The Experts below are selected from a list of 246 Experts worldwide ranked by ideXlab platform
Pathik Mandal - One of the best experts on this subject based on the ideXlab platform.
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Improving process Improvement: executing the analyze and Improve Phases of DMAIC better
International Journal of Lean Six Sigma, 2012Co-Authors: Pathik MandalAbstract:Purpose – This paper aims to highlight that a define, measure, analyze, Improve, and control (DMAIC) project should be carried out keeping the broader business goal of achieving continuous Improvement in mind and that a design of experiment (DOE) based Improvement approach should be preferred to achieve this goal.Design/methodology/approach – “Ease of control” of the Improved process and “gain in process knowledge” from a DMAIC study are identified as two measures for judging the contribution of a DMAIC project towards continuous Improvement. Various Improvement approaches are classified into seven groups and the likely impact of each of these seven approaches on the above two quality measures are discussed.Findings – The Improvement approach adopted during the Improve Phase is partially determined by the nature of the root cause(s) – type X or type Y. The type Y root cause leads to the adoption of the “innovation‐prioritization” approach, which is very popular but has many limitations. Accordingly, an “a...
Peter R. Kinget - One of the best experts on this subject based on the ideXlab platform.
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Tail current-shaping to Improve Phase noise in LC voltage-controlled oscillators
IEEE Journal of Solid-State Circuits, 2006Co-Authors: Babak Soltanian, Peter R. KingetAbstract:This paper introduces a tail current-shaping technique in LC-VCOs to increase the amplitude and to reduce the Phase noise while keeping the power dissipation constant. The tail current is made large when the oscillator output voltage reaches its maximum or minimum value and when the sensitivity of the output Phase to injected noise is the smallest; the tail current is made small during the zero crossings of the output voltage when the Phase noise sensitivity is large. The Phase noise contributions of the active devices are decreased and the VCO has a larger oscillation amplitude and thus better DC to RF conversion compared to a standard VCO with equal power dissipation. A circuit design to implement tail current-shaping is presented that does not dissipate any extra power, does not use additional (noisy) active devices and occupies a small area. The operation and performance of the presented circuit is extensively analyzed and compared to an ideal pulse biased technique. The presented analysis is confirmed by measurement results of two 2-GHz differential nMOS VCOs fabricated in 0.25-mum BiCMOS process
Ruikang K Wang - One of the best experts on this subject based on the ideXlab platform.
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Strategies to Improve Phase-stability of ultrafast swept source optical coherence tomography for single shot imaging of transient mechanical waves at 16 kHz frame rate
Applied Physics Letters, 2016Co-Authors: Shaozhen Song, Bao-yu Hsieh, Tueng T. Shen, Ivan Pelivanov, Matthew O'donnell, Ruikang K WangAbstract:We present single-shot Phase-sensitive imaging of propagating mechanical waves within tissue, enabled by an ultrafast optical coherence tomography (OCT) system powered by a 1.628 MHz Fourier domain mode-locked (FDML) swept laser source. We propose a practical strategy for Phase-sensitive measurement by comparing the Phases between adjacent OCT B-scans, where the B-scan contains a number of A-scans equaling an integer number of FDML buffers. With this approach, we show that micro-strain fields can be mapped with ∼3.0 nm sensitivity at ∼16 000 fps. The system's capabilities are demonstrated on porcine cornea by imaging mechanical wave propagation launched by a pulsed UV laser beam, promising non-contact, real-time, and high-resolution optical coherence elastography.
Elizabeth G Ryan - One of the best experts on this subject based on the ideXlab platform.
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using bayesian adaptive designs to Improve Phase iii trials a respiratory care example
BMC Medical Research Methodology, 2019Co-Authors: Elizabeth G Ryan, Julie Bruce, Andrew J Metcalfe, Nigel Stallard, Sarah E Lamb, Kert Viele, Duncan YoungAbstract:Bayesian adaptive designs can Improve the efficiency of trials, and lead to trials that can produce high quality evidence more quickly, with fewer patients and lower costs than traditional methods. The aim of this work was to determine how Bayesian adaptive designs can be constructed for Phase III clinical trials in critical care, and to assess the influence that Bayesian designs would have on trial efficiency and study results. We re-designed the High Frequency OSCillation in Acute Respiratory distress syndrome (OSCAR) trial using Bayesian adaptive design methods, to allow for the possibility of early stopping for success or futility. We constructed several alternative designs and studied their operating characteristics via simulation. We then performed virtual re-executions by applying the Bayesian adaptive designs using the OSCAR data to demonstrate the practical applicability of the designs. We constructed five alternative Bayesian adaptive designs and identified a preferred design based on the simulated operating characteristics, which had similar power to the original design but recruited fewer patients on average. The virtual re-executions showed the Bayesian sequential approach and original OSCAR trial yielded similar trial conclusions. However, using a Bayesian sequential design could have led to a reduced sample size and earlier completion of the trial. Using the OSCAR trial as an example, this case study found that Bayesian adaptive designs can be constructed for Phase III critical care trials. If the OSCAR trial had been run using one of the proposed Bayesian adaptive designs, it would have terminated at a smaller sample size with fewer deaths in the trial, whilst reaching the same conclusions. We recommend the wider use of Bayesian adaptive approaches in Phase III clinical trials. OSCAR Trial registration ISRCTN, ISRCTN10416500 . Retrospectively registered 13 June 2007.
Long Wang - One of the best experts on this subject based on the ideXlab platform.
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a new strategy for parameter optimization to Improve Phase dependent locomotion mode recognition
Neurocomputing, 2015Co-Authors: Baojun Chen, Qining Wang, Enhao Zheng, Long WangAbstract:Phase-dependent recognition strategy is an effective approach for lower-limb locomotion mode recognition. However, in previous studies, classifiers, feature sets and other parameters for the classification are the same for all the Phases. The potential of this method could therefore be limited, as movement characteristics of different Phases are not the same. In this paper, we aim to further Improve Phase-dependent recognition by proposing a new parameter optimization strategy which optimizes classifier, feature set and window size individually for each Phase. Seven able-bodied subjects and one transtibial amputee subject are recruited in this research and they are required to perform six kinds of locomotion tasks. Signals recorded from two inertial measurement units and one pressure insole of the measured side are used for feature set calculation. And Phase-dependent recognition method with four Phases defined is applied for locomotion mode identification. The proposed strategy for parameter optimization is proved to be more efficient than the conventional optimization strategy by providing better overall recognition performance and lower computation burden.
