Narrative Approaches to Wellbeing

The importance of narratives in therapeutic processes such as convalescence, psychotherapy and counselling is well-established. Such narrative-based approaches highlight the benefit of sense-making, coping and positive affect in circumstances of illness or psychological distress. These phenomena are consistent with theories of narrative which emphasise contextualisation and the restoration of equilibrium. This paper proposes to open up further areas of enquiry by examining a range of theoretical models of narrative as an imaginative space. It will examine a selection of established models of narrative in literary and media disciplines, and identify some themes and categories which recur in the practice of story-telling – such as inevitability and agency, community and individuality, freedom and destiny, absurdity and purpose. The paper will conclude by articulating some of the major themes that narrative suggests as a discipline, and which therefore might prove fruitful in understanding not only how story-telling plays a part in therapeutic processes, but how narrative might help to formulate a more generalised notion of wellbeing

Implementation of a robotic flexible assembly system

As part of the Intelligent Task Automation program, a team developed enabling technologies for programmable, sensory controlled manipulation in unstructured environments. These technologies include 2-D/3-D vision sensing and understanding, force sensing and high speed force control, 2.5-D vision alignment and control, and multiple processor architectures. The subsequent design of a flexible, programmable, sensor controlled robotic assembly system for small electromechanical devices is described using these technologies and ongoing implementation and integration efforts. Using vision, the system picks parts dumped randomly in a tray. Using vision and force control, it performs high speed part mating, in-process monitoring/verification of expected results and autonomous recovery from some errors. It is programmed off line with semiautomatic action planning

DESIGN AND EVALUATION OF A NONVERBAL COMMUNICATION PLATFORM BETWEEN ASSISTIVE ROBOTS AND THEIR USERS

Assistive robotics will become integral to the everyday lives of a human population that is increasingly mobile, older, urban-centric and networked. The overwhelming demands on healthcare delivery alone will compel the adoption of assistive robotics. How will we communicate with such robots, and how will they communicate with us? This research makes the case for a relatively \u27artificial\u27 mode of nonverbal human-robot communication that is non-disruptive, non-competitive, and non-invasive human-robot communication that we envision will be willingly invited into our private and working lives over time. This research proposes a non-verbal communication (NVC) platform be conveyed by familiar lights and sounds, and elaborated here are experiments with our NVC platform in a rehabilitation hospital. This NVC is embedded into the Assistive Robotic Table (ART), developed within our lab, that supports the well-being of an expanding population of older adults and those with limited mobility. The broader aim of this research is to afford people robot-assistants that exist and interact with them in the recesses, rather than in the foreground, of their intimate and social lives. With support from our larger research team, I designed and evaluated several alternative modes of nonverbal robot communication with the objective of establishing a nonverbal, human-robot communication loop that evolves with users and can be modified by users. The study was conducted with 10-13 clinicians -- doctors and occupational, physical, and speech therapists -- at a local rehabilitation hospital through three iterative design and evaluation phases and a final usability study session. For our test case at a rehabilitation hospital, medical staff iteratively refined our NVC platform, stated a willingness to use our platform, and declared NVC as a desirable research path. In addition, these clinicians provided the requirements for human-robot interaction (HRI) in clinical settings, suggesting great promise for our mode of human-robot communication for this and other applications and environments involving intimate HRI

Integrating Multiple Sketch Recognition Methods to Improve Accuracy and Speed

Sketch recognition is the computer understanding of hand drawn diagrams. Recognizing sketches instantaneously is necessary to build beautiful interfaces with real time feedback. There are various techniques to quickly recognize sketches into ten or twenty classes. However for much larger datasets of sketches from a large number of classes, these existing techniques can take an extended period of time to accurately classify an incoming sketch and require significant computational overhead. Thus, to make classification of large datasets feasible, we propose using multiple stages of recognition. In the initial stage, gesture-based feature values are calculated and the trained model is used to classify the incoming sketch. Sketches with an accuracy less than a threshold value, go through a second stage of geometric recognition techniques. In the second geometric stage, the sketch is segmented, and sent to shape-specific recognizers. The sketches are matched against predefined shape descriptions, and confidence values are calculated. The system outputs a list of classes that the sketch could be classified as, along with the accuracy, and precision for each sketch. This process both significantly reduces the time taken to classify such huge datasets of sketches, and increases both the accuracy and precision of the recognition

Integrating Multiple Sketch Recognition Methods to Improve Accuracy and Speed

Sketch recognition is the computer understanding of hand drawn diagrams. Recognizing sketches instantaneously is necessary to build beautiful interfaces with real time feedback. There are various techniques to quickly recognize sketches into ten or twenty classes. However for much larger datasets of sketches from a large number of classes, these existing techniques can take an extended period of time to accurately classify an incoming sketch and require significant computational overhead. Thus, to make classification of large datasets feasible, we propose using multiple stages of recognition. In the initial stage, gesture-based feature values are calculated and the trained model is used to classify the incoming sketch. Sketches with an accuracy less than a threshold value, go through a second stage of geometric recognition techniques. In the second geometric stage, the sketch is segmented, and sent to shape-specific recognizers. The sketches are matched against predefined shape descriptions, and confidence values are calculated. The system outputs a list of classes that the sketch could be classified as, along with the accuracy, and precision for each sketch. This process both significantly reduces the time taken to classify such huge datasets of sketches, and increases both the accuracy and precision of the recognition

The effect of salience on Chinese pun comprehension : a visual world paradigm study

The present study adopted the printed-word visual world paradigm to investigate the salience effect on Chinese pun comprehension. In such an experiment, participants listen to a spoken sentence while looking at a visual display of four printed words (including a semantic competitor, a phonological competitor, and two unrelated distractors). Previous studies based on alphabetic languages have found robust phonological effects (participants fixated more at phonological competitors than distractors during the unfolding of the spoken target words), while controversy remains regarding the existence of a similar semantic effect. A recent Chinese study reported reliable semantic effects in two experiments using this paradigm, suggesting that Chinese participants could actively map the semantic input from the auditory modality with the semantic information retrieved from printed words. In light of their study, we designed an experiment with two conditions: a replication condition to test the validity of using the printed-word world paradigm in Chinese semantic research, and a pun condition to assess the role played by salience during pun comprehension. Indeed, global analyses have revealed robust semantic effects in both experimental conditions, where participants were found more attracted to the semantic competitors than to the distractors with the emergence of target words. More importantly, the local analyses from the pun condition have shown that the participants were more attracted to the semantic competitors related to the salient meaning of the ambiguous word in a pun than to those related to the less salient meanings within 200 ms after target word offset. This finding suggests that the salient meaning of the ambiguous word in a pun is activated and assessed faster than its less salient counterpart. The initial advantage observed in the present study is consistent with the prediction of the graded salience hypothesis rather than the direct access model

Some Varieties of Superparadox. The implications of dynamic contradiction, the characteristic form of breakdown of breakdown of sense to which self-reference is prone

The Problem of the Paradoxes came to the fore in philosophy and mathematics with the discovery of Russell's Paradox in 1901. It is the "forgotten" intellectual-scientific problem of the Twentieth Century, because for more than sixty years a pretence was maintained, by a consensus of logicians, that the problem had been "solved"