Tabular data is pervasive in the form of spreadsheets and relational databases. Although tables often describe multivariate data without explicit network semantics, it may be advantageous to explore the data modeled as a graph or network for analysis. Even when a given table design conveys some static network semantics, analysts may want to look at multiple networks from different perspectives, at different levels of abstraction, and with different edge semantics. This dissertation is motivated by the observation that a general approach for performing multi-dimensional and multi-level network-based visual analysis on multivariate tabular data is necessary. We present a formal framework based on the relational data model that systematically specifies the construction and transformation of graphs from relational data tables. In the framework, a set of relational operators provide the basis for rich expressive power for network modeling. Powered by this relational algebraic framework, we design and implement a visual analytics system called Ploceus. Ploceus supports flexible construction and transformation of networks through a direct manipulation interface, and integrates dynamic network manipulation with visual exploration for a seamless analytic experience.

<p>Our project presents the research on visualization of statistical contents. Here wewill introduce the concepts of visualization, software quality metrics andproposed visualization technique (line chart). Our aim to study the existingvisualization techniques for visualization of software metrics and then proposedthe visualization approach that is more time efficient and easy to perceive byviewer.In this project, we focus on the practical aspects of visualization of multipleprojects with respect to the versions and metrics. This project also gives animplementation of proposed visualization techniques of software metrics. In thisresearch based work, we have to compare practically the proposed visualizationapproaches. We will discuss the software development life cycle of our proposedvisualization system, and we will also describe the complete softwareimplementation of implemented software.</p>

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Horizontal displays, such as tabletop systems, are emerging as the de facto platform for engaging participants in collaborative tasks. Despite significant efforts in improving the interactivity of information on such systems, very little research has been invested in understanding how groups of people view data visualizations in such environments. Numerous studies introduced different techniques to support viewing visualization for groups of people, such as duplicating or reorienting the visual displays. However, when visualizations compete for pixels on the display, prior solutions do not work effectively. In this thesis, I explore whether orientation on horizontal displays impacts the legibility of simple visualizations such as graphs. I have found that users are best at reading a graph when it is right side up, and takes them 20% less time than when it is read upside down. The main objective of this thesis was to investigate whether the readability and understandability of simple graphs can be improved. I have introduced the Orientation Agnostic Graph (OA-Graph) which is legible regardless of orientation. The OA-Graph uses a radial layout which has several interesting properties such as implicit orientation, points equidistant to center, and flexible rearrangement. OA-Graphs perform better than graphs that are presented upside down. I have converted several popular types of graphs into their OA counterpart for improved legibility on tabletop systems. Guidelines are presented that describe how other visualizations can be converted to being orientation agnostic.

Horizontal displays, such as tabletop systems, are emerging as the de facto platform for engaging participants in collaborative tasks. Despite significant efforts in improving the interactivity of information on such systems, very little research has been invested in understanding how groups of people view data visualizations in such environments. Numerous studies introduced different techniques to support viewing visualization for groups of people, such as duplicating or reorienting the visual displays. However, when visualizations compete for pixels on the display, prior solutions do not work effectively. In this thesis, I explore whether orientation on horizontal displays impacts the legibility of simple visualizations such as graphs. I have found that users are best at reading a graph when it is right side up, and takes them 20% less time than when it is read upside down. The main objective of this thesis was to investigate whether the readability and understandability of simple graphs can be improved. I have introduced the Orientation Agnostic Graph (OA-Graph) which is legible regardless of orientation. The OA-Graph uses a radial layout which has several interesting properties such as implicit orientation, points equidistant to center, and flexible rearrangement. OA-Graphs perform better than graphs that are presented upside down. I have converted several popular types of graphs into their OA counterpart for improved legibility on tabletop systems. Guidelines are presented that describe how other visualizations can be converted to being orientation agnostic.

The application of Statistical Process Control (SPC) to software processes has been a challenging issue for software engineers and researchers. Although SPC is suggested for providing process control and achieving higher process maturity levels, there are very few resources that describe success stories, implementation details, and implemented guidelines for applying SPC to specific metrics. In this thesis the findings of a case study that is performed for investigating the applicability of SPC to software metrics in an emergent CMM Level 3 software organization are presented. As being one of the basic and most sophisticated tools of SPC, control charts are used for the analysis. The difficulties in application of Statistical Process Control to a CMM Level 3 organization are observed by using the existing data of defect density, rework percentage, productivity and review performance metrics and relevant suggestions are provided for dealing with them. Finally the analysis results are summarized and a guideline is prepared for software companies who want to utilize control charts by using their existing metric data.

In this thesis, we introduce a concept of directional quantile envelopes, the intersection of the halfspaces determined by directional quantiles, and show that they allow for explicit probabilistic interpretation, compared to other multivariate quantile concepts. Directional quantile envelopes provide a way to perform multivariate quantile regression: to ``regress contours'' on covariates. We also develop theory and algorithms for an important application of multivariate quantile regression in biometry: bivariate growth charts. We prove that directional quantiles are continuous and derive their closed-form expression for elliptically symmetric distributions. We provide probabilistic interpretations of directional quantile envelopes and establish that directional quantile envelopes are essentially halfspace depth contours. We show that distributions with smooth directional quantile envelopes are uniquely determined by their envelopes. We describe an estimation scheme of directional quantile envelopes and prove its affine equivariance. We establish the consistency of the estimates of directional quantile envelopes and describe their accuracy. The results are applied to estimation of bivariate extreme quantiles. One of the main contributions of this thesis is the construction of bivariate growth charts, an important application of multivariate quantile regression. We discuss the computation of our multivariate quantile regression by developing a fast elimination algorithm. The algorithm constructs the set of active halfspaces to form a directional quantile envelope. Applying this algorithm to a large number of quantile halfspaces, we can construct an arbitrary exact approximation of the direction quantile envelope. In the remainder of the thesis, we exhibit the connection between depth contours and directional regression quantiles (Laine, 2001), stated without proof in Koenker (2005). Our proof uses the duality theory of primal-dual linear programming. Aiming at interpreting halfspace depth contours, we explore their properties for empirical distributions, absolutely continuous distributions and certain general distributions. Finally, we propose a generalized quantile concept, depth quantile, inspired by halfspace depth (Tukey, 1975) and regression depth (Rousseeuw and Hubert, 1999). We study its properties in various data-analytic situations: multivariate and univariate locations, regression with and without intercept. In the end, we show an example that while the quantile regression of Koenker and Bassett (1978) fails, our concept provides sensible answers. / Statistics

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The objective of this research is to explore high-speed analog-to-digital converters (ADCs) using silicon-germanium (SiGe) heterojunction bipolar transistors (HBTs) for wireless digital receiver applications. The stringent requirements of ADCs for the high-performance next-generation wireless digital receiver include (1) low power, (2) low cost, (3) wide input signal bandwidth, (4) high sampling rate, and (5) medium to high resolution. The proposed research achieves the objective by implementing high-performance ADC's key building blocks and integrating these building blocks into a complete sigma-delta analog-to-digital modulator that satisfies the demanding specifications of next-generation wireless digital receiver applications. The scope of this research is divided into two main parts: (1) high-performance key building blocks of the ADC, and (2) high-speed sigma-delta analog-to-digital modulator. The research on ADC's building blocks includes the design of two high-speed track-and-hold amplifiers (THA) and two wide-bandwidth comparators operating at the sampling rate > 10 GS/sec with satisfying resolution. The research on high-speed sigma-delta analog-to-digital modulator includes the design and experimental characterization of a high-speed second-order low-pass sigma-delta modulator, which can operate with a sampling rate up to 20 GS/sec and with a medium resolution. The research is envisioned to demonstrate that the SiGe HBT technology is an ideal platform for the design of high-speed ADCs.