Safety Implications of Multiday Driving Schedules for Truck Drivers

2005 ◽  
Vol 1922 (1) ◽  
pp. 167-174 ◽  
Author(s):  
Sang-Woo Park ◽  
Aviroop Mukherjee ◽  
Frank Gross ◽  
Paul P. Jovanis
Keyword(s):  
Field Experiments ◽  
Early Morning ◽  
Time Of Day ◽  
Elevated Risk ◽  
Truck Drivers ◽  
Crash Risk ◽  
Crash Analysis ◽  
Data Set ◽  
Using Data ◽  
Duty Time

The detailed analysis of preexisting crash and noncrash data representing an estimated 16 million vehicle miles of travel has revealed strong consistency between crash analysis using data from the 1980s and field experiments conducted in the 1990s. Time of day of driving is associated with crash risk: night and early morning driving has elevated risk in the range of 20% to 70% compared with daytime driving. Overall, 16 of 27 night and early morning driving schedules had elevated risk. Irregular schedules with primarily night and early morning driving had relative risk increases of 30% to 80%. In addition, there remains a persistent finding of increased crash risk associated with hours driving, with risk increases of 30% to more than 80% compared with the first hour of driving. These increases are less than previously reported and are of similar magnitude to the risk increases caused by multiday schedules. Finally, there is some evidence, although it is far from persuasive, that risk increases may be associated with significant off-duty time, in some cases in the range of 24 to 48 h. The implication is that “restart” programs should be approached with caution. Areas for additional research include further studies of crash risk associated with extended off-duty time, closer examination of irregular schedules that better reflect truckload operations, and analysis of irregular schedules with primarily daytime driving (largely nonexistent in this data set) to further explore the effect of variability.

scholarly journals Modelling temperature variations in polar snow using DAISY

1997 ◽  
Vol 43 (143) ◽  
pp. 180-191 ◽  
Author(s):  
Ε. M. Morris ◽  
H. -P. Bader ◽  
P. Weilenmann
Keyword(s):  
Field Experiments ◽  
A Priori ◽  
Model Parameters ◽  
Data Set ◽  
International Geophysical Year ◽  
Snow Model ◽  
Using Data ◽  
Polar Snow ◽  
Parameter Values ◽  
The Antarctic

AbstractA physics-based snow model has been calibrated using data collected at Halley Bay, Antarctica, during the International Geophysical Year. Variations in snow temperature and density are well-simulated using values for the model parameters within the range reported from other polar field experiments. The effect of uncertainty in the parameter values on the accuracy of the predictions is no greater than the effect of instrumental error in the input data. Thus, this model can be used with parameters determined a priori rather than by optimization. The model has been validated using an independent data set from Halley Bay and then used to estimate 10 m temperatures on the Antarctic Peninsula plateau over the last half-century.

scholarly journals A Method for Extracting Travel Patterns Using Data Polishing

2020 ◽  
Author(s):  
Mio Hosoe ◽  
Masashi Kuwano ◽  
Taku Moriyama
Keyword(s):  
Analysis Data ◽  
Time Of Day ◽  
Clustering Methods ◽  
Travel Patterns ◽  
Data Set ◽  
Smart Card Data ◽  
Information And Communication ◽  
Data Points ◽  
Destination Station ◽  
Using Data

Abstract With the development of ICT (Information and Communication Technology), interest in using the large amount of accumulated data for traffic policy planning has been increasing. In recent years, data polishing has been proposed as a new methodology for big data analysis. Data polishing is one of the graphical clustering methods. This method can be used to extract patterns that are similar or related to each other by clarifying the cluster structures in the data. The purpose of this study is to reveal travel patterns of railway passengers by applying data polishing to smart card data collected in Kagawa Prefecture, Japan. This study uses 9,008,709 data points collected during the 15 months from December 1st, 2013 to February 28th, 2015. This data set includes such information as trip histories and types of passengers. The study uses the data polishing method to cluster 4,667,520 combinations of information about individual rides: day of the week, time of day, passenger type, origin station, and destination station. As a result, 127 characteristic travel patterns were specified from those combinations.

scholarly journals Modelling temperature variations in polar snow using DAISY

1997 ◽  
Vol 43 (143) ◽  
pp. 180-191 ◽  
Author(s):  
Ε. M. Morris ◽  
H. -P. Bader ◽  
P. Weilenmann
Keyword(s):  
Field Experiments ◽  
A Priori ◽  
Model Parameters ◽  
Data Set ◽  
International Geophysical Year ◽  
Snow Model ◽  
Using Data ◽  
Polar Snow ◽  
Parameter Values ◽  
The Antarctic

AbstractA physics-based snow model has been calibrated using data collected at Halley Bay, Antarctica, during the International Geophysical Year. Variations in snow temperature and density are well-simulated using values for the model parameters within the range reported from other polar field experiments. The effect of uncertainty in the parameter values on the accuracy of the predictions is no greater than the effect of instrumental error in the input data. Thus, this model can be used with parameters determined a priori rather than by optimization. The model has been validated using an independent data set from Halley Bay and then used to estimate 10 m temperatures on the Antarctic Peninsula plateau over the last half-century.

Thermoregulatory responses to cold water at different times of day

1999 ◽  
Vol 87 (1) ◽  
pp. 243-246 ◽  
Author(s):  
John W. Castellani ◽  
Andrew J. Young ◽  
James E. Kain ◽  
Michael N. Sawka
Keyword(s):  
Cold Water ◽  
Water Immersion ◽  
Early Morning ◽  
Cold Water Immersion ◽  
Time Of Day ◽  
Mean Skin Temperature ◽  
Mean Body Temperature ◽  
Metabolic Heat ◽  
Body Temperature Change ◽  
The Mean

This study examined how time of day affects thermoregulation during cold-water immersion (CWI). It was hypothesized that the shivering and vasoconstrictor responses to CWI would differ at 0700 vs. 1500 because of lower initial core temperatures (Tcore) at 0700. Nine men were immersed (20°C, 2 h) at 0700 and 1500 on 2 days. No differences ( P > 0.05) between times were observed for metabolic heat production (M˙, 150 W ⋅ m−2), heat flow (250 W ⋅ m−2), mean skin temperature (T sk, 21°C), and the mean body temperature-change in M˙(ΔM˙) relationship. Rectal temperature (Tre) was higher ( P < 0.05) before (Δ = 0.4°C) and throughout CWI during 1500. The change in Tre was greater ( P < 0.05) at 1500 (−1.4°C) vs. 0700 (−1.2°C), likely because of the higher Tre-T skgradient (0.3°C) at 1500. These data indicate that shivering and vasoconstriction are not affected by time of day. These observations raise the possibility that CWI may increase the risk of hypothermia in the early morning because of a lower initial Tcore.

Design of a Brassica rapa core collection for association mapping studiesThis article is one of a selection of papers from the conference “Exploiting Genome-wide Association in Oilseed Brassicas: a model for genetic improvement of major OECD crops for sustainable farming”.

Genome ◽  
2010 ◽  
Vol 53 (11) ◽  
pp. 884-898 ◽  
Author(s):  
Jianjun Zhao ◽  
Anna Artemyeva ◽  
Dunia Pino Del Carpio ◽  
Ram Kumar Basnet ◽  
Ningwen Zhang ◽  
...  
Keyword(s):  
Association Mapping ◽  
Flowering Time ◽  
Brassica Rapa ◽  
Core Collection ◽  
Field Experiments ◽  
Research Centre ◽  
Candidate Gene Approach ◽  
Core Collections ◽  
Genome Wide ◽  
Using Data

A Brassica rapa collection of 239 accessions, based on two core collections representing different morphotypes from different geographical origins, is presented and its use for association mapping is illustrated for flowering time. We analyzed phenotypic variation of leaf and seed pod traits, plant architecture, and flowering time using data collected from three field experiments and evaluated the genetic diversity with a set of SSR markers. The Wageningen University and Research Centre (WUR) and the Vavilov Research Institute of Plant Industry (VIR) core collections had similar representations of most morphotypes, as illustrated by the phenotypic and genetic variation within these groups. The analysis of population structure revealed five subgroups in the collection, whereas previous studies of the WUR core collection indicated four subgroups; the fifth group identified consisted mainly of oil accessions from the VIR core collection, winter oils from Pakistan, and a number of other types. A very small group of summer oils is described, that is not related to other oil accessions. A candidate gene approach was chosen for association mapping of flowering time with a BrFLC1 biallelic CAPS marker and a BrFLC2 multiallelic SSR marker. The two markers were significantly associated with flowering time, but their effects were confined to certain morphotypes and (or) alleles. Based on these results, we discuss the optimal design for an association mapping population and the need to fix the heterogeneous accessions to facilitate phenotyping and genotyping.

scholarly journals Influence of Land Cover and Soil Moisture on the Horizontal Distribution of Sensible and Latent Heat Fluxes in Southeast Kansas during IHOP_2002 and CASES-97

2007 ◽  
Vol 8 (1) ◽  
pp. 68-87 ◽  
Author(s):  
Margaret A. LeMone ◽  
Fei Chen ◽  
Joseph G. Alfieri ◽  
Mukul Tewari ◽  
Bart Geerts ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Latent Heat ◽  
Land Surface ◽  
Field Experiments ◽  
Time Of Day ◽  
Horizontal Distribution ◽  
Heat Fluxes ◽  
Surface Model ◽  
Green Vegetation ◽  
The Impact

Abstract Analyses of daytime fair-weather aircraft and surface-flux tower data from the May–June 2002 International H2O Project (IHOP_2002) and the April–May 1997 Cooperative Atmosphere Surface Exchange Study (CASES-97) are used to document the role of vegetation, soil moisture, and terrain in determining the horizontal variability of latent heat LE and sensible heat H along a 46-km flight track in southeast Kansas. Combining the two field experiments clearly reveals the strong influence of vegetation cover, with H maxima over sparse/dormant vegetation, and H minima over green vegetation; and, to a lesser extent, LE maxima over green vegetation, and LE minima over sparse/dormant vegetation. If the small number of cases is producing the correct trend, other effects of vegetation and the impact of soil moisture emerge through examining the slope ΔxyLE/ΔxyH for the best-fit straight line for plots of time-averaged LE as a function of time-averaged H over the area. Based on the surface energy balance, H + LE = Rnet − Gsfc, where Rnet is the net radiation and Gsfc is the flux into the soil; Rnet − Gsfc ∼ constant over the area implies an approximately −1 slope. Right after rainfall, H and LE vary too little horizontally to define a slope. After sufficient drying to produce enough horizontal variation to define a slope, a steep (∼−2) slope emerges. The slope becomes shallower and better defined with time as H and LE horizontal variability increases. Similarly, the slope becomes more negative with moister soils. In addition, the slope can change with time of day due to phase differences in H and LE. These trends are based on land surface model (LSM) runs and observations collected under nearly clear skies; the vegetation is unstressed for the days examined. LSM runs suggest terrain may also play a role, but observational support is weak.

Risk-based capital regulation revisited: evidence from the early 2000s

2015 ◽  
Vol 23 (2) ◽  
pp. 115-134 ◽  
Author(s):  
Thomas L. Hogan ◽  
Neil R. Meredith ◽  
Xuhao (Harry) Pan
Keyword(s):  
Design Methodology ◽  
Banking Regulation ◽  
Bank Performance ◽  
Capital Regulation ◽  
Data Set ◽  
Content Type ◽  
Future Performance ◽  
Capital Ratios ◽  
Using Data ◽  
Capital Regulations

Purpose – The purpose of this study is to replicate Avery and Berger’s (1991) analysis using data from 2001 through 2011. Although risk-based capital (RBC) regulation is a key component of US banking regulation, empirical evidence of the effectiveness of these regulations has been mixed. Among the first studies of RBC regulation, Avery and Berger (1991) provide evidence from data on US banks that new RBC regulations outperformed old capital regulations from 1982 through 1989. Design/methodology/approach – Using data from the Federal Reserve’s Call Reports, the authors compare banks’ capital ratios and RBC ratios to five measures of bank performance: income, standard deviation of income, non-performing loans, loan charge-offs and probability of failure. Findings – Consistent with Avery and Berger (1991), the authors find banks’ risk-weighted assets to be significant predictors of their future performance and that RBC ratios outperform regular capital ratios as predictors of risk. Originality/value – The study improves on Avery and Berger (1991) by using an updated data set from 2001 through 2011. The authors also discuss some potential limitations of this method of analysis.

Twitter users exhibited coping behaviours during the COVID-19 lockdown: an analysis of tweets using mixed methods

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ruchi Mittal ◽  
Wasim Ahmed ◽  
Amit Mittal ◽  
Ishan Aggarwal
Keyword(s):  
Data Analysis ◽  
The Body ◽  
Data Set ◽  
Content Type ◽  
Twitter Data ◽  
Long Run ◽  
The World ◽  
Twitter Users ◽  
The Government ◽  
Using Data

Purpose Using data from Twitter, the purpose of this paper is to assess the coping behaviour and reactions of social media users in response to the initial days of the COVID-19-related lockdown in different parts of the world. Design/methodology/approach This study follows the quasi-inductive approach which allows the development of pre-categories from other theories before the sampling and coding processes begin, for use in those processes. Data was extracted using relevant keywords from Twitter, and a sample was drawn from the Twitter data set to ensure the data is more manageable from a qualitative research standpoint and that meaningful interpretations can be drawn from the data analysis results. The data analysis is discussed in two parts: extraction and classification of data from Twitter using automated sentiment analysis; and qualitative data analysis of a smaller Twitter data sample. Findings This study found that during the lockdown the majority of users on Twitter shared positive opinions towards the lockdown. The results also found that people are keeping themselves engaged and entertained. Governments around the world have also gained support from Twitter users. This is despite the hardships being faced by citizens. The authors also found a number of users expressing negative sentiments. The results also found that several users on Twitter were fence-sitters and their opinions and emotions could swing either way depending on how the pandemic progresses and what action is taken by governments around the world. Research limitations/implications The authors add to the body of literature that has examined Twitter discussions around H1N1 using in-depth qualitative methods and conspiracy theories around COVID-19. In the long run, the government can help citizens develop routines that help the community adapt to a new dangerous environment – this has very effectively been shown in the context of wildfires in the context of disaster management. In the context of this research, the dominance of the positive themes within tweets is promising for policymakers and governments around the world. However, sentiments may wish to be monitored going forward as large-spikes in negative sentiment may highlight lockdown-fatigue. Social implications The psychology of humans during a pandemic can have a profound impact on how COVID-19 shapes up, and this shall also include how people behave with other people and with the larger environment. Lockdowns are the opposite of what societies strive to achieve, i.e. socializing. Originality/value This study is based on original Twitter data collected during the initial days of the COVID-19-induced lockdown. The topic of “lockdowns” and the “COVID-19” pandemic have not been studied together thus far. This study is highly topical.

Investigating the clinical usefulness of definitions of progression with 10-2 visual field

2021 ◽  
pp. bjophthalmol-2020-318188
Author(s):  
Shotaro Asano ◽  
Hiroshi Murata ◽  
Yuri Fujino ◽  
Takehiro Yamashita ◽  
Atsuya Miki ◽  
...  
Keyword(s):  
Visual Field ◽  
False Positive ◽  
False Positive Rate ◽  
Clinical Validity ◽  
Data Set ◽  
Humphrey Field Analyzer ◽  
Positive Rate ◽  
Using Data ◽  
Sensitivity Specificity ◽  
Higher Sensitivity

Background/AimTo investigate the clinical validity of the Guided Progression Analysis definition (GPAD) and cluster-based definition (CBD) with the Humphrey Field Analyzer 10-2 test in diagnosing glaucomatous visual field (VF) progression, and to introduce a novel definition with optimised specificity by combining the ‘any-location’ and ‘cluster-based’ approaches (hybrid definition).Methods64 400 stable glaucomatous VFs were simulated from 664 pairs of 10-2 tests (10 sets × 10 VF series × 664 eyes; data set 1). Using these simulated VFs, the specificity to detect progression and the effects of changing the parameters (number of test locations or consecutive VF tests, and percentile cut-off values) were investigated. The hybrid definition was designed as the combination where the specificity was closest to 95.0%. Subsequently, another 5000 actual glaucomatous 10-2 tests from 500 eyes (10 VFs each) were collected (data set 2), and their accuracy (sensitivity, specificity and false positive rate) and the time needed to detect VF progression were evaluated.ResultsThe specificity values calculated using data set 1 with GPAD and CBD were 99.6% and 99.8%. Using data set 2, the hybrid definition had a higher sensitivity than GPAD and CBD, without detriment to the specificity or false positive rate. The hybrid definition also detected progression significantly earlier than GPAD and CBD (at 3.1 years vs 4.2 years and 4.1 years, respectively).ConclusionsGPAD and CBD had specificities of 99.6% and 99.8%, respectively. A novel hybrid definition (with a specificity of 95.5%) had higher sensitivity and enabled earlier detection of progression.

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