Statistical analysis and meta-analysis of microarray data

The microarray technology provides a high-throughput technique to study gene expression. Microarrays can help us diagnose different types of cancers, understand biological processes, assess host responses to drugs and pathogens, find markers for specific diseases, and much more. Microarray experiments generate large amounts of data. Thus, effective data processing and analysis are critical for making reliable inferences from the data. ^ The first part of dissertation addresses the problem of finding an optimal set of genes (biomarkers) to classify a set of samples as diseased or normal. Three statistical gene selection methods (GS, GS-NR, and GS-PCA) were developed to identify a set of genes that best differentiate between samples. A comparative study on different classification tools was performed and the best combinations of gene selection and classifiers for multi-class cancer classification were identified. For most of the benchmarking cancer data sets, the gene selection method proposed in this dissertation, GS, outperformed other gene selection methods. The classifiers based on Random Forests, neural network ensembles, and K-nearest neighbor (KNN) showed consistently god performance. A striking commonality among these classifiers is that they all use a committee-based approach, suggesting that ensemble classification methods are superior. ^ The same biological problem may be studied at different research labs and/or performed using different lab protocols or samples. In such situations, it is important to combine results from these efforts. The second part of the dissertation addresses the problem of pooling the results from different independent experiments to obtain improved results. Four statistical pooling techniques (Fisher inverse chi-square method, Logit method. Stouffer's Z transform method, and Liptak-Stouffer weighted Z-method) were investigated in this dissertation. These pooling techniques were applied to the problem of identifying cell cycle-regulated genes in two different yeast species. As a result, improved sets of cell cycle-regulated genes were identified. The last part of dissertation explores the effectiveness of wavelet data transforms for the task of clustering. Discrete wavelet transforms, with an appropriate choice of wavelet bases, were shown to be effective in producing clusters that were biologically more meaningful. ^

Exploring the integration of data mining and data visualization

Due to the rapid advances in computing and sensing technologies, enormous amounts of data are being generated everyday in various applications. The integration of data mining and data visualization has been widely used to analyze these massive and complex data sets to discover hidden patterns. For both data mining and visualization to be effective, it is important to include the visualization techniques in the mining process and to generate the discovered patterns for a more comprehensive visual view. In this dissertation, four related problems: dimensionality reduction for visualizing high dimensional datasets, visualization-based clustering evaluation, interactive document mining, and multiple clusterings exploration are studied to explore the integration of data mining and data visualization. In particular, we 1) propose an efficient feature selection method (reliefF + mRMR) for preprocessing high dimensional datasets; 2) present DClusterE to integrate cluster validation with user interaction and provide rich visualization tools for users to examine document clustering results from multiple perspectives; 3) design two interactive document summarization systems to involve users efforts and generate customized summaries from 2D sentence layouts; and 4) propose a new framework which organizes the different input clusterings into a hierarchical tree structure and allows for interactive exploration of multiple clustering solutions.

An experimental study of micro-end-milling operations

Cutting tools less than 2mm diameter can be considered as micro-tool. Microtools are used in variety of applications where precision and accuracy are indispensable. In micro-machining operations, a small amount of material is removed and very small cutting forces are created. The small cross sectional area of the micro-tools drastically reduces their strength and makes their useful life short and unpredictable; so cutting parameters should be selected carefully to avoid premature tool breakage. The main objective of this study is to develop new techniques to select the optimal cutting conditions with minimum number of experiments and to evaluate the tool wear in machining operations. Several experimental setups were prepared and used to investigate the characteristics of cutting force and AE signals during the micro-end-milling of different materials including steel, aluminum and graphite electrodes. The proposed optimal cutting condition selection method required fewer experiments than conventional approaches and avoided premature tool breakage. The developed tool wear monitoring technique estimated the used tool life with ±10% accuracy from the machining data collected during the end-milling of non-metal materials.

The relationship between higher education curricular variables and human flight performance in a preliminary flying training program

The ability of the United States Air Force (USAF) to sustain a high level of operational ability and readiness is dependent on the proficiency and expertise of its pilots. Recruitment, education, training, and retention of its pilot force are crucial factors in the USAF's attainment of its operational mission: defense of this nation and its allies. Failure of a student pilot during a training program does not only represent a loss of costly training expenditures to the American public, but often consists of loss of human life, aircraft, and property. This research focused on the Air Force Reserve Officer Training Corps' (AFROTC) selection method for student pilots for the light aircraft training (LATR) program. The LATR program is an intense 16 day flight training program that precedes the Air Force's undergraduate pilot training (UPT) program. The study subjects were 265 AFROTC cadets in the LATR program. A variety of independent variables from each subject's higher education curricular background as well as results of preselection tests, participation in varsity athletics, prior flying experience and gender were evaluated against subsequent performance in LATR. Performance was measured by a quantitative performance score developed by this researcher based on 28 graded training factors as well as overall pass or fail of the LATR program. Study results showed participation in university varsity athletics was very significantly and positively related to performance in the LATR program, followed by prior flying experience and to a very slight degree portions of the Air Force Officers Qualifying Test. Not significantly related to success in the LATR program were independent variables such as grade point average, scholastic aptitude test scores, academic major, gender and the AFROTC selection and ranking system.

The order selection and lot sizing problem in the make-to-order environment

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.

An automated method for the determination of electroreception thresholds in weakly electric fish

Weakly electric fish produce a dual function electric signal that makes them ideal models for the study of sensory computation and signal evolution. This signal, the electric organ discharge (EOD), is used for communication and navigation. In some families of gymnotiform electric fish, the EOD is a dynamic signal that increases in amplitude during social interactions. Amplitude increase could facilitate communication by increasing the likelihood of being sensed by others or by impressing prospective mates or rivals. Conversely, by increasing its signal amplitude a fish might increase its sensitivity to objects by lowering its electrolocation detection threshold. To determine how EOD modulations elicited in the social context affect electrolocation, I developed an automated and fast method for measuring electroreception thresholds using a classical conditioning paradigm. This method employs a moving shelter tube, which these fish occupy at rest during the day, paired with an electrical stimulus. A custom built and programmed robotic system presents the electrical stimulus to the fish, slides the shelter tube requiring them to follow, and records video of their movements. I trained the electric fish of the genus Sternopygus was trained to respond to a resistive stimulus on this apparatus in 2 days. The motion detection algorithm correctly identifies the responses 91% of the time, with a false positive rate of only 4%. This system allows for a large number of trials, decreasing the amount of time needed to determine behavioral electroreception thresholds. This novel method enables the evaluation the evolutionary interplay between two conflicting sensory forces, social communication and navigation.

Selection and passage of county land preservation voter referendum: The role of government

County jurisdictions in America are increasingly exercising self-government in the provision of public community services through the context of second order federalism. In states exercising this form of contemporary governance, county governments with "reformed" policy-making structures and professional management practices, have begun to rival or surpass municipalities in the delivery of local services with regional implications such as environmental protection (Benton 2002, 2003; Marando and Reeves, 1993). ^ The voter referendum, a form of direct democracy, is an important component of county land preservation and environmental protection governmental policies. The recent growth and success of land preservation voter referendums nationwide reflects an increase in citizen participation in government and their desire to protect vacant land and its natural environment from threats of over-development, urbanization and sprawl, loss of open space and farmland, deterioration of ecosystems, and inadequate park and recreational amenities. ^ The study's design employs a sequential, mixed method. First, a quantitative approach employs the Heckman two-step model. It is fitted with variables for the non-random sample of 227 voter referendum counties and all non-voter referendum counties in the U.S. from 1988 to 2009. Second, the qualitative data collected from the in-depth investigation of three South Florida county case studies with twelve public administrator interviews is transformed for integration with the quantitative findings. The purpose of the qualitative method is to complement, explain and enrich the statistical analysis of county demographic, socio-economic, terrain, regional, governance and government, political preference, environmentalism, and referendum-specific factors. ^ The research finds that government factors are significant in terms of the success of land preservation voter referendums; more specifically, the presence of self-government authority (home rule charter), a reformed structure (county administrator/manager or elected executive), and environmental interest groups. In addition, this study concludes that successful counties are often located coastal, exhibit population and housing growth, and have older and more educated citizens who vote democratic in presidential elections. The analysis of case study documents and public administrator interviews finds that pragmatic considerations of timing, local politics and networking of regional stakeholders are also important features of success. Further research is suggested utilizing additional public participation, local government and public administration factors.^

Liquidity, governance and adverse selection in asset pricing

A plethora of recent literature on asset pricing provides plenty of empirical evidence on the importance of liquidity, governance and adverse selection of equity on pricing of assets together with more traditional factors such as market beta and the Fama-French factors. However, literature has usually stressed that these factors are priced individually. In this dissertation we argue that these factors may be related to each other, hence not only individual but also joint tests of their significance is called for. ^ In the three related essays, we examine the liquidity premium in the context of the finer three-digit SIC industry classification, joint importance of liquidity and governance factors as well as governance and adverse selection. Recent studies by Core, Guay and Rusticus (2006) and Ben-Rephael, Kadan and Wohl (2010) find that governance and liquidity premiums are dwindling in the last few years. One reason could be that liquidity is very unevenly distributed across industries. This could affect the interpretation of prior liquidity studies. Thus, in the first chapter we analyze the relation of industry clustering and liquidity risk following a finer industry classification suggested by Johnson, Moorman and Sorescu (2009). In the second chapter, we examine the dwindling influence of the governance factor if taken simultaneously with liquidity. We argue that this happens since governance characteristics are potentially a proxy for information asymmetry that may be better captured by market liquidity of a company's shares. Hence, we jointly examine both the factors, namely, governance and liquidity - in a series of standard asset pricing tests. Our results reconfirm the importance of governance and liquidity in explaining stock returns thus independently corroborating the findings of Amihud (2002) and Gompers, Ishii and Metrick (2003). Moreover, governance is not subsumed by liquidity. Lastly, we analyze the relation of governance and adverse selection, and again corroborate previous findings of a priced governance factor. Furthermore, we ascertain the importance of microstructure measures in asset pricing by employing Huang and Stoll's (1997) method to extract an adverse selection variable and finding evidence for its explanatory power in four-factor regressions.^

The use of quantitative polymerase chain reaction amplification method to determine sex ratio of human spermatozoa in semen and to determine maternal contamination of amniotic fluid samples

We have modified a technique which uses a single pair of primer sets directed against homologous but distinct genes on the X and Y chromosomes, all of which are coamplified in the same reaction tube with trace amounts of radioactivity. The resulting bands are equal in length, yet distinguishable by restriction enzyme sites generating two independent bands, a 364 bp X-specific band and a 280 bp Y-specific band. A standard curve was generated to show the linear relationship between X/Y ratio average vs. %Y or %X chromosomal content. Of the 51 purified amniocyte DNA samples analyzed, 16 samples showed evidence of high % X contamination while 2 samples demonstrated higher % Y than the expected 50% X and 50% Y chromosomal content. With regards to the 25 processed sperm samples analyzed, X-sperm enrichment was evident when compared to the primary sex ratio whereas Y-sperm was enriched when we compared before and after selection samples.

Selection and Passage of County Land Preservation Voter Referendum: The Role of Government

County jurisdictions in America are increasingly exercising self-government in the provision of public community services through the context of second order federalism. In states exercising this form of contemporary governance, county governments with “reformed” policy-making structures and professional management practices, have begun to rival or surpass municipalities in the delivery of local services with regional implications such as environmental protection (Benton 2002, 2003; Marando and Reeves, 1993). The voter referendum, a form of direct democracy, is an important component of county land preservation and environmental protection governmental policies. The recent growth and success of land preservation voter referendums nationwide reflects an increase in citizen participation in government and their desire to protect vacant land and its natural environment from threats of over-development, urbanization and sprawl, loss of open space and farmland, deterioration of ecosystems, and inadequate park and recreational amenities. The study’s design employs a sequential, mixed method. First, a quantitative approach employs the Heckman two-step model. It is fitted with variables for the non-random sample of 227 voter referendum counties and all non-voter referendum counties in the U.S. from 1988 to 2009. Second, the qualitative data collected from the in-depth investigation of three South Florida county case studies with twelve public administrator interviews is transformed for integration with the quantitative findings. The purpose of the qualitative method is to complement, explain and enrich the statistical analysis of county demographic, socio-economic, terrain, regional, governance and government, political preference, environmentalism, and referendum-specific factors. The research finds that government factors are significant in terms of the success of land preservation voter referendums; more specifically, the presence of self-government authority (home rule charter), a reformed structure (county administrator/manager or elected executive), and environmental interest groups. In addition, this study concludes that successful counties are often located coastal, exhibit population and housing growth, and have older and more educated citizens who vote democratic in presidential elections. The analysis of case study documents and public administrator interviews finds that pragmatic considerations of timing, local politics and networking of regional stakeholders are also important features of success. Further research is suggested utilizing additional public participation, local government and public administration factors.

Liquidity, Governance and Adverse Selection in Asset Pricing

A plethora of recent literature on asset pricing provides plenty of empirical evidence on the importance of liquidity, governance and adverse selection of equity on pricing of assets together with more traditional factors such as market beta and the Fama-French factors. However, literature has usually stressed that these factors are priced individually. In this dissertation we argue that these factors may be related to each other, hence not only individual but also joint tests of their significance is called for. In the three related essays, we examine the liquidity premium in the context of the finer three-digit SIC industry classification, joint importance of liquidity and governance factors as well as governance and adverse selection. Recent studies by Core, Guay and Rusticus (2006) and Ben-Rephael, Kadan and Wohl (2010) find that governance and liquidity premiums are dwindling in the last few years. One reason could be that liquidity is very unevenly distributed across industries. This could affect the interpretation of prior liquidity studies. Thus, in the first chapter we analyze the relation of industry clustering and liquidity risk following a finer industry classification suggested by Johnson, Moorman and Sorescu (2009). In the second chapter, we examine the dwindling influence of the governance factor if taken simultaneously with liquidity. We argue that this happens since governance characteristics are potentially a proxy for information asymmetry that may be better captured by market liquidity of a company’s shares. Hence, we jointly examine both the factors, namely, governance and liquidity – in a series of standard asset pricing tests. Our results reconfirm the importance of governance and liquidity in explaining stock returns thus independently corroborating the findings of Amihud (2002) and Gompers, Ishii and Metrick (2003). Moreover, governance is not subsumed by liquidity. Lastly, we analyze the relation of governance and adverse selection, and again corroborate previous findings of a priced governance factor. Furthermore, we ascertain the importance of microstructure measures in asset pricing by employing Huang and Stoll’s (1997) method to extract an adverse selection variable and finding evidence for its explanatory power in four-factor regressions.

A Multi-Criteria GIS-Based Route Selection Tool for Hazardous Material Transport: Consideration of Environmental Consequence, Traffic Congestions and Costs

Hazardous materials are substances that, if not regulated, can pose a threat to human populations and their environmental health, safety or property when transported in commerce. About 1.5 million tons of hazardous material shipments are transported by truck in the US annually, with a steady increase of approximately 5% per year. The objective of this study was to develop a routing tool for hazardous material transport in order to facilitate reduced environmental impacts and less transportation difficulties, yet would also find paths that were still compelling for the shipping carriers as a matter of trucking cost. The study started with identification of inhalation hazard impact zones and explosion protective areas around the location of hypothetical hazardous material releases, considering different parameters (i.e., chemicals characteristics, release quantities, atmospheric condition, etc.). Results showed that depending on the quantity of release, chemical, and atmospheric stability (a function of wind speed, meteorology, sky cover, time and location of accidents, etc.) the consequence of these incidents can differ. The study was extended by selection of other evaluation criteria for further investigation because health risk as an evaluation criterion would not be the only concern in selection of routes. Transportation difficulties (i.e., road blockage and congestion) were incorporated as important factor due to their indirect impact/cost on the users of transportation networks. Trucking costs were also considered as one of the primary criteria in selection of hazardous material paths; otherwise the suggested routes would have not been convincing for the shipping companies. The last but not least criterion was proximity of public places to the routes. The approach evolved from a simple framework to a complicated and efficient GIS-based tool able to investigate transportation networks of any given study area, and capable of generating best routing options for cargos. The suggested tool uses a multi-criteria-decision-making method, which considers the priorities of the decision makers in choosing the cargo routes. Comparison of the routing options based on each criterion and also the overall suitableness of the path in regards to all the criteria (using a multi-criteria-decision-making method) showed that using similar tools as the one proposed by this study can provide decision makers insights in the area of hazardous material transport. This tool shows the probable consequences of considering each path in a very easily understandable way; in the formats of maps and tables, which makes the tradeoffs of costs and risks considerably simpler, as in some cases slightly compromising on trucking cost may drastically decrease the probable health risk and/or traffic difficulties. This will not only be rewarding to the community by making cities safer places to live, but also can be beneficial to shipping companies by allowing them to advertise as environmental friendly conveyors.