One of the applications where the use of robots can be beneficial is Wilderness Search and Rescue (WiSAR), which involves the search for a possibly mobile but non-trackable lost person (i.e., the target) in wilderness environments. A mobile target implies that the search area grows continuously and potentially without bound. This fact, combined with the presence of typically rugged, varying terrain and the possibility of inclement weather, poses a considerable challenge to human Search and Rescue (SAR) personnel with respect to the time and effort required to perform the search and the danger entailed to the searchers. Mobile robots can be advantageous in WiSAR due to their ability to provide consistent performance without getting tired and their lower susceptibility to harsh weather conditions compared to humans. Thus, a coordinated team of robots that can assist human SAR personnel by autonomously performing searches in WiSAR scenarios would be of great value. However, to date, a suitable multi-robot coordination methodology for autonomous search that can satisfactorily address the issues relevant to WiSAR is lacking. The objective of this Dissertation is, thus, to develop a methodology that can autonomously coordinate the search strategy of a multi-robot team in wilderness environments to locate a moving target that is neither continuously nor intermittently observed during the search process. Three issues in particular are addressed: (i) target-location prediction, (ii) robot deployment, and (iii) robot-path planning. The corresponding solution approaches devised to address these issues incorporate the influence of varying terrain that may contain a priori known and unknown obstacles, and deal with unique target physiology and psychology as well as found clues left behind by the target. The solution methods for these three tasks work seamlessly together resulting in a tractable MRC methodology for autonomous robotic WiSAR. Comprehensive simulations have been performed that validate the overall proposed methodology. Moreover, the tangible benefits provided by this methodology were further revealed through its comparison with an alternative search method.

Three experiments have been completed to investigate whether and how a software technique called real-time image mosaicing applied to a restricted field of view (FOV) might influence target detection and path integration performance in simulated aerial search scenarios, representing local and global spatial awareness tasks respectively. The mosaiced FOV (mFOV) was compared to single FOV (sFOV) and one with double the single size (dFOV). In addition to advancing our understanding of visual information in mosaicing, the present study examines the advantages and limitations of a number of metrics used to evaluate performance in path integration tasks, with particular attention paid to measuring performance in identifying complex routes. The highlights of the results are summarized as follows, according to Experiments 1 through 3 respectively. 1. A novel response method for evaluating route identification performance was developed. The surmised benefits of the mFOV relative to sFOV and dFOV revealed no significant differences in performance for the relatively simple route shapes tested. Compared to the mFOV and dFOV conditions, target detection performance in the local task was found to be superior in the sFOV condition. 2. In order to appropriately quantify the observed differences in complex route selections made by the participants, a novel analysis method was developed using the Thurstonian Paired Comparisons Method. 3. To investigate the effect of display size and elevation angle (EA) in a complex route environment, a 2x3 experiment was conducted for the two spatial tasks, at a height selected from Experiment 2. Although no significant differences were found in the target detection task, contrasts in the Paired Comparisons Method results revealed that route identification performance were as hypothesised: mFOV > dFOV > sFOV for EA = 90°. Results were similar for EA = 45°, but with mFOV being no different than dFOV. As hypothesised, EA was found to have an effect on route selection performance, with a top down view performing better than an angled view for the mFOV and sFOV conditions.

Previous research has suggested that making certain items visually salient, or highlighting, can speed performance in a visual search task. But designers of interfaces cannot always easily anticipate a user's target, and highlighting items other than the target can be associated with performance decrements. three experiments were performed which demonstrated that people's performance in a visual search task is differentially sensitive to highlighting's predictiveness of target location. That sensitivity depends upon the proportion of instances in which highlighting actually predicts target location. A cognitive model constructed using the ACT-R architecture inferred that people evaluate and adjust their visual search behavior at a very small level of the task. / pages 71-83 and 88-95 are missing from hard copy of text

One of the applications where the use of robots can be beneficial is Wilderness Search and Rescue (WiSAR), which involves the search for a possibly mobile but non-trackable lost person (i.e., the target) in wilderness environments. A mobile target implies that the search area grows continuously and potentially without bound. This fact, combined with the presence of typically rugged, varying terrain and the possibility of inclement weather, poses a considerable challenge to human Search and Rescue (SAR) personnel with respect to the time and effort required to perform the search and the danger entailed to the searchers. Mobile robots can be advantageous in WiSAR due to their ability to provide consistent performance without getting tired and their lower susceptibility to harsh weather conditions compared to humans. Thus, a coordinated team of robots that can assist human SAR personnel by autonomously performing searches in WiSAR scenarios would be of great value. However, to date, a suitable multi-robot coordination methodology for autonomous search that can satisfactorily address the issues relevant to WiSAR is lacking. The objective of this Dissertation is, thus, to develop a methodology that can autonomously coordinate the search strategy of a multi-robot team in wilderness environments to locate a moving target that is neither continuously nor intermittently observed during the search process. Three issues in particular are addressed: (i) target-location prediction, (ii) robot deployment, and (iii) robot-path planning. The corresponding solution approaches devised to address these issues incorporate the influence of varying terrain that may contain a priori known and unknown obstacles, and deal with unique target physiology and psychology as well as found clues left behind by the target. The solution methods for these three tasks work seamlessly together resulting in a tractable MRC methodology for autonomous robotic WiSAR. Comprehensive simulations have been performed that validate the overall proposed methodology. Moreover, the tangible benefits provided by this methodology were further revealed through its comparison with an alternative search method.

Three experiments have been completed to investigate whether and how a software technique called real-time image mosaicing applied to a restricted field of view (FOV) might influence target detection and path integration performance in simulated aerial search scenarios, representing local and global spatial awareness tasks respectively. The mosaiced FOV (mFOV) was compared to single FOV (sFOV) and one with double the single size (dFOV). In addition to advancing our understanding of visual information in mosaicing, the present study examines the advantages and limitations of a number of metrics used to evaluate performance in path integration tasks, with particular attention paid to measuring performance in identifying complex routes. The highlights of the results are summarized as follows, according to Experiments 1 through 3 respectively. 1. A novel response method for evaluating route identification performance was developed. The surmised benefits of the mFOV relative to sFOV and dFOV revealed no significant differences in performance for the relatively simple route shapes tested. Compared to the mFOV and dFOV conditions, target detection performance in the local task was found to be superior in the sFOV condition. 2. In order to appropriately quantify the observed differences in complex route selections made by the participants, a novel analysis method was developed using the Thurstonian Paired Comparisons Method. 3. To investigate the effect of display size and elevation angle (EA) in a complex route environment, a 2x3 experiment was conducted for the two spatial tasks, at a height selected from Experiment 2. Although no significant differences were found in the target detection task, contrasts in the Paired Comparisons Method results revealed that route identification performance were as hypothesised: mFOV > dFOV > sFOV for EA = 90°. Results were similar for EA = 45°, but with mFOV being no different than dFOV. As hypothesised, EA was found to have an effect on route selection performance, with a top down view performing better than an angled view for the mFOV and sFOV conditions.

A number of computational methods have suggested means by which gene transcription – the process through which RNA is created from DNA – is activated, but there are factors at work that no model has been able to fully explain. In eukaryotes, gene regulation is quite complex, so models have primarily focused on a relatively simple species, Saccharomyces cerevisiae (budding yeast). Because of the inherent complexity in higher species, and even in yeast, a method of identifying transcription factor (TF) binding motifs (specific, short DNA sequences) must be efficient and thorough in its analysis. This thesis shows that a method using the Fast Orthogonal Search (FOS) algorithm to uncover binding motifs as well as cooperatively binding groups of motifs can explain variations in gene expression profiles, which reflect the level at which DNA is transcribed into RNA for a number of genes. The algorithm is very fast, exploring a motif list and constructing a final model within seconds to a few minutes. It produces model terms that are consistent with known motifs, while also revealing new motifs and interactions, and it causes impressive reductions in variance with relatively few model terms over the cell-cycle. / Thesis (Master, Electrical & Computer Engineering) -- Queen's University, 2008-08-21 10:30:24.293

This dissertation examines the welfare effects of inflation on employment and output in three different market settings. The theoretical frameworks build on recent studies in the monetary search literature that explicitly models the microfoundations of money and study how monetary policy interacts with real variables. The first essay studies the relationship between inflation and unemployment in a general equilibrium framework where inflation has differential effects on employed and unemployed workers. The model finds that inflation can either increase or decrease employment and output, depending on goods and labor market institutions. Sales taxes, the degree of competitiveness in the goods market and imperfect indexation of unemployment insurance benefits are the major factors determining the direction of this relationship. Through a comparison of these parameters, the model predicts an inflation-unemployment relation that is qualitatively consistent with the empirical evidences. The second essay, co-authored with Liang Wang and Randall Wright, investigates the effect of inflation on people's trading behavior in the goods market. By focusing on buyers' search intensity on the extensive margin, the model unambiguously predicts a rise in inflation leads to an increase in the speed with which agents spend their money and velocity. This is consistent with the phenomenon described by the conventional "hot potato" effect of inflation. We also discuss the welfare implications of different monetary policy. In some circumstances inflating above the Friedman rule may be optimal, but the effect of inflation on output is always negative. The third essay, co-authored with Allen Head, Guido Menzio and Randall Wright, examines the effect of monetary growth on output in a general equilibrium model where price stickiness arises as an equilibrium outcome. The model makes several predictions about individual firms' price adjustment behavior that are consistent with micro data. For instance, the frequency (duration) of price changes increases (decreases) with inflation and the price change hazard declines over time. In contrast to the New Keynesian literature, price rigidities in our model does not generate monetary non-neutrality. Higher inflation reduces real output in the long run, but changes in the aggregate price level has no effect on real allocations. / Thesis (Ph.D, Economics) -- Queen's University, 2010-07-17 00:52:41.487

Decisions are based on multiple sources of information. For example, sensory information encoding environmental features may be combined with prior experience to bias judgements in visual behaviour. With the goal of characterizing the rules by which sensory and non-sensory variables combine to direct saccade selection processes monkeys were trained in a visual search task where the discriminability of a visual target and reward outcome for correct foveation varied systematically. Target discriminability was manipulated across three levels of luminance contrast while reward was manipulated by 'tagging' a spatial location such that target foveation at the tagged location yielded one, two or four times the liquid reward available at all other locations. The location and discriminability of the search target amongst seven distractor stimuli varied randomly from trial-to-trial while the magnitude of reward at the tagged location was fixed for each experimental block. Reward was found to have a large effect on search behaviour when target discriminability was low, but as discriminability increased, the effect of reward diminished. More specifically, reward increased choice probability and reduced the latency of saccades to target and distractor stimuli appearing in the tagged location. Together, the results suggested the effects of reward and luminance on saccade selection were dependent on one another. To characterize the nature of this interaction search psychophysics were couched in saccade selection processes using signal detection theory. Signals carrying target and distractor related information were modelled and taken to capture an actual discrimination process implemented by the brain. It was found that a response bias in saccade selection processes could largely reproduce monkey choice behaviour for both correct and incorrect trials. / Thesis (Master, Neuroscience Studies) -- Queen's University, 2010-08-03 22:22:15.825

This thesis studies the role of multi-stage production for the monetary transmission mechanism. I employ a monetary search model to show how multi-stage production influences both the long run and the short run effects of money growth. Multi-stage production provides an additional channel for money growth having effects through intermediate goods between different production stages. Extending Shi's (1998) model from a single-stage to a multi-stage production model, I show that money growth rate has an unconventional long run effect on quantities per match, and the long run response of input inventory investment is different from that of output inventory investment. Contrary to classic search models, the steady state effect of money growth on the quantity of finished goods per match is not monotonic and depends on the money growth rate. Furthermore, in steady state the quantities per match first increase with the growth rate of money, before falling for large growth rates. Input inventories arise due to search frictions. Money growth also has hump-shaped real effects on steady state input inventory investment. The intermediate goods build a bridge between the labor market and the finished goods market. Intuitively, households hire more labor with higher future revenue and produce more intermediate goods in order to match the employment level. With more labor and more intermediate goods, finished goods producers can produce more when matched. As a consequence, they are stuck with more input inventories. Moreover, my model suggests that changes in the money growth rate would be one of the reasons for the decline of the inventory-to-sales ratio since the mid-1980s. Finally, I calibrate my model to quarterly US data. Contrary to other work, my model is able to replicate the stylized facts on inventory movements over the business cycle by solely relying on monetary shocks. The theoretical impulse response functions can quantitatively reproduce the corresponding empirical ones estimated in a structure autoregressive model. Moreover, the quantitative analysis supports the argument that input inventories amplify aggregate fluctuations over business cycles. / Thesis (Ph.D, Economics) -- Queen's University, 2012-09-16 20:44:21.876

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