Multiple-task environments are pervasive in a variety of workplaces; many jobs require several concurrent, time-sensitive tasks be done in one task space. One concern in these multiple-task environments is attention allocation: To perform well, the operator must be able to know when and where to look. Otherwise, he or she will not be aware of the status of each task or be able to complete them. To aid these jobs, automation has been developed to support attention allocation: Auditory and visual alerts draw attention to where the system determines it is needed. However, imperfect automation may complicate the aid by introducing misses and false alarms to which the operator must also attend. Researchers studying these environments and automation's purview within them have focused on a variety of different topics. Some examples include: different types of automation (alerts, decision aid systems, etc.), levels of reliability (0-100% reliable), what automation supports (attention allocation to situation awareness to performance), and how automation affects multiple task environments (two tasks to many). Because attention had not been directly studied in relation to imperfect automation reliability in multiple-task environments, I decided to analyze the effects of different levels of automation reliability on visual attention allocation and how removal of that automation changed those effects. To study this, I helped to develop the Simultaneous Task Environment Platform (STEP), a program to study and test participants' behavior in multiple-task environments. The STEP program enabled me to vary the frequency and criticality (number of points gained/lost) of the different tasks to disambiguate how automation was affecting the participants. In the study, participants were trained on all four tasks of the STEP system, had the automation explained to them, and then were asked to gain as many points a trial as possible. There were three between-subject conditions; a system where ~70% of the automated alerts were reliable, one where ~90% of the alerts were reliable, and one where the participants received no automated aid at all. The automation was designed to support visual attention allocation. The participants interacted with the system and automation for twenty-four trials, divided into six blocks over two days, at which point they transferred to a system with no automation at all. To better understand exactly how the participants interacted with the system, I measured the number of times they accessed each task (attention allocation, as well as a measure of workload) and the number of points they scored (task performance). Mixed ANOVAs for these two measures, as well as a derived measure of efficiency (points scored per window opened), were conducted crossing automation condition with Block (to measure how the participants changed with experience) and task (to measure how certain tasks' attributes affected the way they were acted upon). Overall, the automation provided a benefit in terms of reduced workload and improved task performance. Participants in the automated conditions opened fewer windows and performed better. This also meant higher efficiency for those conditions. Experience affected conditions differentially. Those in the no automation condition increased their score but also the number of windows opened, causing their efficiency to stay the same. The 70% reliable condition was similar, with a minor point increase and no significant window decrease, resulting in no significant efficiency gain. The 90% reliable condition gained little score boost, but opened fewer windows by the end of the experiment, becoming more efficient. The frequency and criticality of tasks affected both the windows opened and the points scored across conditions, as participants in the two automated conditions opened fewer windows and scored relatively more points on those tasks worth many points that did not appear often. This increased their efficiency on those tasks, but also caused them to suffer greater when the automation was taken away. In the transfer trials, those participants in the automated conditions experienced both a workload increase and a performance decrease. These were centered on the two high-criticality/low-frequency tasks, as the other two tasks showed only small or no change between normal and transfer trials. These results show that automation at different levels of reliability affects the behavior of the operator of that system differentially based on the attributes of the tasks the operator must oversee. Tasks that happen often and are only important when aggregated over many are not aided by automation as much as those tasks that happen rarely and are critical every time they appear. When automation fails, however, those same tasks that are aided the most suffer the most, whereas those that do not get much aid do not suffer as much. Designers of automated systems should consider the type of tasks to be automated and their attributes, as well as the effects of increasing or decreasing the reliability of the automation when designing automation to provide support to system operators.

The objective of this thesis is to generate a discrete alphabet of low-level robotic controllers rich enough to mimic the actions of high-level users using the robot for a specific task. This alphabet will be built through the analysis of various user data sets in a modified version of the motion description language, MDLe. It can then be used to mimic the actions of a future user attempting to perform the task by calling scaled versions of the controls in the alphabet, potentially reducing the amount of data required to be transmitted to the robot, with minimal error. In this thesis, theory is developed that will allow the construction of such an alphabet, as well as its use to mimic new actions. A MATLAB algorithm is then built to implement the theory. This is followed by an experiment in which various users drive a Khepera robot through different courses with a joystick. The thesis concludes by presenting results which suggest that a relatively small group of users can generate an alphabet capable of mimicking the actions of other users, while drastically reducing bandwidth.

The vision of personal robot assistants continues to become more realistic with technological advances in robotics. The increase in the capabilities of robots, presents boundless opportunities for them to perform useful tasks for humans. However, it is not feasible for engineers to program robots for all possible uses. Instead, we envision general-purpose robots that can be programmed by their end-users. Learning from Demonstration (LfD), is an approach that allows users to program new capabilities on a robot by demonstrating what is required from the robot. Although LfD has become an established area of Robotics, many challenges remain in making it effective and intuitive for naive users. This thesis contributes to addressing these challenges in several ways. First, the problems that occur in teaching-learning interactions between humans and robots are characterized through human-subject experiments in three different domains. To address these problems, two mechanisms for guiding human teachers in their interactions are developed: embodied queries and teaching heuristics. Embodied queries, inspired from Active Learning queries, are questions asked by the robot so as to steer the teacher towards providing more informative demonstrations. They leverage the robot's embodiment to physically manipulate the environment and to communicate the question. Two technical contributions are made in developing embodied queries. The first is Active Keyframe-based LfD -- a framework for learning human-segmented skills in continuous action spaces and producing four different types of embodied queries to improve learned skills. The second is Intermittently-Active Learning in which a learner makes queries selectively, so as to create balanced interactions with the benefits of fully-active learning. Empirical findings from five experiments with human subjects are presented. These identify interaction-related issues in generating embodied queries, characterize human question asking, and evaluate implementations of Intermittently-Active Learning and Active Keyframe-based LfD on the humanoid robot Simon. The second mechanism, teaching heuristics, is a set of instructions given to human teachers in order to elicit more informative demonstrations from them. Such instructions are devised based on an understanding of what constitutes an optimal teacher for a given learner, with techniques grounded in Algorithmic Teaching. The utility of teaching heuristics is empirically demonstrated through six human-subject experiments, that involve teaching different concepts or tasks to a virtual agent, or teaching skills to Simon. With a diverse set of human subject experiments, this thesis demonstrates the necessity for guiding humans in teaching interactions with robots, and verifies the utility of two proposed mechanisms in improving sample efficiency and final performance, while enhancing the user interaction.

<p>The purpose of this thesis is to explore how support systems enable human control within normal flight operations. The thesis focuses on the use of memory supports during flight, such as a handheld computing device, memory strategies and checklists. The support systems are studied from the theoretical perspective of Human Factors. In particular, decision making theories have contributed to the thesis. From previous research it is found that feedback to the operator in case of a human error is essential to keep him or her in a safe sequence of decisions and actions.</p><p>To facilitate the pilots’ tasks in cockpit, computing devices are out on the market. Several of the technical aids are computers installed in cockpit whereas others are smaller, portable devices with hardware not specifically designed for use in cockpit. Jump-seat observations have been performed at an airline company to explore the pilots’ work process in cockpit where a handheld computing device, with hardware not specifically designed for cockpit, is in use. Subsequent semi-structured interviews were conducted to receive the pilots’ experiences of findings from the observations and to receive descriptions of decisions and support systems.</p><p>The thesis includes a description of flight operations from a pilot perspective. The main focus is on operations in the preflight phase where the new computing device is used. Identified characteristics in flight operations are factors such as cooperation, communication, interruptions. Furthermore, identified factors in the decision making were such as routine, environmental constraints, discrete alternatives and dependency between decisions. Feedback points during the sequence of tasks performed with the handheld computing device were distinguished. These points are moments when feedback is possible. For example, when the pilots cross-check tasks they receive feedback from each other. It was found that the pilots did not use every opportunity to receive feedback on their performance. The reason of the non-used feedback point was that it was not required by the Standard Operating Procedures or by any functions or design of the device. Within flight operations in general, it was found that the most important techniques to detect a human error such as a memory lapse were by pilots’ earlier experiences, the use of checklists and by receiving feedback from the other pilot.</p>

Robot and sensor networks are needed for safety, security, and rescue applicationssuch as port security and reconnaissance during a disaster. These applications rely on realtimetransmission of images, which generally saturate the available wireless networkinfrastructure. Knowledge-based Compression is a strategy for reducing the video frametransmission rate between robots or sensors and remote operators. Because images mayneed to be archived as evidence and/or distributed to multiple applications with differentpost processing needs, lossy compression schemes, such as MPEG, H.26x, etc., are notacceptable. This work proposes a lossless video server system consisting of three classesof filters (redundancy, task, and priority) which use different levels of knowledge (localsensed environment, human factors associated with a local task, and relative globalpriority of a task) at the application layer of the network. It demonstrates the redundancyand task filters for realistic robot search scenarios. The redundancy filter is shown toreduce the overall transmission bandwidth by 24.07% to 33.42%, and when combinedwith the task filter, reduces overall transmission bandwidth by 59.08% to 67.83%. Byitself, the task filter has the capability to reduce transmission bandwidth by 32.95% to33.78%. While Knowledge-based Compression generally does not reach the same levels ofreduction as MPEG, there are instances where the system outperforms MPEG encoding.

As wearable computers become more ubiquitous in society and work environments, there are concerns that their use could be negatively impactful in some settings. Previous research indicates that mobile phone and wearable computer use can impair walking and driving performance, but as these technologies are adopted into hazardous work environments it is less clear what the impact will be. The current research investigated the effects that head mounted display use has on high angle climbing, a task representative of the extreme physical demands of some hazardous occupations (such as firefighting or search and rescue work). We explored the effect that introducing a secondary word reading and later recall task has on both climbing performance (holds per meter climbed and distance covered), and word reading and recall (dual-task effects). We found a decrease in both climbing performance and word recall under dual task conditions. Further, we examined participant climbing motion around word presentation and non-word presentation times during the climbing traverse. We found that participants slowed around word presentations, relative to periods without word presentation. Finally, we compared our results to those found in previous research using similar dual-tasking paradigms. These comparisons indicated that physical tasks may be more detrimental to word recall than seated tasks, and that visual stimuli might hinder climbing performance more than audible stimuli. This research has important theoretical implications for the dual-tasking paradigm, as well at important practical implications for emergency response operations and other hazardous working environments.

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Security breaches have attracted attention from corporations and scholars alike. The major organisations are determined to stop security breaches as they are detrimental to their success. Arguably the most common factor contributing to these breaches is employee behaviour, which suggests that changes in employee behaviour can have an impact on improving security. This research aims to study the critical factors (CFs) that impact on employee behaviours toward compliance with their organisation's information security policy. This investigation will focus on the various critical success factors based on their grouping into one of the following three major categories, namely: organisational factors, behavioural factors and training factors. Each of these categories affects a different aspect of information security and the objective is to not only understand the interaction of different factors but also to study further the aims in order to provide practical recommendations for improving organisational information security management. This study has utilised empirical research through the use of both qualitative and quantitative methodologies to inform each stage of the research. This study focused on the health, business and education sectors by empirically evaluating the obstacles and success factors that affect employee compliance to organisational security policies. In addition, this study also evaluated the affect of the socio-technical impact on organisational information security management. The final stage of the research focused on developing an effective training and awareness programme. This training programme was constructed by incorporating the techniques that were identified as enhancing employee perceptions, attitudes and motivations, in order to facilitate a better transference of skills and more sustainable and appropriate behaviours to improve organisational information security management in the workplace. The techniques utilised included: effective communication, knowledge reinforcement, pre- and post-assessment and motivational techniques.

Acquisitions are common in today’s business and people involved in acquisitions face challenges when they become part of this process. This thesis aims to provide an understanding of the human factors that determine the outcome of acquisition integration. Various frameworks exist in the literature that focuses on human and task integration as measures for success. In addition to these, the author explores an additional aspect, customer integration, as an important measure to determine overall integration success. Execution is the key to successful acquisition integration. Employees of a technology company were surveyed to gauge their acquisition experiences over three past acquisitions. The survey was a limited targeted case study that focused on analytical value, rather than statistical value. The survey data is analyzed and aligned with the literature data to identify some possible best practices the technology company could follow in future acquisitions. The survey results are used to establish the implications for the company’s acquisition process and to help the development of a playbook for acquisition integration. / text

published_or_final_version / Architecture / Master / Master of Architecture