The value of reliability

We derive the value of reliability in the scheduling of an activity of random duration, such as travel under congested conditions. We show that the minimal expected cost is linear in the mean and standard deviation of duration, regardless of the form of the standardized distribution of durations. This insight provides a unification of the scheduling model and models that include the standard deviation of duration directly as an argument in the cost or utility function. The results generalize approximately to the case where the mean and standard deviation of duration depend on the starting time. Empirical illustration is provided.

A new information theoretical measure of global and local spatial association

In this paper a new measure of spatial association, the S statistics, is developed. The proposed measure is based on information theory by defining a spatially weighted information measure (entropy measure) that takes the spatial configuration into account. The proposed S-statistics has an intuitive interpretation, and furthermore fulfills properties that are expected from an entropy measure. Moreover, the S statistics is a global measure of spatial association that can be decomposed into Local Indicators of Spatial Association (LISA). This new measure is tested using a dataset of employment in the culture sector that was attached to the wards over Stockholm County and later compared with the results from current global and local measures of spatial association. It is shown that the proposed S statistics share many properties with Moran's I and Getis-Ord Gi statistics. The local Si statistics showed significant spatial association similar to the Gi statistic, but has the advantage of being possible to aggregate to a global measure of spatial association. The statistics can also be extended to bivariate distributions. It is shown that the commonly used Bayesian empirical approach can be interpreted as a Kullback-Leibler divergence measure. An advantage of S-statistics is that this measure select only the most robust clusters, eliminating the contribution of smaller ones composed by few observations and that may inflate the global measure.Global and local measure of spatial association, LISA, S-statistics, Gi statistics, Moran's I, Kullback-Leibler divergence,

The Employment Effect of Stricter Rules for Eligibility for DI: Evidence from a Natural Experiment in Sweden

We study the effect of a reform of the Swedish disability insurance (DI) program whereby the special eligibility rules for workers in the age group 60 to 64 were abolished. First, we use a differences-in-differences approach to study changes in the disability take-up as compared to the age group 55 to 59. Then, we use a similar approach to study to what extent the employment effect of the reform is "crowded out" by an increase in the utilization of the sickpay insurance (SI) and/or the unemployment insurance (UI). In an extended analysis, we study the effect of firm closure on employment and the utilization of different labor market insurance programs in different age groups before and after the reform.Disability Insurance; Early Retirement

Model-based traffic state estimation for link traffic using moving cameras

Traffic State Estimation (TSE) is the process of inferring traffic conditions based on partially observed data using prior knowledge of traffic patterns. The type of input data used has a significant impact on the accuracy and methodology of TSE. Traditional TSE methods have relied on data from either stationary sensors like loop detectors or mobile sensors such as GPS-equipped floating cars. However, both approaches have their limitations. This paper proposes a method for estimating traffic states on a road link using vehicle trajectories obtained from cameras mounted on moving vehicles. It involves combining data from multiple moving cameras to construct time-space diagrams and using them to estimate parameters for the link's fundamental diagram (FD) and densities in unobserved regions of space-time. The Cell Transmission Model (CTM) is utilized in conjunction with a Genetic Algorithm (GA) to optimize the FD parameters and boundary conditions necessary for accurate estimation. To evaluate the effectiveness of the proposed methodology, simulated traffic data generated by the SUMO traffic simulator was employed incorporating 140 different space-time diagrams with varying lane density and speed. The evaluation of the simulated data demonstrates the effectiveness of the proposed approach, as it achieves a low root mean square error (RMSE) value of 0.0079 veh/m and is comparable to other CTM-based methods. In conclusion, the proposed TSE method opens new avenues for the estimation of traffic state using an innovative data collection method that uses vehicle trajectories collected from on-board cameras.Comment: Under review for journal submissio

A new information theoretical measure of global and local spatial association

In this paper a new measure of spatial association, the S statistics, is developed. The proposed measure is based on information theory by defining a spatially weighted information measure (entropy measure) that takes the spatial configuration into account. The proposed S-statistics has an intuitive interpretation, and furthermore fulfills properties that are expected from an entropy measure. Moreover, the S statistics is a global measure of spatial association that can be decomposed into Local Indicators of Spatial Association (LISA). This new measure is tested using a dataset of employment in the culture sector that was attached to the wards over Stockholm County and later compared with the results from current global and local measures of spatial association. It is shown that the proposed S statistics share many properties with Moran's I and Getis-Ord Gi statistics. The local Si statistics showed significant spatial association similar to the Gi statistic, but has the advantage of being possible to aggregate to a global measure of spatial association. The statistics can also be extended to bivariate distributions. It is shown that the commonly used Bayesian empirical approach can be interpreted as a Kullback-Leibler divergence measure. An advantage of S-statistics is that this measure select only the most robust clusters, eliminating the contribution of smaller ones composed by few observations and that may inflate the global measure

A new information theoretical measure of global and local spatial association

In this paper a new measure of spatial association, the S statistics, is developed. The proposed measure is based on information theory by defining a spatially weighted information measure (entropy measure) that takes the spatial configuration into account. The proposed S-statistics has an intuitive interpretation, and furthermore fulfills properties that are expected from an entropy measure. Moreover, the S statistics is a global measure of spatial association that can be decomposed into Local Indicators of Spatial Association (LISA). This new measure is tested using a dataset of employment in the culture sector that was attached to the wards over Stockholm County and later compared with the results from current global and local measures of spatial association. It is shown that the proposed S statistics share many properties with Moran's I and Getis-Ord Gi statistics. The local Si statistics showed significant spatial association similar to the Gi statistic, but has the advantage of being possible to aggregate to a global measure of spatial association. The statistics can also be extended to bivariate distributions. It is shown that the commonly used Bayesian empirical approach can be interpreted as a Kullback-Leibler divergence measure. An advantage of S-statistics is that this measure select only the most robust clusters, eliminating the contribution of smaller ones composed by few observations and that may inflate the global measure

Including time in a travel demand model using dynamic discrete choice

Activity based travel demand models are based on the idea that travel is derived from the demand to participate in different activities. Predicting travel demand should therefore include the prediction of demand for activity participation. Time-space constraints, such as working hours, restricts when and where different activities can be conducted, and plays an important role in determining how people choose to travel. Travelling is seen as a possibly costly link between different activities, that also implicitly leads to missed opportunities for activity participation. With a microeconomic foundation, activity based models can further be used for appraisal and for accessibility measures. However, most models up to date lack some dynamic consistency that, e.g., might make it hard to capture the trade-off between activity decisions at different times of the day. In this paper, we show how dynamic discrete choice theory can be used to formulate a travel demand model which includes choice of departure time for all trips, as well as number of trips, location, purpose and mode of transport. We estimate the model on travel diaries and show that the it is able to reproduce the distribution of, e.g., number of trips per day, departure times and travel time distributions

Nonequilibrium transport in quantum impurity models: Exact path integral simulations

We simulate the nonequilibrium dynamics of two generic many-body quantum impurity models by employing the recently developed iterative influence-functional path integral method [Phys. Rev. B {\bf 82}, 205323 (2010)]. This general approach is presented here in the context of quantum transport in molecular electronic junctions. Models of particular interest include the single impurity Anderson model and the related spinless two-state Anderson dot. In both cases we study the time evolution of the dot occupation and the current characteristics at finite temperature. A comparison to mean-field results is presented, when applicable

En applikationsinfrastruktur för massutskick av e-post

In today's society it is becoming more and more important with direct marketing. Some of the direct marketing is done through e-mail, in which companies see an easy way to advertise himself. I did this thesis work at WebDoc Systems. They have a product that creates web documents directly in your browser, also called CMS. The CMS has a module for sending mass e-mail, but this module does not function properly and WebDoc Systems customers are dissatisfied with that part of the product. The problem with the module was that sometimes it didn't send the e-mail, and that it was not possible to obtain some form of follow-up information on the e-mail. The goal of this work was to develop a Web service that could easily send e-mail to many receivers, just as easily be able to view statistics on how mailing has gone. The first step was to do a literature review to get a good picture of available programming platforms, but also to be able create a good application infrastructure. The next step was to implement this design and improve it over time by using an iterative development methodology. The result was an application infrastructure that consists of three main parts and a plugin interface. The parts that were implemented were a Web service application, a Web application and a Windows service application. The three elements cooperate with each other and share a database, and plugins