Using Naturalistic Driving Data to Develop a Typology of Speeding Episodes

2017 ◽  
Vol 2659 (1) ◽  
pp. 91-97 ◽  
Author(s):  
Christian M. Richard ◽  
James L. Brown ◽  
Randolph Atkins ◽  
Gautam Divekar
Keyword(s):  
United States ◽  
The United States ◽  
Speed Limit ◽  
Data Set ◽  
Slowing Down ◽  
Situational Characteristics ◽  
Duration Magnitude ◽  
Naturalistic Driving Study ◽  
Naturalistic Driving ◽  
Study Participants

Speeding-related crashes continue to be a serious problem in the United States. A recently completed NHTSA project, Motivations for Speeding, collected data to address questions about driver speeding behavior. This naturalistic driving study used 1-Hz GPS units to collect data from 88 drivers in Seattle, Washington, to record how fast vehicles traveled on different roadways. The current project further developed this data set to redefine speeding in terms of speeding episodes, which were continuous periods in which drivers exceeded the posted speed limit by at least 10 mph. More than half of all study participants averaged less than one speeding episode per trip taken. Various characteristics of speeding episodes representing aspects such as duration, magnitude, variability, and overall form of speeding were examined. Cluster analyses conducted using these characteristics of speeding episodes identified six types of speeding. These included two types of speeding that occurred around speed-zone transitions (speeding up and slowing down), incidental speeding, casual speeding, cruising speeding, and aggressive speeding. Qualitative examination of the speeding types indicated that these types also differed in terms of the prevalence of additional risky situational characteristics.

Investigating Effect of Driver-, Vehicle-, and Road-Related Factors on Location-Specific Crashes with Naturalistic Driving Data

2019 ◽  
Vol 2673 (6) ◽  
pp. 46-56 ◽  
Author(s):  
Grace Ashley ◽  
Osama A. Osman ◽  
Sherif Ishak ◽  
Julius Codjoe
Keyword(s):  
United States ◽  
Machine Learning ◽  
Traffic Accidents ◽  
The United States ◽  
Crash Risk ◽  
Related Factors ◽  
Data Set ◽  
Intersection Safety ◽  
Naturalistic Driving Study ◽  
Naturalistic Driving

According to NHTSA, traffic accidents cost the United States billions of U.S. dollars each year. Intersection accidents alone accounted for 23% of the 32,675 motor crash deaths in 2014. With the advent of the largest naturalistic driving data set in the United States collected by the SHRP2 Naturalistic Driving Study project, this study performs a crash-only analysis to identify driver-, vehicle-, and roadway-related factors that affect the driving risk at different location types using a machine learning tool. The study then analyzes the most important factors obtained from the machine learning analysis to identify how they affect crash risk. The results, in order of importance of variables, were driver behavior, locality, lane occupied, alignment, and through travel lanes. Also, drivers who violated traffic signals were four times more likely to be involved in a crash than drivers who did not. Those who violated stop signs were two times more likely to be involved in crashes than those who did not. Drivers performing visual-manual (VM) tasks at uncontrolled intersections were 2.7 times more likely to be involved in crashes than those who did not engage in these tasks. At nonintersections, drivers who performed VM tasks were 3.4 times more likely to be involved in crashes than drivers who did not. These findings add to the evidence that the establishment of safety awareness programs geared toward intersection safety is imperative.

Health and Service-related Impact of Sexual and Stalking Victimization During United States Military Service on LGBT Service Members

2020 ◽  
pp. 088626052097031
Author(s):  
Cary Leonard Klemmer ◽  
Ashley C. Schuyler ◽  
Mary Rose Mamey ◽  
Sheree M. Schrager ◽  
Carl Andrew Castro ◽  
...  
Keyword(s):  
United States ◽  
Military Service ◽  
The United States ◽  
Active Duty ◽  
Service Members ◽  
United States Military ◽  
Service Outcomes ◽  
Study Participants ◽  
The Military ◽  
Stalking Victimization

Prior research among military personnel has indicated that sexual harassment, stalking, and sexual assault during military service are related to negative health sequelae. However, research specific to LGBT U.S. service members is limited. The current study aimed to explore the health, service utilization, and service-related impact of stalking and sexual victimization experiences in a sample of active-duty LGBT U.S. service members ( N = 248). Respondent-driven sampling was used to recruit study participants. U.S. service members were eligible to participate if they were 18 years or older and active-duty members of the U.S. Army, U.S. Navy, U.S. Marine Corps, or U.S. Air Force. This study included a sizeable portion of transgender service members ( N = 58, 23.4%). Sociodemographic characteristics, characteristics of military service, health, and sexual and stalking victimization in the military were assessed. Regression was used to examine relationships between health and service outcomes and sexual and stalking victimization during military service. Final adjusted models showed that experiencing multiple forms of victimization in the military increased the odds of visiting a mental health clinician and having elevated somatic symptoms, posttraumatic stress disorder symptomatology, anxiety, and suicidality. Sexual and stalking victimization during U.S. military service was statistically significantly related to the mental and physical health of LGBT U.S. service members. Interventions to reduce victimization experiences and support LGBT U.S. service members who experience these types of violence are indicated. Research that examines the role of LGBT individuals’ experiences and organizational and peer factors, including social support, leadership characteristics, and institutional policies in the United States military is needed.

scholarly journals Altitude and risk of sudden unexpected infant death in the United States

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Richard Johnston ◽  
Xiaohan Yan ◽  
Tatiana M. Anderson ◽  
Edwin A. Mitchell
Keyword(s):  
United States ◽  
Logistic Regression ◽  
Infant Death ◽  
The United States ◽  
Sudden Infant ◽  
Data Set ◽  
Live Births ◽  
Sudden Unexpected Infant Death ◽  
Increased Risk ◽  
Unexpected Infant Death

AbstractThe effect of altitude on the risk of sudden infant death syndrome (SIDS) has been reported previously, but with conflicting findings. We aimed to examine whether the risk of sudden unexpected infant death (SUID) varies with altitude in the United States. Data from the Centers for Disease Control and Prevention (CDC)’s Cohort Linked Birth/Infant Death Data Set for births between 2005 and 2010 were examined. County of birth was used to estimate altitude. Logistic regression and Generalized Additive Model (GAM) were used, adjusting for year, mother’s race, Hispanic origin, marital status, age, education and smoking, father’s age and race, number of prenatal visits, plurality, live birth order, and infant’s sex, birthweight and gestation. There were 25,305,778 live births over the 6-year study period. The total number of deaths from SUID in this period were 23,673 (rate = 0.94/1000 live births). In the logistic regression model there was a small, but statistically significant, increased risk of SUID associated with birth at > 8000 feet compared with < 6000 feet (aOR = 1.93; 95% CI 1.00–3.71). The GAM showed a similar increased risk over 8000 feet, but this was not statistically significant. Only 9245 (0.037%) of mothers gave birth at > 8000 feet during the study period and 10 deaths (0.042%) were attributed to SUID. The number of SUID deaths at this altitude in the United States is very small (10 deaths in 6 years).

scholarly journals Development of a semi-parametric PAR (Photosynthetically Active Radiation) partitioning model for the United States, version 1.0

2014 ◽  
Vol 7 (5) ◽  
pp. 2477-2484 ◽  
Author(s):  
J. C. Kathilankal ◽  
T. L. O'Halloran ◽  
A. Schmidt ◽  
C. V. Hanson ◽  
B. E. Law
Keyword(s):  
United States ◽  
Elevation Angle ◽  
Model Performance ◽  
Diffuse Radiation ◽  
The United States ◽  
Polynomial Model ◽  
Coefficient Of Determination ◽  
Data Set ◽  
Cubic Polynomial ◽  
Solar Elevation Angle

Abstract. A semi-parametric PAR diffuse radiation model was developed using commonly measured climatic variables from 108 site-years of data from 17 AmeriFlux sites. The model has a logistic form and improves upon previous efforts using a larger data set and physically viable climate variables as predictors, including relative humidity, clearness index, surface albedo and solar elevation angle. Model performance was evaluated by comparison with a simple cubic polynomial model developed for the PAR spectral range. The logistic model outperformed the polynomial model with an improved coefficient of determination and slope relative to measured data (logistic: R2 = 0.76; slope = 0.76; cubic: R2 = 0.73; slope = 0.72), making this the most robust PAR-partitioning model for the United States currently available.

Racial Sentiment and Public Support for Arming Teachers with Guns in the United States

2021 ◽  
pp. 215336872110389
Author(s):  
Andrew J. Baranauskas
Keyword(s):  
United States ◽  
African Americans ◽  
Minority Groups ◽  
Public Support ◽  
The United States ◽  
Data Set ◽  
Racial Issue ◽  
Racial Resentment ◽  
Nationally Representative ◽  
Negative Feelings

In the effort to prevent school shootings in the United States, policies that aim to arm teachers with guns have received considerable attention. Recent research on public support for these policies finds that African Americans are substantially less likely to support them, indicating that support for arming teachers is a racial issue. Given the racialized nature of support for punitive crime policies in the United States, it is possible that racial sentiment shapes support for arming teachers as well. This study aims to determine the association between two types of racial sentiment—explicit negative feelings toward racial/ethnic minority groups and racial resentment—and support for arming teachers using a nationally representative data set. While explicit negative feelings toward African Americans and Hispanics are not associated with support for arming teachers, those with racial resentments are significantly more likely to support arming teachers. Racial resentment also weakens the effect of other variables found to be associated with support for arming teachers, including conservative ideology and economic pessimism. Implications for policy and research are discussed.

Septic shock and systemic inflammatory response syndrome patients' CD15+ granulocytes were subjected to global transcriptional profiling (SIRS)

2021 ◽  
Author(s):  
Marni Mack ◽  
Argo Easston
Keyword(s):  
Gene Expression ◽  
United States ◽  
Septic Shock ◽  
Immune Cells ◽  
Transcriptional Profiling ◽  
The United States ◽  
Transcriptional Level ◽  
Data Set ◽  
Transcriptional Alterations ◽  
Level I

In the United States, sepsis, the body's response to infection in a typically sterile circulation, is a leading causeof death (1). To assess the primary transcriptional alterations associated with each illness state, I utilized amicroarray data set from a cohort of thirtyone individuals with septic shock or systemic inflammatory responsesyndrome (2). At the transcriptional level, I discovered that the granulocytes of patients with SIRS weresimilar to those of patients with septic shock. SIRS showed a “intermediate” gene expression state betweenthat of control patients and that of septic shock patients for numerous genes expressed in the granulocyte. Thediscovery of the most differentially expressed genes in the granulocytic immune cells of patients with septicshock might aid the development of new therapies or diagnostics for an illness with a 14.7 percent to 29.9% inhospitaldeath rate despite decades of study (1).

Abstract 615: Association Between Multiple Modifiable Risk Factors of Cardiovascular Disease and Hypertension in a Rural Population of the United States

2016 ◽  
Vol 36 (suppl_1) ◽  
Author(s):  
Hadii M Mamudu ◽  
Timir Paul ◽  
Liang Wang ◽  
Sreenivas P Veeranki ◽  
Hemang B Panchal ◽  
...  
Keyword(s):  
United States ◽  
Risk Factors ◽  
Sedentary Lifestyle ◽  
Subclinical Atherosclerosis ◽  
The United States ◽  
Community Dwelling ◽  
Modifiable Risk Factors ◽  
Obesity And Diabetes ◽  
Asymptomatic Individuals ◽  
Study Participants

Background: Hypertension (HTN) is one of the major risk factors for cardiovascular diseases (CVD) that afflicts one-third of the population in United States (US). This study examined the association between multiple modifiable risk factors for HTN in a rural hard-to-reach population. Methods: During January 2011 and December 2012, 1629 community-dwelling asymptomatic individuals from central Appalachia participated in screening for subclinical atherosclerosis, during which the participants were asked to report whether a physician or health worker has informed them that they had HTN (yes/no). Additionally, baseline data consisting of two non-modifiable risk factors (sex, age) and 5 modifiable risk factors (obesity, diabetes, hypercholesterolemia, smoking, and sedentary lifestyle) were collected. Descriptive statistics involving prevalence of risk factors and multivariate logistic regression analyses to determine the strength of association between hypertension and the number of risk factors were conducted. Results: Of the 1629 study participants, about half (49.8%) had hypertension. Among hypertensive patients, 31.4% were obese and 62.3% having hypercholesterolemia. Overall, having 2 risk factors consisted the largest group of participants with HTN. After adjusting for the non-modifiable risk factors (sex, age), obesity and diabetes increased the odds of having HTN by more than two folds ([OR=2.02, CI=1.57-2.60] and [OR=2.30, CI=1.66-3.18], respectively) and hypercholesterolemia and sedentary lifestyle increased the odds for HTN by more than one fold ([OR=1.26, CI=1.02-1.56) and [OR=1.38, CI=1.12-1.70], respectively). Compared to those without HTN, having 2, 3, and 4 or 5 modifiable risk factors were significantly associated with increased odds of having HTN by about two-folds [OR=1.72, CI=1.21-2.44], two and half folds [OR=2.55, 1.74-3.74], and six folds [OR=5.96, 3.42-10.41], respectively. Conclusion: The study suggests that odds of having HTN increases with the number of modifiable risk factors for CVD. Hence, by implementing an integrated CVD program for treating and controlling modifiable risk factors of HTN would decrease the future risk of CVD and help to achieve the 2020 Impact Goal of the American Health Association.

Legislative Accomplishment and Policy Issue Substance

2013 ◽  
Author(s):  
John S. Lapinski
Keyword(s):  
United States ◽  
Substance P ◽  
Political Behavior ◽  
Policy Issue ◽  
The United States ◽  
Legislative Behavior ◽  
Aggregate Level ◽  
Data Set ◽  
Proper Understanding ◽  
Specific Policy

This chapter introduces a new measure of legislative accomplishment. To understand lawmaking requires that one move beyond studying political behavior in Congress alone and beyond a complete empirical reliance on roll call votes. Moreover, legislative behavior and legislative outputs must be studied in tandem to gain a proper understanding of the lawmaking process in the United States. Although the idea of studying important lawmaking across time is not controversial, constructing an appropriate measure is not a trivial exercise. The chapter constructs a comprehensive lawmaking data set that provides measures of legislative accomplishment at the aggregate level as well as by specific policy issue areas for a 118-year period. It also explains the construction of Congress-by-Congress measures of legislative accomplishment, including measures broken down by the policy-coding schema.

Vendor Master Data Cleaning – a Project for Accounting Class

2021 ◽  
Author(s):  
Sonia Gantman ◽  
Lorrie Metzger
Keyword(s):  
United States ◽  
Problem Solving ◽  
Data Analytics ◽  
Data Cleaning ◽  
The United States ◽  
Public University ◽  
Data Set ◽  
Initial Analysis ◽  
Master Data

We present a data cleaning project that utilizes real vendor master data of a large public university in the United States. Our main objective when developing this case was to identify the areas where students need guidance in order to apply a problem solving approach to the project. This includes initial analysis of the data and the task at hand, planning for cleaning and testing activities, executing this plan, and communicating the results in a written report. We provide a data set with 29K records of vendor master data, and a subset of the same data with 800 records. The assignment has two parts - the planning and the actual cleaning, each with its own deliverable. It can be used in many different courses and completed with almost any data analytics software. We provide suggested solutions and detailed solution notes for Excel and for Alteryx Designer.

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