Using a k-means clustering algorithm to examine patterns of pedestrian involved crashes in Honolulu,Hawaii

The purpose of this paper is twofold: 1) to describe a statistical technique known as K-means clustering in term of its advantages and disadvantages in safety research; and, 2) to use this method to analyze spatial patterns of pedestrian-involved crashes in Honolulu. K-means, a partitioning clustering technique, provides a powerful tool for analyzing and visualizing spatial patterns. While there are other techniques, one of the advantages of the K-means approach is that it is a well established technique that has been used for many different applications other than traffic safety. In this paper, we compare it to hierarchical clustering techniques and suggest that both are useful in the arsenal of spatial analytic tools for safety research.     

On the residual advection of passive constituents

In this paper, the different approaches used to simulate the long-term advection of passive constituents on tidal shelves are discussed in the framework of large scale hydrodynamic modelling. The direct approach in which the unsteady mesoscale (tides and storm surges) and macroscale (monthly or seasonal mean processes) currents are used is very demanding in computer resources (CPU and memory). On the other hand, the use of residual velocities gives a larger understanding of the long-term transport processes and simplifies numerical treatments. However, the definition of such appropriate velocities is still an open question. In the context of large scale models, Lagrangian residuals are not applicable. Eulerian residual transport velocities fail to represent long-term motions when tidal non-linearities are important. The first order Lagrangian residual velocity introduced by Feng et al. (1986) and generalized here is shown to be a very good solution. The North-Western European Continental Shelf (NWECS) is used as an example to compare the numerical solutions obtained with the different approaches.     

NAFTA and Canadian ports

The North American Free Trade Agreement (NAFTA) signed by Canada, the U.S.A. and Mexico and which came into effect on 1 January 1994, is a significant move towards further integration of the North American economies. This paper examines the likely impact of NAFTA on Canadian ports. Three channels of impact are identified. First, there are direct impacts on trade flows between Canada and its North American trading partners. In this regard we find that ports do not typically handle the types of products that are likely to be affected by NAFTA, and so the direct impacts may be minimal. Second, and more significantly, port catchment areas are likely to undergo substantial changes as they respond to a more competitive environment within the free trade area. Third, the transportation sector has itself been included in NAFTA, and Canadian ports will face increased competition from land based transportation modes. We conclude that ports in Canada must learn to work more consciously as agents of regional economic development.     

Towards integrated land use and transportation: A dynamic disequilibrium based microsimulation framework for built space markets

Investigating the factors and processes that influence the spatiotemporal distribution of built space and population in an urban area, plays an extremely important role in our greater understanding of the urban travel behaviour. Existing location of activity centres, especially home and work, strongly influences the short-term individual-level decisions such as mode of transportation, and long-term household-level decisions such as change in job and residential location. Conditions in the built space market also affect households’ and firms’ location and relocation decisions, and hence influence the general travel patterns in an urban area. In this context, this paper addresses a very important, but at the same time, not very widely investigated dimension that plays a key role in the evolution of built space and population distribution: Market. A disequilibrium based microsimulation modelling framework is developed for the built space markets. This framework is then used to operationalize the Greater Toronto and Hamilton Area’s owner-occupied housing market within Integrated Land Use Transportation and Environment (ILUTE) modelling system. Simulation results captured heterogeneity in the transaction prices, due to type of dwellings and different market conditions, in a very disaggregate fashion. The proposed methodology is validated by running the simulation from 1986 to 2006 and comparing the results with the historic data.     

Missing the tide? Workplace cultural differences as a barrier to seafarer mobility in the U.S. workboat and sail training sectors

ABSTRACT

While previous research details the psychological and social benefits of sail training programs for amateur ‘trainees,’ much less is known about the value and transferability of sail training work experience in terms of professional development for seafaring careers. This article reviews the current state of scientific knowledge on sail training and presents the findings of a qualitative study of maritime recruiter perceptions at 10 U.S. flag workboat companies. Results suggest that the maritime industry may benefit from an improved understanding of the role that sail training programs and the sail training community can play in training and inspiring the next generation of motivated and professional seafarers. Workboat recruiters see positive and negative aspects of sail training experience and perceive cultural divides within the maritime industry that may affect a seafarers’ job mobility, whether or not such divides actually exist.     

Air–sea gas exchange at extreme wind speeds measured by autonomous oceanographic floats

Measurements of the air–sea fluxes of N₂ and O₂ were made in winds of 15–57 m s^− 1 beneath Hurricane Frances using two types of air-deployed neutrally buoyant and profiling underwater floats. Two “Lagrangian floats” measured O₂ and total gas tension (GT) in pre-storm and post-storm profiles and in the actively turbulent mixed layer during the storm. A single “EM-APEX float” profiled continuously from 30 to 200 m before, during and after the storm. All floats measured temperature and salinity. N₂ concentrations were computed from GT and O₂ after correcting for instrumental effects. Gas fluxes were computed by three methods. First, a one-dimensional mixed layer budget diagnosed the changes in mixed layer concentrations given the pre-storm profile and a time varying mixed layer depth. This model was calibrated using temperature and salinity data. The difference between the predicted mixed layer concentrations of O₂ and N₂ and those measured was attributed to air–sea gas fluxes F_BO and F_BN. Second, the covariance flux F_CO(z) = wO₂′(z) was computed, where w is the vertical motion of the water-following Lagrangian floats, O₂′ is a high-pass filtered O₂ concentration and (z) is an average over covariance pairs as a function of depth. The profile F_CO(z) was extrapolated to the surface to yield the surface O₂ flux F_CO(0). Third, a deficit of O₂ was found in the upper few meters of the ocean at the height of the storm. A flux F_SO, moving O₂ out of the ocean, was calculated by dividing this deficit by the residence time of the water in this layer, inferred from the Lagrangian floats. The three methods gave generally consistent results. At the highest winds, gas transfer is dominated by bubbles created by surface wave breaking, injected into the ocean by large-scale turbulent eddies and dissolving near 10-m depth. This conclusion is supported by observations of fluxes into the ocean despite its supersaturation; by the molar flux ratio F_BO/F_BN, which is closer to that of air rather than that appropriate for Schmidt number scaling; by O₂ increases at about 10-m depth along the water trajectories accompanied by a reduction in void fraction as measured by conductivity; and from the profile of F_CO(z), which peaks near 10 m instead of at the surface.At the highest winds O₂ and N₂ are injected into the ocean by bubbles dissolving at depth. This, plus entrainment of gas-rich water from below, supersaturates the mixed layer causing gas to flux out of the near-surface ocean. A net influx of gas results from the balance of these two competing processes. At lower speeds, the total gas fluxes, F_BO, F_BN and F_CO(0), are out of the ocean and downgradient.     

Exploring the propensity to perform social activities: a social network approach

Conceptual and empirical models of the propensity to perform social activity–travel behavior are described, which incorporate the influence of individuals’ social context, namely their social networks. More explicitly, the conceptual model develops the concepts of egocentric social networks, social activities, and social episodes, and defines the three sets of aspects that influence the propensity to perform social activities: individuals’ personal attributes, social network composition, and information and communication technology interaction with social network members. Using the structural equation modeling (SEM) technique and data recently collected in Toronto, the empirical model tests the effect of these three aspects on the propensity to perform social activities. Results suggest that the social networks framework provides useful insights into the role of physical space, social activity types, communication and information technology use, and the importance of “with whom” the activity was performed with. Overall, explicitly incorporating social networks into the activity–travel behavior modeling framework provides a promising framework to understand social activities and key aspects of the underlying behavioral process. Juan Antonio Carrasco a PhD candidate in Civil Engineering at the University of Toronto, holds a MSc degree in Transportation Engineering from the Pontificia Universidad Católica de Chile. His doctoral research explores the relationships between social networks, activity–travel behavior, and ICTs. His research interests also include microsimulation, land use-transportation, and econometric modeling. Eric J. Miller is Bahen-Tanenbaum Professor of Civil Engineering at the University of Toronto where he is also Director of the Joint Program in Transportation. His research interests include integrated land-use/transportation modeling, activity-based travel modeling, microsimulation and sustainable transportation planning.     

Lagrangian data in a high-resolution numerical simulation of the North Atlantic: I. Comparison with in situ drifter data

A model/data comparison was performed between simulated drifters from a high-resolution numerical simulation of the North Atlantic and a data set from in situ surface drifters. The comparison makes use of pseudo-Eulerian statistics such as mean velocity and eddy kinetic energy, and Lagrangian statistics such as integral time scales. The space and time distribution of the two data sets differ in the sense that the in situ drifters were released inhomogeneously in space and time while the simulated drifters were homogeneously seeded at the same time over a regular 1° grid. Despite this difference, the total data distributions computed over the complete data sets show some similarities that are mostly related to the large-scale pattern of Ekman divergence/convergence.Comparisons of eddy kinetic energy and root mean square velocity indicate that the numerical model underestimates the eddy kinetic energy in the Gulf Stream extension and in the ocean interior. In addition, the model Lagrangian time scales are longer in the interior than the in situ time scales by approximately a factor of 2. It is suggested that this is primarily due to the lack of high-frequency winds in the model forcing, which causes an underestimation of the directly forced eddy variability. Regarding the mean flow, the comparison has been performed both qualitatively and quantitatively using James' statistical test. The results indicate that over most of the domain, the differences between model and in situ estimates are not significant. However, some areas of significant differences exist, close to high-energy regions, notably around the Gulf Stream path, which in the model lies slightly north of the observed path, although its strength and structure are well represented overall. Mean currents close to the buffer zones, primarily the Azores Current, also exhibit significant differences between model results and in situ estimates. Possibilities for model improvement are discussed in terms of forcings, buffer zone implementations, turbulence and mixed layer parameterizations, in light of our model/data comparison.