A DCT domain smart vicinity reliant fragile watermarking technique for DIBR 3D-TV

This work presents a vicinity reliant intelligent fragile watermarking scheme for depth image-based rendering technique used for three-dimensional television. Depth map of a centre image is implicitly inserted in the block-based discrete cosine transform (DCT) of the same using an aggregate, which also takes into account the presence of its neighbourhood blocks. Based upon the parity of a Boolean operation on the aggregate, parity is modulated which implicitly embeds the watermark. Genetic algorithm is then utilized to select the appropriate frequency bands in the DCT domain to become eligible for watermark embedding based on imperceptibility requirements. Experimental results demonstrate the usefulness of the proposed scheme in terms of its resistance against a set of fragile watermarking attacks and its ability to detect and localize tempering attempts

A Strategy for Classification of “Vaginal vs. Cesarean Section” Delivery: Bivariate Empirical Mode Decomposition of Cardiotocographic Recordings

We propose objective and robust measures for the purpose of classification of “vaginal vs. cesarean section” delivery by investigating temporal dynamics and complex interactions between fetal heart rate (FHR) and maternal uterine contraction (UC) recordings from cardiotocographic (CTG) traces. Multivariate extension of empirical mode decomposition (EMD) yields intrinsic scales embedded in UC-FHR recordings while also retaining inter-channel (UC-FHR) coupling at multiple scales. The mode alignment property of EMD results in the matched signal decomposition, in terms of frequency content, which paves the way for the selection of robust and objective time-frequency features for the problem at hand. Specifically, instantaneous amplitude and instantaneous frequency of multivariate intrinsic mode functions are utilized to construct a class of features which capture nonlinear and nonstationary interactions from UC-FHR recordings. The proposed features are fed to a variety of modern machine learning classifiers (decision tree, support vector machine, AdaBoost) to delineate vaginal and cesarean dynamics. We evaluate the performance of different classifiers on a real world dataset by investigating the following classifying measures: sensitivity, specificity, area under the ROC curve (AUC) and mean squared error (MSE). It is observed that under the application of all proposed 40 features AdaBoost classifier provides the best accuracy of 91.8% sensitivity, 95.5% specificity, 98% AUC, and 5% MSE. To conclude, the utilization of all proposed time-frequency features as input to machine learning classifiers can benefit clinical obstetric practitioners through a robust and automatic approach for the classification of fetus dynamics

Feature Quality-Based Dynamic Feature Selection for Improving Salient Object Detection

Salient object detection is typically accomplished by combining the outputs of multiple primitive feature detectors (that output feature maps or features). The diversity of images means that different basic features are useful in different contexts, which motivates the use of complementary feature detectors in a general setting. However, naive inclusion of features that are not useful for a particular image leads to a reduction in performance. In this paper, we introduce four novel measures of feature quality and then use those measures to dynamically select useful features for the combination process. The resulting saliency is thereby individually tailored to each image. Using benchmark data sets, we demonstrate the efficacy of our dynamic feature selection system by measuring the performance enhancement over the state-of-the-art models for complementary feature selection and saliency aggregation tasks. We show that a salient object detection technique using our approach outperforms competitive models on the PASCAL VOC 2012 dataset. We find that the most pronounced performance improvements occur in challenging images with cluttered backgrounds, or containing multiple salient objects.</p

Simulation of steam gasification of halophyte biomass for syngas production using Aspen Plus

Exploring the new non-edible source of biomass for green energy production becomes extremely important with the increase in global energy crises. The primary objective of this work is to evaluate the potential of halophyte (Phragmites australis), a salt-tolerant plant for syngas production, and provide it as a promising alternative biofuel for sustainable energy production. This study is based on the steady-state chemical equilibrium model simulation of steam gasification of halophyte biomass (Phragmites australis) with CO2 capture through sorbent (CaO) using ASPEN PLUS®. The simulation model works on the principle of Gibbs free energy minimization. The operating parameters such as temperature, steam to biomass ratio (STBR), and CaO/biomass ratio have been varied over a wide range. The effect of high heating value (HHV), low heating value (LHV), H2/CO, carbon conversion efficiency (CCE), and cold gas efficiency (CGE) has been investigated for syngas production. The results showed that with the increase of temperature from 600 to 700 °C, H2 concentration increased from 69.52 to 75.16 vol %, respectively. A reduction in CO2 concentration from 16.91 to 5.4 vol % is observed by increasing the CaO/biomass ratio from 0.1 to 0.9. It has been observed that the product gas hydrogen yield rises with increased temperature. At an optimum temperature of 700 °C with an STBR of 0.4 and CaO/biomass ratio of 1.42, the maximum hydrogen yield is 75.16 vol % with a minimum CO2 content of 5.4 vol %. At these optimum conditions, the values of HHV, LHV, CCE, and CGE are 13.32 MJ/Nm3, 15.20 MJ/Nm3, 42.91%, and 78.63%, respectively. In addition, the developed model is validated against published literature data, and the results show good agreement with the published data. The relative error for hydrogen and carbon monoxide is within limits, i.e., 3.02% and 0.67% at 700 °C, 5.30% and 3.61% at 600 °C, and 10.62% and 35.03% at 500 °C, respectively, which validates the proposed model. It can be concluded that the sorption-based biomass gasification process is a promising technique for greener syngas production.Scopu

Width-wise vessel bifurcation for improved retinal vessel segmentation

Width-wise vessel bifurcation for improved retinal vessel segmentatio

Global economic burden of unmet surgical need for appendicitis

Background There is a substantial gap in provision of adequate surgical care in many low- and middle-income countries. This study aimed to identify the economic burden of unmet surgical need for the common condition of appendicitis. Methods Data on the incidence of appendicitis from 170 countries and two different approaches were used to estimate numbers of patients who do not receive surgery: as a fixed proportion of the total unmet surgical need per country (approach 1); and based on country income status (approach 2). Indirect costs with current levels of access and local quality, and those if quality were at the standards of high-income countries, were estimated. A human capital approach was applied, focusing on the economic burden resulting from premature death and absenteeism. Results Excess mortality was 4185 per 100 000 cases of appendicitis using approach 1 and 3448 per 100 000 using approach 2. The economic burden of continuing current levels of access and local quality was US $92 492 million using approach 1 and$73 141 million using approach 2. The economic burden of not providing surgical care to the standards of high-income countries was $95 004 million using approach 1 and$75 666 million using approach 2. The largest share of these costs resulted from premature death (97.7 per cent) and lack of access (97.0 per cent) in contrast to lack of quality. Conclusion For a comparatively non-complex emergency condition such as appendicitis, increasing access to care should be prioritized. Although improving quality of care should not be neglected, increasing provision of care at current standards could reduce societal costs substantially

Global economic burden of unmet surgical need for appendicitis

Background There is a substantial gap in provision of adequate surgical care in many low- and middle-income countries. This study aimed to identify the economic burden of unmet surgical need for the common condition of appendicitis. Methods Data on the incidence of appendicitis from 170 countries and two different approaches were used to estimate numbers of patients who do not receive surgery: as a fixed proportion of the total unmet surgical need per country (approach 1); and based on country income status (approach 2). Indirect costs with current levels of access and local quality, and those if quality were at the standards of high-income countries, were estimated. A human capital approach was applied, focusing on the economic burden resulting from premature death and absenteeism. Results Excess mortality was 4185 per 100 000 cases of appendicitis using approach 1 and 3448 per 100 000 using approach 2. The economic burden of continuing current levels of access and local quality was US $92 492 million using approach 1 and$73 141 million using approach 2. The economic burden of not providing surgical care to the standards of high-income countries was $95 004 million using approach 1 and$75 666 million using approach 2. The largest share of these costs resulted from premature death (97.7 per cent) and lack of access (97.0 per cent) in contrast to lack of quality. Conclusion For a comparatively non-complex emergency condition such as appendicitis, increasing access to care should be prioritized. Although improving quality of care should not be neglected, increasing provision of care at current standards could reduce societal costs substantially