Theses and Dissertations from UMD
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New submissions to the thesis/dissertation collections are added automatically as they are received from the Graduate School. Currently, the Graduate School deposits all theses and dissertations from a given semester after the official graduation date. This means that there may be up to a 4 month delay in the appearance of a give thesis/dissertation in DRUM
More information is available at Theses and Dissertations at University of Maryland Libraries.
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Item Terrain Classification and Navigability Analysis in Unstructured Outdoor Environments(2021) Guan, Tianrui; Lin, Ming C; Computer Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)We present a new learning-based method for identifying safe and navigable regions inoff-road terrains and unstructured environments from RGB images. Our approach consists of classifying groups of terrains based on their navigability levels using coarse-grained semantic segmentation. We propose a transformer-based deep neural network architecture that uses a novel group-wise attention mechanism to distinguish between navigability levels of different terrains. Our group-wise attention heads enable the network to explicitly focus on the different groups and improve the accuracy. We show through extensive evaluations on the RUGD and RELLIS-3D datasets that our learning algorithm improves visual perception accuracy in off-road terrains for navigation. We compare our approach with prior work on these datasets and achieve an improvement over the state-of-the-art mIoU by 6.74-39.1% on RUGD and 3.82-10.64% on RELLIS-3D. In addition, we deploy our method on a Clearpath Jackal robot. Our approach improves the performance of the navigation algorithm in terms of average progress towards the goal by 54.73% and the false positives in terms of forbidden region by 29.96%.Item Perceptual Decision Impairments in Obsessive-Compulsive Disorder: State and Trait Symptom Effects and The Role of Working Memory(2020) Kaplan, Claire; Solway, Alec; Psychology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Computational models of decision making have identified a relationship between obsessive-compulsive symptomatology and impairments in perceptual evidence accumulation. Past studies have suggested that these impairments in perceptual processing give rise to clusters of OCD symptoms (for example, not effectively “perceiving” that a door is locked or that one’s hands are clean gives rise to compulsive checking or washing). That interpretation has implications for our understanding of the disorder and warrants further testing; one way to investigate that is to determine whether such impairments correlate better with state-level symptoms (i.e., obsessions and compulsions during task performance) or trait-level symptoms (i.e., in general/past week). Using hierarchical drift-diffusion modeling, the current study examines this question in consideration of the alternate possibility that these decision impairments are simply a reflection of off-task processing of active obsessions and compulsions. We also examine whether working memory may mitigate such impairments, in light of prior studies that have associated larger working memory spans with better suppression of distractors and with faster perceptual evidence accumulation. 161 adults completed the random dot-motion task, OSPAN working memory task, and OCD symptom questionnaires online. Participants who reported greater obsessive-compulsive symptoms demonstrated slower evidence accumulation (“drift rate”) in the dot-motion task. These drift rate reductions were better explained by state-level symptom severity than trait-level severity. Working memory span showed a significant negative interaction with state-level symptom score on drift rate, however only for the easiest trials. While the current study does not negate a role of perceptual evidence accumulation deficits in the pathogenesis of OCD, these findings support the possibility that such deficits may also be brought about by active symptoms during task execution. We discuss using impairments in drift rate to approximate attentional bias for off-task symptoms, as this provides a novel computational framework in closer alignment with existing clinical models of OCD.Item LARGE-SCALE NEURAL NETWORK MODELING: FROM NEURONAL MICROCIRCUITS TO WHOLE-BRAIN COMPLEX NETWORK DYNAMICS(2018) Liu, Qin; Anlage, Steven; Horwitz, Barry; Physics; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Neural networks mediate human cognitive functions, such as sensory processing, memory, attention, etc. Computational modeling has been proved as a powerful tool to test hypothesis of network mechanisms underlying cognitive functions, and to understand better human neuroimaging data. The dissertation presents a large-scale neural network modeling study of human brain visual/auditory processing and how this process interacts with memory and attention. We first modeled visual and auditory objects processing and short-term memory with local microcircuits and a large-scale recurrent network. We proposed a biologically realistic network implementation of storing multiple items in short-term memory. We then realized the effect that people involuntarily switch attention to salient distractors and are difficult to distract when attending to salient stimuli, by incorporating exogenous and endogenous attention modules. The integrated model could perform a number of cognitive tasks utilizing different cognitive functions by only changing a task-specification parameter. Based on the performance and simulated imaging results of these tasks, we proposed hypothesis for the neural mechanism beneath several important phenomena, which may be tested experimentally in the future. Theory of complex network has been applied in the analysis of neuroimaging data, as it provides a topological abstraction of the human brain. We constructed functional connectivity networks for various simulated experimental conditions. A number of important network properties were studied, including the scale-free property, the global efficiency, modular structure, and explored their relations with task complexity. We showed that these network properties and their dynamics of our simulated networks matched empirical studies, which verifies the validity and importance of our modeling work in testing neural network hypothesis.Item Active Attention for Target Detection and Recognition in Robot Vision(2017) Luan, Wentao; Baras, John S; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)In this thesis, we address problems in building an efficient and reliable target detection and recognition system for robot applications, where the vision module is only one component of the overall system executing the task. The different modules interact with each other to achieve the goal. In this interaction, the role of vision is not only to recognize but also to select what and where to process. In other words, attention is an essential process for efficient task execution. We introduce attention mechanisms into the recognition system that serve the overall system at different levels of the integration and formulate four problems as below. At the most basic level of integration, attention interacts with vision only. We consider the problem of detecting a target in an input image using a trained binary classifier of the target and formulate the target detection problem as a sampling process. The goal is to localize the windows containing targets in the image, and attention controls which part of the image to process next. We observe that detectors’ response scores of sampling windows fade gradually from the peak response window in the detection area and approximate this scoring pattern with an exponential de- cay function. Exploiting this property, we propose an active sampling procedure to efficiently detect the target while avoiding an exhaustive and expensive search of all the possible window locations. With more knowledge about the target, we describe the target as template graphs over segmented surfaces. Constraint functions are also defined to find the node and edge’s matching between an input scene graph and target’s template graph. We propose to introduce the recognition early into the traditional candidate proposal process to achieve fast and reliable detection performance. The target detection thence becomes finding subgraphs from the segmented input scene graph that match the template graphs. In this problem, attention provides the order of constraints in checking the graph matching, and a reasonable sequence can help filter out negatives early, thus reducing computational time. We put forward a sub-optimal checking order, and prove that it has bounded time cost compared to the optimal checking sequence, which is not obtainable in polynomial time. Experiments on rigid and non-rigid object detection validate our pipeline. With more freedom in control, we allow the robot to actively choose another viewpoint if the current view cannot deliver a reliable detection and recognition result. We develop a practical viewpoint control system and apply it to two human-robot interaction applications, where the detection task becomes more challenging with the additional randomness from the human. Attention represents an active process of deciding the location of the camera. Our viewpoint selection module not only considers the viewing condition constraints for vision algorithms but also incorporates the low-level robot kinematics to guarantee the reachability of the desired viewpoint. By selecting viewpoints fast using a linear time cost score function, the system can deliver smooth user interaction experience. Additionally, we provide a learning from human demonstration method to obtain the score function parameters that better serves the task’s preference. Finally, when recognition results from multiple sources under different environmental factor are available, attention means how to fuse the observations to get reliable output. We consider the problem of object recognition in 3D using an ensemble of attribute-based classifiers. We propose two new concepts to improve classification in practical situations, and show their implementation in an approach implemented for recognition from point-cloud data. First, we study the impact of the distance between the camera and the object and propose an approach to classifier’s accuracy performance, which incorporates distance into the decision making. Second, to avoid the difficulties arising from lack of representative training examples in learning the optimal threshold, we set in our attribute classifier two threshold values to distinguish a positive, a negative and an uncertainty class, instead of just one threshold value. We prove the theoretical correctness of this approach for an active agent who can observe the object multiple times.Item Psychopathic Traits, Affect, and Cocaine Use-Related Outcomes(2014) Long, Katherine; Lejuez, Carl W; Psychology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Substance abuse and associated public health and economic consequences represent a pervasive and costly problem. Among inner-city substance users, crack/cocaine is the most common drug of choice and is associated with health compromising behaviors. Substance Use Disorders (SUDs) are more prevalent, severe, and difficult to treat among individuals with Antisocial Personality Disorder (ASPD). Psychopathy is a construct which is related to but distinct from ASPD, and the relation between primary psychopathic traits and substance use is not well understood. The present laboratory experimental study of cocaine use-related outcomes in the context of mood inductions among cocaine users found that primary psychopathic traits were negatively associated with attentional bias for cocaine-related cues but not associated with self-reported craving. Assignment to the negative affect manipulation was related to greater attentional bias but not to craving. The interaction between mood condition and primary psychopathic traits was not a significant predictor of either outcome.Item Single-Microphone Speech Enhancement Inspired by Auditory System(2014) Mirbagheri, Majid; Shamma, Shihab; Electrical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Enhancing quality of speech in noisy environments has been an active area of research due to the abundance of applications dealing with human voice and dependence of their performance on this quality. While original approaches in the field were mostly addressing this problem in a pure statistical framework in which the goal was to estimate speech from its sum with other independent processes (noise), during last decade, the attention of the scientific community has turned to the functionality of human auditory system. A lot of effort has been put to bridge the gap between the performance of speech processing algorithms and that of average human by borrowing the models suggested for the sound processing in the auditory system. In this thesis, we will introduce algorithms for speech enhancement inspired by two of these models i.e. the cortical representation of sounds and the hypothesized role of temporal coherence in the auditory scene analysis. After an introduction to the auditory system and the speech enhancement framework we will first show how traditional speech enhancement technics such as wiener-filtering can benefit on the feature extraction level from discriminatory capabilities of spectro-temporal representation of sounds in the cortex i.e. the cortical model. We will next focus on the feature processing as opposed to the extraction stage in the speech enhancement systems by taking advantage of models hypothesized for human attention for sound segregation. We demonstrate a mask-based enhancement method in which the temporal coherence of features is used as a criterion to elicit information about their sources and more specifically to form the masks needed to suppress the noise. Lastly, we explore how the two blocks for feature extraction and manipulation can be merged into one in a manner consistent with our knowledge about auditory system. We will do this through the use of regularized non-negative matrix factorization to optimize the feature extraction and simultaneously account for temporal dynamics to separate noise from speech.Item Attention, Emotion Understanding, and Social Competence in Preschool Children: Construct Definitions, Measurement, and Relationships(2013) Genova-Latham, Maria de los Angeles; Teglasi, Hedwig; Counseling and Personnel Services; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Available literature regarding the relations between attention, emotion understanding, and social competence is limited in its utility given discrepancies in construct definitions and measurement. The current study examined the relations between attention, as defined from a temperament perspective, emotion understanding, and social competence in preschool children, emphasizing specificity in the conceptualization and assessment of constructs. Attention was measured via the Structured Temperament Interview (STI) and the Childhood Behavior Questionnaire (CBQ), parent-report measures. Emotion understanding was assessed with the Emotion Comprehension Test (ECT), a performance assessment. The ECT differentiated between a child's ability to identify emotions in others based on facial expressions, situational cues, and behavioral cues. Social competence was measured via teacher ratings on the Social Competence Behavior Evaluation questionnaire (SCBE). Exploratory factor analyses of the STI revealed a two factor solution, including factors Low Distraction from Task, High Duration of Attention and Low Distraction from Emotional Investment. The former demonstrated multiple relations with the Effortful Control factor of the CBQ in correlational analyses, whereas the latter demonstrated multiple relations with the Negative Affect factor. Quantitative data, as well as qualitative analyses of themes emerging from parents' narrative STI responses, indicated that the STI encompasses both self-regulatory and reactive dimensions of attention, as well as features of emotionality and interest. Correlational and hierarchical regression analyses indicated that dimensions of attention including distractibility, attention span/persistence, and attentional focusing are related to a child's ability to identify emotions in others based on situational cues. Self-regulatory and reactive dimensions of attention, as assessed via the CBQ, demonstrated relationships with social competence outcomes, though no relations were evident between STI factors and SCBE scales. Ultimately, though dimensions of attention demonstrated relations with facets of both emotion understanding and social competence, in no case were dimensions of both attention and emotion understanding related to the same facet of social competence.Item INTERPRETIVE BIAS AND ANXIETY VULNERABILITY IN BEHAVIORALLY INHIBITED CHILDREN: DISAMBIGUATING THE COGNITIVE AND EMOTIONAL EFFECTS ASSOCIATED WITH INTERPRETIVE BIAS ACQUISITION(2013) White, Lauren K.; Fox, Nathan A.; Human Development; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Behavioral inhibition (BI), a temperament characterized by a fear of novel and unfamiliar people and situations, is associated with increased risk for anxiety problems throughout life. One mechanism thought to moderate the link between BI and anxiety is a child's interpretive bias (i.e., the manner in which emotional ambiguity is interpreted). Behaviorally inhibited children who consistently interpret ambiguous information in a threatening manner are thought to be at increased risk for anxiety. Conversely, behaviorally inhibited children who consistently interpret ambiguity as benign or non-threatening may be protected from such risk. Little research, however, has experimentally examined interpretive biases in behaviorally inhibited children. This dissertation investigates the causal relations between interpretive biases and anxiety vulnerability in behaviorally inhibited children. To examine if changes in interpretive biases affect anxiety vulnerability, a cognitive bias modification procedure was employed to induce a non-threatening interpretive bias in a group of 9-12 year old behaviorally inhibited children. After training, children were assessed on their mood, emotional vulnerability to stress, and attention bias toward threat in order to determine if bias modification affected anxiety vulnerability. The findings of this study demonstrate that the cognitive bias manipulation was successful; behaviorally inhibited children displayed decreased threat interpretations after training. No training effects on anxiety vulnerability were detected. As a result, the notion that interpretive biases are causally linked to a child's anxiety vulnerability is not supported by the findings of this study. The implications of these findings are discussed in this dissertation.Item A PROGRAMMATIC RESEARCH APPROACH TO UNDERSTANDING THE IMPACT OF TEAM ENVIRONMENT ON CEREBRAL CORTICAL DYNAMICS AND ATTENTION(2012) Miller, Matthew Walker; Hatfield, Bradley D; Neuroscience and Cognitive Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)This dissertation describes a programmatic research approach to understanding how team environments alter individuals' brain dynamics so as to produce variations in individuals' cognitive-motor performances. This research is of fundamental interest as humans frequently perform in team environments. Specifically, the central purpose of this research was to determine if adaptive team environments are conducive to efficient brain dynamics such that tasks are accomplished with minimal neural costs. The dissertation is comprised of four studies (papers), each of which makes a unique contribution to the dissertation's central objective. The first paper reports a positive directional relationship between cerebral cortical activation as well as networking and task load. The second paper describes a new neurophysiological method for indexing attentional reserve, which is positively related to the efficiency of cerebral cortical activation and networking. The third paper describes the development of a paradigm employed to investigate the impact of team environment on neurocognitive functioning. This study used non-physiological techniques to index neurocognitive functioning while participants performed a cognitive-motor task in various team environments. Results suggest that, relative to neutral environments, maintaining performance in maladaptive team environments comes at a neurocognitive cost, while adaptive team environments enhance performance without such a cost. The final study applied the neurophysiological methods described in the first two studies to the team environment paradigm employed in the third study to provide neurobiological evidence in support of the conclusions reached in the third paper. Additionally, the final paper provides insight into the neurobiological changes underlying the alterations in neurocognitive functioning and task performance reported in the third paper. Specifically, the final paper reports that, relative to neutral environments, maintaining performance in maladaptive team environments comes at the expense of the efficiency of cerebral cortical activation and attentional reserve, while adaptive team environments enhance performance without such costs. Additionally, the final paper suggests that adaptive team environments may generate more optimal states of arousal, leading to performance enhancement. By comprehending the impact of team environments on brain dynamics, humans performing as members of teams in a variety of settings may be better equipped to maximize their performances.Item Psychophysiological investigation of attentional processes during motor learning(2011) Rietschel, Jeremy Carl; Hatfield, Bradley D; Neuroscience and Cognitive Science; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)As one becomes more proficient at a motor task the attentional demand required to perform that task decreases. Behavioral evidence suggests that experienced individuals possess greater attentional reserve during task execution compared to novices, such that, they are better able to cope with additional, possibly unexpected, challenges. This advantage may be the result of streamlining the neural processes underlying motor planning and execution over the course of learning. Such psychomotor efficiency reduces the demand on cortical resources imposed by the primary task such that they are available for coping with challenge beyond that of the task. However, this hypothesis has not been tested. The aim of this study was to provide neurobiological evidence of the positive relationship between motor skill and attentional reserve. Twenty-one participants were randomly assigned to one of two groups, a group that learned a novel visuomotor distortion task, and a control group that performed the same task with no distortion (i.e., no learning). For the duration of the task, event-related brain potentials (ERPs) elicited by a set of novel stimuli were recorded. The dynamic modulation of ERP component amplitude was used as an index of attentional reserve. We predicted that component amplitudes would initially be diminished in the learning group relative to the control group, but that there would be a progressive increase in amplitude as a function of learning; by contrast, we predicted that ERP component amplitudes would remain relatively stable in the control group. Importantly, task performance, as measured by initial directional error, was initially worse in the learning group relative to control group and significantly improved over the course of exposure, whereas the control group's performance was stable. This suggests the visuomotor distortion task employed was successful in serving as a model of motor skill acquisition. Analyses of the ERPs elicited by the auditory probes revealed that the exogenous components, N1 and P2, were not different between the two groups and did not change over the course of learning suggesting that early sensory processing was comparable between the two groups. Notably, the novelty P3 component-an index of the involuntary orienting of attention--was initially attenuated in the learning group relative to the control group, but progressively increased in amplitude as a function of learning in the learning group only. This suggests that attentional reserve increased as a function of motor skill acquisition, such that greater attentional resources were available to process the auditory probes. The current study provides psychophysiological evidence that attentional reserve increases as a function of motor skill acquisition. Moreover, the metric developed for this study provides a means to assess cognitive/motor learning in both applied cognitive and clinical domains.