ORCID Profile
0000-0002-9209-9524
Current Organisations
University of South Australia
,
CSIRO
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Publisher: Walter de Gruyter GmbH
Date: 2016
Abstract: This article presents a comprehensive study of 30 color transforms to accurately segment images of halftone prints and thus calculating the parameters of a color prediction model. The transforms are evaluated combining three metrics: the model accuracy,Otsu’s discriminant, and correlation coefficients of histograms. Hierarchical cluster analysis is applied to determine the thresholds to segment the image histogram into paper, ink and mixed area. Among the 30 different transforms discussed in this article, 21 channels are of 7 color space models (RGB, CMYK, CIELAB, HSV, YIQ, YCbCr, and XYZ) and the other 9 channels are specially designed. Notable increase in model accuracy validates the segmentation accuracy and the necessity of choosing the appropriate transform. A set of 180 halftone images of different print properties (such as paper, halftone, ink and printing technology) has been used for the evaluation. It is found that, the most appropriate transform depends on the type of primary ink, but the corresponding transforms in CMYK color space model have shown consistent performance. CMYK-C, XYZ-Y and LAB-B are the best transforms for Cyan, Magenta and Yellow ink color respectively. YIQ-I and HSV-S are good candidates if a single transform is to be chosen for all primary ink colors.
Publisher: Public Library of Science (PLoS)
Date: 24-09-2021
DOI: 10.1371/JOURNAL.PONE.0257300
Abstract: Many in iduals visit rural telemedicine centres to obtain safe and effective health remedies for their physical and emotional illnesses. This study investigates the antecedents of patients’ satisfaction relating to telemedicine adoption in rural public hospitals settings in Bangladesh through the adaptation of Expectation Disconfirmation Theory extended by Social Cognitive Theory. This research advances a theoretically sustained prediction model forecasting patients’ satisfaction with telemedicine to enable informed decision making. A research model explores four potential antecedents: expectations, performance, disconfirmation, and enjoyment that significantly contribute to predicting patients’ satisfaction concerning telemedicine adoption in Bangladesh. This model is validated using two-staged structural equation modeling and artificial neural network approaches. The findings demonstrate the determinants of patients’ satisfaction with telemedicine. The presented model will assist medical practitioners, academics, and information systems practitioners to develop high-quality decisions in the future application of telemedicine. Pertinent implications, limitations and future research directions are endorsed securing long-term telemedicine sustainability.
Publisher: IEEE
Date: 05-2016
Publisher: Springer Science and Business Media LLC
Date: 20-11-2015
Publisher: World Scientific Pub Co Pte Ltd
Date: 26-05-2022
DOI: 10.1142/S0219622022500249
Abstract: This study aims to adapt the Expectation Disconfirmation Theory and Technology Adoption Model to unveil provocative roles in patients’ satisfaction cognitions and subsequent continuity behaviors pertaining to telemedicine services in rural Bangladesh. A quantitative research model is developed and validated using a two-staged deep neural network and partial least squares structural equation modeling approach. The findings of this study provide evidence that five salient determinants expectations, disconfirmation, performance, usefulness, and ease of use dominantly contribute to predicting patients’ satisfaction concerning continuity with telemedicine. This contributes to health informatics and behavioral literature by clarifying the complex interplay between patients’ satisfaction and determinants of continuity behavior in telemedicine’s domain. The findings provide novel insights into predictions of complex patients’ attitudes toward telemedicine continuity, and dynamic changes in adoption trends thereby assisting health professionals, global health experts, policymakers, and IS community in making higher quality informed decisions for people-centered future models of care.
No related grants have been discovered for Md Zahidul Islam.