33 research outputs found

    Consistency of control performance in 3d overhead cranes under payload mass uncertainty

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    The paper addresses the problem of effectively and robustly controlling a 3D overhead crane under the payload mass uncertainty, where the control performance is shown to be consistent. It is proposed to employ the sliding mode control technique to design the closed-loop controller due to its robustness, regardless of the uncertainties and nonlinearities of the under-actuated crane system. The radial basis function neural network has been exploited to construct an adaptive mechanism for estimating the unknown dynamics. More importantly, the adaptation methods have been derived from the Lyapunov theory to not only guarantee stability of the closed-loop control system, but also approximate the unknown and uncertain payload mass and weight matrix, which maintains the consistency of the control performance, although the cargo mass can be varied. Furthermore, the results obtained by implementing the proposed algorithm in the simulations show the effectiveness of the proposed approach and the consistency of the control performance, although the payload mass is uncertain. © 2020 by the authors. Licensee MDPI, Basel, Switzerland

    Covid-19 Pandemic and Performance of Economic Sectors in Vietnam

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    Purpose of the paper: This study aims to consider the Covid impact on stock – price volatility of different industry groups in Vietnam by using the M-GARCH model

    Covid-19 Pandemic and Performance of Economic Sectors in Vietnam

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    Purpose of the paper: This study aims to consider the Covid impact on stock – price volatility of different industry groups in Vietnam by using the M-GARCH model

    Corporate governance and firm performance: Evidence from Vietnamese listed companies

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    The research aims to provide empirical evidence on the relationship between corporate governance and firm performance in Vietnam – a developing economy in Asia. It focuses on the corporate governance of Vietnamese listed companies with a data-set of the five-year period from 2011 to 2015. Vietnamese listed companies are governed and controlled by two boards, Board of Directors and Supervisory Board. The research investigates the impacts of directors’ and supervisors’ characteristics and ownership structure on firm performance. The outcomes reveal that most governance mechanisms employed by Vietnamese listed companies were not effective and had no effect on the companies’ performance, except for managerial ownership and Supervisory Board size. Specifically, management ownership and firm performance were negatively correlated. Additional analyses show a positive relationship between the number of supervisors and firm performance, which was measured by market-based measurement

    Robust Reflection Detection and Removal in Rainy Conditions using LAB and HSV Color Spaces

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    In the field of traffic monitoring systems, shadows are the main causes of errors in computer vision-based vehicle detection and classification. A great number of  research have been carried out to detect and remove shadows. However, these research works only focused on solving shadow problems in daytime traffic scenes. Up to now, far too little attention has been paid to the problem caused by vehicles’ reflections in rainy conditions. Unlike shadows in the daytime, which are homogeneous gray shades, reflection shadows are inhomogeneous regions of different colors. This characteristic makes reflections harder to detect and remove. Therefore, in this paper, we aim to develop a reflection detection and removal method from single images or video. Reflections are detected by determining a combination of L and B channels from LAB color space and H channel from HSV color space. The reflection removal method is performed by determining the optimal intensity of reflected areas so that they match with neighbor regions. The advantage of our method is that all reflected areas are removed without affecting vehicles’ textures or details

    Analytical study of the sth-order perturbative corrections to the solution to a one-dimensional harmonic oscillator perturbed by a spatially power-law potential Vper(x) = λxα

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    In this work, we present a rigorous mathematical scheme for the derivation of the sth-order perturbative corrections to the solution to a one-dimensional harmonic oscillator perturbed by the potential V-per(x) = lambda x(alpha), where alpha is a positive integer, using the non-degenerate time-independent perturbation theory. To do so, we derive a generalized formula for the integral I = integral(+infinity)(-infinity)x(alpha)exp(-x(2))H-n(x)H-m(x)d(x), where H-n(x) denotes the Hermite polynomial of degree n, using the generating function of orthogonal polynomials. Finally, the analytical results with alpha = 3 and alpha = 4 are discussed in detail and compared with the numerical calculations obtained by the Lagrange-mesh method

    Awareness and preparedness of healthcare workers against the first wave of the COVID-19 pandemic: A cross-sectional survey across 57 countries.

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    BACKGROUND: Since the COVID-19 pandemic began, there have been concerns related to the preparedness of healthcare workers (HCWs). This study aimed to describe the level of awareness and preparedness of hospital HCWs at the time of the first wave. METHODS: This multinational, multicenter, cross-sectional survey was conducted among hospital HCWs from February to May 2020. We used a hierarchical logistic regression multivariate analysis to adjust the influence of variables based on awareness and preparedness. We then used association rule mining to identify relationships between HCW confidence in handling suspected COVID-19 patients and prior COVID-19 case-management training. RESULTS: We surveyed 24,653 HCWs from 371 hospitals across 57 countries and received 17,302 responses from 70.2% HCWs overall. The median COVID-19 preparedness score was 11.0 (interquartile range [IQR] = 6.0-14.0) and the median awareness score was 29.6 (IQR = 26.6-32.6). HCWs at COVID-19 designated facilities with previous outbreak experience, or HCWs who were trained for dealing with the SARS-CoV-2 outbreak, had significantly higher levels of preparedness and awareness (p<0.001). Association rule mining suggests that nurses and doctors who had a 'great-extent-of-confidence' in handling suspected COVID-19 patients had participated in COVID-19 training courses. Male participants (mean difference = 0.34; 95% CI = 0.22, 0.46; p<0.001) and nurses (mean difference = 0.67; 95% CI = 0.53, 0.81; p<0.001) had higher preparedness scores compared to women participants and doctors. INTERPRETATION: There was an unsurprising high level of awareness and preparedness among HCWs who participated in COVID-19 training courses. However, disparity existed along the lines of gender and type of HCW. It is unknown whether the difference in COVID-19 preparedness that we detected early in the pandemic may have translated into disproportionate SARS-CoV-2 burden of disease by gender or HCW type

    Safety and efficacy of fluoxetine on functional outcome after acute stroke (AFFINITY): a randomised, double-blind, placebo-controlled trial

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    Background Trials of fluoxetine for recovery after stroke report conflicting results. The Assessment oF FluoxetINe In sTroke recoverY (AFFINITY) trial aimed to show if daily oral fluoxetine for 6 months after stroke improves functional outcome in an ethnically diverse population. Methods AFFINITY was a randomised, parallel-group, double-blind, placebo-controlled trial done in 43 hospital stroke units in Australia (n=29), New Zealand (four), and Vietnam (ten). Eligible patients were adults (aged ≥18 years) with a clinical diagnosis of acute stroke in the previous 2–15 days, brain imaging consistent with ischaemic or haemorrhagic stroke, and a persisting neurological deficit that produced a modified Rankin Scale (mRS) score of 1 or more. Patients were randomly assigned 1:1 via a web-based system using a minimisation algorithm to once daily, oral fluoxetine 20 mg capsules or matching placebo for 6 months. Patients, carers, investigators, and outcome assessors were masked to the treatment allocation. The primary outcome was functional status, measured by the mRS, at 6 months. The primary analysis was an ordinal logistic regression of the mRS at 6 months, adjusted for minimisation variables. Primary and safety analyses were done according to the patient's treatment allocation. The trial is registered with the Australian New Zealand Clinical Trials Registry, ACTRN12611000774921. Findings Between Jan 11, 2013, and June 30, 2019, 1280 patients were recruited in Australia (n=532), New Zealand (n=42), and Vietnam (n=706), of whom 642 were randomly assigned to fluoxetine and 638 were randomly assigned to placebo. Mean duration of trial treatment was 167 days (SD 48·1). At 6 months, mRS data were available in 624 (97%) patients in the fluoxetine group and 632 (99%) in the placebo group. The distribution of mRS categories was similar in the fluoxetine and placebo groups (adjusted common odds ratio 0·94, 95% CI 0·76–1·15; p=0·53). Compared with patients in the placebo group, patients in the fluoxetine group had more falls (20 [3%] vs seven [1%]; p=0·018), bone fractures (19 [3%] vs six [1%]; p=0·014), and epileptic seizures (ten [2%] vs two [<1%]; p=0·038) at 6 months. Interpretation Oral fluoxetine 20 mg daily for 6 months after acute stroke did not improve functional outcome and increased the risk of falls, bone fractures, and epileptic seizures. These results do not support the use of fluoxetine to improve functional outcome after stroke

    Local-Global Support for Earth Sciences: Economic Analysis

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    Most funding for science comes from taxpayers. So, it is very important to be able to convince taxpayers that this funding is potentially beneficial for them. This task is easier in Earth sciences, e.g., in meteorology, where there are clear local benefits. The problem is that while many people support local studies focused on their region, they do not always have a good understanding of the fact that effective local benefits require also studying surrounding areas -- and what should be the optimal balance between local and (more) global studies. In this paper, on a (somewhat) simplified model of the situation, we explain what is the appropriate balance. We hope that the corresponding methodology can (and will) be applied to more realistic -- and thus, more complex -- local-global models as well
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