10 resultados para 230101 Mathematical Logic, Set Theory, Lattices And Combinatorics

em Digital Commons at Florida International University


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This dissertation develops a new mathematical approach that overcomes the effect of a data processing phenomenon known as “histogram binning” inherent to flow cytometry data. A real-time procedure is introduced to prove the effectiveness and fast implementation of such an approach on real-world data. The histogram binning effect is a dilemma posed by two seemingly antagonistic developments: (1) flow cytometry data in its histogram form is extended in its dynamic range to improve its analysis and interpretation, and (2) the inevitable dynamic range extension introduces an unwelcome side effect, the binning effect, which skews the statistics of the data, undermining as a consequence the accuracy of the analysis and the eventual interpretation of the data. ^ Researchers in the field contended with such a dilemma for many years, resorting either to hardware approaches that are rather costly with inherent calibration and noise effects; or have developed software techniques based on filtering the binning effect but without successfully preserving the statistical content of the original data. ^ The mathematical approach introduced in this dissertation is so appealing that a patent application has been filed. The contribution of this dissertation is an incremental scientific innovation based on a mathematical framework that will allow researchers in the field of flow cytometry to improve the interpretation of data knowing that its statistical meaning has been faithfully preserved for its optimized analysis. Furthermore, with the same mathematical foundation, proof of the origin of such an inherent artifact is provided. ^ These results are unique in that new mathematical derivations are established to define and solve the critical problem of the binning effect faced at the experimental assessment level, providing a data platform that preserves its statistical content. ^ In addition, a novel method for accumulating the log-transformed data was developed. This new method uses the properties of the transformation of statistical distributions to accumulate the output histogram in a non-integer and multi-channel fashion. Although the mathematics of this new mapping technique seem intricate, the concise nature of the derivations allow for an implementation procedure that lends itself to a real-time implementation using lookup tables, a task that is also introduced in this dissertation. ^

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This dissertation develops a new mathematical approach that overcomes the effect of a data processing phenomenon known as "histogram binning" inherent to flow cytometry data. A real-time procedure is introduced to prove the effectiveness and fast implementation of such an approach on real-world data. The histogram binning effect is a dilemma posed by two seemingly antagonistic developments: (1) flow cytometry data in its histogram form is extended in its dynamic range to improve its analysis and interpretation, and (2) the inevitable dynamic range extension introduces an unwelcome side effect, the binning effect, which skews the statistics of the data, undermining as a consequence the accuracy of the analysis and the eventual interpretation of the data. Researchers in the field contended with such a dilemma for many years, resorting either to hardware approaches that are rather costly with inherent calibration and noise effects; or have developed software techniques based on filtering the binning effect but without successfully preserving the statistical content of the original data. The mathematical approach introduced in this dissertation is so appealing that a patent application has been filed. The contribution of this dissertation is an incremental scientific innovation based on a mathematical framework that will allow researchers in the field of flow cytometry to improve the interpretation of data knowing that its statistical meaning has been faithfully preserved for its optimized analysis. Furthermore, with the same mathematical foundation, proof of the origin of such an inherent artifact is provided. These results are unique in that new mathematical derivations are established to define and solve the critical problem of the binning effect faced at the experimental assessment level, providing a data platform that preserves its statistical content. In addition, a novel method for accumulating the log-transformed data was developed. This new method uses the properties of the transformation of statistical distributions to accumulate the output histogram in a non-integer and multi-channel fashion. Although the mathematics of this new mapping technique seem intricate, the concise nature of the derivations allow for an implementation procedure that lends itself to a real-time implementation using lookup tables, a task that is also introduced in this dissertation.

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This symposium describes a multi-dimensional strategy to examine fidelity of implementation in an authentic school district context. An existing large-district peer mentoring program provides an example. The presentation will address development of a logic model to articulate a theory of change; collaborative creation of a data set aligned with essential concepts and research questions; identification of independent, dependent, and covariate variables; issues related to use of big data that include conditioning and transformation of data prior to analysis; operationalization of a strategy to capture fidelity of implementation data from all stakeholders; and ways in which fidelity indicators might be used.

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This research is motivated by the need for considering lot sizing while accepting customer orders in a make-to-order (MTO) environment, in which each customer order must be delivered by its due date. Job shop is the typical operation model used in an MTO operation, where the production planner must make three concurrent decisions; they are order selection, lot size, and job schedule. These decisions are usually treated separately in the literature and are mostly led to heuristic solutions. The first phase of the study is focused on a formal definition of the problem. Mathematical programming techniques are applied to modeling this problem in terms of its objective, decision variables, and constraints. A commercial solver, CPLEX is applied to solve the resulting mixed-integer linear programming model with small instances to validate the mathematical formulation. The computational result shows it is not practical for solving problems of industrial size, using a commercial solver. The second phase of this study is focused on development of an effective solution approach to this problem of large scale. The proposed solution approach is an iterative process involving three sequential decision steps of order selection, lot sizing, and lot scheduling. A range of simple sequencing rules are identified for each of the three subproblems. Using computer simulation as the tool, an experiment is designed to evaluate their performance against a set of system parameters. For order selection, the proposed weighted most profit rule performs the best. The shifting bottleneck and the earliest operation finish time both are the best scheduling rules. For lot sizing, the proposed minimum cost increase heuristic, based on the Dixon-Silver method performs the best, when the demand-to-capacity ratio at the bottleneck machine is high. The proposed minimum cost heuristic, based on the Wagner-Whitin algorithm is the best lot-sizing heuristic for shops of a low demand-to-capacity ratio. The proposed heuristic is applied to an industrial case to further evaluate its performance. The result shows it can improve an average of total profit by 16.62%. This research contributes to the production planning research community with a complete mathematical definition of the problem and an effective solution approach to solving the problem of industry scale.

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This qualitative study used grounded theory methods and purposeful sampling to explore perceptions on caring and being cared-for. Twenty-four adolescent male participants, identified as at-risk for school failure, completed a two phase interview process exploring these phenomena within three relationships; the relationship with the friend, with the most caring person they knew and with the teacher they felt cared for them. ^ Each participant was asked a predetermined set of open questions in an initial semi-structured interview. In addition each participant was encouraged to explore his own reflections on caring. A second interview allowed for member checking and for the participant to continue sharing his meaning of caring and being cared-for. ^ Line by line analysis with open, axial and selective coding was applied to interview transcripts along with a constant comparative method. Results indicated that the core category integrating all other categories was attachment bonding. Participants' stories manifested characteristics of proximity seeking, secure base, safe haven and distress upon involuntary separation from an attachment figure. ^ Strategies facilitating attachment bonding were influenced by the power positions of the relational players. Participants responded positively to the one-caring when they felt cared-for. Results further indicated that participants did not need to feel a sense of belonging in order to feel cared-for. Teacher behaviors indicating openness for authentic connections with students were specific to teacher's friendliness and professional competence. Teachers who nurtured feelings of being cared-for were uncommon in the participants' educational experience. ^ The number of adolescent males leaving high school prematurely is both a personal problem and a social problem. Despite a “mask” of indifference often exhibited by adolescent males at-risk for school failure, teachers might consider the social/emotional needs of these students when implementing the curriculum. In addition, policy makers might consider the social/emotional needs of this vulnerable population when developing programs meant to foster psychological well-being and connectedness for adolescent males at-risk for school failure. ^

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In this research, I analyze the effects of candidate nomination rules and campaign financing rules on elite recruitment into the national legislatures of Germany and the United States. This dissertation is both theory-driven and constitutes exploratory research, too. While the effects of electoral rules are frequently studied in political science, the emphasis is thereby on electoral rules that are set post-election. My focus, in contrast, is on electoral rules that have an effect prior to the election. Furthermore, my dissertation is comparative by design.^ The research question is twofold. Do electoral rules have an effect on elite recruitment, and does it matter? To answer these question, I create a large-N original data set, in which I code the behavior and recruitment paths and patterns of members of the American House of Representatives and the German Bundestag. Furthermore, I include interviews with members of the said two national legislatures. Both the statistical analyses and the interviews provide affirmative evidence for my working hypothesis that differences in electoral rules lead to a different type of elite recruitment. To that end, I use the active-politician concept, through which I dichotomously distinguish the economic behavior of politicians.^ Thanks to the exploratory nature of my research, I also discover the phenomenon of differential valence of local and state political office for entrance into national office in comparative perspective. By statistically identifying this hitherto unknown paradox, as well as evidencing the effects of electoral rules, I show that besides ideology and culture, institutional rules are key in shaping the ruling elite. The way institutional rules are set up, in particular electoral rules, does not only affect how the electorate will vote and how seats will be distributed, but it will also affect what type of people will end up in elected office.^

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The work motivation construct is central to the theory and practice of many social science disciplines. Yet, due to the novelty of validated measures appropriate for a deep cross-national comparison, studies that contrast different administrative regimes remain scarce. This study represents an initial empirical effort to validate the Public Service Motivation (PSM) instrument proposed by Kim and colleagues (2013) in a previously unstudied context. The two former communist countries analyzed in this dissertation—Belarus and Poland— followed diametrically opposite development strategies: a fully decentralized administrative regime in Poland and a highly centralized regime in Belarus. The employees (n = 677) of public and nonprofit organizations in the border regions of Podlaskie Wojewodstwo (Poland) and Hrodna Voblasc (Belarus) are the subjects of study. Confirmatory factor analysis revealed three dimensions of public service motivation in the two regions: compassion, self-sacrifice, and attraction to public service. The statistical models tested in this dissertation suggest that nonprofit sector employees exhibit higher levels of PSM than their public sector counterparts. Nonprofit sector employees also reveal a similar set of values and work attitudes across the countries. Thus, the study concludes that in terms of PSM, employees of nonprofit organizations constitute a homogenous group that exists atop the administrative regimes. However, the findings propose significant differences between public sector agencies across the two countries. Contrary to expectations, data suggest that organization centralization in Poland is equal to—or for some items even higher than—that of Belarus. We can conclude that the absence of administrative decentralization of service provision in a country does not necessarily undermine decentralized practices within organizations. Further analysis reveals strong correlations between organization centralization and PSM for the Polish sample. Meanwhile, in Belarus, correlations between organization centralization items and PSM are weak and mostly insignificant. The analysis indicates other factors beyond organization centralization that significantly impact PSM in both sectors. PSM of the employees in the studied region is highly correlated with their participation in religious practices, political parties, or labor unions as well as location of their organization in a capital and type of social service provided.

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With the rapid growth of the Internet, computer attacks are increasing at a fast pace and can easily cause millions of dollar in damage to an organization. Detecting these attacks is an important issue of computer security. There are many types of attacks and they fall into four main categories, Denial of Service (DoS) attacks, Probe, User to Root (U2R) attacks, and Remote to Local (R2L) attacks. Within these categories, DoS and Probe attacks continuously show up with greater frequency in a short period of time when they attack systems. They are different from the normal traffic data and can be easily separated from normal activities. On the contrary, U2R and R2L attacks are embedded in the data portions of the packets and normally involve only a single connection. It becomes difficult to achieve satisfactory detection accuracy for detecting these two attacks. Therefore, we focus on studying the ambiguity problem between normal activities and U2R/R2L attacks. The goal is to build a detection system that can accurately and quickly detect these two attacks. In this dissertation, we design a two-phase intrusion detection approach. In the first phase, a correlation-based feature selection algorithm is proposed to advance the speed of detection. Features with poor prediction ability for the signatures of attacks and features inter-correlated with one or more other features are considered redundant. Such features are removed and only indispensable information about the original feature space remains. In the second phase, we develop an ensemble intrusion detection system to achieve accurate detection performance. The proposed method includes multiple feature selecting intrusion detectors and a data mining intrusion detector. The former ones consist of a set of detectors, and each of them uses a fuzzy clustering technique and belief theory to solve the ambiguity problem. The latter one applies data mining technique to automatically extract computer users’ normal behavior from training network traffic data. The final decision is a combination of the outputs of feature selecting and data mining detectors. The experimental results indicate that our ensemble approach not only significantly reduces the detection time but also effectively detect U2R and R2L attacks that contain degrees of ambiguous information.

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This thesis consists of a large composition for violoncello and orchestra, together with an analytical paper in which I discuss my compositional techniques and some of their historical antecedents. The composition draws on the genres of imaginary musical theater, the symphonic poem, and the concerto. It was also inspired by the story of Hermes, the messenger god from Greek mythology. While the myth partially informs the compositional structure, the work is ultimately meant to showcase the versatility of the cello, the coloristic range of the orchestra (in some cases emulating the orchestral styles of previous composers), the balance of cello and orchestra together, and the eclectic invocation of many compositional techniques separately and simultaneously. These techniques encompass set theory (the use of unordered pitch collections), polytonality, and serialism. It is composed in a post-romantic style.

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The work motivation construct is central to the theory and practice of many social science disciplines. Yet, due to the novelty of validated measures appropriate for a deep cross-national comparison, studies that contrast different administrative regimes remain scarce. This study represents an initial empirical effort to validate the Public Service Motivation (PSM) instrument proposed by Kim and colleagues (2013) in a previously unstudied context. The two former communist countries analyzed in this dissertation—Belarus and Poland—followed diametrically opposite development strategies: a fully decentralized administrative regime in Poland and a highly centralized regime in Belarus. The employees (n = 677) of public and nonprofit organizations in the border regions of Podlaskie Wojewodstwo (Poland) and Hrodna Voblasc (Belarus) are the subjects of study. ^ Confirmatory factor analysis revealed three dimensions of public service motivation in the two regions: compassion, self-sacrifice, and attraction to public service. The statistical models tested in this dissertation suggest that nonprofit sector employees exhibit higher levels of PSM than their public sector counterparts. Nonprofit sector employees also reveal a similar set of values and work attitudes across the countries. Thus, the study concludes that in terms of PSM, employees of nonprofit organizations constitute a homogenous group that exists atop the administrative regimes. ^ However, the findings propose significant differences between public sector agencies across the two countries. Contrary to expectations, data suggest that organization centralization in Poland is equal to—or for some items even higher than—that of Belarus. We can conclude that the absence of administrative decentralization of service provision in a country does not necessarily undermine decentralized practices within organizations. Further analysis reveals strong correlations between organization centralization and PSM for the Polish sample. Meanwhile, in Belarus, correlations between organization centralization items and PSM are weak and mostly insignificant. ^ The analysis indicates other factors beyond organization centralization that significantly impact PSM in both sectors. PSM of the employees in the studied region is highly correlated with their participation in religious practices, political parties, or labor unions as well as location of their organization in a capital and type of social service provided.^