Towards Proactive Context-aware Computing and Systems

A primary goal of context-aware systems is delivering the right information at the right place and right time to users in order to enable them to make effective decisions and improve their quality of life. There are three key requirements for achieving this goal: determining what information is relevant, personalizing it based on the users’ context (location, preferences, behavioral history etc.), and delivering it to them in a timely manner without an explicit request from them. These requirements create a paradigm that we term as “Proactive Context-aware Computing”. Most of the existing context-aware systems fulfill only a subset of these requirements. Many of these systems focus only on personalization of the requested information based on users’ current context. Moreover, they are often designed for specific domains. In addition, most of the existing systems are reactive - the users request for some information and the system delivers it to them. These systems are not proactive i.e. they cannot anticipate users’ intent and behavior and act proactively without an explicit request from them. In order to overcome these limitations, we need to conduct a deeper analysis and enhance our understanding of context-aware systems that are generic, universal, proactive and applicable to a wide variety of domains. To support this dissertation, we explore several directions. Clearly the most significant sources of information about users today are smartphones. A large amount of users’ context can be acquired through them and they can be used as an effective means to deliver information to users. In addition, social media such as Facebook, Flickr and Foursquare provide a rich and powerful platform to mine users’ interests, preferences and behavioral history. We employ the ubiquity of smartphones and the wealth of information available from social media to address the challenge of building proactive context-aware systems. We have implemented and evaluated a few approaches, including some as part of the Rover framework, to achieve the paradigm of Proactive Context-aware Computing. Rover is a context-aware research platform which has been evolving for the last 6 years. Since location is one of the most important context for users, we have developed ‘Locus’, an indoor localization, tracking and navigation system for multi-story buildings. Other important dimensions of users’ context include the activities that they are engaged in. To this end, we have developed ‘SenseMe’, a system that leverages the smartphone and its multiple sensors in order to perform multidimensional context and activity recognition for users. As part of the ‘SenseMe’ project, we also conducted an exploratory study of privacy, trust, risks and other concerns of users with smart phone based personal sensing systems and applications. To determine what information would be relevant to users’ situations, we have developed ‘TellMe’ - a system that employs a new, flexible and scalable approach based on Natural Language Processing techniques to perform bootstrapped discovery and ranking of relevant information in context-aware systems. In order to personalize the relevant information, we have also developed an algorithm and system for mining a broad range of users’ preferences from their social network profiles and activities. For recommending new information to the users based on their past behavior and context history (such as visited locations, activities and time), we have developed a recommender system and approach for performing multi-dimensional collaborative recommendations using tensor factorization. For timely delivery of personalized and relevant information, it is essential to anticipate and predict users’ behavior. To this end, we have developed a unified infrastructure, within the Rover framework, and implemented several novel approaches and algorithms that employ various contextual features and state of the art machine learning techniques for building diverse behavioral models of users. Examples of generated models include classifying users’ semantic places and mobility states, predicting their availability for accepting calls on smartphones and inferring their device charging behavior. Finally, to enable proactivity in context-aware systems, we have also developed a planning framework based on HTN planning. Together, these works provide a major push in the direction of proactive context-aware computing.

CIVIL WAR SETTLEMENTS AND COMBATANTS’ BEHAVIORS: STRATEGY, PERCEPTION, AND REPUTATION

Three projects in my dissertation focus on the termination of internal conflicts based on three critical factors: a combatant’s bargaining strategy, perceptions of relative capabilities, and reputation for toughness. My dissertation aims to provide the relevant theoretical framework to understand war termination beyond the simple two-party bargaining context. The first project focuses on the government’s strategic use of peace agreements. The first project suggests that peace can also be designed strategically to create a better bargain in the near future by changing the current power balance, and thus the timing and nature of peace is not solely a function of overcoming current barriers to successful bargaining. As long as the government has no overwhelming capability to defeat all rebel groups simultaneously, it needs to keep multiple rebel groups as divided as possible. This strategic partial peace helps to deter multiple rebel groups from collaborating in the battlefield and increases the chances of victory against non-signatories. The second project deals with combatants’ perceptions of relative capabilities. While bargaining theories of war suggest that war ends when combatants share a similar perception about their relative capabilities, combatants’ perceptions about relative capabilities are not often homogeneous. While focusing on information problems, this paper examines when a rebel group underestimates the government’s supremacy in relative capabilities and how this heterogeneous perception about the power gap influences negotiated settlements. The third project deals with the tension between different types of reputations in the context of civil wars: 1) a reputation for resolve and 2) a reputation for keeping human rights standards. In the context of civil wars, the use of indiscriminate violence by the government is costly, and as such, it signals the government’s toughness (or resolve) to rebel groups. I argue that the rebels are more likely to accept the government’s offer when the government recently engaged in indiscriminate violence against civilians during the conflict. This effect, however, is conditional on the government’s international human rights reputation; suggesting that rebel groups interpret this violence as a signal particularly when the government does not have a penchant for attacking civilians in general.

A communication partner training program: Assessing conversational behaviors and attitudes towards communication in Persons with Aphasia and their Communication Partners

This study examined the conversational behaviors of eleven dyads consisting of a person with aphasia (PWA) and their familiar communication partner (CP), and investigated changes in behaviors as a result of attending a communication partner-training program CPT). Attitudes about communication were examined and related to conversational behaviors observed pre- and post- training. Results indicated that CPs and PWA used significantly more facilitating behaviors than barrier behaviors, although most dyads experienced some barriers. A comparison of pre-and post-CPT conversations revealed a significant interaction between time and type of behavior, with the increase in the number of facilitators approaching significance. Overall, persons with aphasia and their conversational partners expressed positive attitudes about communication. There were no significant correlations between scores on attitude surveys and behaviors pre or post-training. This study demonstrated that these dyads employed facilitative conversational behaviors even before CPT, and that facilitative behaviors can increase after a one-day training workshop.

AN EMPIRICAL ASSESSMENT OF USER ONLINE SECURITY BEHAVIOR: EVIDENCE FROM A UNIVERSITY

The ever-increasing number and severity of cybersecurity breaches makes it vital to understand the factors that make organizations vulnerable. Since humans are considered the weakest link in the cybersecurity chain of an organization, this study evaluates users’ individual differences (demographic factors, risk-taking preferences, decision-making styles and personality traits) to understand online security behavior. This thesis studies four different yet tightly related online security behaviors that influence organizational cybersecurity: device securement, password generation, proactive awareness and updating. A survey (N=369) of students, faculty and staff in a large mid-Atlantic U.S. public university identifies individual characteristics that relate to online security behavior and characterizes the higher-risk individuals that pose threats to the university’s cybersecurity. Based on these findings and insights from interviews with phishing victims, the study concludes with recommendations to help similat organizations increase end-user cybersecurity compliance and mitigate the risks caused by humans in the organizational cybersecurity chain.