Thesis (Ph. D.)--University of Missouri-Columbia, 2002. / Typescript. Vita. Includes bibliographical references (leaves 169-178). Also available on the Internet.

Thesis (Ph. D.)--University of California, Berkeley, 2001. / Includes bibliographical references (leaves 214-223).

Thesis (Ed. D.)--Illinois State University, 1987. / Title from title page screen, viewed August 22, 2005. Dissertation Committee: Ronald L. Laymon, Kenneth H. Strand (co-chairs), Robert L. Arnold, Sally B. Pancrazio, William F. Stimeling. Includes bibliographical references (leaves 86-96) and abstract. Also available in print.

Thesis (Ph.D.) in Interdisciplinary--University of Maine, 2009. / Includes vita. Includes bibliographical references (leaves397-307).

Thesis (M.A.)--West Virginia University, 2005. / Title from document title page. Document formatted into pages; contains v, 45 p. Includes abstract. Includes bibliographical references (p. 33-38).

Thesis (Ph. D.)--University of Texas at Austin, 2007. / Vita. Includes bibliographical references.

This thesis aims to explore the paradoxes and unintended consequences of China’s official Legal Popularization Campaign, the so-called pufa yundong (普法运动) , which was not only aimed to popularize the current laws, but tries to combine legal action with political ideology. In doing so, this thesis will analyze and reveal the socio-political background in which the campaign has been pursued and implemented over the last thirty years across China. What I want to explore is whether this campaign is a reaction to the crisis of legitimacy by the Communist government, or is seen as a remedial measure to counter lawlessness typically found in contemporary Chinese society. As a result, the campaign can be viewed in the light of the modern doctrine of the rule of law, upon which the New China as a nation-state could be built. Ironically, both political propaganda and sincere legal efforts are mixed together. In this way, it is not hard to understand that paradoxes have arisen as well as unintended consequences with variable outcomes.

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La communauté de Calcul Haute Performance est constamment confrontée à de nouveaux défis en raison de la demande toujours croissante de la puissance de traitement provenant dapplications scientifiques diverses. Les systèmes parallèles et distribués sont la clé pour accélérer lexécution de ces applications, et atteindre les défis associés car de nombreux processus peuvent être exécutés simultanément. Ces systèmes sont partagés par de nombreux utilisateurs qui soumettent des tâches sur de longues périodes au fil du temps et qui attendent un traitement équitable par lordonnanceur. Le travail effectué dans cette thèse se situe dans ce contexte: analyser et développer des algorithmes équitables et efficaces pour la gestion des ressources informatiques partagés entre plusieurs utilisateurs. Nous analysons les scénarios avec de nombreux soumissions issues de plusieurs utilisateurs. Ces soumissions contiennent un ou plusieurs processus et lensemble des soumissions sont organisées dans des campagnes successives. Dans ce que nous appelons le modèle dordonnancement des campagnes les processus dune campagne ne commencent pas avant que tous les processus de la campagne précédente soient terminés. Chaque utilisateur est intéressé à minimiser la somme des temps dexécution de ses campagnes. Cela est motivé par le comportement de lutilisateur tandis que lexécution dune campagne peut être réglé par les résultats de la campagne précédente. Dans la première partie de ce travail, nous définissons un modèle théorique pour lordonnancement des campagnes sous des hypothèses restrictives et nous montrons que, dans le cas général, il est NP-difficile. Pour le cas mono-utilisateur, nous montrons que lalgorithme dapproximation pour le problème (classique) dordonnancement de processus parallèles fournit également le même rapport dapproximation pour lordonnancement des campagnes. Pour le cas général avec plusieurs utilisateurs, nous établissons un critère déquité inspiré par une situation idéalisée de partage des ressources. Ensuite, nous proposons un algorithme dordonnancement appelé FairCamp qui impose des dates limite pour les campagnes pour assurer léquité entre les utilisateurs entre les campagnes successives. La deuxième partie de ce travail explore un modèle dordonnancement de campagnes plus relâché et réaliste, avec des caractéristiques dynamiques. Pour gérer ce cadre, nous proposons un nouveau algorithme appelé OStrich dont le principe est de maintenir un ordonnancement partagé virtuel dans lequel le même nombre de processeurs est assigné à chaque utilisateur. Les temps dachèvement dans lordonnancement virtuel déterminent lordre dexécution sur le processeurs physiques. Ensuite, les campagnes sont entrelacées de manière équitable. Pour des travaux indépendants séquentiels, nous montrons que OStrich garantit le stretch dune campagne en étant proportionnel à la taille de la campagne et le nombre total dutilisateurs. Le stretch est utilisé pour mesurer le ralentissement par rapport au temps quil prendrait dans un système dédié. Enfin, la troisième partie de ce travail étend les capacités dOStrich pour gérer des tâches parallèles rigides. Cette nouvelle version exécute les campagnes utilisant une approche gourmande et se sert aussi dun mécanisme de redimensionnement basé sur les événements pour mettre à jour lordonnancement virtuel selon le ratio dutilisation du système. / The High Performance Computing community is constantly facing new challenges due to the ever growing demand for processing power from scientific applications that represent diverse areas of human knowledge. Parallel and distributed systems are the key to speed up the execution of these applications as many jobs can be executed concurrently. These systems are shared by many users who submit their jobs over time and expect a fair treatment by the scheduler. The work done in this thesis lies in this context: to analyze and develop fair and efficient algorithms for managing computing resources shared among multiple users. We analyze scenarios with many submissions issued from multiple users over time. These submissions contain several jobs and the set of submissions are organized in successive campaigns. In what we define as the Campaign Scheduling model, the jobs of a campaign do not start until all the jobs from the previous campaign are completed. Each user is interested in minimizing the flow times of their own campaigns. This is motivated by the user submission behavior whereas the execution of a new campaign can be tuned by the results of the previous campaign. In the first part of this work, we define a theoretical model for Campaign Scheduling under restrictive assumptions and we show that, in the general case, it is NP-hard. For the single-user case, we show that an approximation scheduling algorithm for the (classic) parallel job scheduling problem also delivers the same approximation ratio for the Campaign Scheduling problem. For the general case with multiple users, we establish a fairness criteria inspired by time sharing. Then, we propose a scheduling algorithm called FairCamp which uses campaign deadlines to achieve fairness among users between consecutive campaigns. The second part of this work explores a more relaxed and realistic Campaign Scheduling model, provided with dynamic features. To handle this setting, we propose a new algorithm called OStrich whose principle is to maintain a virtual time-sharing schedule in which the same amount of processors is assigned to each user. The completion times in the virtual schedule determine the execution order on the physical processors. Then, the campaigns are interleaved in a fair way. For independent sequential jobs, we show that OStrich guarantees the stretch of a campaign to be proportional to campaigns size and to the total number of users. The stretch is used for measuring by what factor a workload is slowed down relatively to the time it takes to be executed on an unloaded system. Finally, the third part of this work extends the capabilities of OStrich to handle parallel jobs. This new version executes campaigns using a greedy approach and uses an event-based resizing mechanism to shape the virtual time-sharing schedule according to the system utilization ratio.

Only 25 women are currently serving in the United States Senate and there have only been 56 women to ever hold these positions in the history of the United States. The purpose of this research is to compare the identities and finances of campaigns in the 2016 Senatorial race, with respect to gender, to better understand possible reasons for the gender gap in this political institution. The data used in this study was primarily gathered from the Federal Election Commission. The information of the candidates includes party affiliation, types of candidates (incumbent, challenger, or open-seat), and financial contributions to the campaigns. The financial data examined was from the contributions of prominent Political Action Committees, donations from individuals, and party organizations. Concluding the research, results of the winning candidates were compiled with data from Ballotopedia to examine the successful campaigns. The results, in comparing men and women candidates, showed 17.7% of candidates were women and 82.3% were men. There was not a variation on the type of seat the candidates were competing for, whether an open-seat race or challenging race, besides a 6% difference in incumbent candidates between men and women, which could be explained by the lack of women currently serving. Gender did, however, have an effect on party affiliation with a majority of women identifying with the Democratic Party and the majority of men with the Republican Party. The ways in which men and women fund their campaigns differ, as well. The data shows that, unlike men, women derive most campaign funds from individual donors and rely on smaller contributions than do men. The Democratic Senatorial Campaign Committee used the majority of their funds opposing Republican male candidates, a minority opposing Republican female candidates, and even spent some funds in support of Democratic women candidates. The National Republican Senate Committee directed their funds to oppose Democratic women the most and some funds to oppose Democratic men. Political Action Committees that are considered “women’s PACs,” such as Emily’s List, had a significant role in funding campaigns for women, with liberally ideological committees being more effective than their conservative counterparts. The winning candidates included 82.4% men and 17.6% women. A majority of women, with 83.33%, were Democrats and a majority of men, with 71.4%, were Republican. The ratio of winning candidates who were men to women correlates to the ratio of men and women that entered the race, strengthening previous research preformed by other scholars. This leads to the conclusion that the number of women in the Senate will rise if a higher percentage of women will run for office.