diff --git a/.gitignore b/.gitignore index bc87b30..88d6cd0 100644 --- a/.gitignore +++ b/.gitignore @@ -1,5 +1,6 @@ private/ Data/ +!Data/savedrecs.txt Getting_traffic_safety_data_from_online_resource_cache/ Getting_traffic_safety_data_from_online_resource_files/ .Rproj.user diff --git a/Getting traffic safety data from online resource.Rmd b/Getting traffic safety data from online resource.Rmd index 17a88d6..b6532d5 100644 --- a/Getting traffic safety data from online resource.Rmd +++ b/Getting traffic safety data from online resource.Rmd @@ -144,7 +144,7 @@ out <- capture.output(summary(netstat, k=60)) ![A keyword co-occurrence network of the literature, depicting the 60 most used keywords.](Figures/keywords-co-occ-60words.png){width=500px} -## A conceptual Structure Map +## A conceptual structure map Creating a Conceptual Structure Map from the Titles Using the MCA Method with terms mentioned at least 25 times in the title @@ -394,8 +394,8 @@ datatable( -An example of clustering{.tabset .tabset-fade} -======================== +A clustering example {.tabset .tabset-fade} +==================== *** The following codes attempts to replicate the visual clustering approach by @van1999cluster @@ -550,9 +550,13 @@ summary(poisson_fit) For a detailed explanation on interpreting the results of a Poisson regression, the readers can refer to [the example by the UCLA](https://stats.idre.ucla.edu/r/dae/poisson-regression/). +# Optimization + +Since optimization code is mostly Python-based, we do not provide code on the optimization section here. Should the readers have interest in this part, they can contact Qiong, Amir, and Alex. + # Acknowledgement{-} -We thank the National Science Foundation for supporting our research. We also thank the DarkSky API for providing us five million free calls to their weather database. +This work was supported in part by the National Science Foundation (CMMI-1635927 and CMMI-1634992), the Ohio Supercomputer Center (PMIU0138 and PMIU0162), the American Society of Safety Professionals (ASSP) Foundation, the University of Cincinnati Education and Research Center Pilot Research Project Training Program, and the Transportation Informatics Tier I University Transportation Center (TransInfo). We also thank the DarkSky API for providing us five million free calls to their weather database. # References {#references .unnumbered} diff --git a/Getting_traffic_safety_data_from_online_resource.html b/Getting_traffic_safety_data_from_online_resource.html index 22cd63c..b058e29 100644 --- a/Getting_traffic_safety_data_from_online_resource.html +++ b/Getting_traffic_safety_data_from_online_resource.html @@ -3962,14 +3962,14 @@
Creating a Conceptual Structure Map from the Titles Using the MCA Method with terms mentioned at least 25 times in the title
CS <- conceptualStructure(
M,field="ID_TM", method="MCA", minDegree=20,
@@ -4319,8 +4320,8 @@ 2.3.2 Historical (daily)
The following codes attempts to replicate the visual clustering approach by Van Wijk and Van Selow (1999)
@@ -4507,9 +4508,13 @@R code
Since optimization code is mostly Python-based, we do not provide code on the optimization section here. Should the readers have interest in this part, they can contact Qiong, Amir, and Alex.
+We thank the National Science Foundation for supporting our research. We also thank the DarkSky API for providing us five million free calls to their weather database.
+This work was supported in part by the National Science Foundation (CMMI-1635927 and CMMI-1634992), the Ohio Supercomputer Center (PMIU0138 and PMIU0162), the American Society of Safety Professionals (ASSP) Foundation, the University of Cincinnati Education and Research Center Pilot Research Project Training Program, and the Transportation Informatics Tier I University Transportation Center (TransInfo). We also thank the DarkSky API for providing us five million free calls to their weather database.
In this review paper, we attempt to provide a comprehensive review on transportation research and optimization models. This website serves as the supplementary materials to create reproducible examples in the manuscript Bridging the Gap between Transportation Safety Research and its Incorporation inOptimization Models: a Detailed Review and Perspective. It has been submitted to Transportation Research Part C: Emerging Technologies.
+In this review paper, we attempt to provide a comprehensive review on transportation research and optimization models. This website serves as the supplementary materials to create reproducible examples in the manuscript Bridging the Gap between Transportation Safety Research and its Incorporation in Optimization Models: a Detailed Review and Perspective. It has been submitted to Transportation Research Part C: Emerging Technologies.
This vignette includes examples on the following five aspects:
To maximize the readability of this vignette, we hided all R codes by default, but readers can look into any code by clicking the code
button.
To maximize the readability of this website, we hided all R codes by default, but readers can look into any code by clicking the code
button. The data folder is not uploaded to the GitHub repository since the files exceed the limited size, but all the data are open access and interested readers can download all the files at the link given in each section.
Creating a Conceptual Structure Map from the Titles Using the MCA Method with terms mentioned at least 25 times in the title
CS <- conceptualStructure(
M,field="ID_TM", method="MCA", minDegree=20,
@@ -4319,8 +4320,8 @@ 2.3.2 Historical (daily)
The following codes attempts to replicate the visual clustering approach by Van Wijk and Van Selow (1999)
@@ -4507,9 +4508,13 @@R code
Since optimization code is mostly Python-based, we do not provide code on the optimization section here. Should the readers have interest in this part, they can contact Qiong, Amir, and Alex.
+We thank the National Science Foundation for supporting our research. We also thank the DarkSky API for providing us five million free calls to their weather database.
+This work was supported in part by the National Science Foundation (CMMI-1635927 and CMMI-1634992), the Ohio Supercomputer Center (PMIU0138 and PMIU0162), the American Society of Safety Professionals (ASSP) Foundation, the University of Cincinnati Education and Research Center Pilot Research Project Training Program, and the Transportation Informatics Tier I University Transportation Center (TransInfo). We also thank the DarkSky API for providing us five million free calls to their weather database.