[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

Gaining a better understanding of the factors that affect the likelihood of a vehicle crash has been an area of research focus for many decades. However, in the absence of detailed driving data that would help improve the identification of cause and effect relationships with individual vehicle crashes, most researchers have addressed this problem by framing it in terms of understanding the factors that affect the frequency of crashes - the number of crashes occurring in some geographical space (usually a roadway segment or intersection) over some specified time period. This paper provides a detailed review of the key issues associated with crash-frequency data as well as the strengths and weaknesses of the various methodological approaches that researchers have used to address these problems. While the steady march of methodological innovation (including recent applications of random parameter and finite mixture models) has substantially improved our understanding of the factors that affect crash-frequencies, it is the prospect of combining evolving methodologies with far more detailed vehicle crash data that holds the greatest promise for the future.

http://ceprofs.tamu.edu/dlord/Papers/Lord-Mannering_Review.pdf

The statistical analysis of crash-frequency data: A review and assessment of methodological alternatives

The Analysis of Variance.

We describe the draft genome of the microcrustacean Daphnia pulex, which is only 200 megabases and contains at least 30,907 genes. The high gene count is a consequence of an elevated rate of gene duplication resulting in tandem gene clusters. More than a third of Daphnia's genes have no detectable homologs in any other available proteome, and the most amplified gene families are specific to the Daphnia lineage. The coexpansion of gene families interacting within metabolic pathways suggests that the maintenance of duplicated genes is not random, and the analysis of gene expression under different environmental conditions reveals that numerous paralogs acquire divergent expression patterns soon after duplication. Daphnia-specific genes, including many additional loci within sequenced regions that are otherwise devoid of annotations, are the most responsive genes to ecological challenges.

/pdf/the-ecoresponsive-genome-of-daphnia-pulex-bywdhwk6v1.pdf

The ecoresponsive genome of Daphnia pulex

The questionnaires from the field were received, checked and stored by the data processing personnel. They checked: 1. The completeness of the questionnaires 2. The correct bubbling 3. The correct number of questionnaires per household, if total males + total females > 8 as the questionnaire ONLY accommodated maximum of 8 household members. 4. The reference number appears in all the 10 pages of the questionnaires.

Population and Housing Census

Men Shape a Downward Trend in Car Use among Young Adults—Evidence from Six Industrialized Countries

Bivariate ordered-response probit model of driver’s and passenger’s injury severities in collisions with fixed objects ☆

The behavior of time allocation to two types of discretionary activities is formulated as a doubly-censored Tobit model. The model is capable of incorporating cases where the entire amount of time available for discretionary activity is allocated to one type of activity and the other type of activity is not engaged at all. The model is applied to examine individuals' allocation of time to in-home and out-of-home discretionary activities on working days and non-working days, using a weekly time-use data set from the Netherlands. Workers' daily activity patterns vary significantly between working days and non-working days, while it can be expected that patterns of time allocation are correlated between working days and non-working days. A set of error components is introduced into the model to represent this correlation, adopting a mass point approach which requires no assumption about the distribution of the error components. The validity of the model is examined statistically.

An analysis of time allocation to in-home and out-of-home discretionary activities across working days and non- working days

Underreporting in traffic accident data, bias in parameters and the structure of injury severity models.

The objective of this study was to develop a heterogeneous traffic-flow model to study the possible impact of connected and autonomous vehicles (CAVs) on the traffic flow. Based on a recently proposed two-state safe-speed model (TSM), a two-lane cellular automaton (CA) model was developed, wherein both the CAVs and conventional vehicles were incorporated in the heterogeneous traffic flow. In particular, operation rules for CAVs are established considering the new characteristics of this emerging technology, including autonomous driving through the adaptive cruise control and inter-vehicle connection via short-range communication. Simulations were conducted under various CAV-penetration rates in the heterogeneous flow. The impact of CAVs on the road capacity was numerically investigated. The simulation results indicate that the road capacity increases with an increase in the CAV-penetration rate within the heterogeneous flow. Up to a CAV-penetration rate of 30%, the road capacity increases gradually; the effect of the difference in the CAV capability on the growth rate is insignificant. When the CAV-penetration rate exceeds 30%, the growth rate is largely decided by the capability of the CAV. The greater the capability, the higher the road-capacity growth rate. The relationship between the CAV-penetration rate and the road capacity is numerically analyzed, providing some insights into the possible impact of the CAVs on traffic systems.

Toshiyuki Yamamoto

Papers

Men Shape a Downward Trend in Car Use among Young Adults—Evidence from Six Industrialized Countries

Bivariate ordered-response probit model of driver’s and passenger’s injury severities in collisions with fixed objects ☆

An analysis of time allocation to in-home and out-of-home discretionary activities across working days and non- working days

Underreporting in traffic accident data, bias in parameters and the structure of injury severity models.

Modeling connected and autonomous vehicles in heterogeneous traffic flow