Modified canny edge detection technique for identifying endpoints

Edge detection is an image processing technique that retains the edges of an object in an image while discarding other features. The Canny edge detection technique is regarded as one of the most successful edge detection algorithms because of the good edge detection effect. However, one of its problems is the discontinued edges. In this paper, we present an endpoint identification algorithm that can pinpoint the position of the discontinued edges. After the endpoints are identified, they are paired together based on distance, and the broken gaps are filled by connecting the endpoints. Results have shown that, visually, our method has fewer discontinued edges when compared to Canny. Also, the mean square error of our method is lower than traditional Canny, indicating that our technique produces edge images that are more accurate than the traditional Canny

Enhanced Canny edge detection for Covid-19 and pneumonia X-Ray images

In image processing, one of the most fundamental technique is edge detection. It is a process to detect edges from images by identifying discontinuities in brightness. In this research, we present an enhanced Canny edge detection technique. This method integrates local morphological contrast enhancement and Canny edge detection. Furthermore, the proposed edge detection technique was also applied for pneumonia and COVID-19 detection in digital x-ray images by utilising convolutional neural networks. Results show that this enhanced Canny edge detection technique is better than the traditional Canny technique. Also, we were able to produce classifiers that can classify edge x-ray images into COVID-19, normal, and pneumonia classes with high accuracy, sensitivity, and specificity

A survey on proof of retrievability for cloud data integrity and availability: cloud storage state-of-the-art, issues, solutions and future trends

Cloud storage has emerged as the latest trend for data storage over the traditional storage method which consume more storage spaces of data owner resources for backup and disaster recovery purposes. Due to the openness nature of cloud storage, trustworthy to the storage providers remains a critical issue amongst data owners. Hence, a huge number of businesses around the world remains choosing traditional storage method over cloud storage. This indicates a need for cloud storage providers to adopt cloud integrity schemes to ensure the outsourced data is secured to gain trustworthiness from clients. There are two main cloud integrity schemes available to ensure data integrity and availability: (i) Provable Data Possession (PDP) and (ii) Proof of Retrievability (PoR). PDP and PoR are protocols designed for cloud storage to proof to clients that the stored data is intact. Although PDP and PoR have similar functionality for providing cloud data integrity and availability, PoR is found to be much better than PDP with respect to full data retrievability as PoR provides recovery to faulty or corrupted outsourced data in which PDP does not cover. The objective of this paper is to examine the state-of-the-art of PoR and subsequently to identify the issues of employing PoR on cloud storage and suggest possible solutions. We analyse available PoR schemes. Then, the issues and challenges as a result of employing PoR specifically and cloud storage generally are described. Some possible countermeasures to address the identified issues are suggested. Finally, the potential future work of PoR schemes and future trends of cloud storage are presente

COVID-19 detection using deep learning classifiers and contrast-enhanced canny edge detected x-ray images

COVID-19 is a deadly disease, and should be efficiently detected. COVID-19 shares similar symptoms with pneumonia, another type of lung disease, which remains a cause of morbidity and mortality. This article aims to demonstrate an ensemble deep learning approach that can differentiate COVID-19 and pneumonia based on chest X-ray images. The original X-ray images were processed to produce two sets of images with different features. The first set was images enhanced with contrast limited adaptive histogram equalization. The second set was edge images produced by contrast-enhanced canny edge detection. Convolutional neural networks were used to extract features from the images and train classifiers, which were able to classify COVID-19, pneumonia, and healthy lungs cases. Results show that the classifiers were able to differentiate X-rays of different classes, where the best performing ensemble achieved an overall accuracy of 97.90%, with a sensitivity of 99.47%, and specificity of 98.94% for COVID-19 detection

Factors Associated with Mutations: Their Matching Rates to Cardiovascular and Neurological Diseases

Monogenic hypertension is rare and caused by genetic mutations, but whether factors associated with mutations are disease-specific remains uncertain. Given two factors associated with high mutation rates, we tested how many previously known genes match with (i) proximity to telomeres or (ii) high adenine and thymine content in cardiovascular diseases (CVDs) related to vascular stiffening. We extracted genomic information using a genome data viewer. In human chromosomes, 64 of 79 genetic loci involving \u3e25 rare mutations and single nucleotide polymorphisms satisfied (i) or (ii), resulting in an 81% matching rate. However, this high matching rate was no longer observed as we checked the two factors in genes associated with essential hypertension (EH), thoracic aortic aneurysm (TAA), and congenital heart disease (CHD), resulting in matching rates of 53%, 70%, and 75%, respectively. A matching of telomere proximity or high adenine and thymine content projects the list of loci involving rare mutations of monogenic hypertension better than those of other CVDs, likely due to adoption of rigorous criteria for true-positive signals. Our data suggest that the factor–disease matching rate is an accurate tool that can explain deleterious mutations of monogenic hypertension at a \u3e80% match—unlike the relatively lower matching rates found in human genes of EH, TAA, CHD, and familial Parkinson’s disease

The Explanatory Sentence in Arabic Grammar: An Opinion on the Significance and the Place of Syntax

This study attempts to reveal the nature of the explanatory sentence in its two types, and to discuss the positions of grammarians regarding its relevance and definition, taking into consideration the positions of grammarians, their approaches and trends in linguistic analysis, and their preferences in what they have taken regarding this issue. Based on the descriptive and analytical approaches that it adopted, the study was able to add some of the connotations and meanings that the explanatory sentence conveys through the texts and evidence that it included. It discussed some of the well-established connotations that grammarians believed and gave weight to what it reassured with its weightings

Viral metagenomics analysis of stool specimens from children with unresolved gastroenteritis in Qatar

Acute gastroenteritis (AGE) is associated with significant global morbidity and mortality, especially among children under five years of age. Viruses are well established as etiologic agents of gastroenteritis since they are the most common pathogens that contribute to the disease burden in developing countries. Despite the advances in molecular diagnosis, a substantial proportion of AGE etiology remain unresolved. We implemented a viral metagenomics pipeline to determine the potential viral etiology associated with AGE among children under the age of five years in Qatar with undiagnosed etiology. Following enriching for the viral genome, ∼1.3 billion sequences were generated from 89 stool specimens using the Illumina HiSeq platform, of which 7% were mapped to viral genomes. Human viruses were detected in 34 specimens (38.2%); 14 were adenovirus, nine coxsackievirus A16, five rotavirus (G9P[8] and G4P[8]), four norovirus (GII), one influenza A virus (H3), and one respiratory syncytial virus A (RSVA). In conclusion, the viral metagenomics approach is useful for determining AGE's etiology when routine molecular diagnostic assays fail.This study was supported by Qatar National Research Fund (QNRF) funding, grant # NPRP 9–133–1-025, and partial funding from Hamad Medical Corporation, grant # 16173/16

Home exposure to Arabian incense (bakhour) and asthma symptoms in children: a community survey in two regions in Oman

<p>Abstract</p> <p>Background</p> <p>Incense burning has been reported to adversely affect respiratory health. The aim of this study was to explore whether exposure to bakhour contributes to the prevalence of asthma and/or triggers its symptoms in Omani children by comparing two Omani regions with different prevalence of asthma.</p> <p>Methods</p> <p>A randomly selected sample of 10 years old schoolchildren were surveyed using an Arabic version of ISAAC Phase II questionnaires with the addition of questions concerning the use and effect of Arabian incense on asthma symptoms. Current asthma was defined as positive response to wheeze in the past 12 months or positive response to "ever had asthma" together with a positive response to exercise wheeze or night cough in the past 12 months. Simple and multivariable logistic regression analyses were performed to estimate the effect of bakhour exposure and other variables on current asthma diagnosis and parents' response to the question: "Does exposure to bakhour affect your child breathing?"</p> <p>Results</p> <p>Of the 2441 surveyed children, 15.4% had current asthma. Bakhour use more than twice a week was three times more likely to affect child breathing compared to no bakhour use (adjusted OR 3.01; 95% CI 2.23–4.08) and this effect was 2.55 times higher in asthmatics (adjusted OR 2.55; 95% CI 1.97–3.31) compared to non-asthmatics. In addition, bakhour caused worsening of wheeze in 38% of the asthmatics, making it the fourth most common trigger factor after dust (49.2%), weather (47.6%) and respiratory tract infections (42.2%). However, there was no significant association between bakhour use and the prevalence of current asthma (adjusted OR 0.87; 95% CI 0.63–1.20).</p> <p>Conclusion</p> <p>Arabian incense burning is a common trigger of wheezing among asthmatic children in Oman. However, it is not associated with the prevalence asthma.</p

Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10&nbsp;years; 78.2% included were male with a median age of 37&nbsp;years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020

Erratum to: 36th International Symposium on Intensive Care and Emergency Medicine

[This corrects the article DOI: 10.1186/s13054-016-1208-6.]