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. ^

Business process quantitative analysis and optimization for service industries

The total time a customer spends in the business process system, called the customer cycle-time, is a major contributor to overall customer satisfaction. Business process analysts and designers are frequently asked to design process solutions with optimal performance. Simulation models have been very popular to quantitatively evaluate the business processes; however, simulation is time-consuming and it also requires extensive modeling experiences to develop simulation models. Moreover, simulation models neither provide recommendations nor yield optimal solutions for business process design. A queueing network model is a good analytical approach toward business process analysis and design, and can provide a useful abstraction of a business process. However, the existing queueing network models were developed based on telephone systems or applied to manufacturing processes in which machine servers dominate the system. In a business process, the servers are usually people. The characteristics of human servers should be taken into account by the queueing model, i.e. specialization and coordination. ^ The research described in this dissertation develops an open queueing network model to do a quick analysis of business processes. Additionally, optimization models are developed to provide optimal business process designs. The queueing network model extends and improves upon existing multi-class open-queueing network models (MOQN) so that the customer flow in the human-server oriented processes can be modeled. The optimization models help business process designers to find the optimal design of a business process with consideration of specialization and coordination. ^ The main findings of the research are, first, parallelization can reduce the cycle-time for those customer classes that require more than one parallel activity; however, the coordination time due to the parallelization overwhelms the savings from parallelization under the high utilization servers since the waiting time significantly increases, thus the cycle-time increases. Third, the level of industrial technology employed by a company and coordination time to mange the tasks have strongest impact on the business process design; as the level of industrial technology employed by the company is high; more division is required to improve the cycle-time; as the coordination time required is high; consolidation is required to improve the cycle-time. ^

The Role of GIS in DRR: Classifying and Improving GIS Capabilities in Small Towns and Rural Areas

Optimizing GIS capability does not always require that the municipality obtain cutting edge professionals and resources. This paper offers a disaster risk reduction (DRR) design methodology for small towns and rural areas that employs a multi-variable classification system, enabling customization for effective DRR. Determining appropriate GIS capacity requires that a community first be evaluated in order to identify its disaster risk reduction/disaster management (DRR/DM) requirements. These requirements are then considered in conjunction with the municipality's resources to establish the desired capability. Qualification levels for major aspects of GIS capability with respect to DRR/DM are provided along with descriptions of each level and suggested procedures for advancement to the next level. It should be noted that a municipality can be classified at a different level with respect to different variables. Needs vary according to the community, thus attainment of a uniform capability level may not be necessary.

Development and evaluation of a geographic information system based method to estimate flooding susceptibility in an area of Broward County, Florida

The objective of this study was to develop a GIS-based multi-class index overlay model to determine areas susceptible to inland flooding during extreme precipitation events in Broward County, Florida. Data layers used in the method include Airborne Laser Terrain Mapper (ALTM) elevation data, excess precipitation depth determined through performing a Soil Conservation Service (SCS) Curve Number (CN) analysis, and the slope of the terrain. The method includes a calibration procedure that uses "weights and scores" criteria obtained from Hurricane Irene (1999) records, a reported 100-year precipitation event, Doppler radar data and documented flooding locations. Results are displayed in maps of Eastern Broward County depicting types of flooding scenarios for a 100-year, 24-hour storm based on the soil saturation conditions. As expected the results of the multi-class index overlay analysis showed that an increase for the potential of inland flooding could be expected when a higher antecedent moisture condition is experienced. The proposed method proves to have some potential as a predictive tool for flooding susceptibility based on a relatively simple approach.

Automated detection of hematological abnormalities through classification of flow cytometric data patterns

Flow Cytometry analyzers have become trusted companions due to their ability to perform fast and accurate analyses of human blood. The aim of these analyses is to determine the possible existence of abnormalities in the blood that have been correlated with serious disease states, such as infectious mononucleosis, leukemia, and various cancers. Though these analyzers provide important feedback, it is always desired to improve the accuracy of the results. This is evidenced by the occurrences of misclassifications reported by some users of these devices. It is advantageous to provide a pattern interpretation framework that is able to provide better classification ability than is currently available. Toward this end, the purpose of this dissertation was to establish a feature extraction and pattern classification framework capable of providing improved accuracy for detecting specific hematological abnormalities in flow cytometric blood data. ^ This involved extracting a unique and powerful set of shift-invariant statistical features from the multi-dimensional flow cytometry data and then using these features as inputs to a pattern classification engine composed of an artificial neural network (ANN). The contribution of this method consisted of developing a descriptor matrix that can be used to reliably assess if a donor’s blood pattern exhibits a clinically abnormal level of variant lymphocytes, which are blood cells that are potentially indicative of disorders such as leukemia and infectious mononucleosis. ^ This study showed that the set of shift-and-rotation-invariant statistical features extracted from the eigensystem of the flow cytometric data pattern performs better than other commonly-used features in this type of disease detection, exhibiting an accuracy of 80.7%, a sensitivity of 72.3%, and a specificity of 89.2%. This performance represents a major improvement for this type of hematological classifier, which has historically been plagued by poor performance, with accuracies as low as 60% in some cases. This research ultimately shows that an improved feature space was developed that can deliver improved performance for the detection of variant lymphocytes in human blood, thus providing significant utility in the realm of suspect flagging algorithms for the detection of blood-related diseases.^

3D navigation with six degrees-of-freedom using a multi-touch display

With the introduction of new input devices, such as multi-touch surface displays, the Nintendo WiiMote, the Microsoft Kinect, and the Leap Motion sensor, among others, the field of Human-Computer Interaction (HCI) finds itself at an important crossroads that requires solving new challenges. Given the amount of three-dimensional (3D) data available today, 3D navigation plays an important role in 3D User Interfaces (3DUI). This dissertation deals with multi-touch, 3D navigation, and how users can explore 3D virtual worlds using a multi-touch, non-stereo, desktop display. ^ The contributions of this dissertation include a feature-extraction algorithm for multi-touch displays (FETOUCH), a multi-touch and gyroscope interaction technique (GyroTouch), a theoretical model for multi-touch interaction using high-level Petri Nets (PeNTa), an algorithm to resolve ambiguities in the multi-touch gesture classification process (Yield), a proposed technique for navigational experiments (FaNS), a proposed gesture (Hold-and-Roll), and an experiment prototype for 3D navigation (3DNav). The verification experiment for 3DNav was conducted with 30 human-subjects of both genders. The experiment used the 3DNav prototype to present a pseudo-universe, where each user was required to find five objects using the multi-touch display and five objects using a game controller (GamePad). For the multi-touch display, 3DNav used a commercial library called GestureWorks in conjunction with Yield to resolve the ambiguity posed by the multiplicity of gestures reported by the initial classification. The experiment compared both devices. The task completion time with multi-touch was slightly shorter, but the difference was not statistically significant. The design of experiment also included an equation that determined the level of video game console expertise of the subjects, which was used to break down users into two groups: casual users and experienced users. The study found that experienced gamers performed significantly faster with the GamePad than casual users. When looking at the groups separately, casual gamers performed significantly better using the multi-touch display, compared to the GamePad. Additional results are found in this dissertation.^

3D Navigation with Six Degrees-of-Freedom using a Multi-Touch Display

With the introduction of new input devices, such as multi-touch surface displays, the Nintendo WiiMote, the Microsoft Kinect, and the Leap Motion sensor, among others, the field of Human-Computer Interaction (HCI) finds itself at an important crossroads that requires solving new challenges. Given the amount of three-dimensional (3D) data available today, 3D navigation plays an important role in 3D User Interfaces (3DUI). This dissertation deals with multi-touch, 3D navigation, and how users can explore 3D virtual worlds using a multi-touch, non-stereo, desktop display. The contributions of this dissertation include a feature-extraction algorithm for multi-touch displays (FETOUCH), a multi-touch and gyroscope interaction technique (GyroTouch), a theoretical model for multi-touch interaction using high-level Petri Nets (PeNTa), an algorithm to resolve ambiguities in the multi-touch gesture classification process (Yield), a proposed technique for navigational experiments (FaNS), a proposed gesture (Hold-and-Roll), and an experiment prototype for 3D navigation (3DNav). The verification experiment for 3DNav was conducted with 30 human-subjects of both genders. The experiment used the 3DNav prototype to present a pseudo-universe, where each user was required to find five objects using the multi-touch display and five objects using a game controller (GamePad). For the multi-touch display, 3DNav used a commercial library called GestureWorks in conjunction with Yield to resolve the ambiguity posed by the multiplicity of gestures reported by the initial classification. The experiment compared both devices. The task completion time with multi-touch was slightly shorter, but the difference was not statistically significant. The design of experiment also included an equation that determined the level of video game console expertise of the subjects, which was used to break down users into two groups: casual users and experienced users. The study found that experienced gamers performed significantly faster with the GamePad than casual users. When looking at the groups separately, casual gamers performed significantly better using the multi-touch display, compared to the GamePad. Additional results are found in this dissertation.