A Study on the Impact of Reference Frame Implementation Strategy on GNSS Time Series for Regional Network Analysis

2015 ◽  
pp. 11-20 ◽  
Author(s):  
Miltiadis Chatzinikos ◽  
Athanasios Dermanis
Keyword(s):  
Time Series ◽  
Network Analysis ◽  
Reference Frame ◽  
Implementation Strategy ◽  
Regional Network ◽  
The Impact ◽  
Gnss Time Series

Regional Network Analysis of Primary-Industry Truck Traffic on Public Roads in New Zealand by Using Geographic Information Systems

2003 ◽  
Vol 1819 (1) ◽  
pp. 104-108 ◽  
Author(s):  
Robert A. Douglas
Keyword(s):  
Information Systems ◽  
New Zealand ◽  
Geographic Information Systems ◽  
Network Analysis ◽  
Dairy Industry ◽  
Geographic Information ◽  
Regional Network ◽  
Truck Traffic ◽  
The Impact ◽  
Logging Truck

Industrial forestry activities in New Zealand are now in a phase of unprecedented growth: the annual cut will double from 18 million m3 to well over 30 million m3 a year during the next 5 years. Given that most of the wood is taken from forest to mill or port by road in New Zealand, including a portion of the trip on public highways, the impacts of the doubling in logging truck traffic will be significant and severe. New Zealand’s roads have, for the most part, thin-sealed, unbound pavements. New Zealand’s second-largest industrial sector is tourism. Pavements and tourists will feel the impact of the looming increase in logging truck traffic unless steps are taken to anticipate the changes in traffic volumes and patterns. There is the complicating factor that the dairy industry too is now expanding rapidly with associated increases in raw milk tanker traffic. There is some friction between the forest industry and the dairy industry over which will be responsible for the increased strengthening, rehabilitation, and maintenance of roads. Research is under way to use regional network analysis and geographic information systems to predict the increases in heavy-truck traffic and changes in its distribution on public roads. This is the first step toward devising measures to mitigate the impacts and is a precursor to the implementation of pavement management. A unique opportunity exists in southern New Zealand: cooperation between forest operators and government agencies in the Otago and Southland region of the South Island of New Zealand on large-scale projects, providing the environment needed to examine such large, landscape-scale problems.

Helmert transformation strategies in analysis of GPS position time-series

2020 ◽  
Vol 223 (2) ◽  
pp. 973-992
Author(s):  
Shiwei Guo ◽  
Chuang Shi ◽  
Na Wei ◽  
Min Li ◽  
Lei Fan ◽  
...  
Keyword(s):  
Time Series ◽  
Reference Frame ◽  
Scale Factor ◽  
Network Effect ◽  
Satellite Orbits ◽  
Surface Mass ◽  
Helmert Transformation ◽  
Position Time Series ◽  
Transformation Parameters ◽  
The Impact

SUMMARY Global positioning system (GPS) position time-series generated using inconsistent satellite products should be aligned to a secular Terrestrial Reference Frame by Helmert transformation. However, unmodelled non-linear variations in station positions can alias into transformation parameters. Based on 17 yr of position time-series of 112 stations produced by precise point positioning (PPP), we investigated the impact of network configuration and scale factor on long-term time-series processing. Relative to the uniform network, the uneven network can introduce a discrepancy of 0.7–1.1 mm, 21.3–27.5 μas and 1.3 mm in terms of root mean square (RMS) for the translation, rotation and scale factor (if estimated), respectively, no matter whether the scale factor is estimated. The RMS of vertical annual amplitude differences caused by such network effect reaches 0.5–0.6 mm. Whether estimating the scale factor mostly affects the Z-translation and vertical annual amplitude, leading to a difference of 1.3 mm when the uneven network is used. Meanwhile, the annual amplitude differences caused by the scale factor present different geographic location dependences over the north, east and up components. The seasonal signals derived from the transformation using the uniform network and without estimating scale factor have better consistency with surface mass loadings with more than 41 per cent of the vertical annual variations explained. Simulation studies show that 40–50 per cent of the annual signals in the scale factor can be explained by the aliasing of surface mass loadings. Another finding is that GPS draconitic errors in station positions can also alias into transformation parameters, while different transformation strategies have limited influence on identifying the draconitic errors. We suggest that the uniform network should be used and the scale factor should not be estimated in Helmert transformation. It is also suggested to perform frame alignment on PPP time-series, even though the used satellite products belong to a consistent reference frame, as the origin of PPP positions inherited from satellite orbits and clocks is not so stable during a long period. With Helmert transformation, the seasonal variations would better agree with surface mass loadings, and noise level of time-series is reduced.

scholarly journals Survey on Blockchain Based Accounting and Finance Algorithms Using Bibliometric Approach

2021 ◽  
Author(s):  
Sezer Bozkus Kahyaoglu ◽  
Tamer Aksoy
Keyword(s):  
Network Analysis ◽  
Implementation Strategy ◽  
The Future ◽  
Strategic Role ◽  
Restructuring Process ◽  
The Uk ◽  
The Impact ◽  
Bibliometric Approach ◽  
Innovation Policies

The aim of this study is to evaluate the impact of blockchain especially on accounting and finance functions, the strategic role of CFOs, and to the restructuring process of accounting and finance functions in the future. In this respect, a business model is recommended that finance, accounting, and audit professionals can benefit from. It is aimed to contribute to the literature by providing blockchain adaptation and implementation strategy via providing information about accounting, finance, and auditing algorithm samples for revolutionizing these functions. To the best of our knowledge, this will be a pioneering work that makes a survey by examining blockchain algorithm samples in the field of accounting, auditing, and finance by using Bibliometric Network Analysis. In this analysis, six major clusters are estimated for defining the impacts of blockchain in the literature based on “Co-citation” aspects for the period 2005–2021 considering the SSCI indexed articles. In addition, the ranking of the top three contributing countries is found to be China, USA, and the UK respectively. This indicates the power of these countries to shape the future of accounting, finance, and auditing standards by means of producing blockchain algorithms and determining innovation policies of these professions in the future.

scholarly journals First Results of Time Series Analysis of the Permanent GNSS Observations at Polish EPN Stations Using GipsyX Software

2021 ◽  
Vol 56 (3) ◽  
pp. 101-118
Author(s):  
Adam Łyszkowicz ◽  
Renata Pelc-Mieczkowska ◽  
Anna Bernatowicz ◽  
Stepan Savchuk
Keyword(s):  
Time Series ◽  
Reference Frame ◽  
Small Time ◽  
Earth’S Crust ◽  
Global Navigation Satellite Systems ◽  
Time Interval ◽  
Vertical Movements ◽  
Earth's Crust ◽  
The Impact ◽  
Gnss Observations

Abstract The aim of this work is to explore, for the first time in Poland, the possibility of determining Earth’s crust movements from permanent observations at selected permanent stations using the GipsyX software for a period of 8 years (2011–2018) in the ITRF2014 reference frame. The data used in this work are from 15 Aktywna Sieć Geodezyjna (ASG)-EUPOS stations from 2011 to 2018, which are also European Permanent Network (EPN) stations. The stations Borowa Góra, Borowiec, Józefosław, Lamkówko, and Wroclaw are also International Global Navigation Satellite Systems (GNSS) Service (IGS) stations. Daily data, rinex files, for these stations have been made available for this work by the Main Office of Surveying and Cartography. The calculations were made using the GipsyX software in the ITRF14 reference frame. The tests performed have shown that daily solutions from 8-year-long time series give secular trends with an accuracy of 0.01 mm/yr. Our results suggest that there are small differences in horizontal and vertical velocities and in the accuracy estimated between our and EPN solutions. At some stations, for example, Łódź, the differences are much larger. The impact of additional GNSS observations on the accuracy of determination of horizontal and vertical movements of the Earth’s crust shows a submillimeter accuracy in computed coordinates of stations even at a relatively small time interval. It means that multi-GNSS Precise Point Positioning (PPP) processing can be used in the future for the estimation of geodynamic processes.

River-Basin Planning for Control of Nitrate Pollution

1982 ◽  
Vol 14 (4-5) ◽  
pp. 245-252 ◽  
Author(s):  
C S Sinnott ◽  
D G Jamieson
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
River Basin ◽  
Water Resource ◽  
Potable Water ◽  
Potential Problem ◽  
Nitrate Pollution ◽  
Optimal Mix ◽  
Regional Basis ◽  
The Impact

The combination of increasing nitrate concentrations in the River Thames and the recent EEC Directive on the acceptable level in potable water is posing a potential problem. In assessing the impact of nitrates on water-resource systems, extensive use has been made of time-series analysis and simulation. These techniques are being used to define the optimal mix of alternatives for overcoming the problem on a regional basis.

Análise da relação entre O3, NO e NO2 usando técnicas de regressão linear múltipla.

GEOgraphia ◽  
2018 ◽  
Vol 20 (43) ◽  
pp. 124
Author(s):  
Amaury De Souza ◽  
Priscilla V Ikefuti ◽  
Ana Paula Garcia ◽  
Debora A.S Santos ◽  
Soetania Oliveira
Keyword(s):  
Time Series ◽  
Linear Regression ◽  
Nitrogen Dioxide ◽  
Multiple Linear Regression ◽  
Quality Parameters ◽  
Environmental Pollutant ◽  
Environmental Research ◽  
Linear Regression Models ◽  
Mato Grosso ◽  
The Impact

Análise e previsão de parâmetros de qualidade do ar são tópicos importantes da pesquisa atmosférica e ambiental atual, devido ao impacto causado pela poluição do ar na saúde humana. Este estudo examina a transformação do dióxido de nitrogênio (NO2) em ozônio (O3) no ambiente urbano, usando o diagrama de séries temporais. Foram utilizados dados de concentração de poluentes ambientais e variáveis meteorológicas para prever a concentração de O3 na atmosfera. Foi testado o emprego de modelos de regressão linear múltipla como ferramenta para a predição da concentração de O3. Os resultados indicam que o valor da temperatura e a presença de NO2 influenciam na concentração de O3 em Campo Grande, capital do Estado do Mato Grosso do Sul. Palavras-chave: Ozônio. Dióxido de nitrogênio. Séries cronológicas. Regressões. ANALYSIS OF THE RELATIONSHIP BETWEEN O3, NO AND NO2 USING MULTIPLE LINEAR REGRESSION TECHNIQUES.Abstract: Analysis and prediction of air quality parameters are important topics of current atmospheric and environmental research due to the impact caused by air pollution on human health. This study examines the transformation of nitrogen dioxide (NO2) into ozone (O3) in the urban environment, using the time series diagram. Environmental pollutant concentration and meteorological variables were used to predict the O3 concentration in the atmosphere. The use of multiple linear regression models was tested as a tool to predict O3 concentration. The results indicate that the temperature value and the presence of NO2 influence the O3 concentration in Campo Grande, capital of the State of Mato Grosso do Sul.Keywords: Ozone. Nitrogen dioxide. Time series. Regressions. ANÁLISIS DE LA RELACIÓN ENTRE O3, NO Y NO2 UTILIZANDO MÚLTIPLES TÉCNICAS DE REGRESIÓN LINEAL.Resumen: Análisis y previsión de los parámetros de calidad del aire son temas importantes de la actual investigación de la atmósfera y el medio ambiente, debido al impacto de la contaminación atmosférica sobre la salud humana. Este estudio examina la transformación del dióxido de nitrógeno (NO2) en ozono (O3) en el entorno urbano, utilizando el diagrama de series de tiempo. Las concentraciones de los contaminantes ambientales de datos y variables climáticas fueron utilizadas para predecir la concentración de O3 en la atmósfera. El uso de múltiples modelos de regresión lineal como herramienta para predecir la concentración de O3 se puso a prueba. Los resultados indican que el valor de la temperatura y la presencia de NO2 influyen en la concentración de O3 en Campo Grande, capital del Estado de Mato Grosso do Sul.Palabras clave: Ozono. Dióxido de nitrógeno. Series de tiempo. Regresiones.

Intervention Modeling

2017 ◽  
Author(s):  
Richard McCleary ◽  
David McDowall ◽  
Bradley J. Bartos
Keyword(s):  
Time Series ◽  
Autocorrelation Function ◽  
Moving Average ◽  
Intervention Model ◽  
Noise Component ◽  
Autoregressive Integrated Moving Average ◽  
Noise Function ◽  
Modeling Strategy ◽  
The Impact ◽  
True Structure

The general AutoRegressive Integrated Moving Average (ARIMA) model can be written as the sum of noise and exogenous components. If an exogenous impact is trivially small, the noise component can be identified with the conventional modeling strategy. If the impact is nontrivial or unknown, the sample AutoCorrelation Function (ACF) will be distorted in unknown ways. Although this problem can be solved most simply when the outcome of interest time series is long and well-behaved, these time series are unfortunately uncommon. The preferred alternative requires that the structure of the intervention is known, allowing the noise function to be identified from the residualized time series. Although few substantive theories specify the “true” structure of the intervention, most specify the dichotomous onset and duration of an impact. Chapter 5 describes this strategy for building an ARIMA intervention model and demonstrates its application to example interventions with abrupt and permanent, gradually accruing, gradually decaying, and complex impacts.

EFFECTS OF TREND AND PERIODICITY ON THE CORRELATION DIMENSION AND THE LYAPUNOV EXPONENTS

2008 ◽  
Vol 18 (12) ◽  
pp. 3679-3687 ◽  
Author(s):  
AYDIN A. CECEN ◽  
CAHIT ERKAL
Keyword(s):  
Time Series ◽  
Lyapunov Exponent ◽  
Lyapunov Exponents ◽  
Correlation Dimension ◽  
Time Series Data ◽  
Logistic Map ◽  
Model Identification ◽  
Series Data ◽  
Largest Lyapunov Exponent ◽  
The Impact

We present a critical remark on the pitfalls of calculating the correlation dimension and the largest Lyapunov exponent from time series data when trend and periodicity exist. We consider a special case where a time series Zi can be expressed as the sum of two subsystems so that Zi = Xi + Yi and at least one of the subsystems is deterministic. We show that if the trend and periodicity are not properly removed, correlation dimension and Lyapunov exponent estimations yield misleading results, which can severely compromise the results of diagnostic tests and model identification. We also establish an analytic relationship between the largest Lyapunov exponents of the subsystems and that of the whole system. In addition, the impact of a periodic parameter perturbation on the Lyapunov exponent for the logistic map and the Lorenz system is discussed.

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