Query equivalence is a fundamental problem within database theory. The correctness of all forms of logical query rewriting—join minimization, view flattening, rewriting over materialized views, various semantic optimizations that exploit schema dependencies, federated query processing and other forms of data integration—requires proving that the final executed query is equivalent to the original user query. Hence, advances in the theory of query equivalence enable advances in query processing and optimization. In this thesis we address the problem of deciding query equivalence between conjunctive SQL queries containing aggregation operators that may be nested. Our focus is on understanding the interaction between nested aggregation operators and the other parts of the query body, and so we model aggregation functions simply as abstract collection constructors. Hence, the precise language that we study is a conjunctive algebraic language that constructs complex objects from databases of flat relations. Using an encoding of complex objects as flat relations, we reduce the query equivalence problem for this algebraic language to deciding equivalence between relational encodings output by traditional conjunctive queries (not containing aggregation). This encoding-equivalence cleanly unifies and generalizes previous results for deciding equivalence of conjunctive queries evaluated under various processing semantics. As part of our study of aggregation operators that can construct empty sub-collections—so-called “scalar” aggregation—we consider query equivalence for conjunctive queries extended with a left outer join operator, a very practical class of queries for which the general equivalence problem has never before been analyzed. Although we do not completely solve the equivalence problem for queries with outer joins or with scalar aggregation, we do propose useful sufficient conditions that generalize previously known results for restricted classes of queries. Overall, this thesis offers new insight into the fundamental principles governing the behaviour of nested aggregation.

Semantic query optimization is an important issue in many contexts of databases including information integration, view maintenance and data warehousing and can substantially improve performance, especially in today's database systems which contain gigabytes of data. A crucial issue in semantic query optimization is query containment. Several papers have dealt with the problem of conjunctive query containment. In particular, some of the literature admits SQL like query languages with aggregate operations such as sum/count. Moreover, since real SQL requires a richer semantics than set semantics, there has been work on bag-semantics for SQL, essentially by introducing an interpreted column. One important technique for reasoning about query containment in the context of bag semantics is to translate the queries to alternatives using aggregate functions and assuming set semantics. Furthermore, in SQL, order by is the operator by which the results are sorted based on certain attributes and, clearly, ordering is an important issue in query optimization. As such, there has been work done in support of ordering based on the application of the domain. However, a final step is required in order to introduce a rich semantics in support. In this work, we integrate set and bag semantics to be able to reason about real SQL queries. We demonstrate an ordered bag semantics for SQL using a relational algebra with aggregates. We define a set algebra with various expressions of interest, then define syntax and semantics for bag algebra, and finally extend these definitions to ordered bags. This is done by adding a pair of additional interpreted columns to computed relations in which the first column is used in the standard fashion to capture duplicate tuples in query results, and the second adds an ordering priority to the output. We show that the relational algebra with aggregates can be used to compute these interpreted columns with sufficient flexibility to work as a semantics for standard SQL queries, which are allowed to include order by and duplicate preserving select clauses. The reduction of a workable ordered bag semantics for SQL to the relational algebra with aggregates - as we have developed it - can enable existing query containment theory to be applied in practical query containment.

Query equivalence is a fundamental problem within database theory. The correctness of all forms of logical query rewriting—join minimization, view flattening, rewriting over materialized views, various semantic optimizations that exploit schema dependencies, federated query processing and other forms of data integration—requires proving that the final executed query is equivalent to the original user query. Hence, advances in the theory of query equivalence enable advances in query processing and optimization. In this thesis we address the problem of deciding query equivalence between conjunctive SQL queries containing aggregation operators that may be nested. Our focus is on understanding the interaction between nested aggregation operators and the other parts of the query body, and so we model aggregation functions simply as abstract collection constructors. Hence, the precise language that we study is a conjunctive algebraic language that constructs complex objects from databases of flat relations. Using an encoding of complex objects as flat relations, we reduce the query equivalence problem for this algebraic language to deciding equivalence between relational encodings output by traditional conjunctive queries (not containing aggregation). This encoding-equivalence cleanly unifies and generalizes previous results for deciding equivalence of conjunctive queries evaluated under various processing semantics. As part of our study of aggregation operators that can construct empty sub-collections—so-called “scalar” aggregation—we consider query equivalence for conjunctive queries extended with a left outer join operator, a very practical class of queries for which the general equivalence problem has never before been analyzed. Although we do not completely solve the equivalence problem for queries with outer joins or with scalar aggregation, we do propose useful sufficient conditions that generalize previously known results for restricted classes of queries. Overall, this thesis offers new insight into the fundamental principles governing the behaviour of nested aggregation.

The small-sample size issue is a prevalent problem in Genomics and Proteomics today. Bootstrap, a resampling method which aims at increasing the efficiency of data usage, is considered to be an effort to overcome the problem of limited sample size. This dissertation studies the application of bootstrap to two problems of supervised learning with small sample data: estimation of the misclassification error of Gaussian discriminant analysis, and the bagging ensemble classification method. Estimating the misclassification error of discriminant analysis is a classical problem in pattern recognition and has many important applications in biomedical research. Bootstrap error estimation has been shown empirically to be one of the best estimation methods in terms of root mean squared error. In the first part of this work, we conduct a detailed analytical study of bootstrap error estimation for the Linear Discriminant Analysis (LDA) classification rule under Gaussian populations. We derive the exact formulas of the first and the second moment of the zero bootstrap and the convex bootstrap estimators, as well as their cross moments with the resubstitution estimator and the true error. Based on these results, we obtain the exact formulas of the bias, the variance, and the root mean squared error of the deviation from the true error of these bootstrap estimators. This includes the moments of the popular .632 bootstrap estimator. Moreover, we obtain the optimal weight for unbiased and minimum-RMS convex bootstrap estimators. In the univariate case, all the expressions involve Gaussian distributions, whereas in the multivariate case, the results are written in terms of bivariate doubly non-central F distributions. In the second part of this work, we conduct an extensive empirical investigation of bagging, which is an application of bootstrap to ensemble classification. We investigate the performance of bagging in the classification of small-sample gene-expression data and protein-abundance mass spectrometry data, as well as the accuracy of small-sample error estimation with this ensemble classification rule. We observed that, under t-test and RELIEF filter-based feature selection, bagging generally does a good job of improving the performance of unstable, overtting classifiers, such as CART decision trees and neural networks, but that improvement was not sufficient to beat the performance of single stable, non-overtting classifiers, such as diagonal and plain linear discriminant analysis, or 3-nearest neighbors. Furthermore, the ensemble method did not improve the performance of these stable classifiers significantly. We give an explicit definition of the out-of-bag estimator that is intended to remove estimator bias, by formulating carefully how the error count is normalized, and investigate the performance of error estimation for bagging of common classification rules, including LDA, 3NN, and CART, applied on both synthetic and real patient data, corresponding to the use of common error estimators such as resubstitution, leave-one-out, cross-validation, basic bootstrap, bootstrap 632, bootstrap 632 plus, bolstering, semi-bolstering, in addition to the out-of-bag estimator. The results from the numerical experiments indicated that the performance of the out-of-bag estimator is very similar to that of leave-one-out; in particular, the out-of-bag estimator is slightly pessimistically biased. The performance of the other estimators is consistent with their performance with the corresponding single classifiers, as reported in other studies. The results of this work are expected to provide helpful guidance to practitioners who are interested in applying the bootstrap in supervised learning applications.

Liquid droplet breakup and dynamics is a phenomena of immense practical importance in a wide variety of applications in science and engineering. Albeit, researchers have been studying this problem for over six decades, the fundamental physics governing droplet deformation and fragmentation is still unknown, not to mention the formulation and development of generalized correlations to predict droplet dynamics. The presence of disparate length and time scales, along with the complex unsteady physics, makes this a formidable problem, theoretically, experimentally and computationally. One of the important applications of interest and the motivation for the current research is a liquid fueled propulsion device, such as diesel, gas turbine or rocket engine. Droplet vaporization and ensuing combustion is accelerated if the droplet size is smaller, which makes any process leading to a reduction in drop size of prime importance in the combustion system design. This thesis is an attempt to address several unanswered questions currently confronting the spray community. Unanswered questions include identification and prediction of breakup modes at varying operating conditions, quantitative description of fundamental processes underlying droplet breakup and generalized correlations for child droplet size distributions and drag coefficient associated with the deformation and fragmentation of Newtonian and non-Newtonian fluids. The present work is aimed at answering the above questions by investigating the detailed flowfield and structure dynamics of liquid droplet breakup process and extracting essential physics governing this complex multiphase phenomena. High-fidelity direct numerical simulations are conducted using a volume-of-fluid (VOF) interface capturing methodology. To isolate the hydrodynamic mechanisms dictating droplet breakup phenomena, evaporation and compressibility are neglected, and numerical studies are performed for incompressible fluids at isothermal conditions. For Newtonian fluids, four different mechanisms are identified- oscillatory, bag, multimode and shear breakup modes. Various events during the deformation and fragmentation process are quantitatively identified and correlations are developed to predict the breakup mechanisms and droplet size distributions for a broad range of operating conditions. It was found that for We > 300 and Oh < 0.1 for rho_l/rho_g = 8.29, the child droplet size distributions can be modeled by a log-normal distribution. A correlation to predict the sauter mean diameter, d32, is also developed, given by d32 / D = 8We^-0.72 / Cd. Temporal evolution of momentum balance and droplet structure are also used to calculate the drag coefficient at each time step from first principles. Results show that the drag coefficient first increases to a maximum as the droplet frontal area increases and then decreases at the initiation of breakup. The drag coefficient reaches a steady value at the end of droplet lifetime, corresponding to the momentum retained by the droplet. A correlation to predict the time-mean drag coefficient given by, Cd / Cd,0 = 2We-^0.175, is developed, which indicates that the time averaged drag coefficient decreases with Weber number. The motivation to study non-Newtonian liquid droplet breakup stems from the various advantages gelled propellants offer as compared to traditional liquid or solid propellants in combustion systems, particularly in rocket engines. It was found that the breakup behavior of pseudoplastic, non-Newtonian liquids is drastically different as compared to Newtonian droplets. Several flow features commonly exhibited by non-Newtonian fluids are observed during the breakup process. The breakup initiates with the formation of beads-in-a-string due to the non-Newtonian nature of the fluid under consideration. This is followed by rapid rotation of the droplet with the appearance of helical instability and liquid budges, which forms the sites for primary and satellite droplet shedding. Child droplet size distribution are also examined and it is found that a Gaussian curve universally characterizes the droplets produced during non-Newtonian droplet breakup process. To put all things in perspective, the objectives of the thesis were two folds: (1) elucidate breakup physics for Newtonian and non-Newtonian liquid droplet deformation and breakup, and (2) develop correlations which can be used in an Eulerian-Lagrangian framework to study large-scale engineering problems. It is hoped that this research contributed to droplet breakup and dynamics literature by providing a more thorough and quantitative understanding of the breakup phenomena of liquid droplets and furnished models which can be used in future research endeavors.

Localization is an important problem that must be resolved in order for a robot to make an estimation of its location based on observation and odometry updates. Relying on artificial landmarks such as the lines, circles, and goalposts in the robot soccer domain, current robot localization requires prior knowledge and suffers from uncertainty problems due to partial observation, and thus is less generalizable compared to human beings, who refer to their surroundings for complimentary information. To improve the certainty of the localization model, we propose a framework that recognizes orientation by actively using natural landmarks from the off-field surroundings, extracting these visual features from raw images. Our approach involves identifying visual features and natural landmarks, training with localization information to understand the surroundings, and prediction based on matching of features. This approach can increase the precision of robot orientation and improve localization accuracy by eliminating uncertain hypotheses, and in addition, it is also a general approach that can be extended and applied to other localization problems as well. / text

In the last decades camera systems have continuously evolved and have found wide range of applications. One of the main applications of a modern camera system is surveillance in outdoor areas. The camera system, based on local computations, can detect and classify objects autonomously. However, the distance of the objects from the camera plays a vital role on the classification results. This could be specially challenging when lighting conditions are varying. Therefore, in this thesis, we are examining the effect of changing dis-tances on object in terms of number of pixels. In addition, the effect of distance on classification is studied by preparing four different sets. For consideration of high signal to noise ratio, we are integrating thermal and visual image sensors for the same test in order to achieve better spectral resolution. In this study, four different data sets, thermal, visu-al, binary from visual and binary from thermal have been prepared to train the classifier. The categorized objects include bicycle, human and vehicle. Comparative studies have been performed in order to identify the data sets accuracy. It has been demonstrated that for fixed distances bi-level data sets, obtained from visual images, have better accuracy. By using our setup, the object (human) with a length of 179 and width of 30 has been classified correctly with minor error up to 150 meters for thermal, visual as well as binary from visual. Moreover, for bi-level images from thermal, the human object has been correctly classified as far away as 250 meters.

Recirculating aquaculture systems (RAS) produce aquaculture products on land with minimal discharge of waste products and minimal water loss. High costs associated with waste treatment for RAS have triggered the growth of integrated aquaculture systems (IAS) which incorporate macrophytes (aquatic plants) into the treatment train. The objective of this research was to examine a pilot scale inland marine IAS with three different methods for solids treatment: a sand filter followed by a plant bed, only a plant bed, and geotextile bags. Florida Pompano (Trachinotus carolinus) were grown along with Smooth Cordgrass (Spartina alterniflora), Black Needle Rush (Juncus romerianus), and Red Mangrove (Rhizophora mangle). Between May 2011 and April 2012, water quality was tested at seven points located throughout the IAS for total suspended solids (TSS), chemical oxygen demand (COD), total nitrogen (TN), ammonium (NH4+), nitrate (NO3-), total phosphorus (TP), and orthophosphate (PO43-) concentrations every 4 to 6 weeks. Plant and soil samples were collected three times and analyzed for total nitrogen and total phosphorus. A statistically significant difference in the effluent concentrations for the three treatments was not found; however, due to the recombination of effluent from the solid treatments and the variability inherent in a pilot scale system it was difficult to isolate the individual efficiencies of each treatment. Therefore, on average the complete system achieved COD and TSS removal efficiency of 59% and 88%, respectively and TN and TP removal efficiency of 48% and 19%, respectively. Nutrient uptake by plants did not vary significantly between the plant beds. In general, the system provided sufficient nutrient removal for safe fish production, and the fish provided enough nutrients for ample plant growth.

Darbo objektas – skirtingų treniravimo priemonių poveikis smūgio jėgai. Hipotezė – manome, kad skirtingos treniravimo priemonės duos teigiamą poveikį smūgio jėgai, didžiausią poveikį – atsispaudimai su suplojimu. Darbo tikslas – nustatyti skirtingų treniravimo priemonių poveikį smūgio jėgai. Darbo uždaviniai: 1. Nustatyti vienkartinių smūgių jėgą į bokso maišą dominuojančia ir nedominuojančia ranka. 2. Nustatyti ir palyginti skirtingų jėgos treniravimo priemonių efektyvumą smūgio jėgai. Išvados: 1. Didžiausia smūgio jėga nustatyta kontrolinėje tiriamųjų grupėje, o mažiausia pirmos, antros ir trečios grupės tiriamųjų, kurie tyrimo metu ją lavino kimštiniu kamuoliu, elastine guma ar svarmenų pagalba. 2. Eksperimento metu nustatyta, kad efektyviausiai smūgio jėgą lavino taikytos treniravimo priemonės su kimštiniu kamuoliu ir svarmenimis. Smūgio jėgos lavinimui taikytos treniravimo priemonės su elastine guma ir atsispaudimais nuo grindų su suplojimu nebuvo efektyvios, smūgio jėga per eksperimentinį laikotarpį nepadidėjo. / Object of the work – the influence of different training measures on punch impact. Hypothesis – we think that different training measures will have a positive influence on punch impact, and the biggest influence will be done by the clapping push-ups off the ground. Aim of the work – to determine the influence of different training measures on punch impact. Objectives: 1. To determine the impact of single punches into the boxing bag with dominant and non-dominant hand. 2. To determine and compare the efficiency of different training measures of punch impact. Conclusions: 1. The maximum punch impact during the research was determined in the research group that did not apply any measures, and the minimum punch impact was determined in the group that developed it during the experiment by using stuffed ball, elastic rubber or weights. 2. The experiment revealed that the most effective way to exercise punch impact was the one with the stuffed ball and weights. The training measures with elastic rubber and clapping push-ups off the ground applied to develop punch impact were not effective and unch impact during the experiment did not improve.

Bakalauro darbą sudaro: • Kūrybinė dalis: trys konceptualios ir funkcionalios rankinės-krepšiai jaunimui; • Projektinė dalis: 2 planšetai pristatantys kolekcijos idėją, aiškinamieji brėžiniai; • Teorinis aprašas: pateikiama netradicinius aksesuarus kuriančių dizainerių ir aksesuarų tendencijų analizė bei prieduose - verslo planas susietas su gaminių realizavimu. Pagrindinė kūrybinio darbo idėja – remiantis fiziologinėmis gyvūnų kūnų savybėmis, sukurti netradicinių rankinių-krepšių kolekciją, kuri padėtų suformuoti liberalesnį požiūrį į kasdienius aksesuarus ir praplėsti jų pasirinkimą. Originalaus dizaino, konceptualių idėjų trūkumas jaunimo rankinėse, įkvėpė sukurti netradicines rankines-krepšius laisvalaikiui, turinčius funkciją. Kuriant, prototipais prinkti trys gyvosios gamtos žinduoliai – kengūra, skujuotis ir šikšnosparnis. Jų kūnų funkciniai ypatumai interpretuoti krepšių dizaine: kengūros sterblė – kuprinė priekyje, skujuočio kūną dengiantis šarvas – kuprinės ir gobtuvo sintezė ir šikšnosparnio sparnas – krepšys tvirtinamas prie klubo ir rankos riešo. Kolekcijos pavadinimas „Urbe animalis“ (lot. miesto gyvūnai), atspindi pamatinę kolekcijos idėją – žmonių atsigręžimą į savo ištakas, į gyvają gamtą, o gaminiai skirti sąmoningam, šiuolaikiniam miesto jaunimui. Krepšių spalvinis sprendimas parinktas atsižvelgiant į žmogaus ir faunos aplinkoms būdingas spalvas – žalią, mėlyną ir pilką. / Thesis consists of: • Creative part: three conceptual and functional bags-baskets for youth; • Project part: 2 planchets, which represents idea of collection and explaining schemas; • Theoretical part: presented analysis of designers who are making non-traditional accessories and their tendencies as well enclose business plan related with realization of products. Main idea of creative work – referencing to physiological animal bodies’ characteristics, create non-traditional collection of bags-baskets, which would help to shape more liberal attitude to casual accessories and extend a choise of their. Lack of original design, conceptual ideas in bags for youth, had inspired to create non-traditional bags-baskets for leisure, containing functionality. Three mammalian animals were selected from nature as prototypes – kangaroo, pangolin and bat. Their body singularity and functionality are interpreted in bags design: pouch of kangaroo – bag on a front; shell, covering back of pangolin – synthesis of backpack and hood; wing of a bat – bag, which is attached between hip and wrist. Collection named “Urbe animalis” (lat. city animals), reflects the main idea of collection – human redounding to it’s origins, living nature and designated to conscious, contemporary city’s youth. Solution of colours were chosen considering to inherent human’s and fauna’s surroundings – green, blue and gray.