scholarly journals From Local to Global Analysis of Music Time Series

2005 ◽  
pp. 217-231 ◽  
Author(s):  
Claus Weihs ◽  
Uwe Ligges
Keyword(s):  
Time Series ◽  
Global Analysis

scholarly journals Using barometric time series of the IMS infrasound network for a global analysis of thermally induced atmospheric tides

2018 ◽  
Vol 11 (4) ◽  
pp. 2027-2040 ◽  
Author(s):  
Patrick Hupe ◽  
Lars Ceranna ◽  
Christoph Pilger
Keyword(s):  
Time Series ◽  
Global Analysis ◽  
Atmospheric Dynamics ◽  
Air Pressure ◽  
Atmospheric Tides ◽  
High Temporal Resolution ◽  
Data Sets ◽  
Atmospheric Conditions ◽  
Thermally Induced ◽  
Tidal Harmonics

Abstract. The International Monitoring System (IMS) has been established to monitor compliance with the Comprehensive Nuclear-Test-Ban Treaty and comprises four technologies, one of which is infrasound. When fully established, the IMS infrasound network consists of 60 sites uniformly distributed around the globe. Besides its primary purpose of determining explosions in the atmosphere, the recorded data reveal information on other anthropogenic and natural infrasound sources. Furthermore, the almost continuous multi-year recordings of differential and absolute air pressure allow for analysing the atmospheric conditions. In this paper, spectral analysis tools are applied to derive atmospheric dynamics from barometric time series. Based on the solar atmospheric tides, a methodology for performing geographic and temporal variability analyses is presented, which is supposed to serve for upcoming studies related to atmospheric dynamics. The surplus value of using the IMS infrasound network data for such purposes is demonstrated by comparing the findings on the thermal tides with previous studies and the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2), which represents the solar tides well in its surface pressure fields. Absolute air pressure recordings reveal geographical characteristics of atmospheric tides related to the solar day and even to the lunar day. We therefore claim the chosen methodology of using the IMS infrasound network to be applicable for global and temporal studies on specific atmospheric dynamics. Given the accuracy and high temporal resolution of the barometric data from the IMS infrasound network, interactions with gravity waves and planetary waves can be examined in future for refining the knowledge of atmospheric dynamics, e.g. the origin of tidal harmonics up to 9 cycles per day as found in the barometric data sets. Data assimilation in empirical models of solar tides would be a valuable application of the IMS infrasound data.

scholarly journals Global & Geographical Mapping and Visualization Method for Personal/Collective Health Data with 5D World Map System

2020 ◽  
Author(s):  
Shiori Sasaki ◽  
Koji Murakami ◽  
Yasushi Kiyoki ◽  
Asako Uraki
Keyword(s):  
Time Series ◽  
Health Monitoring ◽  
Potential Risk ◽  
Global Analysis ◽  
Collaborative Work ◽  
Health Data ◽  
Multimedia Data ◽  
Personal Health ◽  
Single View ◽  
Semantic Correlation

This paper presents a new knowledge base creation method for personal/collective health data with knowledge of preemptive care and potential risk inspection with a global and geographical mapping and visualization functions of 5D World Map System. The final goal of this research project is a realization of a system to analyze the personal health/bio data and potential-risk inspection data and provide a set of appropriate coping strategies and alert with semantic computing technologies. The main feature of 5D World Map System is to provide a platform of collaborative work for users to perform a global analysis for sensing data in a physical space along with the related multimedia data in a cyber space, on a single view of time-series maps based on the spatiotemporal and semantic correlation calculations. In this application, the concrete target data for world-wide evaluation is (1) multi-parameter personal health/bio data such as blood pressure, blood glucose, BMI, uric acid level etc. and daily habit data such as food, smoking, drinking etc., for a health monitoring and (2) time-series multi-parameter collective health/bio data in the national/regional level for global analysis of potential cause of disease. This application realizes a new multidimensional data analysis and knowledge sharing for both a personal and global level health monitoring and disease analysis. The results are able to be analyzed by the time-series difference of the value of each spot, the differences between the values of multiple places in a focused area, and the time-series differences between the values of multiple locations to detect and predict a potential-risk of diseases.

scholarly journals A Data-Intensive Approach to Address Food Sustainability: Integrating Optic and Microwave Satellite Imagery for Developing Long-Term Global Cropping Intensity and Sowing Month from 2001 to 2015

2020 ◽  
Vol 12 (8) ◽  
pp. 3227 ◽  
Author(s):  
Anjar Dimara Sakti ◽  
Wataru Takeuchi
Keyword(s):  
Time Series ◽  
Land Surface ◽  
Vegetation Index ◽  
Time Series Data ◽  
Global Analysis ◽  
Local Level ◽  
Series Data ◽  
Pixel Resolution ◽  
Cropping Intensity

It is necessary to develop a sustainable food production system to ensure future food security around the globe. Cropping intensity and sowing month are two essential parameters for analyzing the food–water–climate tradeoff as food sustainability indicators. This study presents a global-scale analysis of cropping intensity and sowing month from 2000 to 2015, divided into three groups of years. The study methodology integrates the satellite-derived normalized vegetation index (NDVI) of 16-day composite Moderate Resolution Imaging Spectroradiometer (MODIS) and daily land-surface-water coverage (LSWC) data obtained from The Advanced Microwave Scanning Radiometer (AMSR-E/2) in 1-km aggregate pixel resolution. A fast Fourier transform was applied to normalize the MODIS NDVI time-series data. By using advanced methods with intensive optic and microwave time-series data, this study set out to anticipate potential dynamic changes in global cropland activity over 15 years representing the Millennium Development Goal period. These products are the first global datasets that provide information on crop activities in 15-year data derived from optic and microwave satellite data. The results show that in 2000–2005, the total global double-crop intensity was 7.1 million km2, which increased to 8.3 million km2 in 2006–2010, and then to approximately 8.6 million km2 in 2011–2015. In the same periods, global triple-crop agriculture showed a rapid positive growth from 0.73 to 1.12 and then 1.28 million km2, respectively. The results show that Asia dominated double- and triple-crop growth, while showcasing the expansion of single-cropping area in Africa. The finer spatial resolution, combined with a long-term global analysis, means that this methodology has the potential to be applied in several sustainability studies, from global- to local-level perspectives.

scholarly journals Unfolding the relationship between seasonal forecast skill and value in hydropower production: A global analysis

2021 ◽  
Author(s):  
Donghoon Lee ◽  
Jia Yi Ng ◽  
Stefano Galelli ◽  
Paul Block
Keyword(s):  
Time Series ◽  
Prediction Models ◽  
Global Analysis ◽  
Forecast Accuracy ◽  
Forecast Skill ◽  
Statistical Prediction ◽  
Control Rules ◽  
Streamflow Forecasts ◽  
Expected Benefits ◽  
Global And Local

Abstract. The potential benefits of seasonal streamflow forecasts for the hydropower sector have been evaluated for several basins across the world, but with contrasting conclusions on the expected benefits. This raises the prospect of a complex relationship between reservoir characteristics, forecast skill and value. Here, we unfold the nature of this relationship by studying time series of simulated power production for 735 headwater dams worldwide. The time series are generated by running a detailed dam model over the period 1958–2000 with three operating schemes: basic control rules, perfect forecast-informed, and realistic forecast-informed. The realistic forecasts are issued by tailored statistical prediction models—based on lagged global and local hydro-climatic variables—predicting seasonal monthly dam inflows. As expected, results show that most dams (94 %) could benefit from perfect forecasts. Yet, the benefits for each dam vary greatly and are primarily controlled by the time-to-fill and the ratio between reservoir depth and hydraulic head. When realistic forecasts are adopted, 25 % of dams demonstrate improvements with respect to basic control rules. In this case, the likelihood of observing improvements is controlled not only by design specifications but also by forecast skill. We conclude our analysis by identifying two groups of dams of particular interest: dams that fall in regions expressing strong forecast accuracy and have the potential to reap benefits from forecast-informed operations, and dams with strong potential to benefit from forecast-informed operations but fall in regions lacking forecast accuracy. Overall, these results represent a first qualitative step towards informing site-specific hydropower studies.

scholarly journals MCMCI: A code to fully characterise an exoplanetary system

2020 ◽  
Vol 635 ◽  
pp. A6 ◽  
Author(s):  
A. Bonfanti ◽  
M. Gillon
Keyword(s):  
Time Series ◽  
Light Curve ◽  
Radial Velocity ◽  
Global Analysis ◽  
Major Axis ◽  
Theoretical Models ◽  
Integrated Analysis ◽  
Physical Parameters ◽  
Light Curve Analysis ◽  
Semi Major Axis

Context. Useful information can be retrieved by analysing the transit light curve of a planet-hosting star or induced radial velocity oscillations. However, inferring the physical parameters of the planet, such as mass, size, and semi-major axis, requires preliminary knowledge of some parameters of the host star, especially its mass or radius, which are generally inferred through theoretical evolutionary models. Aims. We seek to present and test a whole algorithm devoted to the complete characterisation of an exoplanetary system thanks to the global analysis of photometric or radial velocity time series combined with observational stellar parameters derived either from spectroscopy or photometry. Methods. We developed an integrated tool called MCMCI. This tool combines the Markov chain Monte Carlo (MCMC) approach of analysing photometric or radial velocity time series with a proper interpolation within stellar evolutionary isochrones and tracks, known as isochrone placement, to be performed at each chain step, to retrieve stellar theoretical parameters such as age, mass, and radius. Results. We tested the MCMCI on the HD 219134 multi-planetary system hosting two transiting rocky super Earths and on WASP-4, which hosts a bloated hot Jupiter. Even considering different input approaches, a final convergence was reached within the code, we found good agreement with the results already stated in the literature and we obtained more precise output parameters, especially concerning planetary masses. Conclusions. The MCMCI tool offers the opportunity to perform an integrated analysis of an exoplanetary system without splitting it into the preliminary stellar characterisation through theoretical models. Rather this approach favours a close interaction between light curve analysis and isochrones, so that the parameters recovered at each step of the MCMC enter as inputs for purposes of isochrone placement.

scholarly journals Using barometric time series of the IMS infrasound network for a global analysis of thermally induced atmospheric tides

2017 ◽  
Author(s):  
Patrick Hupe ◽  
Lars Ceranna ◽  
Christoph Pilger
Keyword(s):  
Time Series ◽  
Global Analysis ◽  
Atmospheric Dynamics ◽  
Air Pressure ◽  
Atmospheric Tides ◽  
High Temporal Resolution ◽  
Data Sets ◽  
Atmospheric Conditions ◽  
Thermally Induced ◽  
Tidal Harmonics

Abstract. The International Monitoring System (IMS) has been established to monitor compliance with the Comprehensive Nuclear-Test-Ban Treaty and comprises four technologies, one of which is infrasound. When fully established, the IMS infrasound network consists of 60 sites homogeneously distributed around the globe. Besides its primary purpose of determining explosions in the atmosphere, the recorded data reveal information on other anthropogenic and natural infrasound sources. Furthermore, the almost continuous multiyear recordings of differential and absolute air pressure allow for analysing the atmospheric conditions. In this paper, spectral analysis tools are applied to derive atmospheric dynamics from barometric time series. Based on the solar atmospheric tides, a methodology for performing geographic and temporal variability analyses is presented which is supposed to serve for upcoming studies related to atmospheric dynamics. The surplus value of using the IMS infrasound network data for such purposes is demonstrated by comparing the findings on the thermal tides with previous studies and the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), which well represents the solar tides in its surface pressure fields. Absolute air pressure recordings reveal geographic characteristics of atmospheric tides related to the solar day and even to the lunar day. We therefore claim the chosen methodology of using the IMS infrasound network to be applicable for global and temporal studies on specific atmospheric dynamics. Given the accuracy and high temporal resolution of the barometric data from the IMS infrasound network, interactions with gravity waves and planetary waves can be examined in future for refining the knowledge of atmospheric dynamics; e.g., the origin of tidal harmonics up to 9 cycles per day as found in the barometric data sets. Data assimilation in empirical models of solar tides would be a valuable application of the IMS infrasound data.

scholarly journals Non-linear regulation of cardiac autonomic modulation in obese youths: interpolation of ultra-short time series

2019 ◽  
Vol 29 (09) ◽  
pp. 1196-1201
Author(s):  
David M. Garner ◽  
Franciele M. Vanderlei ◽  
Vitor E. Valenti ◽  
Luiz Carlos M. Vanderlei
Keyword(s):  
Time Series ◽  
Spline Interpolation ◽  
Global Analysis ◽  
Statistical Tests ◽  
Cubic Spline ◽  
Short Time Series ◽  
Rr Intervals ◽  
Cohen’S D ◽  
Cohen's D ◽  
Short Time

AbstractBackground:In this study, we applied ultra-short time series of interbeat intervals (RR-intervals) to evaluate heart rate variability through default chaotic global techniques with the purpose of discriminating obese youths from non-obese youth patients.Method:Chaotic global analysis of the RR-intervals from the electrocardiogram and pre-processing adjustments was undertaken. The effect of cubic spline interpolations was assessed, while the spectral parameters remained fixed. Exactly, 125 RR-intervals of data were recorded.Results:CFP1, CFP3, and CFP6 were the only significant combinations of chaotic globals when the standard conditions were enforced and at the level p<0.01 (or <1%). These significances were acheived via Kruskal–Wallis and Cohen’s ds effects sizes tests of significance after Anderson–Darling and Lilliefors statistical tests indicated non-normal distributions in the majority of cases. Adjustments of the cubic spline interpolation from 1 to 13 Hz were revealed to be inconsequential when measured by Kruskal–Wallis and Cohen’s ds, regarding the outcome between the two datasets.Conclusion:Chaotic global analysis was offered as a robust technique to distinguish autonomic dysfunction in obese youths. It can discriminate the two different groups using ultra-short data lengths, and no cubic spline interpolations need be applied.

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