scholarly journals STATISTICAL ANALYSIS OF THE MARIANA TRENCH GEOMORPHOLOGY USING R PROGRAMMING LANGUAGE

2019 ◽  
Vol 45 (2) ◽  
pp. 57-84 ◽  
Author(s):  
Polina Lemenkova
Keyword(s):  
Statistical Analysis ◽  
Programming Language ◽  
Slope Angle ◽  
Geographic Location ◽  
Mariana Trench ◽  
Tectonic Plates ◽  
Factors Affecting ◽  
R Programming Language ◽  
R Programming ◽  
The Impact

This paper introduces an application of R programming language for geostatistical data processing with a case study of the Mariana Trench, Pacific Ocean. The formation of the Mariana Trench, the deepest among all hadal oceanic depth trenches, is caused by complex and diverse geomorphic factors affecting its development. Mariana Trench crosses four tectonic plates: Mariana, Caroline, Pacific and Philippine. The impact of the geographic location and geological factors on its geomorphology has been studied by methods of statistical analysis and data visualization using R libraries. The methodology includes following steps. Firstly, vector thematic data were processed in QGIS: tectonics, bathymetry, geomorphology and geology. Secondly, 25 cross-section profiles were drawn across the trench. The length of each profile is 1000-km. The attribute information has been derived from each profile and stored in a table containing coordinates, depths and thematic information. Finally, this table was processed by methods of the statistical analysis on R. The programming codes and graphical results are presented. The results include geospatial comparative analysis and estimated effects of the data distribution by tectonic plates: slope angle, igneous volcanic areas and depths. The innovativeness of this paper consists in a cross-disciplinary approach combining GIS, statistical analysis and R programming.

scholarly journals Statistical Analysis of the Mariana Trench Geomorphology Using R Programming Language

2018 ◽  
Author(s):  
Polina Lemenkova
Keyword(s):  
Statistical Analysis ◽  
Programming Language ◽  
Slope Angle ◽  
Geographic Location ◽  
Mariana Trench ◽  
Tectonic Plates ◽  
Factors Affecting ◽  
R Programming Language ◽  
R Programming ◽  
The Impact

This paper introduces an application of R programming language for geostatistical data processing with a case study of the Mariana Trench, Pacific Ocean. The formation of the Mariana Trench, the deepest among all hadal oceanic depth trenches, is caused by complex and diverse geomorphic factors affecting its development. Mariana Trench crosses four tectonic plates: Mariana, Caroline, Pacific and Philippine. The impact of the geographic location and geological factors on its geomorphology has been studied by methods of statistical analysis and data visualization using R libraries. The methodology includes following steps. Firstly, vector thematic data were processed in QGIS: tectonics, bathymetry, geomorphology and geology. Secondly, 25 cross-section profiles were drawn across the trench. The length of each profile is 1000-km. The attribute information has been derived from each profile and stored in a table containing coordinates, depths and thematic information. Finally, this table was processed by methods of the statistical analysis on R. The programming codes and graphical results are presented. The results include geospatial comparative analysis and estimated effects of the data distribution by tectonic plates: slope angle, igneous volcanic areas and depths. The innovativeness of this paper consists in a cross-disciplinary approach combining GIS, statistical analysis and R programming.

scholarly journals An Empirical Study of R Applications for Data Analysis in Marine Geology

2018 ◽  
Author(s):  
Polina LEMENKOVA
Keyword(s):  
Marine Geology ◽  
Gis Analysis ◽  
Mariana Trench ◽  
Tectonic Plates ◽  
Factors Affecting ◽  
R Programming Language ◽  
Gis Data ◽  
R Programming ◽  
Geological Research

The study focuses on the application of R programming language towards marine geological research with a case study of Mariana Trench. Due to its logical and straightforward syntax, multi-functional standard libraries, R is especially attractive to the geologists for the scientific computing. Using R libraries, the unevenness of various factors affecting Mariana Trench geomorphic structure has been studied. These include sediment thickness, slope steepness, angle aspect, depth at the basement and magmatism of the nearby areas. Methods includes using following R libraries: {ggplot2} for regression analysis, Kernel density curves, compositional charts; {ggalt} for Dumbbell charts for data comparison by tectonic plates, ranking dot plots for correlation analysis; {vcd} for mosaic plots, silhouette plots for compositional similarities among the bathymetric profiles, association plots; {car} for ANOVA. Bathymetric GIS data processing was dome in QGIS and LaTeX. The innovativeness of the work consists in the multi-disciplinary approach combining GIS analysis and statistical methods of R which contributes towards studies of ocean trenches, aimed at geospatial analysis of big data.

scholarly journals Comparative Evaluation of Resistance to Cyclic Fatigue of Three Rotary Endodontic Ni-Ti Instruments

2019 ◽  
Vol 23 (1) ◽  
pp. 36-39
Author(s):  
Lampros Intzes ◽  
Zoi-Despoina Tzima ◽  
Christos Gogos
Keyword(s):  
Stainless Steel ◽  
New Mexico ◽  
Statistical Analysis ◽  
Programming Language ◽  
Comparative Evaluation ◽  
Cyclic Fatigue ◽  
R Programming Language ◽  
R Programming ◽  
Number Of Cycles ◽  
Better Than

SummaryBackground/Aim: The present study examined the resistance to cyclic fatigue of three different rotary Ni-Ti instruments: K3XF (Kerr, Orange, CA), HyFlex CM (Coltene/Whaledent, Altstätten, Switzerland) and X7 EdgeFile (EdgeEndo, Albuquerque, New Mexico).Material and Methods: Thirty instruments (n=30) of each type were used with tip size 25 and 0.04 taper. All instruments were constrained to 600 of curvature with a radius of 5 mm by the use of two grooved stainless steel rods and rotated at a speed of 300 rpm and 3.0 Ncm of torque. The time until separation was recorded for each of the instruments and the number of cycles to fracture (NCF) was calculated. Statistical analysis was performed using R Programming language.Results: The X7 EdgeFile instrument showed significantly greater resistance to cyclic fatigue when compared to the HyFlex CM and the K3XF with mean NCF for each instrument 1046 ± 311, 707 ± 219 and 360 ± 96 respectively. HyFlex CM performed significantly better than K3XF.Conclusions: The X7 EdgeFile Ni-Ti file appears to be significantly more resistant to fracture, due to flexural fatigue, than the HyFlex CM and the K3XF.

scholarly journals Visualizations with statistical details: The 'ggstatsplot' approach

2021 ◽  
Author(s):  
Indrajeet Patil
Keyword(s):  
Statistical Analysis ◽  
Statistical Model ◽  
Programming Language ◽  
Scholarly Publication ◽  
R Programming Language ◽  
Graphical Displays ◽  
Statistical Approaches ◽  
R Programming

Graphical displays can reveal problems in a statistical model that might not be apparent from purely numerical summaries. Such visualizations can also be helpful for the reader to evaluate validity of a model if the said analysis is reported in a scholarly publication/report. But, given the onerous costs involved, researchers can avoid preparing information-rich graphics and exploring several statistical approaches/tests available. The `ggstatsplot` package in R programming language provides a one-line syntax to create densely informative `ggplot2`-based visualizations with the results from statistical analysis embedded in the visualization itself. In doing so, the package helps researchers adopt a rigorous, reliable, and robust data exploratory and reporting workflow.

scholarly journals Developing Social Media in Ukraine: Statistical Forecasting

2020 ◽  
pp. 30-39
Author(s):  
O. TUMANOV
Keyword(s):  
Social Media ◽  
Programming Language ◽  
The Internet ◽  
Main Role ◽  
Moving Averages ◽  
R Programming Language ◽  
Ancient Times ◽  
R Programming ◽  
Use Of Social Media ◽  
The Impact

Predictions and divination have always interested people. Since ancient times, oracles and wizards have answered questions that interest people in completely different areas of life. Today, this interest remains, but now the main role is given to analysts, who, armed with science and software, are trying to maintain a continuing interest at the proper level, giving sometimes quite good forecasts. Nowadays, the spectrum of approaches to the same problem has grown to unprecedented sizes: from trend lines and moving averages to neural networks and using several methods at once. It is not possible to describe all the approaches in one article. The article discusses basic preparation steps for forecasting, data correction, and common simple forecasting methods based on moving averages. Examples are given. R Studio, which is based on the R programming language and has a number of advantages and additional features, has been used for calculations and graphing, which greatly simplifies the work of the researcher. The article also provides code for graphing in a given programming language on an already configured environment and with attached libraries. In recent years, social media spread on the internet has burst into the lives of millions of people. That is why the visualization of relations of use of social media in Ukraine was made. Using the data on the population that uses the Internet in Ukraine, as well as on the data on the growth of Facebook users, a forecast was made with the growth of social network users in 5 years. A detailed description of the input and the results are provided. The issues that may be encountered and the impact of these problems on the final results and projections are also discussed.

scholarly journals Developing codes for validation of PM10, PM2.5, and O3 datasets using R programming language

2019 ◽  
Author(s):  
Ramin Nabizadeh ◽  
Mostafa Hadei
Keyword(s):  
Air Pollution ◽  
Programming Language ◽  
Assessment Method ◽  
Daily Maximum ◽  
Data Handling ◽  
R Programming Language ◽  
Wide Range ◽  
Us Epa ◽  
R Programming ◽  
Pm 10

Introduction: The wide range of studies on air pollution requires accurate and reliable datasets. However, due to many reasons, the measured concentra-tions may be incomplete or biased. The development of an easy-to-use and reproducible exposure assessment method is required for researchers. There-fore, in this article, we describe and present a series of codes written in R Programming Language for data handling, validating and averaging of PM10, PM2.5, and O3 datasets.   Findings: These codes can be used in any types of air pollution studies that seek for PM and ozone concentrations that are indicator of real concentra-tions. We used and combined criteria from several guidelines proposed by US EPA and APHEKOM project to obtain an acceptable methodology. Separate   .csv files for PM 10, PM 2.5 and O3 should be prepared as input file. After the file was imported to the R Programming software, first, negative and zero values of concentrations within all the dataset will be removed. Then, only monitors will be selected that have at least 75% of hourly concentrations. Then, 24-h averages and daily maximum of 8-h moving averages will be calculated for PM and ozone, respectively. For output, the codes create two different sets of data. One contains the hourly concentrations of the interest pollutant (PM10, PM2.5, or O3) in valid stations and their average at city level. Another is the   final 24-h averages of city for PM10 and PM2.5 or the final daily maximum 8-h averages of city for O3. Conclusion: These validated codes use a reliable and valid methodology, and eliminate the possibility of wrong or mistaken data handling and averaging. The use of these codes are free and without any limitation, only after the cita-tion to this article.

scholarly journals Spatial variation of physicochemical parameters in a constructed wetland for wastewater treatment: An example of the use of the R programming language

2021 ◽  
Vol 13 (1) ◽  
pp. 15
Author(s):  
Junior Pastor Pérez-Molina ◽  
Carola Scholz ◽  
Roy Pérez-Salazar ◽  
Carolina Alfaro-Chinchilla ◽  
Ana Abarca Méndez ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Spatial Variation ◽  
Water Flow ◽  
Programming Language ◽  
Constructed Wetland ◽  
Physicochemical Parameters ◽  
Preferential Flow ◽  
Oxygen Demand ◽  
R Programming Language ◽  
R Programming

Introduction: The implementation of wastewater treatment systems such as constructed wetlands has a growing interest in the last decade due to its low cost and high effectiveness in treating industrial and residential wastewater. Objective: To evaluate the spatial variation of physicochemical parameters in a constructed wetland system of sub-superficial flow of Pennisetum alopecuroides (Pennisetum) and a Control (unplanted). The purpose is to provide an analysis of spatial dynamic of physicochemical parameters using R programming language. Methods: Each of the cells (Pennisetum and Control) had 12 piezometers, organized in three columns and four rows with a separation distance of 3,25m and 4,35m, respectively. The turbidity, biochemical oxygen demand (BOD), chemical oxygen demand (COD), total Kjeldahl nitrogen (TKN), ammoniacal nitrogen (N-NH4), organic nitrogen (N-org.) and phosphorous (P-PO4-3) were measured in water under in-flow and out-flow of both conditions Control and Pennisetum (n= 8). Additionally, the oxidation-reduction potential (ORP), dissolved oxygen (DO), conductivity, pH and water temperature, were measured (n= 167) in the piezometers. Results: No statistically significant differences between cells for TKN, N-NH4, conductivity, turbidity, BOD, and COD were found; but both Control and Pennisetum cells showed a significant reduction in these parameters (P<0,05). Overall, TKN and N-NH4 removal were from 65,8 to 84,1% and 67,5 to 90,8%, respectively; and decrease in turbidity, conductivity, BOD, and COD, were between 95,1-95,4%; 15-22,4%; 65,2-77,9% and 57,4-60,3% respectively. Both cells showed ORP increasing gradient along the water-flow direction, contrary to conductivity (p<0,05). However, OD, pH and temperature were inconsistent in the direction of the water flow in both cells. Conclusions: Pennisetum demonstrated pollutant removal efficiency, but presented results similar to the control cells, therefore, remains unclear if it is a superior option or not. Spatial variation analysis did not reflect any obstruction of flow along the CWs; but some preferential flow paths can be distinguished. An open-source repository of R was provided. 

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