In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperforms the two other methods in its estimations for different noise conditions.
Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye
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Document source identification in printer forensics involves determining the origin of a printed document based on characteristics such as the printer model, serial number, defects, or unique printing artifacts. This process is crucial in forensic investigations, particularly in cases involving counterfeit documents or unauthorized printing. However, consistent pattern identification across various printer types remains challenging, especially when efforts are made to alter printer-generated artifacts. Machine learning models are often used in these tasks, but selecting discriminative features while minimizing noise is essential. Traditional KNN classifiers require a careful selection of distance metrics to capture relevant printing
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Background: evaluate the effects of three different intracoronal bleaching agents on the shear bond strengths (SBS) and failure site of stainless steel and monocrystalline (sapphire) orthodontic brackets bonded to endodontically treated teeth using light cured orthodontic adhesive in vitro. Materials and methods: Eighty extracted sound human upper first premolars were selected, endondontically treated and randomly divided equally (according to the type of the brackets used) into two main groups (n = 40 per group). Each main group were subdivided (according to the bleaching agent used) into four subgroups 10 teeth each; as following : control (un bleached) group, hydrogen peroxide group (Hp) 35%, carbamide peroxide group (CP) 37% group and s
... Show MoreBackground: The need of the patient for a more reasonable esthetic orthodontic intervention has risen nowadays. Thus, orthodontists make use of esthetic orthodontic materials like brackets, ligature elastics, and arch wires. The esthetic brackets come as different forms of materials, such as ceramic brackets, which have their stainability remaining as the most important consideration for the patients and the orthodontists. This study aimed to compare the staining effects of various staining materials, including black tea, cigarette smoke and Pepsi, as well as the time effect on the color stability of sapphire ceramic brackets bonded with three kinds of light cure orthodontic adhesives: Transbond, Resilience and Enlight. Materials and Met
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The energy expectation values for Li and Li-like ions ( , and ) have been calculated and examined within the ground state and the excited state in position space. The partitioning technique of Hartree-Fock (H-F) has been used for existing wave functions.
In this research the performance of 5G mobile system is evaluated through the Ergodic capacity metric. Today, in any wireless communication system, many parameters have a significant role on system performance. Three main parameters are of concern here; the source power, number of antennas, and transmitter-receiver distance. User equipment’s (UEs) with equal and non-equal powers are used to evaluate the system performance in addition to using different antenna techniques to demonstrate the differences between SISO, MIMO, and massive MIMO. Using two mobile stations (MS) with different distances from the base station (BS), resulted in showing how using massive MIMO system will improve the performance than the standar
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The problem of independent motion control of mobile robot (МR) in conditions when unforeseen changes of conditions of interaction of wheels with a surface are considered. An example of such changes can be sudden entrance МR a slippery surface. The deployment of an autonomous unmanned ground vehicle for field applications provides the means by which the risk to personnel can be minimized and operational capabilities improved. In rough terrain, it is critical for mobile robots to maintain good wheel traction. Wheel slip could cause the rover to lose control and become trapped. This paper describes the application of fuzzy control to a feedback system within slippery environment. The study is conducted on an example of М
... Show MoreBy driven the moment estimator of ARMA (1, 1) and by using the simulation some important notice are founded, From the more notice conclusions that the relation between the sign and moment estimator for ARMA (1, 1) model that is: when the sign is positive means the root gives invertible model and when the sign is negative means the root gives invertible model. An alternative method has been suggested for ARMA (0, 1) model can be suitable when