally predominantly is based on (amplified) acoustical elements (e.g. acoustic drums and acoustic/electric bass/guitars) and that electronic music generally predominantly is based on electronic elements (e.g. beats and synthesizers). The stimuli for the study consisted of 24 top-five hit songs from the Billboard charts between 2016-2020, divided by genre. A fast fourier transform approach was used for the computation of target spectrums as well as low level descriptors for the two independent datasets of recordings. Spectral analysis followed with the goal of answering the following research questions: What do the spectral stylistic conventions appear to be in rock versus vocal-based electronic music and what spectral differences/similarities exists between these two distinct popular music genres? The results showed that there were some significant spectral differences between the two genres, especially noticeable in the low end of the frequency spectrum. Other genre-specific spectral trends and overall spectral conventions were found as well.

For the construction of a wind farm, one needs to assess the wind resources of the considered site location. Using reference time series from numerical weather prediction models, global assimilation databases or observations close to the area considered, the on-site measured wind speeds and wind directions are corrected in order to represent the actual long-term wind conditions. This long-term correction (LTC) is in the typical case performed by making use of the linear regression within the Measure-Correlate-Predict (MCP) method. This method and two other methods, Sector-Bin (SB) and Synthetic Time Series (ST), respectively, are used for the determination of the uncertainties that are associated with LTC.The test area that has been chosen in this work, is located in the region of the North Sea, using 22 quality controlled meteorological (met) station observations from offshore or nearby shore locations in Denmark, Norway and Sweden. The time series that has been used cover the eight year period from 2002 to 2009 and the year with the largest variability in the wind speeds, 2007, is used as the short-term measurement period. The long-term reference datasets that have been used are the Weather Research and Forecast model, based on both ECMWF Interim Re-Analysis (ERA-Interim) and National Centers for Environmental Prediction Final Analysis (NCEP/FNL), respectively and additional reference datasets of Modern Era Re-Analysis (MERRA) and QuikSCAT satellite observations. The long-term period for all of the reference datasets despite QuikSCAT, correspond to the one of stations observations. The QuikSCAT period of observations used cover the period from November 1st, 1999 until October 31st, 2009.The analysis is divided into three parts. Initially, the uncertainty connected to the corresponding reference dataset, when used in LTC method, is investigated. Thereafter the uncertainty due to the concurrent length of the on-site measurements and reference dataset is analyzed. Finally, the uncertainty is approached using a re-sampling method of the Non-Parametric Bootstrap. The uncertainty of the LTC method SB, for a fixed concurrent length of the datasets is assessed by this methodology, in an effort to create a generic model for the estimation of uncertainty in the predicted values for SB.The results show that LTC with WRF model datasets based on NCEP/FNL and ERA-Interim, respectively, is slightly different, but does not deviate considerably in comparison when comparing with met station observations. The results also suggest the use of MERRA reference dataset in connection with long-term correction methods. However, the datasets of QuikSCAT does not provide much information regarding the overall quality of long-term correction, and a different approach than using station coordinates for the withdrawal of QuikSCAT time series is preferred. Additionally, the LTC model of Sector-Bin is found to be robust against variation in the correlation coefficient between the concurrent datasets. For the uncertainty dependence of concurrent time, the results show that an on-site measurement period of one consistent year or more, gives the lowest uncertainties compared to measurements of shorter time. An additional observation is that the standard deviation of long-term corrected means decreases with concurrent time. Despite the efforts of using the re-sampling method of Non-Parametric Bootstrap the estimation of the uncertainties is not fully determined. However, it does give promising results that are suggested for investigation in further work.<br>För att bygga en vindkraftspark är man i behov av att kartlägga vindresurserna i det aktuella området. Med hjälp av tidsserier från numeriska vädermodeller (NWP), globala assimileringsdatabaser och intilliggande observationer korrigeras de uppmätta vindhastigheterna och vindriktningarna för att motsvara långtidsvärdena av vindförhållandena. Dessa långtidskorrigeringsmetoder (LTC) genomförs generellt sett med hjälp av linjär regression i Mät-korrelera-predikera-metoden (MCP). Denna metod, och två andra metoder, Sektor-bin (SB) och Syntetiska tidsserier (ST), används i denna rapport för att utreda de osäkerheter som är knutna till långtidskorrigering.Det testområde som är valt för analys i denna rapport omfattas av Nordsjöregionen, med 22 meteorologiska väderobservationsstationer i Danmark, Norge och Sverige. Dessa stationer är till största del belägna till havs eller vid kusten. Tidsserierna som används täcker åttaårsperioden från 2002 till 2009, där det året med högst variabilitet i uppmätt vindhastighet, år 2007, används som den korta mätperiod som blir föremål för långtidskorrigeringen. De långa referensdataseten som använts är väderprediktionsmodellen WRF ( Weather Research and Forecast Model), baserad både på data från NCEP/FNL (National Centers for Environmental Prediciton Final Analysis) och ERA-Interim (ECMWF Interim Re-analysis). Dessutom används även data från MERRA (Modern Era Re-Analysis) och satellitobservationer från QuikSCAT. Långtidsperioden för alla dataset utom QuikSCAT omfattar samma period som observationsstationerna. QuikSCAT-datat som använts omfattar perioden 1 november 1999 till 31 oktober 2009.Analysen är indelad i tre delar. Inledningsvis behandlas osäkerheten som är kopplad till referensdatans ingående i långtidskorrigeringsmetoderna. Därefter analyseras osäkerhetens beroende av längden på den samtidiga datan i referens- och observationsdataseten. Slutligen utreds osäkerheten med hjälp av en icke-parametrisk metod, en s.k. Bootstrap: Osäkerheten i SB-metoden för en fast samtidig längd av tidsserierna från observationer och referensdatat uppskattas genom att skapa en generell modell som estimerar osäkerheten i estimatet.Resultatet visar att skillnaden när man använder WRF-modellen baserad både på NCEP/FNL och ERA-Interim i långtidskorrigeringen är marginell och avviker inte markant i förhållande till stationsobservationerna. Resultatet pekar också på att MERRA-datat kan användas som långtidsreferensdataset i långtidsdkorrigeringsmetoderna. Däremot ger inte QuikSCAT-datasetet tillräckligt med information för att avgöra om det går att använda i långtidskorrigeringsmetoderna. Därför föreslås ett annat tillvägagångssätt än stationsspecifika koordinater vid val av koordinater lämpliga för långtidskorrigering. Ytterligare ett resultat vid analys av långtidskorrigeringsmetoden SB, visar att metoden är robust mot variation i korrelationskoefficienten.Rörande osäkerhetens beroende av längden på samtidig data visar resultaten att en sammanhängande mätperiod på ett år eller mer ger den lägsta osäkerheten i årsmedelvindsestimatet, i förhållande till mätningar av kortare slag. Man kan även se att standardavvikelsen av de långtidskorrigerade medelvärdena avtar med längden på det samtidiga datat. Den implementerade ickeparametriska metoden Bootstrap, som innefattar sampling med återläggning, kan inte estimera osäkerheten till fullo. Däremot ger den lovande resultat som föreslås för vidare arbete.

Objective: This study’s purpose was to examine dietary quality, macronutrient intake, and micronutrient adequacy among long term weight loss maintainers (WLM) in a commercial weight management program. Methods: Participants were 1,207 WLM in WW (formerly Weight Watchers) who had maintained a 9.1 kg or greater weight loss (29.7 kg on average) for 3.4 years, and had an average BMI of 28.3 kg/m2. A control group of weight stable adults with obesity (Controls; N=102) had a BMI of 41.1 kg/m2 and 2.3 kg or less weight change over the previous five years. Results: WLM vs. Controls had a 10.1 point higher HEI-2015 score (70.2 [69.7 - 70.7] vs 60.1 [58.4 - 61.8], respectively; p=0.0001) in analyses that adjusted for group difference in demographic factors. WLM versus Controls had a significantly higher average percentage of calories from carbohydrates (50.3% [49.7 - 50.8] vs 46.7% [44.8 - 48.7], respectively; p=0.0001) and protein (18.2% [18.0-18.5] vs 15.9% [15.1-16.6], respectively; p=0.0001) and lower percentage of calories from fat (32.3% [31.9-32.8] vs 37.4% [35.8-38.9], respectively; p=0.0001). Examining micronutrients, WLM had significantly higher odds for meeting the EAR for copper (OR=5.8 [2.6-13.1]; p=0.0001), magnesium (OR=2.9 [1.8-4.7]; p=0.0001), potassium (OR=4.7 [1.4-16.5]; p=0.015), vitamin A (OR=2.8 [1.7-4.8]; p=0.0001), thiamin (OR=2.3 [1.3-4.1]; p=0.003), riboflavin (OR=6.5 [2.2-19.3]; p=0.001), vitamin B6 (OR=2.91 [1.6-5.2]; p=0.0001), vitamin C (OR=5.0 [2.8-8.8]; p=0.0001), folate (OR=2.2 [1.3-3.7]; p=0.003), and vitamin E (OR=1.8 [1.1-2.8]; p=0.014) and didn’t differ in calcium (OR=1.15 [0.7-1.7]; p=0.823), iron (OR=1.9 [0.8-4.6]; p=0.151), phosphorus (OR=2.0 [0.9-4.5]; p=0.101), selenium (OR=1.6 [0.6-3.8]; p=0.332), zinc (OR=1.7 [0.9-3.0]; p=0.095), niacin (B3) (OR=1.9 [0.8-4.1]; p=0.136), vitamin B12 (OR=1.2 [0.5-2.8]; p=0.625), and vitamin D (OR=1.5 [0.9-2.4]; p=0.09). Conclusions In a widely available commercial program, WLM consumed a healthier and more micronutrient rich diet than adults who were weight stable with obesity. Future research is needed to examine whether improved micronutrient status among WLM reduces risk of chronic disease.

Kyoto University (京都大学)<br>0048<br>新制・課程博士<br>博士(人間・環境学)<br>甲第22535号<br>人博第938号<br>新制||人||223(附属図書館)<br>2019||人博||938(吉田南総合図書館)<br>京都大学大学院人間・環境学研究科共生人間学専攻<br>(主査)准教授 櫻川 貴司, 教授 立木 秀樹, 教授 日置 尋久<br>学位規則第4条第1項該当

Detecting abnormal operating conditions, which will lead to faults developing later, has important economic implications for industries trying to meet their performance and production goals. It is unacceptable to wait for failures that have potential safety, environmental and financial consequences. Moving from a “reactive” strategy to a “proactive” strategy can improve critical equipment reliability and availability while constraining maintenance costs, reducing production deferrals, decreasing the need for spare parts. Once the fault initiates, predicting its progression and deterioration can enable timely interventions without risk to personnel safety or to equipment integrity. This work presents an online-integrated condition monitoring and prognostics framework that addresses the above issues holistically. The proposed framework aligns fully with ISO 17359:2011 and derives from the I-P and P-F curve. Depending upon the running state of machine with respect to its I-P and P-F curve an algorithm will do one of the following: (1) Predict the ideal behaviour and any departure from the normal operating envelope using a combination of Evolving Clustering Method (ECM), a normalised fuzzy weighted distance and tracking signal method. (2) Identify the cause of the departure through an automated diagnostics system using a modified version of ECM for classification. (3) Predict the short-term progression of fault using a modified version of the Dynamic Evolving Neuro-Fuzzy Inference System (DENFIS), called here MDENFIS and a tracking signal method. (4) Predict the long term progression of fault (Prognostics) using a combination of Autoregressive Integrated Moving Average (ARIMA)- Empirical Mode Decomposition (EMD) for predicting the future input values and MDENFIS for predicting the long term progression of fault (output). The proposed model was tested and compared against other models in the literature using benchmarks and field data. This work demonstrates four noticeable improvements over previous methods: (1) Enhanced testing prediction accuracy, (2) comparable processing time if not better, (3) the ability to detect sudden changes in the process and finally (4) the ability to identify and isolate the problem source with high accuracy.