Mapping Changes in Desert Pavement Surfaces of the Lower Colorado Desert of Southern California using Landsat Time Series Analysis

Research background and hypothesis. Traditional time series analysis techniques, which are also used for the analysis of cardiovascular signals, do not reveal the relationship between the changes in the indices recorded associated with the multiscale and chaotic structure of the tested object, which allows establishing short-and long-term structural and functional changes.Research aim was to reveal the dynamical peculiarities of interactions of cardiovascular system indices while evaluating the functional state of track-and-field athletes and Greco-Roman wrestlers.Research methods. Twenty two subjects participated in the study, their average age of 23.5 ± 1.7 years. During the study standard 12 lead electrocardiograms (ECG) were recorded. The following ECG parameters were used in the study: duration of RR interval taken from the II standard lead, duration of QRS complex, duration of JT interval and amplitude of ST segment taken from the V standard lead.Research results. Significant differences were found between inter-parametric connections of ST segment amplitude and JT interval duration at the pre and post-training testing. Observed changes at different hierarchical levels of the body systems revealed inadequate cardiac metabolic processes, leading to changes in the metabolic rate of the myocardium and reflected in the dynamics of all investigated interactions.Discussion and conclusions. It has been found that peculiarities of the interactions of ECG indices interactions show the exposure of the functional changes in the body at the onset of the workload. The alterations of the functional state of the body and the signs of fatigue, after athletes performed two high intensity training sessions per day, can be assessed using the approach of the evaluation of interactions between functional variables. Therefore the evaluation of the interactions of physiological signals by using time series analysis methods is suitable for the observation of these processes and the functional state of the body.Keywords: electrocardiogram, time series, functional state.

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Discerning cognitive stages in a working memory and decision making task from human fMRI data using multivariate time series analysis

Frontiers in Computational Neuroscience ◽

10.3389/conf.fncom.2012.55.00228 ◽

2012 ◽

Vol 6 ◽

Author(s):

Durstewitz Daniel

Keyword(s):

Decision Making ◽

Working Memory ◽

Time Series ◽

Time Series Analysis ◽

Multivariate Time Series ◽

Fmri Data ◽

Series Analysis ◽

Multivariate Time Series Analysis

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The Contribution of Foreign Direct Investment for Economic Growth of Ethiopia: Time Series Analysis

International Journal of Contemporary Research and Review ◽

10.15520/ijcrr/2018/9/01/414 ◽

2018 ◽

Vol 9 (02) ◽

Author(s):

Addissie Melak

Keyword(s):

Economic Growth ◽

Time Series ◽

Foreign Direct Investment ◽

Time Series Analysis ◽

Direct Investment ◽

Policy Framework ◽

Annual Growth Rate ◽

African Countries ◽

Series Analysis ◽

Integration Test

Economic growth of countries is one of the fundamental questions in economics. Most African countries are opening their economies for welcoming of foreign investors. As such Ethiopia, like many African countries took measures to attract and improve foreign direct investment. The purpose of this study is to examine the contribution of foreign direct investment (FDI) for economic growth of Ethiopia over the period of 1981-2013. The study shows an overview of Ethiopian economy and investment environment by the help of descriptive and econometric methods of analysis to establish empirical investigation for the contribution of FDI on Ethiopian economy. OLS method of time series analysis is employed to analyse the data. The stationary of the variables have been checked by using Augmented Dickey Fuller (ADF) Unit Root test and hence they are stationery at first difference. The co- integration test also shows that there is a long run relationship between the dependent and independent variables. Accordingly, the finding of the study shows that FDI, GDP per capita, exchange rate, total investment as percentage of GDP, inflow of FDI stock, trade as percentage of GDP, annual growth rate of GDP and liberalization of the economy have positive impact on Ethiopian GDP. Whereas Gross fixed domestic investment, inflows of FDI and Gross capital formation influence economic growth of Ethiopia negatively. This finding suggests that there should be better policy framework to attract and improve the volume of FDI through creating conducive environment for investment.

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