Vision loss happens due to diabetic retinopathy (DR) in severe stages. Thus, an automatic detection method applied to diagnose DR in an earlier phase may help medical doctors to make better decisions. DR is considered one of the main risks, leading to blindness. Computer-Aided Diagnosis systems play an essential role in detecting features in fundus images. Fundus images may include blood vessels, exudates, micro-aneurysm, hemorrhages, and neovascularization. In this paper, our model combines automatic detection for the diabetic retinopathy classification with localization methods depending on weakly-supervised learning. The model has four stages; in stage one, various preprocessing techniques are applied to smooth the data set. In stage two, the network had gotten deeply to the optic disk segment for eliminating any exudate's false prediction because the exudates had the same color pixel as the optic disk. In stage three, the network is fed through training data to classify each label. Finally, the layers of the convolution neural network are re-edited, and used to localize the impact of DR on the patient's eye. The framework tackles the matching technique between two essential concepts where the classification problem depends on the supervised learning method. While the localization problem was obtained by the weakly supervised method. An additional layer known as weakly supervised sensitive heat map (WSSH) was added to detect the ROI of the lesion at a test accuracy of 98.65%, while comparing with Class Activation Map that involved weakly supervised technology achieved 0.954. The main purpose is to learn a representation that collect the central localization of discriminative features in a retina image. CNN-WSSH model is able to highlight decisive features in a single forward pass for getting the best detection of lesions.
The assessment of data quality from different sources can be considered as a key challenge in supporting effective geospatial data integration and promoting collaboration in mapping projects. This paper presents a methodology for assessing positional and shape quality for authoritative large-scale data, such as Ordnance Survey (OS) UK data and General Directorate for Survey (GDS) Iraq data, and Volunteered Geographic Information (VGI), such as OpenStreetMap (OSM) data, with the intention of assessing possible integration. It is based on the measurement of discrepancies among the datasets, addressing positional accuracy and shape fidelity, using standard procedures and also directional statistics. Line feature comparison has been und
... Show MoreThe coronavirus disease 2019 (COVID-19) pandemic and the infection escalation around the globe encourage the implementation of the global protocol for standard care patients aiming to cease the infection spread. Evaluating the potency of these therapy courses has drawn particular attention in health practice. This observational study aimed to assess the efficacy of Remdesivir and Favipiravir drugs compared to the standard care patients in COVID-19 confirmed patients. One hundred twenty-seven patients showed the disease at different stages, and one hundred and fifty patients received only standard care as a control group were included in this study. Patients under the Remdesivir therapy protocol were (62.20%); meanwhile, there (30.71
... Show MoreIn this study, aluminum alloyAA6061-T6 was joined by a hot press process with three types of material; polyamide PA 6.6 (nylon), 1% carbon nanotube/PA6.6 and 30% carbon fiber/PA6.6 composites. Three parameters were considered in the hot pressing; temperature (180, 200 and 220°C), pressure (2, 3, 4, 5 and 6 bar) and time of pressing (1, 2, 3, 4 and 5 minutes for 200ºC, and 0.25, 0.5, 0.75, 1 and 1.25 minutes for220ºC). Applied pressure has great effect on shear strength of the joint, corresponding to bonding time and temperature. Maximum shear strength was 8.89MPa obtained for PA6.6 at bonding conditions of 4 bar, 220ºC and 0.75 minute. For 30% carbon fiber/PA6,6 shear recorded was
In this paper the research represents an attempt of expansion in using the parametric and non-parametric estimators to estimate the median effective dose ( ED50 ) in the quintal bioassay and comparing between these methods . We have Chosen three estimators for Comparison. The first estimator is
( Spearman-Karber ) and the second estimator is ( Moving Average ) and The Third estimator is ( Extreme Effective Dose ) . We used a minimize Chi-square as a parametric method. We made a Comparison for these estimators by calculating the mean square error of (ED50) for each one of them and comparing it with the optimal the mean square
Varied uses of international rivers in the past few decades dramatically, resulting in this multiplicity of uses and all associated with it for the occurrence of freshwater scarcity activities, and thus an increase in conflicts and disputes around on the rights of each of the riparian countries to benefit from the waters of the river at various purposes, particularly the establishment of dams on some of them as is the case (Renaissance Ethiopian) big impact on downstream countries Dam (Egypt and Sudan), due to the Oukuahma at the end of the Nile Valley made them vulnerable to environmental fluctuations, political crises facing the Nile basin countries, and any reduction in the proportion of water is not only the Nile River, but for all r
... Show MoreOne of ciphering systems depends on transposition of letters in plain text to generate cipher text. The programming of transposition depends mainly on 2-dimension matrix in either methods but the difference is in columnar .We print columns in the matrix according to their numbers in key but in the fixed, the cipher text will be obtained by printing matrix by rows.
The study included the investigation of fungi ringed and inventory and Aflatoxins in rice and recorded average temperatures and humidity 22.75 degree Celsius and 13.2% respectively were obtained 1356 isolation innate possible diagnosis 15 species inherent in rice imported back to 8 races represented races b Fusarium , Cladosporium, Aspergillus and Alternaria
In this paper, a compression system with high synthetic architect is introduced, it is based on wavelet transform, polynomial representation and quadtree coding. The bio-orthogonal (tap 9/7) wavelet transform is used to decompose the image signal, and 2D polynomial representation is utilized to prune the existing high scale variation of image signal. Quantization with quadtree coding are followed by shift coding are applied to compress the detail band and the residue part of approximation subband. The test results indicate that the introduced system is simple and fast and it leads to better compression gain in comparison with the case of using first order polynomial approximation.