Estimating freeway travel time and its reliability using radar sensor data

<p>Travel time and its reliability are intuitive system performance measures for freeway traffic operations. This paper proposes a method to estimate travel times based on data collected from roadside radar sensors, considering spatially correlated traffic conditions. Link-level and corridor-level travel time distributions are estimated using these travel time estimates and compared with the ones estimated based on probe vehicle data. The maximum likelihood estimation is used to estimate the parameters of Weibull, gamma, normal, and lognormal distributions. According to the log-likelihood values, lognormal distribution is the best fit among all the tested distributions. Corridor-level travel time reliability measures are extracted from the travel time distributions. The proposed travel time estimation model can well capture the temporal pattern of travel time and its distribution.</p

Multivariate regression model to predict anterior chamber depth associated with age and gender in normal subjects.

<p>Multivariate regression model to predict anterior chamber depth associated with age and gender in normal subjects.</p

Scatter plot of (A) age against central corneal thickness, and (B) age against anterior chamber depth as measured by the Galilei Scheimpflug system.

<p>Line: univariate regression summarizing the relationship between the two variables.</p

Correlations between total corneal power (TCP) and axial curvature (AC) of the central cornea of 8 mm diameter.

<p>Correlations between total corneal power (TCP) and axial curvature (AC) of the central cornea of 8 mm diameter.</p

Difference between anterior instantaneous curvature (AIC) and simulated keratometry (SimK) values.

<p>Note: diopter (D); † Two-tailed independent sample t-test.</p

Scatter plots of (A) high order aberration against total corneal wavefront, and (B) spherical aberration against high order aberration as measured by the Galilei Scheimpflug system.

<p>Lines: univariate regression summarizing the relationship between the two variables.</p

Improved Lower Bounds of DNA Tags Based on a Modified Genetic Algorithm

<div><p>The well-known massively parallel sequencing method is efficient and it can obtain sequence data from multiple individual samples. In order to ensure that sequencing, replication, and oligonucleotide synthesis errors do not result in tags (or barcodes) that are unrecoverable or confused, the tag sequences should be abundant and sufficiently different. Recently, many design methods have been proposed for correcting errors in data using error-correcting codes. The existing tag sets contain small tag sequences, so we used a modified genetic algorithm to improve the lower bound of the tag sets in this study. Compared with previous research, our algorithm is effective for designing sets of DNA tags. Moreover, the GC content determined by existing methods includes an imprecise range. Thus, we improved the GC content determination method to obtain tag sets that control the GC content in a more precise range. Finally, previous studies have only considered perfect self-complementarity. Thus, we considered the crossover between different tags and introduced an improved constraint into the design of tag sets.</p></div

Results obtained using the improved perfect complementarity constraint.

<p>Results obtained using the improved perfect complementarity constraint.</p

A flow chart depicting the decentration and tilt angle analysis of the intraocular lens (IOL).

<p>A flow chart depicting the decentration and tilt angle analysis of the intraocular lens (IOL).</p

Results obtained by Faircloth et al.

<p>Results obtained by Faircloth et al.</p