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Phased array systems present desirable antenna features like beam steering and high gain. However, due to their high cost, civilian applications cannot generally afford them, restricting their usage to military. Hardware involved in phased array systems is expensive and the number of devices is high, since there is usually one device of each kind (filter, amplifier, shifter..) for each individual antenna. Alternative techniques, mainly based on TDMA, have been developed looking for lowering the number of elements in the system. However, these approaches increase the system bandwidth, multiplying it by a factor of $N$ (Number of antennas), as they use redundant information. In this thesis, a novel phased receiver, based on an economic sampling scheme is proposed. All the elements in an array receive a common information (signal amplitude) and a unique information (relative delay between elements). The idea is to sample only the information required to reconstruct the transmitted signal and discard the redundant one. This idea is achieved by sampling just one antenna during each RF cycle and then gathering all the information taking in account the relative delay between different antenna elements. The proposed technique is mathematically proved and validated by simulation. As a first approach, the equation for the received signal in the frequency domain is derived for a linear array. The radiation pattern and the received signals are simulated for equally spaced planar and linear arrays. Bandwidth signal transmission is demonstrated and tapering effects are shown. After that, the proposed technique is expanded for arbitrary structures and the resulting system bandwidth is enhanced by using different sampling order sequences. / Master of Science

Fast and accurate estimations for complex queries are profoundly beneficial for large databases with heavy workloads. The most widely adopted query optimizers use synopses to tune up the databases in manners of optimization and re-optimization. From Chapter 1 to Chapter 3, we focus on the synopses for query optimization. We propose a statistical summary for a database, called CS2 (Correlated Sample Synopsis), to provide rapid and accurate result size estimations for all queries with joins and arbitrary selections. Unlike the state-of-the-art techniques, CS2 does not completely rely on simple random samples, but mainly consists of correlated sample tuples that retain join relationships with less storage. We introduce a statistical technique, called reverse sample, and design an innovative estimator, called reverse estimator, to fully utilize correlated sample tuples for query estimation. We prove both theoretically and empirically that the reverse estimator is unbiased and accurate using CS2. Extensive experiments on multiple datasets show that CS2 is fast to construct and derives more accurate estimations than existing methods with the same space budget. In Chapter 4, we focus on the synopses for query re-optimization on repetitive queries. Repetitive queries refer to those queries that are likely to be executed repeatedly in the future, such as those that are used to generate periodic reports, perform routine maintenance, summarize data for analysis, etc. They can constitute a large part of daily activities of a database system and deserve more optimization efforts. In this paper, we propose to collect information about how tuples are joined in a query, called the query or join trace, during execution of a query. We intend to use this join trace to compute the selectivities of joins in all join orders for the query. We use existing operators, as well as new operators, to gather such information. We show that the trace gathered from a query is sufficient to compute the exact selectivities of all plans of the query. To reduce the overheads of generating a trace, we propose a sampling scheme that generates only a sample of the trace. Experimental results have shown that with only a small sample of the trace, accurate estimates of join selectivities can be obtained. The sample trace makes re-estimation of join selectivities of a repetitive query efficient and accurate.

The fully Bayesian estimation via the use of Markov chain Monte Carlo (MCMC) techniques has become popular for estimating item response theory (IRT) models. The current development of MCMC includes two major algorithms: Gibbs sampling and the No-U-Turn sampler (NUTS). While the former has been used with fitting various IRT models, the latter is relatively new, calling for the research to compare it with other algorithms. The purpose of the present study is to evaluate the performances of these two emerging MCMC algorithms in estimating two two-parameter logistic (2PL) IRT models, namely, the 2PL unidimensional model and the 2PL multi-unidimensional model under various test situations. Through investigating the accuracy and bias in estimating the model parameters given different test lengths, sample sizes, prior specifications, and/or correlations for these models, the key motivation is to provide researchers and practitioners with general guidelines when it comes to estimating a UIRT model and a multi-unidimensional IRT model. The results from the present study suggest that NUTS is equally effective as Gibbs sampling at parameter estimation under most conditions for the 2PL IRT models. Findings also shed light on the use of the two MCMC algorithms with more complex IRT models.

SÖRAB:s återvinningsanläggning (ÅVA) i Hagby hanterar olika typer av avfall som t.ex. bygg- och rivningsavfall, textilier, grovavfall från hushåll, trädgårds-, elavfall samt farligt avfall. Vatten från behandlings- och lagringsytorna samlas upp, provtas och renas i anläggningens vattenreningsanläggning. Vid provtagning av processvattnet på anläggningen har poly- och perfluorerade alkylsubstanser (PFAS) påträffats. PFAS är ett samlingsnamn för flertalet syntetiskt tillverkade kemikalier och idag finns fler än 3000 olika PFAS-ämnen på världsmarknaden. PFAS har använts under många år i bl.a. brandsläckningsskum, impregneringsmedel samt vid tillverkning av teflon. Ämnena har tillverkats sedan 1950-talet men först under 00-talet uppmärksammades den miljöpåverkan som PFAS har. Syftet med projektresultatet är att förhindra eller reducera risken för ytterligare utsläpp av PFAS från föroreningskällan/föroreningskällorna. Målet var att undersöka och kartlägga vilka ytor/verksamheter som ger eller har gett upphov till PFAS i processvattnet samt ta fram förslag för hur föroreningskällan kan åtgärdas alternativt föreslå metoder för rening av slam och/eller vatten. Provtagning genomfördes på Hagby ÅVA genom stickprov i sju olika provpunkter under tre provomgångar med tre veckors mellanrum. Samtliga provpunkter vid samtliga provtagningar innehöll PFAS. Högsta halterna PFAS som påträffades i Hagby återvinningsanläggnings (ÅVA) processvatten synes i denna undersökning komma från de ytor där grovavfall, bygg- och rivningsavfall samt elektronikavfall sorteras och lagras. Då flödet på avrinningen från dessa ytor inte går att mäta på ett tillförlitligt sätt är det svårt att veta vilken yta som bidrar med störst mängd PFAS till vattenreningssystemet. Viss mängd PFAS kommer från vallen för inneslutna avfallsmassor som PFAS-halter från provpunkten visar. PFAS-halterna var konstanta vid samtliga provtagningar. Fortsatt kontroll av provpunkten behövs för att kontrollera att PFAS-halterna inte stiger, om så är fallet får vidare utredning av området genomföras. Förslag till åtgärd är att börja med att utreda hur bra reningsanläggningen, inklusive kolfiltret, på Hagby klarar av att rena PFAS från processvattnet. Frågor som behöver besvaras är hur mycket som släpps ut till recipienten och om PFAS/PFOS-halterna klarar riktvärdena. Ett annat förslag är även att slamsuga där det är möjligt samt undersöka om enskilda PFAS-källor kan identifieras och elimineras från ytorna. Metoder som anses lämpliga för rening av PFAS på Hagby är förslagsvis aktivt kol med ett ytterligare förfiltersteg med antracit eller sand för att förebygga igensättning av det befintliga kolfiltret på anläggningen. Förslag är att kontakta de anläggningar som använt sig av kombination av förfiltrering med antracit och kolfilter för att få information om erfarenheter av metoden, hur mycket PFAS-halter lyckats reduceras och kostnader för processen. En annan lämplig metod som har höga reningsgrader är jonbytarteknik (IEX). Försök behöver utföras specifikt för processvattnet på Hagby eftersom inga studier om rening av PFAS i vatten från ÅVA hittats i litteraturen. Nanofiltrering och omvänd osmos har hög effektivitet vid separering av PFAS. Nackdelen är att filtreringen inte är selektiv och att membranen riskerar att sättas igen vid behandling av processvattnet på Hagby ÅVA på grund av flera olika ämnen i vattnet. Fler metoder för behandling av PFAS är lovande som t.ex. elektrokemisk oxidation, biologisk behandling med kiselalger, plasmabehandling, ozonbehandling men är komplexa, dyra och behöver utvecklas samt effektiviseras för en möjlig uppskalning. / SÖRAB's recycling plant in Hagby handles various types of waste such as textiles, garden, electrical and hazardous waste. Water from the surfaces is collected, tested and purified in the plant's water treatment plant. When sampling the process water at the plant, poly- and perfluorinated alkyl substances (PFAS) have been found. PFAS is a collective name for the majority of synthetically manufactured chemicals and today there are more than 3000 different PFAS substances in the world market. PFAS has been used for many years in for example fire extinguishing foam, impregnating agents and in the manufacture of Teflon. The substances have been manufactured since the 1950s but the environmental impact of PFAS was first noticed in the 2000s. The purpose of the project result is to prevent or reduce the risk of further emissions of PFAS from the source of pollution/ pollutions. The aim was to investigate and map out the areas/ activities that give or have given rise to PFAS in the process water and to make proposals for how the source of pollution can be treated or to propose methods for the purification of sludge and/ or water. Sampling was carried out at Hagby recycling plant by sampling at seven different test points during three test runs at three-week intervals. All test points for all three sampling test runs contained PFAS. The highest levels of PFAS found in the process water of Hagby recycling plant appear in this study to come from the areas where construction, demolition and electronic waste are sorted and stored. Since the flow of the drainage from these surfaces cannot be measured reliably, it is difficult to know which surface contributes the greatest amount of PFAS to the water purification system. A certain amount of PFAS comes from the embankment for enclosed waste masses, as levels of PFAS from the test point show. Levels of PFAS were constant for all samples. Continued monitoring of the test point is needed to check that the levels of PFAS don not rise, if this is the case, further investigation of the area may be carried out Proposed action is to investigate how effective the treatment plant, including the carbon filter, at Hagby is to remove PFAS from the process water. Questions that need to be answered are how much is emitted to the recipient and whether levels of PFAS/PFOS can meet the guideline values. Another suggestion is also to remove sludge wherever possible and to investigate whether individual sources of PFAS can be identified and eliminated from the surfaces. Methods considered suitable for the purification of PFAS at Hagby recycling plant are activated carbon with an additional pre-filter step with anthracite or sand to prevent fouling of the existing carbon filter at the plant. Suggestion is to contact the plants that are using the combination of pre-filtration with anthracite and carbon filters to obtain information on the experience of the method, PFAS levels that have been successfully treated and costs for the process. Another suitable method is ion exchange technology (IEX). Experiments need to be carried out specifically for the process water at Hagby as no studies on purification of PFAS with water from recycling plants have been found in the literature. Nanofiltration and reverse osmosis have high efficiency in separating PFAS. The disadvantage is that the filtration is not selective and that the membranes run risk of fouling when treating the process water at Hagby recycling plant due to several different substances in the water. Several methods for treating PFAS are promising, e.g. electrochemical oxidation, biological treatment with silica algae, plasma treatment, ozone treatment but the methods are complex, expensive and need to be developed and made more efficient for a possible application in full scale.

Wildlife management and conservation frequently rely on understanding mechanisms that influence distribution and abundance of animals. I quantified space use for a population of inland riverine adult male alligators in Mississippi. Results indicated habitat selection is a scale-dependent process and aquatic vegetation, water depth, and water temperature may be important factors influencing alligator foraging and thermoregulation. Apparent habitat suitability and low alligator density did not manifest in an observed body size-based dominance hierarchy. I also analyzed long-term Mississippi alligator spotlight survey data for trends and effects of environmental covariates on counts. Model results indicated alligator counts have increased over time. This response likely reflects benefits accrued from decades of protection and wetland conservation. Distance sampling does not appear to be a feasible monitoring technique for riverine alligator populations. Nevertheless, it is important that survey protocols and monitoring programs account for imperfect detection and model important covariates.

Stochastic bandit algorithms are increasingly being used in the domain of recommender systems, when the environment is very dynamic and the items to recommend are frequently changing over time. While traditional approaches consider a single bandit instance which assumes all users to be equal, recent developments in the literature showed that the quality of recommendations can be improved when individual bandit instances for different users are considered and clustering techniques are used. In this work we develop an algorithm which clusters users based on the context at disposal using a Bayesian framework called Thompson Sampling, opposed to a similar algorithm called CAB recently presented at ICML 2017 (International Conference on Machine Learning), which uses a deterministic strategy. We show extensively through experiments on synthetic and real world data that the perfor- mance of our algorithm is in line with its deterministic version CAB when it comes to the quality of recommendations. On the other hand, our approach is relatively faster when considering running time. / Stokastiska bandit-algoritmer används allt mer för rekommenderande system där omgivningen är väldigt dynamisk och de rekommenderade föremålen ständigt byts ut. Medan traditionella tillvägagångssätt använder en enkel bandit-instans som antar alla användare att vara likadana, har litteraturen under senare tid visat att kvaliteten av rekommendationerna kan förhöjas med användarspecifika bandit-instanser och med hjälp av klustringsalgoritmer. I detta projekt har en algoritm utvecklats som klustrar användare baserat på kontexten för disposition genom att använda ett Bayesianskt ramverk som kallas Thompson-sampling, till skillnad från den liknande algoritmen CAD som nyligen presenterades vid ICML 2017 (International Conference on Machine Learning), som använder en deterministisk strategi. Projektet visar med stor omfattning, med hjälp av experiment som använt både syntetiska och reella data, att den framtagna algoritmens genererade rekommendationer håller likvärdig kvalitet som den deterministiska varianten av CAB. Däremot ger vårt presenterade tillvägagångssätt högre prestanda avseende tidsåtgång.

One area of forest biometrics that continues to progress is the development of statistical models as tools to describe tree taper. Taper models allow for the prediction of multiple tree level attributes including: diameter at any height, total tree stem volume, merchantable volume and height to any upper stem diameter from any lower stem height, individual log volumes, and subsequently total tree value. In this work, we generalize segmented regression taper models to include multiple segments and compare it to the traditional 3-Segment (2-Knot) models commonly observed in the forestry literature. We then focus on predicting a future realization of diameter given previously observed data. This is accomplished by comparing a segmented taper model under both the Generalized Algebraic Difference Approach (GADA) and Nonlinear Mixed Effects Models (NLMM) methodologies. Both the GADA and NLMM allow for predictions at the individual tree level of a future realization diameter given a differing number of observed height-diameter pairs. Finally, we explore the prediction and cost/benefit of total tree volume obtained from an integrated taper equation with the incorporation of tree specific random effects given differing observed height-diameter pairs.

Real-time path generation, including collision checks, is vital in critical driving scenarios such as navigating non-signalized intersections. These intersections lack organized traffic flow, which raises the risk of accidents. Rapidly Exploring Random Trees (RRT) is a widely adopted algorithm in robotics for motion planning due to its simplicity and probabilistic completeness. Over the years, researchers have made modifications to the basic RRT algorithm to improve its performance in dynamic environments, making it a favored planning algorithm for autonomous driving. Among these variants, probabilistic RRT (pRRT) demonstrates promising capabilities for efficient online replanning. The first part of the thesis thoroughly studies the pRRT algorithm and compares its performance to the standard RRT and RRT* algorithms through Python simulations. The pRRT algorithm outperformed the RRT and RRT* algorithms in terms of success rate and time to find a safe trajectory. The algorithm was implemented experimentally on scaled cars for the validation of its feasibility. The experimental results show good sim-to-real transfer for this algorithm. The second part of the thesis proposes a novel algorithm for path planning. The algorithm outperforms the standard RRT and pRRT techniques in terms of optimality and conformance to human instincts. The generated paths are much smoother and easier for the controller to track. The AV implementation combines the probabilistic RRT with the RRT-Connect algorithm to mitigate the problem of parameter tuning of the standard pRRT algorithm. The idea is to generate intermediate critical points around the obstacles to grow multiple trees between these points, which are then eventually connected if a safe trajectory is found. The algorithm was tested in simulation and showed comparatively better performance in handling obstacles. / Master of Science / Due to uncontrolled traffic flow, non-signalized intersections are critical for autonomous driving. Motion planning is responsible for the vehicle's decision-making and generating actions based on its surroundings. Rapidly Exploring Random Trees (RRT) is one of the most widely used algorithms for motion planning in robotics due to its simplicity and a guarantee of finding a collision-free path if it exists. Due to the randomness of the algorithm, the time to find a collision-free path increases rapidly as the surrounding environment complicates. In this thesis, we thoroughly study a modified version of RRT called the probabilistic RRT (pRRT) for motion planning of autonomous vehicles. The pRRT algorithm reduces the randomness of the standard RRT algorithm and takes into account the destination location and the positions of the obstacles to find a path around the obstacles and toward the destination point. The algorithm was experimentally validated and confirmed the simplistic transfer from simulations to reality. In the second part of the thesis, we propose a novel algorithm that combines the properties of pRRT and another well-known algorithm called RRT-Connect. This algorithm plans collision-free paths from the start, and the goal points towards free space around the obstacles simultaneously and then combines these fragmented paths. This reduces the overall planning time and was found to be better at providing smooth paths.

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