A proposed feature extraction algorithm for handwriting Arabic words. The proposed method uses a 4 levels discrete wavelet transform (DWT) on binary image. sliding window on wavelet space and computes the stander derivation for each window. The extracted features were classified with multiple Support Vector Machine (SVM) classifiers. The proposed method simulated with a proposed data set from different writers. The experimental results of the simulation show 94.44% recognition rate.

Correct grading of apple slices can help ensure quality and improve the marketability of the final product, which can impact the overall development of the apple slice industry post-harvest. The study intends to employ the convolutional neural network (CNN) architectures of ResNet-18 and DenseNet-201 and classical machine learning (ML) classifiers such as Wide Neural Networks (WNN), Naïve Bayes (NB), and two kernels of support vector machines (SVM) to classify apple slices into different hardness classes based on their RGB values. Our research data showed that the DenseNet-201 features classified by the SVM-Cubic kernel had the highest accuracy and lowest standard deviation (SD) among all the methods we tested, at 89.51 %  1.66 %. This

O estudo destaca a necessidade crítica de se focar nas capacidades físicas, motoras e técnicas das jogadoras de esgrima, desenvolvendo e testando metodologias de treino modernas, baseadas na ciência, adaptadas às exigências específicas do desporto. O objetivo do estudo foi avaliar a eficácia do treino tridimensional visando melhorar as capacidades motoras e o desempenho técnico dos participantes. Recorrendo a um desenho experimental, o estudo envolveu a formação de grupos experimentais e de controlo. A amostra incluiu 16 esgrimistas da Faculdade Feminina de Educação Física e Ciências do Desporto. Após a exclusão de dois jogadores durante a fase exploratória, os restantes 14 foram divididos igualmente em grupos experimental

The purpose of the current study was to explore the standards that teachers take into consideration when selecting and using assistive technology (AT), in addition to their knowledge and skills in this area. A quantitative, descriptive survey design was used and a convenience sample of 79 teachers of students with intellectual disabilities and autism spectrum disorder (ASD) participated in the current study. Based on the four main areas of the SETT Framework—student, environment, tasks, and tools—, teachers reported a lack consideration for most of the standards in each area. Among other findings, statistically significant differences were found between teachers’ standards of the SETT Framework, with teachers who had previous profe

This research considers the preservation of environment through recycling old toys. This is achieved by transforming the old toys into educational clothing accessories for kindergarten stages. The research methodology adapts both descriptive and applied approaches. The research questionnaire targeted a sample of 35 teachers to collect information about the waste toys in kindergarten. Also, another sample of 30 teachers and mothers were targeted to measure the suitability of the clothing designs for the early childhood stages. The results shows that both teachers and mothers were well satisfied with clothing accessories designed with the toys waste. This concept contributes to limiting the pollution caused by toys and could save time, eff

The tongue is one of the important organs of vertebrates, as it plays an important role in the process of food intake, absorption and swallowing, It varies the morphological according to the organism, the habitat, and the nature of the food for it. The aim of the study is to reveal the histologist structure of the tongue of the guinea pig(Cavia porcellus), where we took three samples of adult males, and crosses the tongue similar to rodents, except for some differences in terms of the epithelial layers, mucosa, the muscular layer, the number of tongue layers and the spread of papillae on the tongue, which is, differences due to adaptation to the habitat and their diet.

Lung cancer, similar to other cancer types, results from genetic changes. However, it is considered as more threatening due to the spread of the smoking habit, a major risk factor of the disease. Scientists have been collecting and analyzing the biological data for a long time, in attempts to find methods to predict cancer before it occurs. Analysis of these data requires the use of artificial intelligence algorithms and neural network approaches. In this paper, one of the deep neural networks was used, that is the enhancer Deep Belief Network (DBN), which is constructed from two Restricted Boltzmann Machines (RBM). The visible nodes for the first RBM are 13 nodes and 8 nodes in each hidden layer for the two RBMs. The enhancer DBN was tr