456 research outputs found
Assessing the Impact of Haptic Peripheral Displays for UAV Operators
Objectives: A pilot study was conducted to investigate the effectiveness of continuous haptic
peripheral displays in supporting multiple UAV supervisory control. Background: Previous
research shows that continuous auditory peripheral displays can enhance operator performance in
monitoring events that are continuous in nature, such as monitoring how well UAVs stay on their
pre-planned courses. This research also shows that auditory alerts can be masked by other
auditory information. Command and control operations are generally performed in noisy
environments with multiple auditory alerts presented to the operators. In order to avoid this
masking problem, another potentially useful sensory channel for providing redundant
information to UAV operators is the haptic channel. Method: A pilot experiment was conducted
with 13 participants, using a simulated multiple UAV supervisory control task. All participants
completed two haptic feedback conditions (continuous and threshold), where they received alerts
based on UAV course deviations and late arrivals to targets. Results: Threshold haptic feedback
was found to be more effective for late target arrivals, whereas continuous haptic feedback
resulted in faster reactions to course deviations. Conclusions: Continuous haptic feedback
appears to be more appropriate for monitoring events that are continuous in nature (i.e., how well
a UAV keeps its course). In contrast, threshold haptic feedback appears to better support
response to discrete events (i.e., late target arrivals). Future research: Because this is a pilot
study, more research is needed to validate these preliminary findings. A direct comparison
between auditory and haptic feedback is also needed to provide better insights into the potential
benefits of multi-modal peripheral displays in command and control of multiple UAVs.Prepared for Charles River Analytics, Inc
Robust Least Squares Methods Under Bounded Data Uncertainties
Cataloged from PDF version of article.We study the problem of estimating an unknown deterministic signal that is observed through
an unknown deterministic data matrix under additive noise. In particular, we present a minimax
optimization framework to the least squares problems, where the estimator has imperfect data
matrix and output vector information. We define the performance of an estimator relative to the
performance of the optimal least squares (LS) estimator tuned to the underlying unknown data
matrix and output vector, which is defined as the regret of the estimator. We then introduce an
efficient robust LS estimation approach that minimizes this regret for the worst possible data matrix
and output vector, where we refrain from any structural assumptions on the data. We demonstrate
that minimizing this worst-case regret can be cast as a semi-definite programming (SDP) problem.
We then consider the regularized and structured LS problems and present novel robust estimation
methods by demonstrating that these problems can also be cast as SDP problems. We illustrate
the merits of the proposed algorithms with respect to the well-known alternatives in the literature
through our simulations
Modified Cooper Harper scales for assessing unmanned vehicle displays
Unmanned vehicle (UV) displays are often the only information link between operators and vehicles, so their design is critical to mission success. However, there is currently no standardized methodology for operators to subjectively assess a display's support of mission tasks. This paper proposes a subjective UV display evaluation tool: the Modified Cooper-Harper for Unmanned Vehicle Displays (MCH-UVD). The MCH-UVD is adapted from the Cooper-Harper aircraft handling scale by shifting focus to support of operator information processing. An experiment was conducted to evaluate and refine the MCH-UVD, as well as assess the need for mission-specific versus general versions. Participants (86%) thought that MCH-UVD helped them identify display deficiencies, and 32% said that they could not have identified the deficiencies without the tool. No major additional benefits were observed with mission-specific versions over the general scale.U.S. Army Aberdeen Test Cente
Auditory Decision Aiding in Supervisory Control of Multiple Unmanned Aerial Vehicles
This paper investigates the effectiveness of sonification, continuous auditory alert mapped to the state of a monitored task, in supporting unmanned aerial vehicle (UAV) supervisory control. Background: UAV supervisory control requires monitoring each UAV across multiple tasks (e.g., course maintenance) via a predominantly visual display, which currently is supported with discrete auditory alerts. Sonification has been shown to enhance monitoring performance in domains such as anesthesiology by allowing an operator to immediately determine an entity's (e.g., patient) current and projected states, and is a promising alternative to discrete alerts in UAV control. However, minimal research compares sonification to discrete alerts, and no research assesses the effectiveness of sonification for monitoring multiple entities (e.g., multiple UAVs). Method: An experiment was conducted with 39 military personnel, using a simulated setup. Participants controlled single and multiple UAVs, and received sonifications or discrete alerts based on UAV course deviations and late target arrivals.
Results: Regardless of the number of UAVs supervised, the course deviation sonification resulted in 1.9 s faster reactions to course deviations, a 19% enhancement from discrete alerts. However, course deviation sonification interfered with the effectiveness of discrete late arrival alerts in general, and with operator response to late arrivals when supervising multiple vehicles.
Conclusions: Sonifications can outperform discrete alerts when designed to aid operators to predict future states of monitored tasks. However, sonifications may mask other auditory alerts, and interfere with other monitoring tasks that require divided attention.US Army through a Small Business Innovation Research led by Charles River Analytics, Inc
Phosphate release contributes to the rate-limiting step for unwinding by an RNA helicase
RNA helicases function in numerous aspects of RNA biology. These enzymes are RNA-stimulated ATPases that translocate on RNA and unwind or remodel structured RNA in an ATP-dependent fashion. How ATP and the ATPase cycle fuel the work performed by helicases is not completely clear. The hepatitis C virus RNA helicase, NS3, is an important model system for this class of enzymes. NS3 binding to a single-/double-strand RNA or DNA junction leads to ATP-independent melting of the duplex and formation of a complex capable of ATP-dependent unwinding by using a spring-loaded mechanism. We have established an RNA substrate for NS3 that can be unwound in a single sub-step. Our studies are consistent with a model in which a single ATP binding and/or hydrolysis event sets the unwinding spring and phosphate dissociation contributes to release of the spring, thereby driving the power stroke used for unwinding
Isoforms of U1-70k control subunit dynamics in the human spliceosomal U1 snRNP
Most human protein-encoding genes contain multiple exons that are spliced together, frequently in alternative arrangements, by the spliceosome. It is established that U1 snRNP is an essential component of the spliceosome, in human consisting of RNA and ten proteins, several of which are post- translationally modified and exist as multiple isoforms. Unresolved and challenging to investigate are the effects of these post translational modifications on the dynamics, interactions and stability of the particle. Using mass spectrometry we investigate the composition and dynamics of the native human U1 snRNP and compare native and recombinant complexes to isolate the effects of various subunits and isoforms on the overall stability. Our data reveal differential incorporation of four protein isoforms and dynamic interactions of subunits U1-A, U1-C and Sm-B/B’. Results also show that unstructured post- ranslationally modified C-terminal tails are
responsible for the dynamics of Sm-B/B’ and U1-C and that their interactions with the Sm core are controlled by binding to different U1-70k isoforms and their phosphorylation status in vivo. These results therefore provide the important functional link between proteomics and structure as well as insight into the dynamic quaternary structure of the native U1 snRNP important for its function.This work was funded by: BBSRC (OVM), BBSRC and EPSRC (HH and NM), EU Prospects (HH), European Science Foundation (NM), the Royal Society (CVR), and fellowship from JSPS and HFSP (YM and DAPK respectively)
Thermal error modelling for real-time error compensation
A modelling strategy for the prediction of both the scalar and the position-dependent thermal error components is presented. Two types of empirical modelling method based on the multiple regression analysis (MRA) and the artificial neural network (ANN) have been proposed for the real-time prediction of thermal errors with multiple temperature measurements. Both approaches have a systematic and computerised algorithm to search automatically for the nonlinear and interaction terms between different temperature variables. The experimental results on a machining centre show that both the MRA and the ANN can accurately predict the time-variant thermal error components under different spindle speeds and temperature fields. The accuracy of a horizontal machining centre can be improved through experiment by a factor of ten and the errors of a cut aluminium workpiece owing to thermal distortion have been reduced from 92.4 µm to 7.2 µm in the lateral direction. The depth difference due to the spindle thermal growth has been reduced from 196 µm to 8 µm.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/45884/1/170_2005_Article_BF01239613.pd
BoostingTree: parallel selection of weak learners in boosting, with application to ranking
Boosting algorithms have been found successful in many areas of machine learning and, in particular, in ranking. For typical classes of weak learners used in boosting (such as decision stumps or trees), a large feature space can slow down the training, while a long sequence of weak hypotheses combined by boosting can result in a computationally expensive model. In this paper we propose a strategy that builds several sequences of weak hypotheses in parallel, and extends the ones that are likely to yield a good model. The weak hypothesis sequences are arranged in a boosting tree, and new weak hypotheses are added to promising nodes (both leaves and inner nodes) of the tree using some randomized method. Theoretical results show that the proposed algorithm asymptotically achieves the performance of the base boosting algorithm applied. Experiments are provided in ranking web documents and move ordering in chess, and the results indicate that the new strategy yields better performance when the length of the sequence is limited, and converges to similar performance as the original boosting algorithms otherwise. © 2013 The Author(s)
Prevalence and features of ICF-disability in Spain as captured by the 2008 National Disability Survey
<p>Abstract</p> <p>Background</p> <p>Since 1986, the study of disability in Spain has been mainly addressed by National Disability Surveys (NDSs). While international attempts to frame NDS designs within the International Classification of Functioning, Disability and Health (ICF) have progressed, in general, the ICF has hardly been used in either the NDS or epidemiological studies. This study sought to identify ICF Activity- and Participation-related content in the most recent Spanish NDS, the 2008 Survey on Disabilities, Independence and Dependency Situations (<it>Encuesta sobre discapacidades, autonomía personal y situaciones de Dependencia </it>- <it>EDAD 2008</it>), and estimate the prevalence of such ICF-framed disability.</p> <p>Methods</p> <p><it>EDAD 2008 </it>methods and questions were perused. Of the 51 EDAD items analysed, 29 were backcoded to specific d2-d7 domains of the ICF Checklist and, by rating the recorded difficulty to perform specific tasks with or without help, these were then taken as performance and capacity respectively. A global ICF score was also derived, albeit lacking data for d1, "Learning and applying knowledge", d8, "Major Life Areas" and d9, "Community, Social and Civic Life". Data were grouped by sex, age, residence and initial positive screening, and prevalence figures were calculated by disability level both for the general population, using the originally designed weights, and for the population that had screened positive to disability. Data for institutionalised persons were processed separately.</p> <p>Results</p> <p>Crude prevalence of ICF severe/complete and moderate disability among the community-dwelling population aged ≥6 years was 0.9%-2.2% respectively, and that of severe/complete disability among persons living in sheltered accommodation was 0.3%.</p> <p>Prevalence of severe/complete disability was: higher in women than in men, 0.8% vs. 0.4%; increased with age; and was particularly high in domains such as "Domestic Life", 3.4%, "Mobility", 1.8%, and "Self-care", 1.9%, in which prevalence decreased when measured by reference to performance. Moreover, global scores indicated that severe/complete disability in these same domains was frequent among the moderately disabled group.</p> <p>Conclusions</p> <p>The <it>EDAD 2008 </it>affords an insufficient data set to be ICF-framed when it comes to the Activity and Participation domains. Notwithstanding their unknown validity, ratings for available ICF domains may, however, be suitable for consideration under the ADL model of functional dependency, suggesting that there are approximately 500,000 persons suffering from severe/complete disability and 1,000,000 suffering from moderate disability, with half the latter being severely disabled in domains capable of benefiting from technical or personal aid. Application of EDAD data to the planning of services for regions and other subpopulations means that need for personal help must be assessed, unmet needs ascertained, and knowledge of social participation and support, particularly for the mentally ill, improved. International, WHO-supported co-operation in ICF planning and use of NDSs in Spain and other countries is needed.</p
Evaluation of the ICT Tuberculosis test for the routine diagnosis of tuberculosis
BACKGROUND: Rapid and accurate diagnosis of tuberculosis (TB) is crucial to facilitate early treatment of infectious cases and thus to reduce its spread. To improve the diagnosis of TB, more rapid diagnostic techniques such as antibody detection methods including enzyme-linked immunosorbent assay (ELISA)-based serological tests and immunochromatographic methods were developed. This study was designed to evaluate the validity of an immunochromatographic assay, ICT Tuberculosis test for the serologic diagnosis of TB in Antalya, Turkey. METHODS: Sera from 72 patients with active pulmonary (53 smear-positive and 19 smear-negative cases) and eight extrapulmonary (6 smear-positive and 2 smear-negative cases) TB, and 54 controls from different outpatient clinics with similar demographic characteristics as patients were tested by ICT Tuberculosis test. RESULTS: The sensitivity, specificity, and negative predictive value of the ICT Tuberculosis test for pulmonary TB were 33.3%, 100%, and 52.9%, respectively. Smear-positive pulmonary TB patients showed a higher positivity rate for antibodies than smear-negative patients, but the difference was not statistically significant. Of the eight patients with extrapulmonary TB, antibody was detected in four patients. CONCLUSION: Our results suggest that ICT Tuberculosis test can be used to aid TB diagnosis in smear-positive patients until the culture results are available
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