Description: Globally distributed software teams are widespread throughout industry. But finding reliable methods that can properly assess a team's activities is a real challenge. Methods such as surveys and manual coding of activities are too time consuming and are often unreliable. Recent advances in information retrieval and linguistics, however, suggest that automated and/or semi-automated text classification algorithms could be an effective way of finding differences in the communication patterns among individuals and groups. Communication among group members is frequent and generates a significant amount of data. Thus having a web-based tool that can automatically analyze the communication patterns among global software teams could lead to a better understanding of group performance. The goal of this thesis, therefore, is to compare automatic and semi-automatic measures of communication and evaluate their effectiveness in classifying different types of group activities that occur within a global software development project. In order to achieve this goal, we developed a web-based component that can be used to help clean and classify communication activities. The component was then used to compare different automated text classification techniques on various group activities to determine their effectiveness in correctly classifying data from a global software development team project.

Description: The recent growth in sensor technology allows easier information gathering in real-time as sensors have grown smaller, more accurate, and less expensive. The resulting data is often in a geo-stream format continuously changing input with a spatial extent. Researchers developing geo-streaming management systems (GSMS) require a benchmark system for evaluation, which is currently lacking. This thesis presents GSMark, a benchmark for evaluating GSMSs. GSMark provides a data generator that creates a combination of synthetic and real geo-streaming data, a workload simulator to present the data to the GSMS as a data stream, and a set of benchmark queries that evaluate typical GSMS functionality and query performance. In particular, GSMark generates both moving points and evolving spatial regions, two fundamental data types for a broad range of geo-stream applications, and the geo-streaming queries on this data.

Description: Extracting information from a stack of data is a tedious task and the scenario is no different in proteomics. Volumes of research papers are published about study of various proteins in several species, their interactions with other proteins and identification of protein(s) as possible biomarker in causing diseases. It is a challenging task for biologists to keep track of these developments manually by reading through the literatures. Several tools have been developed by computer linguists to assist identification, extraction and hypotheses generation of proteins and protein-protein interactions from biomedical publications and protein databases. However, they are confronted with the challenges of term variation, term ambiguity, access only to abstracts and inconsistencies in time-consuming manual curation of protein and protein-protein interaction repositories. This work attempts to attenuate the challenges by extracting protein-protein interactions in humans and elicit possible interactions using associative rule mining on full text, abstracts and captions from figures available from publicly available biomedical literature databases. Two such databases are used in our study: Directory of Open Access Journals (DOAJ) and PubMed Central (PMC). A corpus is built using articles based on search terms. A dataset of more than 38,000 protein-protein interactions from the Human Protein Reference Database (HPRD) ...

Description: Sense amplifiers are important circuit components of a dynamic random access memory (DRAM), which forms the main memory of digital computers. The ability of the sense amplifier to detect and amplify voltage signals to correctly interpret data in DRAM cells cannot be understated. The sense amplifier plays a significant role in the overall speed of the DRAM. Sense amplifiers require matched transistors for optimal performance. Hence, the effects of mismatch through process variations must be minimized. This thesis presents a research which leads to optimal nanoscale CMOS sense amplifiers by incorporating the effects of process variation early in the design process. The effects of process variation on the performance of a standard voltage sense amplifier, which is used in conventional DRAMs, is studied. Parametric analysis is performed through circuit simulations to investigate which parameters have the most impact on the performance of the sense amplifier. The figures-of-merit (FoMs) used to characterize the circuit are the precharge time, power dissipation, sense delay and sense margin. Statistical analysis is also performed to study the impact of process variations on each FoM. By analyzing the results from the statistical study, a method is presented to select parameter values that minimize the effects of ...

Description: Epidemics have caused major human and monetary losses through the course of human civilization. It is very important that epidemiologists and public health personnel are prepared to handle an impending infectious disease outbreak. the ever-changing demographics, evolving infrastructural resources of geographic regions, emerging and re-emerging diseases, compel the use of simulation to predict disease dynamics. By the means of simulation, public health personnel and epidemiologists can predict the disease dynamics, population groups at risk and their geographic locations beforehand, so that they are prepared to respond in case of an epidemic outbreak. As a consequence of the large numbers of individuals and inter-personal interactions involved in simulating infectious disease spread in a region such as a county, sizeable amounts of data may be produced that have to be analyzed. Methods to visualize this data would be effective in facilitating people from diverse disciplines understand and analyze the simulation. This thesis proposes a framework to simulate and visualize the spread of an infectious disease in a population of a region such as a county. As real-world populations have a non-homogeneous demographic and spatial distribution, this framework models the spread of an infectious disease based on population of and geographic distance between ...