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).
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Companies compete greatly with each other today, so they need to focus on innovation to develop their products and make them competitive. Lean product development is the ideal way to develop product, foster innovation, maximize value, and reduce time. Set-Based Concurrent Engineering (SBCE) is an approved lean product improvement mechanism that builds on the creation of a number of alternative designs at the subsystem level. These designs are simultaneously improved and tested, and the weaker choices are removed gradually until the optimum solution is reached finally. SBCE implementations have been extensively performed in the automotive industry and there are a few case studies in the aerospace industry. This research describe the use o
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Two- dimensional numerical simulations are carried out to study the elements of observing a Dirac point source and a Dirac binary system. The essential features of this simulation are demonstrated in terms of the point spread function and the modulation transfer function. Two mathematical equations have been extracted to present, firstly the relationship between the radius of optical telescope and the distance between the central frequency and cut-off frequency of the optical telescope, secondly the relationship between the radius of the optical telescope and the average frequency components of the modulation transfer function.
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This paper is focused on orthogonal function approximation technique FAT-based adaptive backstepping control of a geared DC motor coupled with a rotational mechanical component. It is assumed that all parameters of the actuator are unknown including the torque-current constant (i.e., unknown input coefficient) and hence a control system with three motor control modes is proposed: 1) motor torque control mode, 2) motor current control mode, and 3) motor voltage control mode. The proposed control algorithm is a powerful tool to control a dynamic system with an unknown input coefficient. Each uncertain parameter/term is represented by a linear combination of weighting and orthogonal basis function vectors. Chebyshev polynomial is used
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Background: Animal bite is one of the public health problems all over the world, especially in poor countries. Animal bites have an impact on human health due to rabies disease, which is a viral transmitted disease from animal to human with a high mortality rate.
Objective: To determine the epidemiological characteristics of animal bite cases by person, time, and place.
Method: Descriptive cross sectional study was done by reviewing cases caused by animal bites., Data including the demographic characteristics of age, gender, occupation, site of bite, and attending health institutions searching treatment were all included.
Results: There were 11600 animal bite cases. Most of bites caused by stray dogs 11577(99.8%), and the males
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The novel groups of organic chromophores containing triphenylamine (TPA) (ATP-I to ATP-IV) have been constructed by structural modification of electron donors with substitution biphenyl and bipyridine rings inserting a π-linkage. Density functional theory (DFT) and time-dependent type of it (TD-DFT) have been operated to study results of donating ability of TPA and spacer on absorption, geometrical, photovoltaic, and energetic attributes of these sensitizers. Structural attributes have been revealed that incorporation of TPA, acceptor and π bridge include a perfect coplanar conformation in TPA-III. Based on frequency computations and ground-state optimization, bandgap (Eg) energy, ELUMO, EHOMO have been determined. For enlightening maximu
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