Clinical keratoconus (KCN) detection is a challenging and time-consuming task. In the diagnosis process, ophthalmologists must revise demographic and clinical ophthalmic examinations. The latter include slit-lamb, corneal topographic maps, and Pentacam indices (PI). We propose an Ensemble of Deep Transfer Learning (EDTL) based on corneal topographic maps. We consider four pretrained networks, SqueezeNet (SqN), AlexNet (AN), ShuffleNet (SfN), and MobileNet-v2 (MN), and fine-tune them on a dataset of KCN and normal cases, each including four topographic maps. We also consider a PI classifier. Then, our EDTL method combines the output probabilities of each of the five classifiers to obtain a decision based on the fusion of probabilities. Individually, the classifier based on PI achieved 93.1% accuracy, whereas the deep classifiers reached classification accuracies over 90% only in isolated cases. Overall, the average accuracy of the deep networks over the four corneal maps ranged from 86% (SfN) to 89.9% (AN). The classifier ensemble increased the accuracy of the deep classifiers based on corneal maps to values ranging (92.2% to 93.1%) for SqN and (93.1% to 94.8%) for AN. Including in the ensemble-specific combinations of corneal maps’ classifiers and PI increased the accuracy to 98.3%. Moreover, visualization of first learner filters in the networks and Grad-CAMs confirmed that the networks had learned relevant clinical features. This study shows the potential of creating ensembles of deep classifiers fine-tuned with a transfer learning strategy as it resulted in an improved accuracy while showing learnable filters and Grad-CAMs that agree with clinical knowledge. This is a step further towards the potential clinical deployment of an improved computer-assisted diagnosis system for KCN detection to help ophthalmologists to confirm the clinical decision and to perform fast and accurate KCN treatment.
The aim of this study to identity using Daniel's model and Driver’s model in learning a kinetic chain on the uneven bars in the artistic gymnastics for female students. The researchers used the experimental method to design equivalent groups with a preand post-test, and the research community was identified with the students of the third stage in the college for the academic year 2020-2021 .The subject was, (3) class were randomly selected, so (30) students distributed into (3) groups). has been conducted pretesting after implementation of the curriculum for (4) weeks and used the statistical bag of social sciences(SPSS)to process the results of the research and a set of conclusions was reached, the most important of which is t
... Show Moreهدفت الدراسة الى الاهتمام واستغلال ماهو جديد من تقنيات واجهزة حديثة في تعليم السباحة الحرة عن طريق توجيه الاطفال على تطوير مداركهم واستيعابهم بالتطور التكنولوجي الذي يتناوله العالم ،قامت الباحثتان باعداد منهج تعليمي باستخدام نظارة الواقع الافتراضي وذالك بتوفير بيئة مشابهة للبيئة الحقيقية تحاكي مدارك عقول الاطفال في عالم افتراضي لتتكون صورة كاملة عن مهارات السباحة الحرة ،ومن هنا اتت المشكلة نتيجة تعل
... Show MoreRecently, a great rise in the population and fast manufacturing processes were noticed. These processes release significant magnitudes of waste. These wastes occupied a notable ground region, generating big issues for the earth and the environment. To enhance the geotechnical properties of fine-grained soil, a sequence of research projects in the lab were conducted to analyze the impacts of adding sludge waste (SW). The tests were done on both natural and mixed soil with SW at various proportions (2%, 4%, 6%, 8%, and 10%) based on the dry mass of the soil used. The experiments conducted focused on consistency, compaction, and shear strength. With the addition of 10% of SW, the values of LL and PI decreased by 29.7% and 3
... Show MoreThe development of new cephalosporins with improved activity against resistant microbes, such as, MRSA (methicillin resistant Staph. aureus), P. aeruginosa, is of high potential. Chemical synthesis of two new series of thiadiazole linked to cysteine (series 1) and cephalosporins containing thiadiazole linked to cysteine through disulfide bond (series 2) were achieved. The chemical structures of the synthesized compounds were confirmed using spectral (FT-IR, 1H-NMR) and elemental microanalysis. The incorporation of privileged chemical moieties, such as, thiadiazole, Schiff base, cysteine and sulfonamide, has been found to have great contribution to the antimicrobial activities. Compounds of series 1 (1
... Show MorePermeability estimation is a vital step in reservoir engineering due to its effect on reservoir's characterization, planning for perforations, and economic efficiency of the reservoirs. The core and well-logging data are the main sources of permeability measuring and calculating respectively. There are multiple methods to predict permeability such as classic, empirical, and geostatistical methods. In this research, two statistical approaches have been applied and compared for permeability prediction: Multiple Linear Regression and Random Forest, given the (M) reservoir interval in the (BH) Oil Field in the northern part of Iraq. The dataset was separated into two subsets: Training and Testing in order to cross-validate the accuracy
... Show MoreMany consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is s
... Show MoreAnomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the
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