KA Hadi, AH Asma’a, IJONS, 2018 - Cited by 1

Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security

Some experiments need to know the extent of their usefulness to continue providing them or not. This is done through the fuzzy regression discontinuous model, where the Epanechnikov Kernel and Triangular Kernel were used to estimate the model by generating data from the Monte Carlo experiment and comparing the results obtained. It was found that the. Epanechnikov Kernel has a least mean squared error.

Regression models are among the most important tools in scientific research and data analysis. Among these models, fuzzy regression models stand out as a modern form that addresses issues of uncertain data that do not conform to the assumptions of traditional models. In this study, we present fuzzy regression models with a focus on fuzzy linear quantitative models, in addition to fuzzy support vector machine (SVM) models. Generally, linear models are considered less effective compared to non-linear models, and to address this issue, hybrid models combining both types have been introduced. The concept of hybrid models has been generalized to fuzzy models in this paper, where we introduce a hybrid model that combines both linear and non-linea

Praise be to God, Lord of the worlds, and the best of prayers, and extradition was made to our master Muhammad and his whole family and companions:
And after:
Surat Al-Qariah is from the royal fence, which is in the thirtieth part of the Noble Qur’an. The commentators differed on the number of verses, and the reason for its naming. This surah talked about the conditions of people on the Day of Resurrection, and about how people were removed from their graves, all of which I spoke about in the preamble.
The research is divided into six topics: the first topic dealt with strange terms, while the second topic dealt with the most important audio issues mentioned in the surah, namely (slurring, advertising, substitution, and silenc

      The objective of this research is employ the special cases of  function  trapezoid in the composition of fuzzy sets to make decision within the framework of the theory of games traditional to determine the best strategy for the mobile phone networks in the province of  Baghdad and Basra, has been the adoption of different periods of the  functions belonging to see the change happening in the matrix matches and the impact  that the strategies  and decision-making  available to each player and the impact on  societ

Abstract:

               The aim of the research is to verify the role of organizational trust as an “administrative” dimension of objective importance in the relationships adopted by the Iraqi General Insurance Company with customers, as it is one of the basic pillars in building and succeeding companies, which allows the provision of services with high confidence through the customer relationship management system in order to achieve The company's goal is to gain new customers, retain current customers, increase work in insurance companies, and develop the national economy by increasing the company's sales and profitability. The research

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

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