220 resultados para Cognitive Radio, FFT pruning, FPGA
Resumo:
This paper reports the findings of a pilot study aimed at improving learning outcomes from Computer Assisted Instruction (CAI). The study involved second year nursing students at the Queensland University of Technology. Students were assessed for their preferred cognitive style and presented with either matched or mismatched instructional material. The instructional material was developed in accordance with four cognitive styles (Riding & Cheema, 1991). The findings indicate groups that received instructional material which matched their preferred cognitive style, possibly, performed better than groups that received mismatched instructional material. The matched group was particularly better in the explanation and problem solving tasks.
Resumo:
This paper addresses the tradeoff between energy consumption and localization performance in a mobile sensor network application. The focus is on augmenting GPS location with more energy-efficient location sensors to bound position estimate uncertainty in order to prolong node lifetime. We use empirical GPS and radio contact data from a largescale animal tracking deployment to model node mobility, GPS and radio performance. These models are used to explore duty cycling strategies for maintaining position uncertainty within specified bounds. We then explore the benefits of using short-range radio contact logging alongside GPS as an energy-inexpensive means of lowering uncertainty while the GPS is off, and we propose a versatile contact logging strategy that relies on RSSI ranging and GPS lock back-offs for reducing the node energy consumption relative to GPS duty cycling. Results show that our strategy can cut the node energy consumption by half while meeting application specific positioning criteria.
Resumo:
Anxiety disorders have been viewed as manifestations of broad underlying predisposing personality constructs such as neuroticism combined with more specific individual differences of unhelpful information processing styles. Given the high prevalence of anxiety and the significant impairment that it causes, there is an important need to continue to explore successful treatments for this disorder. Research indicates that there is still room for significantly improving attrition rates and treatment adherence. Traditionally Motivational Interviewing (MI) has been used to facilitate health behaviour change. Recently MI has been applied to psychotherapy and has been shown to improve the outcome of CBT. However, these studies have been limited to only considering pre- and post-treatment measures and neglected to consider when changes occur along the course of therapy. This leaves the unanswered question of what is the impact of pre-treatment MI on the treatment trajectory of therapy. This study provides preliminary research into answering this question by tracking changes on a weekly basis along the course of group CBT. Prior to group CBT, 40 individuals with a principal anxiety disorder diagnosis were randomly assigned to receive either 3 individual sessions of MI or placed on a waitlist control group. All participants then received the same dosage of 10 weekly 2 hour sessions of group CBT. Tracking treatment outcome trajectory over the course of CBT, the pre-treatment MI group, compared to the control group, experienced a greater improvement early on in the course of therapy in their symptom distress, interpersonal relationships and quality of life. This early advantage over the control group was then maintained throughout therapy. These results not only demonstrate the value of adding MI to CBT, but also highlight the immediacy of MI effects. Further research is needed to determine the robustness of these effects to inform clinical implications of how to best apply MI to improve treatment adherence to CBT for anxiety disorders.
Resumo:
This paper investigates the field programmable gate array (FPGA) approach for multi-objective and multi-disciplinary design optimisation (MDO) problems. One class of optimisation method that has been well-studied and established for large and complex problems, such as those inherited in MDO, is multi-objective evolutionary algorithms (MOEAs). The MOEA, nondominated sorting genetic algorithm II (NSGA-II), is hardware implemented on an FPGA chip. The NSGA-II on FPGA application to multi-objective test problem suites has verified the designed implementation effectiveness. Results show that NSGA-II on FPGA is three orders of magnitude better than the PC based counterpart.
Resumo:
Objective: Older driver research has mostly focused on identifying that small proportion of older drivers who are unsafe. Little is known about how normal cognitive changes in aging affect driving in the wider population of adults who drive regularly. We evaluated the association of cognitive function and age, with driving errors. Method: A sample of 266 drivers aged 70 to 88 years were assessed on abilities that decline in normal aging (visual attention, processing speed, inhibition, reaction time, task switching) and the UFOV® which is a validated screening instrument for older drivers. Participants completed an on-road driving test. Generalized linear models were used to estimate the associations of cognitive factor with specific driving errors and number of errors in self-directed and instructor navigated conditions. Results: All errors types increased with chronological age. Reaction time was not associated with driving errors in multivariate analyses. A cognitive factor measuring Speeded Selective Attention and Switching was uniquely associated with the most errors types. The UFOV predicted blindspot errors and errors on dual carriageways. After adjusting for age, education and gender the cognitive factors explained 7% of variance in the total number of errors in the instructor navigated condition and 4% of variance in the self-navigated condition. Conclusion: We conclude that among older drivers errors increase with age and are associated with speeded selective attention particularly when that requires attending to the stimuli in the periphery of the visual field, task switching, errors inhibiting responses and visual discrimination. These abilities should be the target of cognitive training.
Resumo:
Objective The current study evaluated part of the Multifactorial Model of Driving Safety to elucidate the relative importance of cognitive function and a limited range of standard measures of visual function in relation to the Capacity to Drive Safely. Capacity to Drive Safely was operationalized using three validated screening measures for older drivers. These included an adaptation of the well validated Useful Field of View (UFOV) and two newer measures, namely a Hazard Perception Test (HPT), and a Hazard Change Detection Task (HCDT). Method Community dwelling drivers (n = 297) aged 65–96 were assessed using a battery of measures of cognitive and visual function. Results Factor analysis of these predictor variables yielded factors including Executive/Speed, Vision (measured by visual acuity and contrast sensitivity), Spatial, Visual Closure, and Working Memory. Cognitive and Vision factors explained 83–95% of age-related variance in the Capacity to Drive Safely. Spatial and Working Memory were associated with UFOV, HPT and HCDT, Executive/Speed was associated with UFOV and HCDT and Vision was associated with HPT. Conclusion The Capacity to Drive Safely declines with chronological age, and this decline is associated with age-related declines in several higher order cognitive abilities involving manipulation and storage of visuospatial information under speeded conditions. There are also age-independent effects of cognitive function and vision that determine driving safety.
Resumo:
Research on strategic decision making (SDM) has proliferated in the last decades. Most of the studies however, focus on the process and content of SDM, whereas relatively little interest was awarded to the factors associated with the decision maker influencing SDM. Moreover, most of the research on SDM focuses on large multinationals and little to no research is available that studies the ways in which entrepreneurs make strategic choices. The present study reviews the entrepreneurial traits that influence SDM. These traits are selected by analyzing the literature on the differences between entrepreneurs and managers, under the assumption that these factors are the most indicative for the particularities of entrepreneurial SDM. One of the most important theoretical propositions resulting from this analysis concerns the mediating role of cognitive complexity in the relation between these entrepreneurial traits and SDM outcomes. Directions for further research emerging from this conceptualization are identified and discussed.
Resumo:
Abstract: How has human information behavior evolved? Our paper explores this question in the form of notions, models and theories about the relationship between information behavior and human evolution. Alexander’s Ecological Dominance and Social Competition/Cooperation (EDSC) model currently provides the most comprehensive overview of human traits in the development of a theory of human evolution and sociality. His model provides a basis for explaining the evolution of human socio-cognitive abilities, including ecological dominance, and social competition/cooperation. Our paper examines the human trait of information behavior as a socio-cognitive ability related to ecological dominance, and social competition/cooperation. The paper first outlines what is meant by information behavior from various interdisciplinary perspectives. We propose that information behavior is a socio-cognitive ability that is related to and enables other sociocognitive abilities such as human ecological dominance, and social competition/cooperation. The paper reviews the current state of evolutionary approaches to information behavior and future directions for this research . Keywords: information behavior, socio-cognitive ability, ecological dominance, social competition, social cooperation.