Recent miniaturization of computer hardware, MEMs sensors, and high energy density batteries have enabled highly capable mobile robots to become available at low cost. This has driven the rapid expansion of interest in multi-rotor unmanned aerial vehicles. Another area which has expanded simultaneously is small powerful computers, in the form of smartphones, which nearly always have a camera attached, many of which now contain a OpenCL compatible graphics processing units. By combining the results of those two developments a low-cost multi-rotor UAV can be produced with a low-power onboard computer capable of real-time computer vision. The system should also use general purpose computer vision software to facilitate a variety of experiments. To demonstrate this I have built a quadrotor UAV based on control hardware from the Pixhawk project, and paired it with an ARM based single board computer, similar those in high-end smartphones. The quadrotor weights 980 g and has a flight time of 10 minutes. The onboard computer capable of running a pose estimation algorithm above the 10 Hz requirement for stable visual control of a quadrotor. A feature tracking algorithm was developed for efficient pose estimation, which relaxed the requirement for outlier rejection during matching. Compared with a RANSAC- only algorithm the pose estimates were less variable with a Z-axis standard deviation 0.2 cm compared with 2.4 cm for RANSAC. Processing time per frame was also faster with tracking, with 95 % confidence that tracking would process the frame within 50 ms, while for RANSAC the 95 % confidence time was 73 ms. The onboard computer ran the algorithm with a total system load of less than 25 %. All computer vision software uses the OpenCV library for common computer vision algorithms, fulfilling the requirement for running general purpose software. The tracking algorithm was used to demonstrate the capability of the system by per- forming visual servoing of the quadrotor (after manual takeoff). Response to external perturbations was poor however, requiring manual intervention to avoid crashing. This was due to poor visual controller tuning, and to variations in image acquisition and attitude estimate timing due to using free running image acquisition. The system, and the tracking algorithm, serve as proof of concept that visual control of a quadrotor is possible using small low-power computers and general purpose computer vision software.

Observations of animal distributions have revealed that population densities have tracked resource quality. Various models have been proposed to account for such “resource matching.” For example, the Ideal Free Distribution (Fretwell and Lucas 1970) model employs habitat selection rules which assume mobile animals evaluate available habitat patches and select the highest quality patch first. I examined movement patterns of northern crayfish (Orconectes virilis) in response to habitat patches of different quality to test this assumption. I found that animals were more likely to leave a low quality patch than a high quality patch even when there were no other patches available, suggesting that the quality of encountered resources plays a significant role in subsequent decisions about movement. However, many animals did not leave the first patch they encountered, even when better habitat existed elsewhere and was well within their ability to sample it. Finally, not all crayfish selected the best site they encountered. My studies demonstrate that the response to resources is complex, and IFDs and other distribution models may rely on overly simplified assumptions about habitat selection behavior.

The field of biometrics has grown significantly in the past decade due to an increase in interest from law enforcement. Law enforcement officials are interested in adding tattoos alongside irises and fingerprints to their toolbox of biometrics. They often use these biometrics to aid in the identification of victims and suspects. Like facial recognition, tattoos have seen a spike in attention over the past few years. Tattoos, however, have not received as much attention by researchers. This lack of attention towards tattoos stems from the difficulty inherent in matching these tattoos. Such difficulties include image quality, affine transformation, warping of tattoos around the body, and in some cases, excessive body hair covering the tattoo. We will utilize context-based image retrieval to find a tattoo in a database which means using one image to query against a database in order to find similar tattoos. We will focus specifically on the keypoint detection process in computer vision. In addition, we are interested in finding not just exact matches but also similar tattoos. We will conclude that the ORB detector pulls the most relevant features and thus is the best chance for yielding an accurate result from content-based image retrieval for tattoos. However, we will also show that even ORB will not work on its own in a content-based image retrieval system. Other processes will have to be involved in order to return accurate matches. We will give recommendations on next-steps to create a better tattoo retrieval system.

Human face detection and recognition techniques play an important role in applica- tions like face recognition, video surveillance, human computer interface and face image databases. Using color information in images is one of the various possible techniques used for face detection. The novel technique used in this project was the combination of various techniques such as skin color detection, template matching, gradient face de- tection to achieve high accuracy of face detection in frontal faces. The objective in this work was to determine the best rotation angle to achieve optimal detection. Also eye and mouse template matching have been put to test for feature detection.

Software agents interact to solve tasks, the details of which need to be described in a language understandable by all the actors involved. Ontologies provide a formalism for defining both the domain of the task and the terminology used to describe it. However, finding a shared ontology has proved difficult: different institutions and developers have different needs and formalise them in different ontologies. In a closed environment it is possible to force all the participants to share the same ontology, while in open and distributed environments ontology mapping can provide interoperability between heterogeneous interacting actors. However, conventional mapping systems focus on acquiring static information, and on mapping whole ontologies, which is infeasible in open systems. This thesis shows a different approach to the problem of heterogeneity. It starts from the intuitive idea that when similar situations arise, similar interactions are performed. If the interactions between actors are specified in formal scripts, shared by all the participants, then when the same situation arises, the same script is used. The main hypothesis that this thesis aims to demonstrate is that by analysing different runs of these scripts it is possible to create a statistical model of the interactions, that reflect the frequency of terms in messages and of ontological relations between terms in different messages. The model is then used during a run of a known interaction to compute the probability distribution for terms in received messages. The probability distribution provides additional information, contextual to the interaction, that can be used by a traditional ontology matcher in order to improve efficiency, by reducing the comparisons to the most likely ones given the context, and possibly both recall and precision, in particular helping disambiguation. The ability to create a model that reflects real phenomena in this sort of environment is evaluated by analysing the quality of the predictions, in particular verifying how various features of the interactions, such as their non-stationarity, affect the predictions. The actual improvements to a matcher we developed are also evaluated. The overall results are very promising, as using the predictor can lower the overall computation time for matching by ten times, while maintaining or in some cases improving recall and precision.

Paper [I] models a game, where two temporary work agencies (TWAs) compete to fill a vacancy at a client firm (CF). They simultaneously choose how much effort to expend, based on their expectation of how good their opponent’s best candidate will be. I then show that this will make the TWAs overconfident, as the rational way of judging your own probability of winning is not looking at the opponents expected best, but comparing how much effort your opponent will expend. Paper [II] examines the misaligned incentives in the temporary work agency sector, where we first look at pure recruiting contracts, that either require payment on delivery, or payment on some specified point in time. We then look at the incentives of recruit-and-rent contracts, where the worker is leased to the client firm. We assume that the better the worker, the higher the probability that the client firm is going to want to hire him/her. If that happens then the TWA will no longer get revenues from said worker, incentivizing the TWA to not always deliver the first match it finds, if it is too good. Lastly we look at how competition can dampen this perverse incentive. Paper [III] models the waiting behavior that can occur if a TWA is contracted to find a worker for a specific time far in the future; the TWA will postpone effort. This behavior is modeled for two types of TWAs; one that is rational and plans ahead, and another that does not plan ahead at all, but instead only looks at the immediate future. I find that the one that only looks at the immediate future starts exerting effort earlier than the planner. After looking at optimal contracts under perfect monitoring and hidden action I provide two extensions. I first show that for the principal to want to delegate search to a rational TWA, the agent has to be better than the CF, by some factor, as it has to make up in efficiency what the principal loses in moral hazard, when the agent waits longer than the principal would like it to. Lastly I prove that it is profit maximizing for the principal to contract one agent and give it a deadline earlier than when the principal would need the worker, and then replace that agent with a competitor if the first one has not succeeded by that earlier deadline. Paper [IV] estimates at the effect of family experience on relative transition probability into the temporary work agency sector. Using register data for all of Sweden we run a bias-reduced logistic regression, where we include various factors that affect the probability of young adults (aged 18-34) entering the sector. This paper ties in to the literature on occupational inheritance, as well as the literature on changing social norms. We find that having had a parent, sibling or partner in the TWA sector increases your probability of entering.

This thesis addresses to what extent childhood family composition – the number of siblings and whether the parents live together, or whether there are non-parental adults and/or half-siblings in the household or not – contributes to variations in adult earnings. The theoretical perspective suggests that resources mediate the effect. While research has shown that siblings, as well as divorce and remarriage, are negatively linked to child outcomes, there are inconsistencies in previous literature. There has been debate over the unconfoundedness of previous studies, something that is handled here by analyzing large sets of representative data using a robust parameter. The longitudinal dataset used is based on Swedish administrative data and the cohorts analyzed are born in the beginning of the 1970s. The data structure is well suited for the assumptions underlying the semi-parametric method propensity score matching. The findings show that family size impacts on adult earnings. However, this is not always of concern. For example, no effect of siblings is found in affluent families, and if siblings are closely spaced this results in better outcomes for children. Divorce and remarriage do not seem to lower the future earnings of children. Thus, this thesis shows that some of the most well-established patterns in the sociology of the family, namely the link between number of siblings and adult earnings, and between divorce/family re-formation and adult earnings, can be broken by resources.

The goal of a parallel algorithm is to solve a single problem using multiple processors working together and to do so in an efficient manner. In this regard, there is a need to categorize strategies in order to solve broad classes of problems with similar structures and requirements. In this dissertation, two parallel algorithm design strategies are considered: linked list ranking and parentheses matching.

It has been shown that pair-matching on an ordered baseline with normally distributed measures reduces the variance of the estimated treatment effect (Park and Johnson, 2006). The main objective of this study is to examine if pair-matching improves the power when the distribution is a mixture of two normal distributions. Multiple scenarios with a combination of different sample sizes and parameters are simulated. The power curves are provided for three cases, with and without matching, as follows: analysis of post-intervention data only, adding baseline as a covariate, and classic pre-post comparison. The study shows that the additional variance reduction provided by pair-matching in the pre-post design is limited for high correlation. When correlation is low, there is a significant power increase. It is shown that the baseline pair-matching improves the power when the two means of a mixture normal distribution are widely spread. The pattern becomes clear for low correlation.

Respiration introduces large tumor motion in the thoracic region which influences treatment outcome for lung cancer patients. Tumor motion management techniques require characterization of temporal tumor motions because tumor motion varies patient to patient, day to day and cycle to cycle. This work develops a markerless algorithm to estimate 3 dimensional (3D) lung-tumor trajectories on free breathing cone beam computed tomography (CBCT) projections, which are 2 dimensional (2D) sequential images rotating about an axis and are used to reconstruct 3D CBCT images. A gold standard tumor trajectory is required to guide the algorithm development and estimate the tumor detection accuracy for markerless tracking algorithms. However, a sufficient strategy to validate markerless tracking algorithms is lacking. A validation framework is developed based on fiducial markers. Markers are segmented and marker trajectories are xiv obtained. The displacement of the tumor to the marker is calculated and added to the segmented marker trajectory to generate reference tumor trajectory. Markerless tumor trajectory estimation (MLTM) algorithm is developed and improved to acquire tumor trajectory with clinical acceptable accuracy for locally advanced lung tumors. The development is separate into two parts. The first part considers none tumor deformation. It investigates shape and appearance of the template, moreover, a constraint method is introduced to narrow down the template matching searching region for more precise matching results. The second part is to accommodate tumor deformation near the end of the treatment. The accuracy of MLTM is calculated and compared against 4D CBCT, which is the current standard of care. In summary, a validation framework based on fiducial markers is successfully built. MLTM is successfully developed with or without the consideration of tumor deformation with promising accuracy. MLTM outperforms 4D CBCT in temporal tumor trajectory estimation.