The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group of signatures, numbering 70 images, were used. Image preprocessing steps were performed on them, and their features were extracted using the median filter. After that, the eigenvector and eigenvalue were calculated using the PCA algorithm. Then the backpropagation neural network algorithm was applied for training and testing where the performance reached 6.7995e−07 for 82 epochs and the accuracy was 99.98%.
Smart systems are the trend for modern organizations and should meet the quality of services that expect to produce. Internet of Everything (IoE) helped smart systems to adopt microcontrollers for improving the performance. Analyzing and controlling data in such a system are critical issues. In this study, a survey of IoE systems conducted to show how to apply a suitable model that meets such system requirements. The analysis of some microcontroller boards is explored based on known features. Factors for applying IoE devices have been defined such as connectivity, power consumption, compatibility, and cost. Different methods have been explained as an overview of applying IoE systems. Further, different approaches for applying IoE technology
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The problem of frequency estimation of a single sinusoid observed in colored noise is addressed. Our estimator is based on the operation of the sinusoidal digital phase-locked loop (SDPLL) which carries the frequency information in its phase error after the noisy sinusoid has been acquired by the SDPLL. We show by computer simulations that this frequency estimator beats the Cramer-Rao bound (CRB) on the frequency error variance for moderate and high SNRs when the colored noise has a general low-pass filtered (LPF) characteristic, thereby outperforming, in terms of frequency error variance, several existing techniques some of which are, in addition, computationally demanding. Moreover, the present approach generalizes on existing work tha
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Recent advances in wireless communication systems have made use of OFDM technique to achieve high data rate transmission. The sensitivity to frequency offset between the carrier frequencies of the transmitter and the receiver is one of the major problems in OFDM systems. This frequency offset introduces inter-carrier interference in the OFDM symbol and then the BER performance reduced. In this paper a Multi-Orthogonal-Band MOB-OFDM system based on the Discrete Hartley Transform (DHT) is proposed to improve the BER performance. The OFDM spectrum is divided into equal sub-bands and the data is divided between these bands to form a local OFDM symbol in each sub-band using DHT. The global OFDM symbol is formed from all sub-bands together using
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It has become necessary to change from a traditional system to an automated system in production processes, because it has high advantages. The most important of them is improving and increasing production. But there is still a need to improve and develop the work of these systems. The objective of this work is to study time reduction by combining multiple sequences of operations into one process. To carry out this work, the pneumatic system is designed to decrease\ increase the time of the sequence that performs a pick and place process through optimizing the sequences based on the obstacle dimensions. Three axes are represented using pneumatic cylinders that move according to the sequence used. The system is implemented and
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Nowadays, the power plant is changing the power industry from a centralized and vertically integrated form into regional, competitive and functionally separate units. This is done with the future aims of increasing efficiency by better management and better employment of existing equipment and lower price of electricity to all types of customers while retaining a reliable system. This research is aimed to solve the optimal power flow (OPF) problem. The OPF is used to minimize the total generations fuel cost function. Optimal power flow may be single objective or multi objective function. In this thesis, an attempt is made to minimize the objective function with keeping the voltages magnitudes of all load buses, real outp
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The primary objective of this paper is to improve a biometric authentication and classification model using the ear as a distinct part of the face since it is unchanged with time and unaffected by facial expressions. The proposed model is a new scenario for enhancing ear recognition accuracy via modifying the AdaBoost algorithm to optimize adaptive learning. To overcome the limitation of image illumination, occlusion, and problems of image registration, the Scale-invariant feature transform technique was used to extract features. Various consecutive phases were used to improve classification accuracy. These phases are image acquisition, preprocessing, filtering, smoothing, and feature extraction. To assess the proposed
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