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In my study, I present the mining, collection and analysis of GitHub projects data in an endeavor to understand how the activity and engagement on the different projects has been before and during the Covid-19 pandemic.  Data was collected from 20 repositories via Github API.  I eventually applied some statistical analysis of the data, applied the ANOVA tests measuring the p-values to understand the level of variance pre and during the Covid-19 pandemic.  Open-Source software have been used since long before and my study seeks to explore the magnitude to which Open-Source software participation on different projects has been affected by the different work environments that the users have become accustomed to lately.  Open-Source software has been under study previously by different authors ie on the participation of users etc.  No study has yet been done on the impact a global pandemic has on the engagement on Open-Source platform on different projects, analysing the trends of participation along the project’s life cycle pre and during the covid-19 pandemic.  In these unpredictable, interesting times the study is aimed at highlighting how Open-Source engagement has been behaving by looking at the trends, patterns of engagement, the decrease or increase of activity in certain projects.  From the results I realise trends and patterns in some projects and also interesting insights in the Github OS project lifecycles.  The findings of my study pointed to how participation and engagement on GitHub Open-Source increased During the Pandemic more than During the Pandemic and this is evidenced by 70% of all the 20 repositories I took under investigation. / <p>The presentation was held via Zoom </p>

Detection systems are widely used in industry. Designers, operators and users of these systems need to choose an appropriate design, based on the intended usage and the operating environment. The purpose of this research is to analyze the effect of various system design variables (controllable) and system parameters (uncontrollable) on the performance of detection systems. To optimize system performance one must manage the tradeoff between two errors that can occur. A False Alarm occurs if the detection system falsely indicates a target is present and a False Clear occurs if the detection system falsely fails to indicate a target is present. Given a particular detection system and a pre-specified false clear (or false alarm) rate, there is a minimal false alarm (or false clear) rate that can be achieved. Earlier research has developed methods that address this false alarm, false clear tradeoff problem (FAFCT) by formulating a Neyman-Pearson hypothesis problem, which can be solved as a Knapsack problem. The objective of this research is to develop guidelines that can be of help in designing detection systems. For example, what system design variables must be implemented to achieve a certain false clear standard for a parallel 2-sensor detection system for Salmonella detection? To meet this objective, an experimental design is constructed and an analysis of variance is performed. Computational results are obtained using the FAFCT-methodology and the results are presented and analyzed using ROC (Receiver Operating Characteristic) curves and an analysis of variance. The research shows that sample size (i.e., size of test data set used to estimate the distribution of sensor responses) has very little effect on the FAFCT compared to other factors. The analysis clearly shows that correlation has the most influence on the FAFCT. Negatively correlated sensor responses outperform uncorrelated and positively correlated sensor responses with large margins, especially for strict FC-standards (FC-standard is defined as the maximum allowed False Clear rate). Suggestions for future research are also included. FC-standard is the second most influential design variable followed by grid size. / Master of Science

It is a well-known fact that a power system contains many sources of uncertainties. These uncertainties coming from the loads, the renewables, the model and the measurement, etc, are influencing the steady state and dynamic response of the power system. Facing this problem, traditional methods, such as the Monte Carlo method and the Perturbation method, are either too time consuming or suffering from the strong nonlinearity in the system. To solve these, this Dissertation will mainly focus on developing the polynomial chaos based method to replace the traditional ones. Using it, the uncertainties from the model and the measurement are propagated through the polynomial chaos bases at a set of collocation points. The approximated polynomial chaos coefficients contain the statistical information. The method can greatly accelerate the calculation efficiency while not losing the accuracy, even when the system is highly stressed. In this dissertation, both the forward problem and the inverse problem of uncertainty quantification will be discussed. The forward problems will include the probabilistic power flow problem and statistical power system dynamic simulations. The generalized polynomial chaos method, the adaptive polynomial chaos-ANOVA method and the multi-element polynomial chaos method will be introduced and compared. The case studies show that the proposed methods have great performances in the statistical analysis of the large-scale power systems. The inverse problems will include the state and parameter estimation problem. A novel polynomial-chaos-based Kalman filter will be proposed. The comparison studies with other traditional Kalman filter demonstrate the good performances of the proposed Kalman filter. We further explored the area dynamic parameter estimation problem under the Bayesian inference framework. The polynomial-chaos-expansions are treated as the response surface of the full dynamic solver. Combing with hybrid Markov chain Monte Carlo method, the proposed method yields very high estimation accuracy while greatly reducing the computing time. For both the forward problem and the inverse problems, the polynomial chaos based methods haven shown great advantages over the traditional methods. These computational techniques can improve the efficiency and accuracy in power system planning, guarantee the rationality and reliability in power system operations, and, finally, speed up the power system dynamic security assessment. / PHD / It is a well-known fact that a power system state is inherently stochastic. Sources of stochasticity include load random variations, renewable energy intermittencies, and random outages of generating units, lines, and transformers, to cite a few. These stochasticities translate into uncertainties in the models that are assumed to describe the steady-sate and dynamic behavior of a power system. Now, these models are themselves approximate since they are based on some assumptions that are typically violated in practice. Therefore, it does not come as a surprise if recent research activities in power systems are focusing on how to cope with uncertainties when dealing with power system planning, monitoring and control. This Dissertation is developing polynomial-chaos-based method in quantifying, and managing these uncertainties. Three major topics, including uncertainty quantification, state estimation and parameter estimation are discussed. The developed method can improve the efficiency and accuracy in power system planning, guarantee the rationality and reliability in power system operations in dealing with the uncertainties, and, finally, enhancing the resilience of the power systems.

This study compares three groups of undergraduate college males in heterosexual dating relationships: those who are physically and psychologically abusive (n=39), those who are solely psychologically abusive (n=44), and those who are non-abusive (n=34). These three groups are compared along the following variables: self-reported history of experiencing family of origin violence; self-reported history of witnessing family of origin violence; level of self-reported impulsivity; level of self-reported satisfaction with life; level of self-reported alcohol use; level of self-reported relationship satisfaction; and amount of self-reported anger management skill. An analysis of variance (ANOVA) revealed significant main effects among the three groups of males along several of the variables examined (Wilks' Lambda F = 4.80, df = 10, 220, p <.001). Post hoc tests revealed significant differences among the three groups of males. This study revealed that these three groups differ significantly along their levels of alcohol use (F = 10.16, p <.001), their reported levels of relationship satisfaction (F = 4.23, p <.05), and their levels of anger management skills (F = 14.56, p<.001). This information can be helpful to clinicians and educators who are working with college populations. It would seem that psychoeducation might be useful for some of these men so that they might develop alternatives to violence, and may hopefully decrease the risk factors associated with the perpetration of relationship violence. Intervening early and effectively with these dating relationships can be a substantive step towards preventing the escalation and maintenance of violence in relationships. / Master of Science

Une méthode non intrusive de construction d’un modèle de remplacement de l’écoulement dans une cavité de système d’air secondaire de turboréacteur est recherchée. Le modèle réduit doit pouvoir être intégré dans un modèle de l’ensemble du moteur et couplé à la thermique de la structure pour simuler son comportement thermique sur une mission complète sous aile. Pour cela, il doit prendre un grand nombre de paramètres en entrée, retourner autant de sorties et être utilisable sur des intervalles de variations étendus de ces paramètres. Plusieurs approches sont envisagées et implémentées, puis appliquées à la modélisation d’une cavité sous turbine fictive :— Création de surfaces de réponse des termes de la décomposition ANOVA des flux pariétaux.— Création de surfaces de réponse des flux pariétaux combinée avec une méthode de raffinement adaptative exploitant la trajectoire dans l’espace d’entrée issue du couplage modèle réduit - modèle de structure.— Réduction de dimension des champs d’interface échangés à partir de résultats des itérations du couplage des modèles thermiques de l’écoulement et de la structure, puis création de surfaces de réponse des coordonnées réduites.Cette dernière voie permets d'obtenir des résultats encourageants sur le cas test proposé d'abord dans le cas à conditions limites d'entrée de l'écoulement fixées, puis en incluant des variations de certaines d'entre-elles. / A non intrusive method to create surrogate models describing the flow in jet engines’ secondary air system is desired. The resulting model must be integrated in a thermal model describing the whole engine during a complete mission under the wing. This requires the model to use a high number of input and output parameters and to be valid on a broad domain of variation of its parameters. Several approches are explored in this thesis and applied to a simplified turbine cavity :— Surrogate modeling of terms of the ANOVA decomposition of wall fluxes.— Surrogate modeling of wall fluxes combined with an adaptive refinement method exploiting the trajectory followed by the input parameters during the coupling between the metamodel and the structural model.— Dimensionality reduction of the interface data exchanged during the coupling between flow and structure thermal model and surrogate modeling of the resulting reduced coordinate.This last approach leads to good results on the test case considered in this thesis with fixed inlet boundary conditions and then with variations of some of the inlet parameters.

This work is devoted to study the influence of the composition on mechanical properties of high performance concret based on portland cement. 29 samples of high performance concrete (HPC) warying in composition were prepared. The constituents used for HPC preparation were: cement Aalborg White, silica fume, finelly ground blast furnace slag, finelly ground silica, calcinated bauxite and polycarboxylate based superplasticizer. The mechanical parameters (flexural and compressive strength) of the samples were observed after 7 and 28 days of moist curing. Compressive strength values after 28 days were in the range of 92 to 194 MPa and the flexural strength values were in the range of 7 to 23 MPa (without using of fiber reinforcement). The graphs showing mechanical parameters depending on the mixture composition were constructed and consequently evaluated.

This paper investigates correlation between energy consumption 24 hours ahead and features used for predicting energy consumption. The features originate from three categories: weather, time and previous energy. The correlations are calculated using Pearson correlation and mutual information. This resulted in the highest correlated features being those representing previous energy consumption, followed by temperature and month. Two identical feature sets containing all attributes1 were obtained by ranking the features according to correlation. Three feature sets were created manually. The first set contained seven attributes representing previous energy consumption over the course of seven days prior to the day of prediction. The second set consisted of weather and time attributes. The third set consisted of all attributes from the first and second set. These sets were then compared on different machine learning models. It was found the set containing all attributes and the set containing previous energy attributes yielded the best performance for each machine learning model. 1In this report, the words ”attribute” and ”feature” are used interchangeably. / I denna rapport undersöks korrelation och betydelsen av olika attribut för att förutspå energiförbrukning 24 timmar framåt. Attributen härstammar från tre kategorier: väder, tid och tidigare energiförbrukning. Korrelationerna tas fram genom att utföra Pearson Correlation och Mutual Information. Detta resulterade i att de högst korrelerade attributen var de som representerar tidigare energiförbrukning, följt av temperatur och månad. Två identiska attributmängder erhölls genom att ranka attributen över korrelation. Tre attributmängder skapades manuellt. Den första mängden innehåll sju attribut som representerade tidigare energiförbrukning, en för varje dag, sju dagar innan datumet för prognosen av energiförbrukning. Den andra mängden bestod av väderoch tidsattribut. Den tredje mängden bestod av alla attribut från den första och andra mängden. Dessa mängder jämfördes sedan med hjälp av olika maskininlärningsmodeller. Resultaten visade att mängden med alla attribut och den med tidigare energiförbrukning gav bäst resultat för samtliga modeller.

The purpose of this study was to explore solution strategies that can enhance the achievement of low-performing Grade 12 learners in the following mathematical aspects: finding the general term of a quadratic sequence, factorising third degree polynomials, determining the centre and radius of a circle, and calculating the angle between two lines. A convenience sample of twenty-five low-performing Grade 12 learners from a secondary school in Capricorn District of Limpopo Province participated in the study which adopted a repeated-measures research design. Learners were exposed to multiple solution strategies and data were collected using achievement tests. Findings indicated significant differences in learners‟ average scores due to the solution strategies used. In determining the general term of a quadratic sequence, learners‟ scores were significantly higher when they used formula and the table method than with the method of residues and solving simultaneous equations. Synthetic division made learners to achieve better scores than long division and equating coefficients in factorising third degree polynomials. The use of formulae to find the centre and radius of a circle made learners to have better achievement scores than completing the square. In calculating the angle between two lines learners‟ scores were better using formula and the cosine rule than using theorems. It was concluded that exposing low-performing Grade 12 learners to multiple solution strategies would enhance their achievement in the mathematical aspects explored in the study. Some of the solution strategies that made learners to achieve better results were not in the prescribed mathematics textbooks. The study therefore recommends that mathematics teaching should not be textbook-driven and that low-performing Grade 12 learners should not be regarded as beyond redemption. / Mathematics Education / M.Sc. (Mathematics, Science and Technology Education)

ITC/USA 2015 Conference Proceedings / The Fifty-First Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2015 / Bally's Hotel & Convention Center, Las Vegas, NV / Over the past several years DoD imposed constraints on test deliverables, requiring objective measures of test results, i.e., statistically defensible test and evaluation (SDT&E) methods and results. These constraints force the tester to employ statistical hypotheses, analyses and perhaps modeling to assess test results objectively, i.e., based on statistical metrics, probability of confidence and logical inference to supplement rather than rely solely on expertise, which is too subjective. Experts often disagree on interpretation. Numbers, although interpretable, are less variable than opinion. Logic, statistical inference and belief are the bases of testable, repeatable and refutable hypothesis and analyses. In this paper we apply linear regression modeling and analysis of variance (ANOVA) to time-space position information (TSPI) to determine if a telemetry (TM) antenna control unit (ACU) under test (AUT) tracks statistically, thus as efficiently, in C-band while receiving both C- and S-band signals. Together, regression and ANOVA compose a method known as analysis of covariance (ANCOVA). In this, the second of three papers, we use data from a range test, but make no reference to the systems under test, nor to causes of error. The intent is to present examples of tools and techniques useful for SDT&E methodologies in testing.