Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You only look once”) neural network algorithm, which is an efficient real-time object identification algorithm, an intelligent system was developed in this thesis to distinguish which faces are wearing a mask and who is not wearing a wrong mask. The proposed system was developed based on data preparation, preprocessing, and adding a multi-layer neural network, followed by extracting the detection algorithm to improve the accuracy of the system. Two global data sets were used to train and test the proposed system and worked on it in three models, where the first contains the AIZOO data set, the second contains the MoLa RGB CovSurv data set, and the third model contains a combined data set for the two in order to provide cases that are difficult to identify and the accuracy results that were obtained. obtained from the merging datasets showed that the face mask (0.953) and the face recognition system were the most accurate in detecting them (0.916).
Bootstrap is one of an important re-sampling technique which has given the attention of researches recently. The presence of outliers in the original data set may cause serious problem to the classical bootstrap when the percentage of outliers are higher than the original one. Many methods are proposed to overcome this problem such Dynamic Robust Bootstrap for LTS (DRBLTS) and Weighted Bootstrap with Probability (WBP). This paper try to show the accuracy of parameters estimation by comparison the results of both methods. The bias , MSE and RMSE are considered. The criterion of the accuracy is based on the RMSE value since the method that provide us RMSE value smaller than other is con
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Computer-aided diagnosis (CAD) has proved to be an effective and accurate method for diagnostic prediction over the years. This article focuses on the development of an automated CAD system with the intent to perform diagnosis as accurately as possible. Deep learning methods have been able to produce impressive results on medical image datasets. This study employs deep learning methods in conjunction with meta-heuristic algorithms and supervised machine-learning algorithms to perform an accurate diagnosis. Pre-trained convolutional neural networks (CNNs) or auto-encoder are used for feature extraction, whereas feature selection is performed using an ant colony optimization (ACO) algorithm. Ant colony optimization helps to search for the bes
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In recent years, English language teaching and second language acquisition has demonstrated a significant accentuation upon basic reasoning abilities improvement in the language capability advancement. Encouraging a point of view of duty to training basic intuition aptitudes in accordance with the English language courses, this paper gives an account of an investigation directed at theoretical meanings of basic deduction, drifts about the centrality of basic speculation for language educating and associations between critical thinking and language learning. The educators have the focal pretended by basic intuition in successful language teaching method, identified to Ennis’ (2011) critical thinking categories. The skill of thinking critic
... Show MoreThis study was conducted to investigate the presence of Staphylococcus aureus in the red and white meat available in local markets. They were selected ten samples of red and white meat randomly (Iraq, Saudi Arabia, Turkey, and Brazil) from different markets in Baghdad, and the results of reading the nutrition facts of media indication card showed that all models confirm to the Iraqi standard quality in terms of scanning all data of the media indication card, except for the birds of Bayader, where the date of expire & production date of the product was not mentioned. Also, the results of the study showed that there is no Staphylococcus aureus in local red and white meat as well as imported.
Coumarins have been recognized as anticancer competitors. HDACis are one of the interesting issues in the field of antitumor research. In order to achieve an increased anticancer efficacy, a series of hybrid compounds bearing coumarin scaffolds have been designed and synthesized as novel HDACis, In this review we present a series of novel HDAC inhibitors comprising coumarin as a core e of cap group of HDAC inhibitors that have been designed, synthesized and assessed for their enzyme inhibitory activity as well as antiproliferative activity. Most of them exhibited potent HDAC inhibitory activity and significant cytotoxicity
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Compression for color image is now necessary for transmission and storage in the data bases since the color gives a pleasing nature and natural for any object, so three composite techniques based color image compression is implemented to achieve image with high compression, no loss in original image, better performance and good image quality. These techniques are composite stationary wavelet technique (S), composite wavelet technique (W) and composite multi-wavelet technique (M). For the high energy sub-band of the 3 rd level of each composite transform in each composite technique, the compression parameters are calculated. The best composite transform among the 27 types is the three levels of multi-wavelet transform (MMM) in M technique wh
... 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.
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Compression for color image is now necessary for transmission and storage in the data bases since the color gives a pleasing nature and natural for any object, so three composite techniques based color image compression is implemented to achieve image with high compression, no loss in original image, better performance and good image quality. These techniques are composite stationary wavelet technique (S), composite wavelet technique (W) and composite multi-wavelet technique (M). For the high energy sub-band of the 3rd level of each composite transform in each composite technique, the compression parameters are calculated. The best composite transform among the 27 types is the three levels of multi-wavelet
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