In the Swedish labor market the immigrant, compared to the native individual, is seen to experience both stigma and discrimination to a bigger degree. This in turn generates some immigrants to have a negative experience correlated to the Swedish worklife in consideration to the unfair treatment in the recruitment process. In this study we investigate the experiences of women from Syria in consideration to their experiences of stigma and discrimination in the Swedish labor market. We have conducted a qualitative study in the form of semi-qualitative interviews with a total of six Syrian migrated women as a measure to gather the women's experience in search for common or shared experiences of discrimination or injustice taking place in the Swedish labor market. Our data analysis is based on three occurring themes where we linked our empirical evidence to former research done in the field, also to relevant theories presented by sociologists investigating the subject of stigma. The study's results show that all women shared the common experience of discrimination and stigma in consideration to the hiring process in the Swedish labor market. Different factors such as their cultural background, language skills, their physical appearance and name were also of importance. / På den svenska arbetsmarknaden tycks invandraren, jämfört med den infödda, uppleva både stigmatisering och diskriminering i högre grad. Detta leder i sin tur till att vissa invandrare får en negativ upplevelse kopplat till det svenska arbetslivet med hänsyn till orättvis behandling i rekryteringsprocessen. I denna studie undersöker vi erfarenheterna av kvinnor från Syrien med hänsyn till deras erfarenheter av stigma och diskriminering på den svenska arbetsmarknaden. Vi har genomfört en kvalitativ studie i form av semi-kvalitativa intervjuer med totalt sex syriska migrerande kvinnor som en insats för att samla kvinnornas erfarenheter i sökandet efter gemensamma eller delade erfarenheter av diskriminering eller orättvisor som äger rum på den svenska arbetsmarknaden. Vår dataanalys är baserad på tre förekommande teman där vi kopplat våra empiriska bevis till tidigare forskning gjord på området, även till relevanta teorier som presenterats av sociologer som undersökt ämnet stigma. Studiens resultat visar att samtliga kvinnor delade en gemensam erfarenhet av diskrimineringoch stigma i hänsyn till anställningsprocessen på den svenska arbetsmarknaden. Olika faktorer såsom deras kulturella bakgrund, språkkunskaper, deras fysiska utseende och namn var också av betydelse.

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No / Grid computing is a computational concept based on an infrastructure that integrates and collaborates the use of high end computers, networks, databases and scientific instruments owned and managed by several organisations. It involves large amounts of data and computing which require secure and reliable resource sharing across organisational domains. Despite its high computing performance orientation, communication delays between grid computing nodes is a big hurdle due to geographical separation in a realistic grid computing environment. Communication schemes such as broadcasting, multicasting and routing should, therefore, take communication delay into consideration. Such communication schemes in a grid computing environment pose a great challenge due to the arbitrary nature of its topology. In this context, a heuristic algorithm for multicast communication is proposed for grid computing networks with finite capacity and bursty background traffic. The scheme facilitates inter-node communication for grid computing networks and it is applicable to a single-port mode of message passing communication. The scheme utilises a queue-by-queue decomposition algorithm for arbitrary open queueing network models, based on the principle of maximum entropy, in conjunction with an information theoretic decomposition criterion and graph theoretic concepts. Evidence based on empirical studies indicates the suitability of the scheme for achieving an optimal multicast communication cost, subject to system decomposition constraints.

Driving field experiment data were used to investigate lane changes in which a slow lead vehicle was present to: 1) characterize lane changes, 2) develop predictive models, 3) provide collision avoidance system (CAS) design guidelines. A total of 3,227 slow lead vehicle lane changes over 23,949 miles were completed by sixteen commuters. Two instrumented vehicles, a sedan and an SUV, were outfitted with video, sensor, and radar data systems that collected data in an unobtrusive manner. Results indicate that 37.2% of lane changes are slow lead vehicle lane changes, with a mean completion time of 6.3 s; most slow lead vehicle lane changes are leftward, rated low in urgency and severity. A stratified sample of 120 lane changes was selected to include a range of maneuvers. On the interstate, lane changes are performed less often, <i>t</i>(30) = 2.83, <i>p</i> = 0.008, with lower urgency ratings, <i>F</i>(1, 31) = 5.24, <i>p</i> = 0.05, as compared to highway lane changes, as interstates are designed for smooth flow. Drivers who usually drive sedans are more likely to make lane changes than drivers of SUVs, <i>X</i> ²⁺(1)= 99.6247, <i>p</i> < 0.0001, suggesting that driving style is maintained regardless of which experimental vehicle is driven. Turn signals are used 64% of the time but some drivers signal after the lane change starts. Of cases in which signals are not used, 70% of them are made with other vehicles nearby. Eyeglance analysis revealed that the forward view, rearview mirror, and left mirror are the most likely glance locations. There are also distinct eyeglance patterns for lane changing and baseline driving. Recommendations are to use forward view or mirror-based visual displays to indicate presence detection, and auditory displays for imminent warnings. The "vehicle + signal" logistic regression model is best overall since it takes advantage of the distance to the front and rear adjacent vehicle, forward time-to-collision (TTC), and turn signal activation. The use of additional regressors would also improve the model. Five design guidelines are included to aid in the development of CAS that are useable, safe, and integrated with other systems, given testing and development. / Ph. D.

In recent years, unmanned aerial vehicles (UAVs) have got a boost in their applications in civilian areas like aerial photography, agriculture, communication, etc. An increasing research effort is being exerted to develop sophisticated trajectory prediction methods for UAVs for collision detection and trajectory planning. The existing techniques suffer from problems such as inadequate uncertainty quantification of predicted trajectories. This work adopts particle filters together with Löwner-John ellipsoid to approximate the highest posterior density region for trajectory prediction and uncertainty quantification. The particle filter is tuned and tested on real-world and simulated data sets and compared with the Kalman filter. A parallel computing approach for particle filter is further proposed. This parallel implementation makes the particle filter faster and more suitable for real-time online applications. / Master of Science / In recent years, unmanned aerial vehicles (UAVs) have got a boost in their applications in civilian areas like aerial photography, agriculture, communication, etc. Over the coming years, the number of UAVs will increase rapidly. As a result, the risk of mid-air collisions grows, leading to property damages and possible loss of life if a UAV collides with manned aircraft. An increasing research effort has been made to develop sophisticated trajectory prediction methods for UAVs for collision detection and trajectory planning. The existing techniques suffer from problems such as inadequate uncertainty quantification of predicted trajectories. This work adopts particle filters, a Bayesian inferencing technique for trajectory prediction. The use of minimum volume enclosing ellipsoid to approximate the highest posterior density region for prediction uncertainty quantification is also investigated. The particle filter is tuned and tested on real-world and simulated data sets and compared with the Kalman filter. A parallel computing approach for particle filter is further proposed. This parallel implementation makes the particle filter faster and more suitable for real-time online applications.