12 research outputs found
Quadtree based mouse trajectory analysis for efficacy evaluation of voice-enabled CAD
Voice-enabled applications have caught considerable research interest in recent years. It is generally believed that voice based interactions can improve the working efficiencies and the overall productivities. Quantitative evaluations on the performance boost by using such Human-Computer interactions (HCI) are therefore necessary to justify the claimed efficacies and the usefulness of the HCI system. In this paper, a quadtree based approach is proposed to analyze the mouse movement distributions in the proposed Voice-enabled Computer-Aided Design (VeCAD) system. The mouse tracker keeps a record of all the mouse movement during the solid modeling process, and a quadtree based approach is applied to analyze the mouse trajectory distributions in both the traditional CAD and the VeCAD system. Our experiments show that the mouse movement is significantly reduced when voice is used to activate CAD modeling commands. ©2009 IEEE.published_or_final_versionThe IEEE International Conference on Virtual Environments, Human-Computer Interfaces, and Measurements Systems (VECIMS) 2009, Hong Kong, 11-13 May 2009. In Conference Proceedings, 2009, p. 196-20
Proceedings of the NASA Conference on Space Telerobotics, volume 2
These proceedings contain papers presented at the NASA Conference on Space Telerobotics held in Pasadena, January 31 to February 2, 1989. The theme of the Conference was man-machine collaboration in space. The Conference provided a forum for researchers and engineers to exchange ideas on the research and development required for application of telerobotics technology to the space systems planned for the 1990s and beyond. The Conference: (1) provided a view of current NASA telerobotic research and development; (2) stimulated technical exchange on man-machine systems, manipulator control, machine sensing, machine intelligence, concurrent computation, and system architectures; and (3) identified important unsolved problems of current interest which can be dealt with by future research
Design revolutions: IASDR 2019 Conference Proceedings. Volume 4: Learning, Technology, Thinking
In September 2019 Manchester School of Art at Manchester Metropolitan University was honoured to host the bi-annual conference of the International Association of Societies of Design Research (IASDR) under the unifying theme of DESIGN REVOLUTIONS. This was the first time the conference had been held in the UK. Through key research themes across nine conference tracks – Change, Learning, Living, Making, People, Technology, Thinking, Value and Voices – the conference opened up compelling, meaningful and radical dialogue of the role of design in addressing societal and organisational challenges. This Volume 4 includes papers from Learning, Technology and Thinking tracks of the conference
The 1989 Goddard Conference on Space Applications of Artificial Intelligence
The following topics are addressed: mission operations support; planning and scheduling; fault isolation/diagnosis; image processing and machine vision; data management; and modeling and simulation
Esprit '91. Proceedings of the annual Esprit conference. Brussels, 25-29 November 1991. EUR 13853 EN
Separator fluid volume requirements in multi-infusion settings
INTRODUCTION. Intravenous (IV) therapy is a widely used method for the administration of medication in hospitals worldwide. ICU and surgical patients in particular often require multiple IV catheters due to incompatibility of certain drugs and the high complexity of medical therapy. This increases discomfort by painful invasive procedures, the risk of infections and costs of medication and disposable considerably. When different drugs are administered through the same lumen, it is common ICU practice to flush with a neutral fluid between the administration of two incompatible drugs in order to optimally use infusion lumens. An important constraint for delivering multiple incompatible drugs is the volume of separator fluid that is sufficient to safely separate them. OBJECTIVES. In this pilot study we investigated whether the choice of separator fluid, solvent, or administration rate affects the separator volume required in a typical ICU infusion setting. METHODS. A standard ICU IV line (2m, 2ml, 1mm internal diameter) was filled with methylene blue (40 mg/l) solution and flushed using an infusion pump with separator fluid. Independent variables were solvent for methylene blue (NaCl 0.9% vs. glucose 5%), separator fluid (NaCl 0.9% vs. glucose 5%), and administration rate (50, 100, or 200 ml/h). Samples were collected using a fraction collector until <2% of the original drug concentration remained and were analyzed using spectrophotometry. RESULTS. We did not find a significant effect of administration rate on separator fluid volume. However, NaCl/G5% (solvent/separator fluid) required significantly less separator fluid than NaCl/NaCl (3.6 ± 0.1 ml vs. 3.9 ± 0.1 ml, p <0.05). Also, G5%/G5% required significantly less separator fluid than NaCl/NaCl (3.6 ± 0.1 ml vs. 3.9 ± 0.1 ml, p <0.05). The significant decrease in required flushing volume might be due to differences in the viscosity of the solutions. However, mean differences were small and were most likely caused by human interactions with the fluid collection setup. The average required flushing volume is 3.7 ml. CONCLUSIONS. The choice of separator fluid, solvent or administration rate had no impact on the required flushing volume in the experiment. Future research should take IV line length, diameter, volume and also drug solution volumes into account in order to provide a full account of variables affecting the required separator fluid volume
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ESICM LIVES 2017 : 30th ESICM Annual Congress. September 23-27, 2017.
INTRODUCTION. Unplanned readmission to intensive care is highly
undesirable in that it contributes to increased variance in care,
disruption, difficulty in resource allocation and may increase length
of stay and mortality particularly if subject to delays. Unlike the ICU
admission from the ward, readmission prediction has received
relatively little attention, perhaps in part because at the point of ICU
discharge, full physiological information is systematically available to
the clinician and so it is expected that readmission should be largely
due to unpredictable factors. However it may be that there are
multidimensional trends that are difficult for the clinician to perceive
that may nevertheless be predictive of readmission.
OBJECTIVES. We investigated whether machine learning (ML)
techniques could be used to improve on the simple published SWIFT
score [1] for the prediction of unplanned readmission to ICU within
48 hours.
METHODS. We extracted systolic BP, pulse pressure, heart and
respiration rate, temperature, SpO2, bilirubin, creatinine, INR, lactate,
white cell count, platelet count, pH, FiO2, and total Glasgow Coma
Score from ICU stays of over 2000 adult patients from our hospital
electronic patient record system. We trained our own custom
multidimensional / time-sensitive algorithmic ML system to predict
failed discharges defined as either readmission or unexpected death
within 48 hours of discharge. We used 10-fold cross validation to assess performance. We also assessed the effect of augmenting our
system by transfer learning (TL) with 44,000 additional cases from
the MIMIC III database.
RESULTS. The SWIFT score performed relatively poorly with an
AUROC of around 0.6 which our ML system trained on local data was
also able to match. However when augmented with an additional
dataset by TL, the AUROC for the ML system improved statistically
and clinically significantly to over 0.7.
CONCLUSIONS. Machine learning is able to improve on predictors
based on simple multiple logistic regression. Thus there is likely to
be information in the trends and in combinations of variables. A
disadvantage with this technique is that ML approaches require large
amounts of data for training. However, ML approaches can be
improved by TL. Basing prediction models on locally derived data
augmented by TL is a potentially novel approach to generating tools
that customised to the institution yet can exploit the potential power
of ML algorithms.
REFERENCES
[1] Gajic O, Malinchoc M, Comfere TB, et al. The Stability and
Workload Index for Transfer score predicts unplanned intensive care
unit patient readmission: initial development and validation. Crit Care
Med. 2008;36(3):676–82.
Grant Acknowledgement
This work was internally funded
Using MapReduce Streaming for Distributed Life Simulation on the Cloud
Distributed software simulations are indispensable in the study of large-scale life models but often require the use of technically complex lower-level distributed computing frameworks, such as MPI. We propose to overcome the complexity challenge by applying the emerging MapReduce (MR) model to distributed life simulations and by running such simulations on the cloud. Technically, we design optimized MR streaming algorithms for discrete and continuous versions of Conway’s life according to a general MR streaming pattern. We chose life because it is simple enough as a testbed for MR’s applicability to a-life simulations and general enough to make our results applicable to various lattice-based a-life models. We implement and empirically evaluate our algorithms’ performance on Amazon’s Elastic MR cloud. Our experiments demonstrate that a single MR optimization technique called strip partitioning can reduce the execution time of continuous life simulations by 64%. To the best of our knowledge, we are the first to propose and evaluate MR streaming algorithms for lattice-based simulations. Our algorithms can serve as prototypes in the development of novel MR simulation algorithms for large-scale lattice-based a-life models.https://digitalcommons.chapman.edu/scs_books/1014/thumbnail.jp