scholarly journals Tidal and Storm Impacts on Hydrodynamics and Sediment Dynamics in an Energetic Ebb Tidal Delta

2020 ◽  
Vol 8 (10) ◽  
pp. 810 ◽  
Author(s):  
Kehui Xu ◽  
P. Ansley Wren ◽  
Yanxia Ma
Keyword(s):  
South Carolina ◽  
Reference Site ◽  
Time Series Data ◽  
Beach Nourishment ◽  
Hurricane Sandy ◽  
Sediment Dynamics ◽  
Series Data ◽  
Port Royal ◽  
Sediment Mobility ◽  
Ebb Tidal Delta

Bottom-mounted instrumentation was deployed at two sites on a large sandy shoal of an ebb tidal delta offshore of the Port Royal Sound of South Carolina of USA to collect hydrodynamics and sediment dynamics data. One site (“borrow site”) was 2 km offshore in a dredge pit for nearby beach nourishment and the other site (“reference site”) was 10 km offshore. In situ time-series data were collected during two periods after the dredging: 15 March–12 June (spring) and 18 August–18 November (fall) of 2012. Data at the reference site indicated active migrating bedforms from centimeters to decimeters tall, and sediment concentrations were highly associated with semidiurnal and fortnightly tidal cycles. In the fall deployment, waves at the reference site were higher than those at the shallow borrow site. Both Tropical Storm Beryl and Hurricane Sandy formed high waves and strong currents but did not generate the greatest sediment fluxes. The two sites were at different depths and distances offshore, and waves contributed more to sediment mobility at the reference site whereas tidal forcing was the key controlling factor at the borrow site. This study provides valuable datasets for the selection of sites, prediction of pit infilling, and the modeling of storm impact in future beach nourishment and coastal restoration projects.

Seabed texture and composition changes offshore of Port Royal Sound, South Carolina before and after the dredging for beach nourishment

2014 ◽  
Vol 149 ◽  
pp. 57-67 ◽  
Author(s):  
Kehui Xu ◽  
Denise Sanger ◽  
George Riekerk ◽  
Stacie Crowe ◽  
Robert F. Van Dolah ◽  
...  
Keyword(s):  
South Carolina ◽  
Beach Nourishment ◽  
Port Royal ◽  
Before And After ◽  
Composition Changes

Graphical Exploratory Data Analysis for Categorical Longitudinal and Time Series Data

2013 ◽  
Author(s):  
Stephen J. Tueller ◽  
Richard A. Van Dorn ◽  
Georgiy Bobashev ◽  
Barry Eggleston
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Exploratory Data Analysis ◽  
Time Series Data ◽  
Series Data ◽  
Exploratory Data

Some statistical and CI models to predict chaotic high-frequency financial data

2020 ◽  
Vol 39 (5) ◽  
pp. 6419-6430
Author(s):  
Dusan Marcek
Keyword(s):  
Time Series Data ◽  
Moving Average ◽  
Methodological Approach ◽  
Back Propagation ◽  
Large Data ◽  
Series Data ◽  
Data Set ◽  
Training Time ◽  
Optimal Population ◽  
Forecast Time

To forecast time series data, two methodological frameworks of statistical and computational intelligence modelling are considered. The statistical methodological approach is based on the theory of invertible ARIMA (Auto-Regressive Integrated Moving Average) models with Maximum Likelihood (ML) estimating method. As a competitive tool to statistical forecasting models, we use the popular classic neural network (NN) of perceptron type. To train NN, the Back-Propagation (BP) algorithm and heuristics like genetic and micro-genetic algorithm (GA and MGA) are implemented on the large data set. A comparative analysis of selected learning methods is performed and evaluated. From performed experiments we find that the optimal population size will likely be 20 with the lowest training time from all NN trained by the evolutionary algorithms, while the prediction accuracy level is lesser, but still acceptable by managers.

Faktor-Faktor Yang Mempengaruhi Nilai Tukar Dollar Amerika Serikat Terhadap Rupiah Tahun 2000–2013

2017 ◽  
Vol 1 (2) ◽  
pp. 177-191
Author(s):  
Rizki Rahma Kusumadewi ◽  
Wahyu Widayat
Keyword(s):  
Time Series ◽  
Exchange Rate ◽  
Money Supply ◽  
Time Series Data ◽  
The United States ◽  
Economic Conditions ◽  
Series Data ◽  
Arch Model ◽  
United States Dollar ◽  
The Exchange Rate

Exchange rate is one tool to measure a country’s economic conditions. The growth of a stable currency value indicates that the country has a relatively good economic conditions or stable. This study has the purpose to analyze the factors that affect the exchange rate of the Indonesian Rupiah against the United States Dollar in the period of 2000-2013. The data used in this study is a secondary data which are time series data, made up of exports, imports, inflation, the BI rate, Gross Domestic Product (GDP), and the money supply (M1) in the quarter base, from first quarter on 2000 to fourth quarter on 2013. Regression model time series data used the ARCH-GARCH with ARCH model selection indicates that the variables that significantly influence the exchange rate are exports, inflation, the central bank rate and the money supply (M1). Whereas import and GDP did not give any influence.

Economic Turmoil in Islamic Banking Investment

ETIKONOMI ◽  
2020 ◽  
Vol 19 (2) ◽  
Author(s):  
Budiandru Budiandru ◽  
Sari Yuniarti
Keyword(s):  
Interest Rates ◽  
Stock Price ◽  
Time Series Data ◽  
Series Data ◽  
Islamic Banking ◽  
Vector Error Correction ◽  
Investment Financing ◽  
Vector Error ◽  
Operational Activities

Investment financing is one of the operational activities of Islamic banking to encourage the real sector. This study aims to analyze the effect of economic turmoil on investment financing, analyze the response to investment financing, and analyze each variable's contribution in explaining the diversity of investment financing. This study uses monthly time series data from 2009 to 2020 using the Vector Error Correction Model (VECM) analysis. The results show that the exchange rate, inflation, and interest rates significantly affect Islamic banking investment financing in the long term. The response to investment financing is the fastest to achieve stability when it responds to shocks to the composite stock price index. Inflation is the most significant contribution in explaining diversity in investment financing. Islamic banking should increase the proportion of funding for investment. Customers can have a larger business scale to encourage economic growth, with investment financing increasing.JEL Classification: E22, G11, G24How to Cite:Budiandru., & Yuniarti, S. (2020). Economic Turmoil in Islamic Banking Investment. Etikonomi: Jurnal Ekonomi, 19(2), xx – xx. https://doi.org/10.15408/etk.v19i2.17206.

An Anomaly Detection Method with Exemplar Subsequence for Time Series Data

2016 ◽  
Vol 136 (3) ◽  
pp. 363-372
Author(s):  
Takaaki Nakamura ◽  
Makoto Imamura ◽  
Masashi Tatedoko ◽  
Norio Hirai
Keyword(s):  
Time Series ◽  
Anomaly Detection ◽  
Time Series Data ◽  
Detection Method ◽  
Series Data

Macro-Economic Disequilibrium and Educational Development in Nigeria between 1980-2017

2019 ◽  
Vol 10 (08) ◽  
pp. 20592-21600
Author(s):  
Gbadebo Salako ◽  
Adejumo Musibau Ojo ◽  
Jaji Ayobami Francis
Keyword(s):  
Time Series Data ◽  
Educational Development ◽  
Negative Relationship ◽  
Series Data ◽  
Explanatory Variables ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Long Run ◽  
Stationarity Test ◽  
Level I

This study empirically investigates the effects of macroeconomic disequilibrium on educational development in Nigeria. The study employed time series data between 1980 and 2017. Autoregressive Distributed Lag method of estimation was employed. The result revealed that the variables stationarity test were mixed between the first difference I(I) and level I(0). The cointegration result shows that there exist long run relationship between the variables. The result revealed that Balance of payment, Poverty, Debt rate inflation and unemployment exhibited negative relationship with educational development. The estimation result showed that all explanatory variables account for 88% variation of educational development in Nigeria. It is therefore recommended that government should fast track policies that can stabilize inflation and exchange rate in the country. Also, Policies must be formulated to reduce poverty and unemployment.

The Comparison of Land Subsidence between East and West Side of Bangkok, Thailand

2020 ◽  
Vol 17 (3) ◽  
pp. 1
Author(s):  
Angkana Pumpuang ◽  
Anuphao Aobpaet
Keyword(s):  
Time Series ◽  
Land Subsidence ◽  
Time Series Data ◽  
Series Data ◽  
Industrial Estates ◽  
Vertical Displacements ◽  
Land Deformation ◽  
Extensive Farming ◽  
Chao Phraya River ◽  
Set Up

The land deformation in line of sight (LOS) direction can be measured using time series InSAR. InSAR can successfully measure land subsidence based on LOS in many big cities, including the eastern and western regions of Bangkok which is separated by Chao Phraya River. There are differences in prosperity between both sides due to human activities, land use, and land cover. This study focuses on the land subsidence difference between the western and eastern regions of Bangkok and the most possible cause affecting the land subsidence rates. The Radarsat-2 single look complex (SLC) was used to set up the time series data for long term monitoring. To generate interferograms, StaMPS for Time Series InSAR processing was applied by using the PSI algorithm in DORIS software. It was found that the subsidence was more to the eastern regions of Bangkok where the vertical displacements were +0.461 millimetres and -0.919 millimetres on the western and the eastern side respectively. The districts of Nong Chok, Lat Krabang, and Khlong Samwa have the most extensive farming area in eastern Bangkok. Besides, there were also three major industrial estates located in eastern Bangkok like Lat Krabang, Anya Thani and Bang Chan Industrial Estate. By the assumption of water demand, there were forty-eight wells and three wells found in the eastern and western part respectively. The number of groundwater wells shows that eastern Bangkok has the demand for water over the west, and the pumping of groundwater is a significant factor that causes land subsidence in the area.Keywords: Subsidence, InSAR, Radarsat-2, Bangkok

Impact of exchange rate and oil price on the yield of sovereign bond and sukuk: Evidence from Malaysian capital market

2017 ◽  
Vol 5 (4) ◽  
pp. 27
Author(s):  
Huda Arshad ◽  
Ruhaini Muda ◽  
Ismah Osman
Keyword(s):  
Exchange Rate ◽  
Capital Market ◽  
Time Series Data ◽  
Oil Prices ◽  
Oil Price ◽  
Series Data ◽  
Sovereign Bond ◽  
Long Run ◽  
Short Run ◽  
The Impact

This study analyses the impact of exchange rate and oil prices on the yield of sovereign bond and sukuk for Malaysian capital market. This study aims to ascertain the effect of weakening Malaysian Ringgit and declining of crude oil price on the fixed income investors in the emerging capital market. This study utilises daily time series data of Malaysian exchange rate, oil price and the yield of Malaysian sovereign bond and sukuk from year 2006 until 2015. The findings show that the weakening of exchange rate and oil prices contribute different impacts in the short and long run. In the short run, the exchange rate and oil prices does not have a direct relation with the yield of sovereign bond and sukuk. However, in the long run, the result reveals that there is a significant relationship between exchange rate and oil prices on the yield of sovereign bond and sukuk. It is evident that only a unidirectional causality relation is present between exchange rate and oil price towards selected yield of Malaysian sovereign bond and sukuk. This study provides numerical and empirical insights on issues relating to capital market that supports public authorities and private institutions on their decision and policymaking process.

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