Master of Science / Department of Computing and Information Sciences / Gurdip Singh / Deluge is a protocol used for remote re-programming of nodes in a wireless sensor networks by injecting messages into a network of motes without having the motes directly connected to the PC. It uses the 3-way handshake protocol consisting of 3 types of messages: advertise, request and data. The protocol is very useful but is restricted to homogeneous networks wherein all nodes must be programmed with the same code. This project is an attempt to modify the existing protocol to work for heterogeneous networks where different motes function differently and have to be programmed differently. The project was developed using Java and nesC (a dialect of C) which supports component based programming. The nodes run an operating system called tinyOS which is specifically designed for sensor networks. The system was tested on a network of micaZ and TelosB motes.

Increasingly, workplace information seeking takes place in digital information environments and is reliant upon search systems. Existing systems are designed to retrieve information that is relevant to the query, but are not capable of identifying information that is well-suited to the context and situation of a search. This is a problem for professionals who often are searching for a small amount of useful information that can be applied to a problem or task, and have limited time to browse through large sets of results. This inability of search systems to discriminate between relevant and useful documents is one of the core problems in information retrieval. In this dissertation, I address this problem by studying the role that contextual factors play in determining how a group of professionals searches for and selects information. The central question concerns the nature of the relationships between these contextual factors, specifically between the genres in the document collection and the tasks of the searcher, with an aim to exploit such relationships to improve workplace information retrieval. Research was conducted through multiple studies in three phases, moving from an exploratory study of workplace information behaviour to a controlled experimental user study. Findings confirm that workplace context shapes search behaviour. This relationship is modeled as a set of key contextual factors and sets of context-dependent access constraints, preferred document characteristics, and search strategies. Among the contextual factors identified, work tasks and information tasks were found to be significantly associated with document genres. This task-genre relationship was modeled as a matrix of associations between domain-specific task and genre taxonomies and successfully implemented as a filtering component in a workplace search system. This is the first major study of the relationship between task and genre in information seeking and of its application to information retrieval systems.

Master of Science / Department of Journalism and Mass Communications / Steven Smethers / Although scholars have increasingly recognized the important role of the Internet within the field of mass communications, little research has been done analyzing the behavior of individuals online. The success or failure of a site is often dependent on the number of visitors it receives (often called “traffic”) and this includes newspapers that are attempting to direct larger audiences to their websites. Theoretical arguments have been made for certain factors (region, social media presence, backlinks, etc.) having a positive correlation with traffic, but few, if any, statistical analyses have been done on traffic patterns. This study looks at a sample of approximately 300 high-traffic websites and forms several regression models in order to analyze which factors are most highly correlated with Internet traffic and what the nature of that correlation is.

Increasingly, workplace information seeking takes place in digital information environments and is reliant upon search systems. Existing systems are designed to retrieve information that is relevant to the query, but are not capable of identifying information that is well-suited to the context and situation of a search. This is a problem for professionals who often are searching for a small amount of useful information that can be applied to a problem or task, and have limited time to browse through large sets of results. This inability of search systems to discriminate between relevant and useful documents is one of the core problems in information retrieval. In this dissertation, I address this problem by studying the role that contextual factors play in determining how a group of professionals searches for and selects information. The central question concerns the nature of the relationships between these contextual factors, specifically between the genres in the document collection and the tasks of the searcher, with an aim to exploit such relationships to improve workplace information retrieval. Research was conducted through multiple studies in three phases, moving from an exploratory study of workplace information behaviour to a controlled experimental user study. Findings confirm that workplace context shapes search behaviour. This relationship is modeled as a set of key contextual factors and sets of context-dependent access constraints, preferred document characteristics, and search strategies. Among the contextual factors identified, work tasks and information tasks were found to be significantly associated with document genres. This task-genre relationship was modeled as a matrix of associations between domain-specific task and genre taxonomies and successfully implemented as a filtering component in a workplace search system. This is the first major study of the relationship between task and genre in information seeking and of its application to information retrieval systems.

Master of Science / Department of Computing and Information Sciences / John M. Hatcliff / Developing a wireless sensor network application includes a variety of tasks, such as coding of the implementation, designing the architecture and assessing availability of hardware components, that provide necessary capabilities. Before compiling an application, the developer has to configure the selection of hardware components and set up required parameters. One has to choose from among a variety of configurations regarding communication parameters, such as frequency, channel, subnet identifier, transmission power, etc.. This configuration step also includes setting up parameters for the selection of hardware components, such as a specific hardware platform, which sensor boards and programmer boards to be used or the use of optional services and more. Reasoning about a proper selection of configuration parameters is often very difficult, since there are a lot of dependencies among these parameters which may rule out some other options. The developer has to know about all these constraints in order to pick a valid configuration. Unfortunately, the existing makefile approach that comes with nesC is poorly organized and does not capture important compatibility constraints. The configuration of a particular nesC application is distributed in multiple makefiles. Therefore a developer has to look at multiple files to make sure all necessary parameter are set up correctly for compiling a specific application. Furthermore without analyzing all makefiles it is unclear what the total configurability of a nesC application is and what options and parameters are provided (e.g. is there a parameter for enabling secure communication). In addition to this, the makefile approach tends to be error-prone, since the developer has to type in variable names and values manually, that match the existing implementation. However, the existing configuration system does not capture important compatibility constraints, such as capabilities of selected hardware components. This thesis proposes the use of feature models to configure nesC-based sensor network applications. We provide a tool-supported framework to model valid configurations and a generator that translates this model into a makefile compatible with existing nesC infrastructure. The framework automatically rules out selection of incompatible features using a build-in constraint language. Since all variables are defined in the model, misspellings of variable names are reduced and their domains are clearly defined because most variables come with all its possible options. A developer just needs to choose one or more of them by enabling certain features, where the problem of cardinality is also handled by the model. We show a detailed analysis of nesC's variability domain and how to use feature models to cover the exact behavior of nesC's makefile approach. In a following chapter we simplify our feature model and include the selection of specific hardware components, its capabilities and its dependencies. The feature model and the makefile generator offer a convenient way to configure nesC applications, that is faster, easier to understand and to handle, more transparent and once implemented it gives the possibility to adopt this configuration tool to an existing development environment.

Master of Science / Department of Computing and Information Sciences / Alley Stoughton / Forlan is a computer toolset for experimenting with formal languages. Forlan is implemented as a set of Standard ML (a functional programming language) modules. Forlan presently includes a tool named ‘JFA’ (Java Finite Automata Editor) which is a Java GUI tool for creating and editing ‘Finite Automata’ and a tool named ’JTR’ (Java Trees Graphical Editor) which is used for creating and editing ‘Parse Trees’ or ’Regular Expression Trees’. The JForlan tool is an attempt to unify the ‘JFA’ and the ‘JTR’ tools into one single tool so as to make it more robust, efficient and easy to use. Apart from integrating the tools a lot more functionality like creating and editing ‘Regular Expression Finite Automata’ and ’Program Trees’ (special kinds of Forlan trees which are used to represent Programs in Forlan) has been added to the tool which were not present in the ‘JFA’ and the ‘JTR’ tools. As the ‘Automata’ and the ‘Trees’ are closely related concepts it is highly beneficial to combine the tools into one single tool. The JForlan tool can be invoked either from Forlan or can be run as a standalone Application. Due to the integration of the ‘JFA’ and the ‘JTR’ tools the user can now view the regular expression which was entered as a transition label in the ‘Automata’ mode as a tree structure in the ‘Tree’ mode. Another important feature which is added to the tool is that during the creation of the trees the user need not follow the top down approach only (i.e. creating first the root and then adding children to it) but can create the nodes of the tree in any order the user wishes. An important feature of the tool is that after drawing the necessary automaton or tree the user can save it directly as an ‘image’ or a JForlan project or can select the option of saving it in Forlan syntax, which translates the figures drawn into the Forlan code automatically. The main purpose of developing this tool is to provide a user friendly, easy to use tool which would be ideal for students as educational software which would help them to learn and understand the basic concepts of automata and tree structure.

Master of Science / Department of Computing and Information Sciences / Xinming Ou / Attack graphs present a visual representation of all the potential vulnerabilities and attack paths in a network. They act as a vital security tool in finding the critical attack paths in the enterprise wide networks. Generated attack graphs for complex networks present thousands of attack paths to visualize and represent to the end user. Enhancing the visualization of attack graphs by adding user interactivity will greatly improve in analyzing attack graphs and identifying the critical attack paths in the enterprise network. The layout of the attack graph can be adjusted to represent the layout of the real world enterprise network. Adding user interactivity to attack graphs is done using Prefuse, a software framework written in Java for information visualization. Prefuse is flexible and got the ability to render large amounts of data in an efficient manner. The visualization framework for the attack graphs provides a GUI tool for interacting with attack graph. The framework is a layered architecture with two important layers, the static layer and the dynamic layer. The static layer translates the attack graph trace generated from MuLVAL into a standard graphviz dot language descriptive file. The dynamic layer translates the graphviz dot file into a graph object that can be interpreted and visualized using the prefuse software framework. Preliminary result in this work has been published in [19].

Doctor of Philosophy / Department of Mathematics / Andrew G. Bennett / The goal of this work is to provide instructors with detailed information about their classes at each assignment during the term. The information is both on an individual level and at the aggregate level. We used the large number of grades, which are available online these days, along with data-mining techniques to build our models. This enabled us to profile each student so that we might individualize our approach. From these profiles, we began to investigate what can be done in order to get students to do better, or at least be less frustrated. Regardless, the interactions with our undergraduates will improve as our knowledge about them increases. We start with a categorization of Studio College Algebra students into groups, or clusters, at some point in time during the semester. In our case, we used the grouping just after the first exam, as described by Dr. Rachel Manspeaker in her PhD. dissertation. From this we built a naive Bayesian model which extends these student clusters from one point in the semester, to a classification at every assignment, attendance score, and exam in the course. A hidden Markov model was then constructed with the transition probabilities being derived from the Bayesian model. With this HMM, we were able to compute the most likely path that students take through the various categories over the semester. We observed that a majority of students settle into a group within the first two weeks of the term.

Master of Science / Department of Computing and Information Sciences / Gurdip Singh / Vehicle Highway Automation has been studied for several years but a practical system has not been possible because of technology limitations. New advances in sensing and communication technology have now brought a realistic system within reach. This paper proposes a Co-Operative Vehicle Highway Automation System for automating traffic information gathering and decision making in a vehicle on a highway which is cost effective and near to real life implementation. Co-Operative Vehicle-Highway Automation System is the system which is implemented by technology on-board a vehicle and also on the intelligent infrastructure technology along a highway. Vehicle Automation, Collision Prevention and Avoidance, Route Guidance, Highway Information System, Vehicle tracking, and Traffic surveillance are some applications which can be implemented in the Co-Operative Vehicle-Highway Automation System. Implementing Vehicle Highway Automation System will provide an ameliorated level of road transportation. The possible benefits to society and individuals are many in terms of time, safety, comfort and overall travel quality.

This research explores the annotation and note-taking practices of graduate students and reports on the sets of activities, habits, objects, tools and methods that define the practice. In particular, this empirical study focuses on understanding the integration of annotation practices within larger scholarly processes. This study therefore aims to describe and analyze annotation not only as material externalities of the research process, but also as crucial epistemic practices allowing students to progress from one research activity to the other. Interviews are supplemented by document collection and analyzed using a multi-perspectival framework. The findings describe an annotation lifecycle and suggest a new model of the scholarly process using annotation practices as units of analysis. The study further discusses annotation as a primitive epistemic practice and examines the productive tensions fostering the student’s progress towards her goals. This research finally proposes requirements for future tools supporting scholarly practice.