Methodology for the analysis of geospatial and vehicle datasets in the R language

2021 ◽  
Author(s):  
Anthony Fuentes ◽  
Michelle Michaels ◽  
Sally Shoop
Keyword(s):  
Open Source ◽  
Statistical Analyses ◽  
Sensor Data ◽  
Source Analysis ◽  
Vehicle Performance ◽  
R Language ◽  
Processing Times ◽  
Military Vehicles ◽  
Gis Data ◽  
The Relationship

The challenge of autonomous off-road operations necessitates a robust understanding of the relationships between remotely sensed terrain data and vehicle performance. The implementation of statistical analyses on large geospatial datasets often requires the transition between multiple software packages that may not be open-source. The lack of a single, modular, and open-source analysis environment can reduce the speed and reliability of an analysis due to an increased number of processing steps. Here we present the capabilities of a workflow, developed in R, to perform a series of spatial and statistical analyses on vehicle and terrain datasets to quantify the relationship between sensor data and vehicle performance in winter conditions. We implemented the R-based workflow on datasets from a large, coordinated field campaign aimed at quantifying the response of military vehicles on snow-covered terrains. This script greatly reduces processing times of these datasets by combining the GIS, data-assimilation and statistical analyses steps into one efficient and modular interface.

scholarly journals Six Reasons to Consider Using R in Psychological Research

2019 ◽  
Author(s):  
Tyson S. Barrett
Keyword(s):  
Open Source ◽  
Psychological Research ◽  
Open Science ◽  
Statistical Analyses ◽  
R Language

The R Statistical Environment is becoming increasingly accessible to non-statistician researchers. This provides an opportunity for many researchers in psychology to consider adopting R in their work. Herein is presented six reasons for why R should not be overlooked by researchers in psychology: 1) R is free and open-source; 2) R has many packages built for common descriptive and statistical analyses in the psychological sciences; 3) the R community is supportive and have freely provided many useful resources, for beginners and advanced users alike; 4) R is becoming increasingly popular in psychology already, making it easier to collaborate using the software; 5) analyses in R can be highly reproducible with features like R Markdown and knitr, simplifying the process to provide open science; and 6) the R language has improved in diverse ways, making common data wrangling tasks fast, dependable, and highly replicable. These reasons are presented with their corresponding limitations.

scholarly journals Implementation of a Six-Layer Smart Factory Architecture with Special Focus on Transdisciplinary Engineering Education

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2944
Author(s):  
Benjamin James Ralph ◽  
Marcel Sorger ◽  
Benjamin Schödinger ◽  
Hans-Jörg Schmölzer ◽  
Karin Hartl ◽  
...  
Keyword(s):  
Open Source ◽  
User Interfaces ◽  
Industrial Revolution ◽  
Low Cost ◽  
Material Behavior ◽  
Sensor Data ◽  
Management Tool ◽  
Special Focus ◽  
Programming Environments ◽  
Metal Processing

Smart factories are an integral element of the manufacturing infrastructure in the context of the fourth industrial revolution. Nevertheless, there is frequently a deficiency of adequate training facilities for future engineering experts in the academic environment. For this reason, this paper describes the development and implementation of two different layer architectures for the metal processing environment. The first architecture is based on low-cost but resilient devices, allowing interested parties to work with mostly open-source interfaces and standard back-end programming environments. Additionally, one proprietary and two open-source graphical user interfaces (GUIs) were developed. Those interfaces can be adapted front-end as well as back-end, ensuring a holistic comprehension of their capabilities and limits. As a result, a six-layer architecture, from digitization to an interactive project management tool, was designed and implemented in the practical workflow at the academic institution. To take the complexity of thermo-mechanical processing in the metal processing field into account, an alternative layer, connected with the thermo-mechanical treatment simulator Gleeble 3800, was designed. This framework is capable of transferring sensor data with high frequency, enabling data collection for the numerical simulation of complex material behavior under high temperature processing. Finally, the possibility of connecting both systems by using open-source software packages is demonstrated.

scholarly journals Internal Quality Evolution of Open-Source Software Systems

2021 ◽  
Vol 11 (12) ◽  
pp. 5690
Author(s):  
Mamdouh Alenezi
Keyword(s):  
Open Source ◽  
Open Source Software ◽  
Software Evolution ◽  
Quality Metrics ◽  
Internal Quality ◽  
Software Systems ◽  
Software Metric ◽  
Significant Difference ◽  
The Relationship

The evolution of software is necessary for the success of software systems. Studying the evolution of software and understanding it is a vocal topic of study in software engineering. One of the primary concepts of software evolution is that the internal quality of a software system declines when it evolves. In this paper, the method of evolution of the internal quality of object-oriented open-source software systems has been examined by applying a software metric approach. More specifically, we analyze how software systems evolve over versions regarding size and the relationship between size and different internal quality metrics. The results and observations of this research include: (i) there is a significant difference between different systems concerning the LOC variable (ii) there is a significant correlation between all pairwise comparisons of internal quality metrics, and (iii) the effect of complexity and inheritance on the LOC was positive and significant, while the effect of Coupling and Cohesion was not significant.

The Achievement of Intelligent Lubrication Adjustment Function of CNC Machine Tools Based on SSAS

2014 ◽  
Vol 556-562 ◽  
pp. 1454-1459
Author(s):  
Dong Sheng You
Keyword(s):  
Machine Tools ◽  
Sensor Data ◽  
Lubricating Oil ◽  
Cnc Machine Tools ◽  
Signal Acquisition ◽  
Cnc Machine ◽  
Lubrication Mode ◽  
Free Function ◽  
And Control ◽  
The Relationship

The use of CNC machine tools signal acquisition, two-way transmission of the temperature sensor data, the ladder design and macro program guide and other methods on the implementation of a temperature sensing system of smart lubrication function. It is not only low-end CNC machine tools can compensate for deficiencies in equipment protection features and maintenance-free function, but also enhance the diversity of processing. Ultimately by analyzing the different lubrication mode, the relationship between the lubricating oil pressure and temperature and other factors, to draw the function in the lubrication in a stabilizing effect on oil pressure and control bearings and nut seat temperature. It is simple and practical, has important theoretical significance and great value.

Validation of the Customer-Based Corporate Reputation Scale in a Retail Context

2014 ◽  
Vol 56 (5) ◽  
pp. 655-671 ◽  
Author(s):  
Nic S. Terblanche
Keyword(s):  
Developing Country ◽  
Corporate Reputation ◽  
Customer Orientation ◽  
Corporate Citizenship ◽  
Statistical Analyses ◽  
Great Care ◽  
Five Dimensions ◽  
Environmentally Responsible ◽  
The One ◽  
The Relationship

A positive corporate reputation held by customers is important for both financial and customer outcome variables. However, limited research has been undertaken to examine the relationship between corporate reputation and customer-related behaviours. This paper deals with a study in which the shortened customer-based corporate reputation (CBCR) scale of Walsh et al. (2009) was validated in a study of supermarket customers in a developing country. The findings support only two of the five dimensions of the Walsh et al. scale. These are customer orientation and competitiveness of the firm. None of the original reputation dimensions or items associated with good corporate citizenship, such as good employer and being socially and environmentally responsible, was part of the dimensions that remained after the statistical analyses. Both customer orientation and competitiveness of the firm are strongly associated with important outcome variables such as trust, loyalty, repatronage intention and overall reputation. The findings of this study reiterate the view that great care should be exercised when scales are considered for application in a context not similar to the one where the scale was developed.

The Usage of R Programming in Finance and Banking Research

2019 ◽  
pp. 34-47
Author(s):  
Ceyhun Ozgur ◽  
Sanjeev Jha ◽  
Bennie B. Myer-Tyson ◽  
David Booth
Keyword(s):  
Operating System ◽  
Comparative Analysis ◽  
Open Source ◽  
Comparative Evaluation ◽  
Statistical Analyses ◽  
User Input ◽  
R Programming ◽  
Business Structures ◽  
Standard Software ◽  
Input Code

R has grown tremendously over the years in terms of number of users and capability with the development of hundreds of packages. In this chapter, the authors investigate the usage of R in finance and banking areas. They begin with a comparative analysis of R with other computing software like SAS and Python. Then they discuss the reasons for the growth of R's usage in financial sector. They end with a comparative evaluation of Python and R's strengths and weaknesses in a classroom. R is software designed to run statistical analyses and output graphics by user-input code. It can run on virtually any operating system and is open source. This makes the software highly appealing, as it is able to keep up with the demands of a growing number of varied business structures. Standard software has been SAS and Python; however, a growing number of jobs are posted looking for experience using R in the data analytics field.

scholarly journals An open source analysis framework for large-scale building energy modeling

2020 ◽  
Vol 13 (5) ◽  
pp. 487-500
Author(s):  
Brian L. Ball ◽  
Nicholas Long ◽  
Katherine Fleming ◽  
Chris Balbach ◽  
Phylroy Lopez
Keyword(s):  
Open Source ◽  
Large Scale ◽  
Building Energy ◽  
Energy Modeling ◽  
Source Analysis ◽  
Analysis Framework ◽  
Building Energy Modeling

scholarly journals Study of the Seasonal Effect of Building Shadows on Urban Land Surface Temperatures Based on Remote Sensing Data

2019 ◽  
Vol 11 (5) ◽  
pp. 497 ◽  
Author(s):  
Ke Yu ◽  
Yunhao Chen ◽  
Dandan Wang ◽  
Zixuan Chen ◽  
Adu Gong ◽  
...  
Keyword(s):  
Land Surface ◽  
Self Regulation ◽  
Central Area ◽  
Urban Land ◽  
Cooling Effect ◽  
Sensor Data ◽  
Seasonal Effect ◽  
Landsat 8 ◽  
Regulation Mechanism ◽  
The Relationship

Building shadows (BSs) frequently occur in urban areas, and their area and distribution display strong seasonal variations that significantly influence the urban land surface temperature (LST). However, it remains unclear how BSs affect the LST at the city scale because it is difficult to extract the shaded area at the subpixel scale and to connect such areas with the LST at the pixel scale. In this study, we combined the sun angle, building height, building footprint and building occlusion to extract the seasonal spatial distribution of BSs in the central area of Beijing. The effect of BSs on the LST was analyzed using LST retrieved from Landsat-8 thermal infrared sensor data. First, the relationship between the LST patch fragmentation and proportion of BSs in the sample areas was modeled without vegetation. Then, we quantitatively studied the mitigated intensity of the LST in pure impervious surfaces (IS) and vegetation pixels covered by BSs; next, we analyzed the LST sensitivity of these pixels to BSs. The results showed that the existence of BSs influences the fragmentation of the low LST patches strongly from summer to winter. On the other hand, pure IS pixels totally covered by BSs experienced a greater cooling effect, with 3.16 K on 10 July, and the lowest cooling occurred between 14 and 25 December, with a mean of 1.24 K. Without considering the relationship in winter, the LST is nonlinearly correlated to the building shadows ratio (BSR) in pixels, and an approximate 10% increase in the BSR resulted in decreases in the LST of approximately 0.33 K (mean of 16 April and 10 May), 0.37 K (10 July) and 0.24 K (28 September) for pure IS pixels, and 0.18 K, 0.20 K and 0.15 K, respectively, for pure vegetation pixels. Further analysis indicates that the LST of pure IS pixels is more sensitive to BSs than that of vegetation because the self-regulation mechanism of vegetation reduces the cooling effect of BSs. These findings can help urban planners understand the cooling characteristics of BSs and design suitable urban forms to resist urban heat islands (UHIs).

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