scholarly journals Application of Synthetic Storm Technique for Diurnal and Seasonal Variation of Slant Path Ka-Band Rain Attenuation Time Series over a Subtropical Location in South Africa

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
J. S. Ojo ◽  
P. A. Owolawi
Keyword(s):  
South Africa ◽  
Time Series ◽  
Seasonal Variation ◽  
Diurnal Variation ◽  
Rain Rate ◽  
Rain Attenuation ◽  
Series Data ◽  
Band Frequency ◽  
Ka Band ◽  
Slant Path

As technology advances and more demands are on satellite services, rain-induced attenuation still creates one of the most damaging effects of the atmosphere on the quality of radio communication signals, especially those operating above 10 GHz. System designers therefore require statistical information on rain-induced attenuation over the coverage area in order to determine the appropriate transmitter and receiver characteristics to be adopted. This paper presents results on the time-varying rain characterization and diurnal variation of slant path rain attenuation in the Ka-band frequency simulated with synthetic storm techniques over a subtropical location in South Africa using 10-year rain rate time-series data. The analysis is based on the CDF of one-minute rain rate; time-series seasonal variation of rain rate observed over four time intervals: 00:00–06:00, 06:00–12:00, 12:00–18:00, and 18:00–24:00; diurnal fades margin; and diurnal variation of rain attenuation. Comparison was also made between the synthesized values and measured attenuation data. The predicted statistics are in good agreement with those obtained from the propagation beacon measurement in the area. The overall results will be needed for an acceptable planning that can effectively reduce the fade margin to a very low value for an optimum data communication over this area.

scholarly journals Determination of Operational Threshold for Coding and Modulation Combination to Improve The Quality of High Throughput Satellite in Ka-Band Frequency in Indonesia

2016 ◽  
Vol 2 (1) ◽  
pp. 9
Author(s):  
M. Pasaribu ◽  
Heroe Wijanto ◽  
Budi Prasetya
Keyword(s):  
Rain Rate ◽  
Weather Condition ◽  
Rain Attenuation ◽  
Link Quality ◽  
Communication Link ◽  
Band Frequency ◽  
Ka Band ◽  
High Rain Rate

The vast enhancement of telecommunication technology has encouraged the increase of demand for more satellite capacity. HTS in Ka-Band frequency, that can deliver more capacity up to 50 GHz, can be a solution. Unfortunately, Ka-Band is susceptible to rain attenuation which is potentially difficult to be implemented in Indonesia because of its high rain rate. But, According to the previous research by Suwadi, Marrudani, and Lye, the combination of coding and modulation technique can be used as a solution to improve the performance of service dealing with rain attenuation. In this research, the writer will try to improve whether the combination of coding and modulation is also able to improve HTS Ka-Band communication link here ini in Indonesia with the high rain rate per year and to determine threshold of which the combination of coding and modulation that is best suited to each weather condition, in order to get the minimum required performance with BER min = 10 − 8. The conclusion of this research shows that the quality of HTS in Ka-Band frequency in Indonesia with BER = 10 − 8 can be improved by using QPSK, 8-APSK, 16-APSK, and 9 types of FEC. Furthermore, the 17 pairs of ModCod can be categorized into 8 thresholds that will determine with that ModCod that should be used in order to get the link quality of BER = 10 − 8 for each certain rain condition.

scholarly journals How applicable is export-led growth and import-led growth hypotheses to South African economy?

2015 ◽  
Vol 4 (2) ◽  
pp. 15-24
Author(s):  
Ntebogang Dinah Moroke ◽  
Molebogeng Manoto
Keyword(s):  
Economic Growth ◽  
South Africa ◽  
Adverse Effect ◽  
Time Series ◽  
South African ◽  
Time Series Data ◽  
Series Data ◽  
Long Run ◽  
Reserve Bank ◽  
Equilibrium Relationship

This paper investigated exports, imports and the economic growth nexus in the context of South Africa. The paper sets out to examine if long-run and causal relationships exist between these variables. Quarterly time series data ranging between 1998 and 2013 obtained from the South African Reserve Bank and Quantec databases was employed. Initial data analysis proved that the variables are integrated at their levels. The results further indicated that exports, imports and economic growth are co-integrated, confirming an existence of a long-run equilibrium relationship. Granger causal results were shown running from exports and imports to GDP and from imports to exports, validating export-led and import-led growth hypotheses in South Africa. A significant causality running from imports to exports, suggests that South Africa imported finished goods in excess. If this is not avoided, lots of problems could be caused. A suggestion was made to avoid such problematic issues as they may lead to replaced domestic output and displacement of employees. Another dreadful ramification may be an adverse effect on the economy which may further be experienced in the long-run.

scholarly journals Characterization of Rain Specific Attenuation and Frequency Scaling Method for Satellite Communication in South Korea

2017 ◽  
Vol 2017 ◽  
pp. 1-16 ◽  
Author(s):  
Sujan Shrestha ◽  
Dong-You Choi
Keyword(s):  
South Korea ◽  
Satellite Communication ◽  
Rain Rate ◽  
Rain Attenuation ◽  
Frequency Scaling ◽  
Scaling Method ◽  
Ka Band ◽  
Specific Attenuation ◽  
Rain Specific Attenuation ◽  
Attenuation Models

The attenuation induced by rain is prominent in the satellite communication at Ku and Ka bands. The paper studied the empirical determination of the power law coefficients which support the calculation of specific attenuation from the knowledge of rain rate at Ku and Ka band for Koreasat 6 and COMS1 in South Korea that are based on the three years of measurement. Rain rate data was measured through OTT Parsivel which shows the rain rate of about 50 mm/hr and attenuation of 10.7, 11.6, and 11.3 dB for 12.25, 19.8, and 20.73 GHz, respectively, for 0.01% of the time for the combined values of rain rate and rain attenuation statistics. Comparing with the measured data illustrates the suitability for estimation of signal attenuation in Ku and Ka band whose validation is done through the comparison with prominent rain attenuation models, namely, ITU-R P.618-12 and ITU-R P. 838-3 with the use of empirically determined coefficient sets. The result indicates the significance of the ITU-R recommended regression coefficients of rain specific attenuation. Furthermore, the overview of predicted year-wise rain attenuation estimation for Ka band in the same link as well as different link is studied which is obtained from the ITU-R P. 618-12 frequency scaling method.

Seasonal variation in liver function tests: a time-series analysis of outpatient data

2009 ◽  
Vol 46 (5) ◽  
pp. 377-384 ◽  
Author(s):  
Kazunori Miyake ◽  
Noriko Miyake ◽  
Shigemi Kondo ◽  
Yoko Tabe ◽  
Akimichi Ohsaka ◽  
...  
Keyword(s):  
Time Series ◽  
Seasonal Variation ◽  
Liver Function ◽  
Seasonal Variations ◽  
Time Series Data ◽  
Liver Function Tests ◽  
Series Data ◽  
Test Results ◽  
Men And Women ◽  
Function Tests

Background Long-term physiological variations, such as seasonal variations, affect the screening efficiency at medical checkups. This study examined the seasonal variation in liver function tests using recently described data-mining methods. Methods The ‘latent reference values’ of aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), gamma-glutamyltransferase ( γGT), cholinesterase (ChE) and total bilirubin (T-Bil) were extracted from a seven-year database of outpatients (aged 20–79 yr; comprising approximately 1,270,000 test results). After calculating the monthly means for each variable, the time-series data were separated into trend and seasonal components using a local regression model (Loess method). Then, a cosine function model (cosinor method) was applied to the seasonal component to determine the periodicity and fluctuation range. A two-year outpatient database (215,000 results) from another hospital was also analysed to confirm the reproducibility of these methods. Results The serum levels of test results tended to increase in the winter. The increase in AST and ALT was about 6% in men and women, and was greater than that in ChE, ALP (in men and women) and γGT (in men). In contrast, T-Bil increased by 3.6% (men) and 5.0% (women) in the summer. The total protein and albumin concentrations did not change significantly. AST and ALT showed similar seasonal variation in both institutions in the comparative analysis. Conclusions The liver function tests were observed to show seasonal variations. These seasonal variations should therefore be taken into consideration when establishing either reference intervals or cut-off values, which are especially important regarding aminotransferases.

Anomaly Detection by STL Decomposition and Extended Isolation Forest on Environmental Univariate Time Series

2020 ◽  
Author(s):  
İsmail Sezen ◽  
Alper Unal ◽  
Ali Deniz
Keyword(s):  
Time Series ◽  
Seasonal Variation ◽  
Anomaly Detection ◽  
Time Series Data ◽  
Complex Structure ◽  
Series Data ◽  
High Concentration ◽  
Univariate Time Series ◽  
Concentration Levels ◽  
Isolation Forest

<p>Atmospheric pollution is one of the primary problems and high concentration levels are critical for human health and environment. This requires to study causes of unusual high concentration levels which do not conform to the expected behavior of the pollutant but it is not always easy to decide which levels are unusual, especially, when data is big and has complex structure. A visual inspection is subjective in most cases and a proper anomaly detection method should be used. Anomaly detection has been widely used in diverse research areas, but most of them have been developed for certain application domains. It also might not be always a good idea to identify anomalies by using data from near measurement sites because of spatio-temporal complexity of the pollutant. That’s why, it’s required to use a method which estimates anomalies from univariate time series data.</p><p>This work suggests a framework based on STL decomposition and extended isolation forest (EIF), which is a machine learning algorithm, to identify anomalies for univariate time series which has trend, multi-seasonality and seasonal variation. Main advantage of EIF method is that it defines anomalies by a score value.</p><p>In this study, a multi-seasonal STL decomposition has been applied on a univariate PM10 time series to remove trend and seasonal parts but STL is not resourceful to remove seasonal variation from the data. The remainder part still has 24 hours and yearly variation. To remove the variation, hourly and annual inter-quartile ranges (IQR) are calculated and data is standardized by dividing each value to corresponding IQR value. This process ensures removing seasonality in variation and the resulting data is processed by EIF to decide which values are anomaly by an objective criterion.</p>

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