More people are striving for increased levels of educational attainment as a result of a global shift towards a more knowledge based economy. Schools and communities have adjusted to this societal change by seeking alignment along the educational pipeline from preschool (P) to graduate school (20), otherwise known as P-20 reform. This reform often develops with the collaboration and guidance of specific P-20 leadership councils that exist at both the local and state levels. The main purpose of this qualitative study was to go beyond the mere descriptions of P-20 councils to examine the policy pathways chosen by P-20 councils, specifically the relationship between policy context, design, and implementation of P-20 reform. Texas and Tennessee were selected as case sites for a cross comparison policy analysis that utilized interviews and document analysis to examine leadership and contextual influences to the reform, with a focus on state and local P-20 councils. An interpretive theoretical framework helped garner the meaning-making of policy leaders throughout the movement’s existence, while Kingdon’s multiple streams model helped organize the episodic nature of policy. Findings showed varied approaches within and between states leading to mixed levels of sustained P-20 councils and leadership. Finally, best practices for P-20 councils are shared as the problems P-20 seeks to address continue to persist and the P-20 movement adapts to a changing local and national context focused on college and career readiness.

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.

This thesis deals with the design and implementation of an optimizer and a transformer of relational queries. Firstly, the thesis describes the theory of the relational query compilers. Secondly, we present the data structures and algorithms used in the implemented tool. Finally, the important implementation details of the developed tool are discussed. Part of the thesis is the selection of used relational algebra operators and design of an appropriate input. Input of the implemented software is a query written in a XML file in the form of relational algebra. Query is optimized and transformed into physical plan which will be executed in the parallelization framework Bobox. Developed compiler outputs physical plan written in the Bobolang language, which serves as an input for the Bobox. Powered by TCPDF (www.tcpdf.org)

Grâce aux progrès réalisés dans le domaine des semi-conducteurs, les plateformes matérielles embarquées sont capables de satisfaire les contraintes de performances d'applications de plus en plus complexes. Cette augmentation conduit à une explosion des coûts de conception, ce qui pousse les concepteurs de ces plateformes à utiliser des outils travaillant à des niveaux d’abstraction plus élevés. Aujourd’hui, les outils de synthèse de haut niveau opèrent sur des descriptions C/C++ pour en générer des accélérateurs matériels spécialisés. Ces outils offrent des gains en productivité significatifs par rapport à la génération précédente, qui opérait sur des descriptions structurelles de l’architecture en VHDL ou Verilog. Ces descriptions algorithmiques doivent être retravaillées pour que les outils puissent générer des circuits performants. Pour faciliter cette tâche, une solution consiste à mettre en œuvre une boite à outils pour des transformations source-à-source orientées synthèse de haut niveau. En particulier, cette thèse s’intéresse aux transformations de boucles, avec pour objectif d’améliorer les performances en exposant des boucles parallèles et en améliorant la localité des accès mémoire. En nous appuyant sur une représentation des boucles dans le modèle polyédrique, nous proposons une approche qui améliore l’applicabilité du pipeline de nids de boucles en vérifiant sa légalité de manière plus précise que les approches existantes. De plus, lorsque la vérification échoue, nous proposons une technique de correction qui insère statiquement des états d’attente pour assurer la légalité du pipeline. Enfin, ce pipeline est mis en œuvre en utilisant une technique de génération de code qui met les nids de boucles à plat. Ces contributions ont été implémentées dans l’infrastructure de compilation source-à-source Gecos, avant d’être appliquées à un ensemble de benchmarks représentatifs des noyaux de calculs cibles de la synthèse de haut niveau. Les résultats montrent un gain en performances significatif, avec un surcoût en surface modéré. / Due to the advances in semiconductor technologies, embedded hardware is capable of satisfying the performance constraints of increasingly complex applications. This leads to a design cost explosion, thus pushing the hardware designers to use tools working with higher levels of abstractions. High-Level Synthesis tools generate custom hardware accelerators out of C/C++ specifications. They offer significant productivity gains compared to the previous generation of tools that worked at the level of hardware description languages, such as VHDL or Verilog. These higher level specifications have to be reworked in order for the High-Level Synthesis tools to generate efficient hardware accelerators. To ease this task, one solution is to provide a source-to-source transformation toolbox targeting High-Level Synthesis. Specifically, this thesis explores loop transformations in order to improve performance by exposing parallel loops and improving the locality of memory accesses. Using polyhedral representation of loop nests, we propose an approach to improve the applicability of nested loop pipelining by verifying its legality in a more precise way than existing approaches. Moreover, we propose a correction mechanism that statically inserts wait states for enforcing the pipeline legality for cases when the verification fails. The resulting pipeline is implemented using a code generation technique that flattens the loop nests. These contributions have been implemented within the GeCoS source-to-source compilation infrastructure, and applied to a set of benchmarks targeted towards High-Level Synthesis. Results show significant performance improvement at the price of a moderate area overhead.

Research in academia and industry continues to identify a decline in enrollment in computer science. One major component of this decline in enrollment is a shortage of female students. The primary reasons for the gender gap presented in the research include lack of computer experience prior to their first year in college, misconceptions about the field, negative cultural stereotypes, lack of female mentors and role models, subtle discriminations in the classroom, and lack of self-confidence (Pollock, McCoy, Carberry, Hundigopal, & You, 2004). Male students are also leaving the field due to misconceptions about the field, negative cultural stereotypes, and a lack of self-confidence. Analysis of first year attrition revealed that one of the major challenges faced by students of both genders is a lack of problem-solving skills (Beaubouef, Lucas & Howatt, 2001; Olsen, 2005; Paxton & Mumey, 2001). The purpose of this study was to investigate whether specific, non-mathematical problem-solving instruction as part of introductory programming courses significantly increased computer programming self-efficacy and achievement of students. The results of this study showed that students in the experimental group had significantly higher achievement than students in the control group. While this shows statistical significance, due to the effect size and disordinal nature of the data between groups, care has to be taken in its interpretation. The study did not show significantly higher programming self-efficacy among the experimental students. There was not enough data collected to statistically analyze the effect of the treatment on self-efficacy and achievement by gender. However, differences in means were observed between the gender groups, with females in the experimental group demonstrating a higher than average degree of self-efficacy when compared with males in the experimental group and both genders in the control group. These results suggest that the treatment from this study may provide a gender-based increase in self-efficacy and future research should focus on exploring this possibility.

The main theme of this dissertation is to develop a distributed computational pipeline for processing next-generation RNA sequencing (RNA-seq) data. RNA-seq experiments generate hundreds of millions of short reads for each DNA/RNA sample. There are many existing bioinformatics tools developed for the analysis and visualization of this data, but very large studies present computational and organizational challenges that are difficult to overcome manually. We designed a comprehensive pipeline for the analysis of RNA sequencing which leverages many existing tools and parallel computing technology to facilitate the analysis of extremely large studies. RNA CoMPASS provides a web-based graphical user interface and distributed computational pipeline including endogenous transcriptome quantification and additionally the investigation of exogenous sequences.

La cristallisation des hydrates pendant la production de pétrole est une source de risques, surtout liés au bouchage des lignes de production dû à l’agglomération des hydrates. Pendant l'extraction de pétrole, l'huile et l'eau circulent dans le pipeline et forment une émulsion instable. La phase eau se combine avec les composants d'hydrocarbures légers et peut former des hydrates. La cristallisation des hydrates a été intensivement étudiée, principalement à faible fraction d’eau. Cependant, lorsque le champ de pétrole devient mature, la fraction d’eau augmente et peut devenir la phase dominante, un système peu étudié concernant à la formation d'hydrates. Plusieurs techniques peuvent être combinées pour éviter ou remédier la formation d'hydrates. Récemment, une nouvelle classe d'additifs a commencé à être étudiée : Inhibiteurs d'Hydrates à Bas Dosage (LDHI), divisés en Inhibiteurs Cinétiques (KHI-LDHI) et anti-agglomérants (AA-LDHI).Ce travail est une étude paramétrique de la formation d'hydrates à partir de l'émulsion, en variant la fraction d’eau, le débit, en absence et en présence d’AA-LDHI. Les expériences ont été réalisées sur la boucle d'écoulement Archimède, qui est en mesure de reproduire les conditions de la mer profonde. L'objectif de cette étude est d'améliorer la compréhension de la formation d'hydrate et de comprendre comment l'additif dispersant évite l'agglomération. Pour ce faire, un modèle comportemental de la cristallisation pour les systèmes sans et avec additif a été développé. Il a également été proposé une technique pour déterminer la phase continue du système et un mécanisme d'action pour l'anti-agglomérant a été suggéré. / Crystallization of hydrates during oil production is a major source of hazards, mainly related to flow lines plugging after hydrate agglomeration. During the petroleum extraction, oil and water circulate in the flow line, forming an unstable emulsion. The water phase in combination with light hydrocarbon components can form hydrates. The crystallization of hydrates has been extensively studied, mainly at low water content systems. However, as the oil field matures, the water fraction increases and can become the dominant phase, a system less known in what concerns hydrate formation. Actually, several techniques can be combined to avoid or remediate hydrate formation. Recently, a new class of additives called Low Dosage Hydrate Inhibitor (LDHI) started to be studied, they are classified as Kinetic Hydrate Inhibitors (KHI-LDHI) and Anti-Agglomerants (AA-LDHI).This work is a parametric study about hydrate formation from emulsion systems ranging from low to high water content, where different flow rates and the anti-agglomerant presence were investigated. The experiments were performed at the Archimède flow loop, which is able to reproduce deep sea conditions. The goal of this study is enhancing the knowledge in hydrate formation and comprehending how the dispersant additive acts to avoid agglomeration. For this matter, it was developed a crystallization topological model for the systems without and with additive. A technique to determine the system continuous phase and a mechanism of the anti-agglomerant action from the chord length measurements were also proposed.

There is a lack of academic research on sales teams, despite team selling becoming more prominent in recent years. Particularly in Inside Sales, there is a lack of clarity as to what are the drivers of optimum team-based selling and their degree of effect on sales performance. We utilize a team-based approach that aims to study the characteristics of Inside Sales teams and their interactions with business leads, using data from a well-reputed leads management software vendor. Based on prior team-based constructs in the literature, we built a framework that posits Quality of Team Composition, Task Utility and Intra-team Coordination leading to different categories of sales performance at various stages of the sales pipeline via their reflective variables. We tested our conceptual model in the following fashion: first, we used text mining on sales results to classify the different stages of the sales pipeline. Following that, we measured the conversion ratio at each stage as appropriate. Next, we discretized each conversion ratio into three levels of performance groups. The outcome variables in the model are different categories of team performance at each stage of the sales pipeline. Subsequently, we used multinomial logistic regression to regress our outcome variables on our team-based predictor variables in the hopes of establishing and validating important drivers for nuanced Inside Sales success. We uncovered new insight regarding team-selling best practices, using pre-identified constructs from the literature which are uniquely suited to teams and also constructs which are aggregated at a team level from an individual level. Our study is especially relevant to the Inside Sales process, as the outcome measures relate to the sales pipeline. Our main finding was that in there is a difference in skills required at different stages of the sales pipeline, in that more customization and experience is needed at the more advanced stages, whereas more repetition of activity is needed at the beginner stages. We also found that smaller team sizes tend to do better in Inside Sales, which was an unsettled research question in team research with plenty of evidence in favor of both smaller and bigger teams. Additionally, even if it was not a primary goal of our study, by virtue of classifying the leads by their final outcomes, we stumbled across an interesting finding, which is that an overwhelming majority of the sales leads tend to stay at one stage in their entire lifecycle. The implications of all our findings are very relevant to both practitioners and researchers of Inside Sales who are interested in team-based sales optimization. More research should be done in the field of Industrial Marketing, building upon what we found to be true for the B2B sector.

Thesis advisor: George M. Barnett / There is currently a shortage of students graduating with STEM (science, technology, engineering, or mathematics) degrees, particularly women and students of color. Approximately half of students who begin a STEM major eventually switch out. Many switchers cite the competitiveness, grading curves, and weed-out culture of introductory STEM classes as reasons for the switch. Variables known to influence resilience include a student's implicit theory of intelligence and achievement goal orientation. Incremental theory (belief that intelligence is malleable) and mastery goals (pursuit of increased competence) are more adaptive in challenging classroom contexts. This dissertation investigates the role that college science grading policies and messages about the importance of effort play in shaping both implicit theories and achievement goal orientation. College students (N = 425) were randomly assigned to read one of three grading scenarios: (1) a "mastery" scenario, which used criterion-referenced grading, permitted tests to be retaken, and included a strong effort message; (2) a "norm" scenario, which used norm-referenced grading (grading on the curve); or (3) an "effort" scenario, which combined a strong effort message with the norm-referenced policies. The dependent variables included implicit theories of intelligence, perceived classroom goal structure, and self-efficacy. A different sample of students (N = 15) were randomly assigned a scenario to read, asked to verbalize their thoughts, and responded to questions in a semi-structured interview. Results showed that students reading the mastery scenario were more likely to endorse an incremental theory of intelligence, perceived greater mastery goal structure, and had higher self-efficacy. The effort message had no effect on self-efficacy, implicit theory, and most of the goal structure measures. The interviews revealed that it was the retake policy in the mastery scenario and the competitive atmosphere in the norm-referenced scenarios that were likely driving the results. Competitive grading policies appear to be incompatible with mastery goals, cooperative learning, and a belief in the efficacy of effort. Implications for college STEM instruction are discussed. / Thesis (PhD) — Boston College, 2015. / Submitted to: Boston College. Lynch School of Education. / Discipline: Teacher Education, Special Education, Curriculum and Instruction.