During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieved lower computational complexity and number of layers, while being more reliable compared with other algorithms applied to recognize face masks. The findings reveal that the model's validation accuracy reaches 97.55% to 98.43% at different learning rates and different values of features vector in the dense layer, which represents a neural network layer that is connected deeply of the CNN proposed model training. Finally, the suggested model enhances recognition performance parameters such as precision, recall, and area under the curve (AUC).
The current research aims to prepare a proposed Programmebased sensory integration theory for remediating some developmental learning disabilities among children, researchers prepared a Programme based on sensory integration through reviewing studies related to the research topic that can be practicedby some active teaching strategies (cooperative learning, peer learning, Role-playing, and educational stories). The Finalformat consists of(39) training sessions.
This paper presents a new algorithm in an important research field which is the semantic word similarity estimation. A new feature-based algorithm is proposed for measuring the word semantic similarity for the Arabic language. It is a highly systematic language where its words exhibit elegant and rigorous logic. The score of sematic similarity between two Arabic words is calculated as a function of their common and total taxonomical features. An Arabic knowledge source is employed for extracting the taxonomical features as a set of all concepts that subsumed the concepts containing the compared words. The previously developed Arabic word benchmark datasets are used for optimizing and evaluating the proposed algorithm. In this paper,
... Show MoreCompetitive advantage is a substantial strategic objective for organizations. It requires high levels in the quality of products and services provided to customers, continuous improvement of costing , care for creativity and innovative employees, and speed unique to the marketing and financial engineering, and business re-engineering processes. The situation in this area, requires actors to attract and develop human resources, including help in proper implementation of the strategic tasks that targeted by those institutions. According to the opinions and viewpoints of management scholars, the competitive advantage resource is the most important issue for organizations in the third millennium, which can be a
... Show MoreModern French novel has gained a distinctive status in the history of French literature during the first half of the twentieth century. This is due to many factors including the new literary descriptive objective style adopted by novelists like Alain Robbe – Grillet that has long been regarded as the outstanding writer of the nouveau roman, as well as its major spokesman, a representative writer and a leading theoretician of the new novel that has broken the classical rules of the one hero and evolved, through questioning the relationship of man and the world and reevaluating the limits of contemporary fiction , into creating a new form of narrative.
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En vue de résu
... Show MoreA new technique for embedding image data into another BMP image data is presented. The image data to be embedded is referred to as signature image, while the image into which the signature image is embedded is referred as host image. The host and the signature images are first partitioned into 8x8 blocks, discrete cosine transformed “DCT”, only significant coefficients are retained, the retained coefficients then inserted in the transformed block in a forward and backward zigzag scan direction. The result then inversely transformed and presented as a BMP image file. The peak signal-to-noise ratio (PSNR) is exploited to evaluate the objective visual quality of the host image compared with the original image.
The research aimed to identify “The impact of an instructional-learning design based on the brain- compatible model in systemic thinking among first intermediate grade female students in Mathematics”, in the day schools of the second Karkh Educational directorate.In order to achieve the research objective, the following null hypothesis was formulated:There is no statistically significant difference at the significance level (0.05) among the average scores of the experimental group students who will be taught by applying an (instructional- learning) design based to on the brain–compatible model and the average scores of the control group students who will be taught through the traditional method in the systemic thinking test.The resear
... Show MoreThis study aims to improve the quality of satellites signals in addition to increase accuracy level delivered from handheld GPS data by building up a program to read and decode data of handheld GPS. Where, the NMEA protocol file, which stands for the National Marine Electronics Association, was generated from handheld GPS receivers in real time using in-house design program. The NMEA protocol file provides ability to choose points positions with best status level of satellites such as number of visible satellite, satellite geometry, and GPS mode, which are defined as accuracy factors. In addition to fix signal quality, least squares technique was adopted in this study to minimize the residuals of GPS observations and enh
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The research utilizes data produced by the Local Urban Management Directorate in Najaf and the imagery data from the Landsat 9 satellite, after being processed by the GIS tool. The research follows a descriptive and analytical approach; we integrated the Markov chain analysis and the cellular automation approach to predict transformations in city structure as a result of changes in land utilization. The research also aims to identify approaches to detect post-classification transformations in order to determine changes in land utilization. To predict the future land utilization in the city of Kufa, and to evaluate data accuracy, we used the Kappa Indicator to determine the potential applicability of the probability matrix that resulted from
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