In this paper, new method have been investigated using evolving algorithms (EA's) to cryptanalysis one of the nonlinear stream cipher cryptosystems which depends on the Linear Feedback Shift Register (LFSR) unit by using cipher text-only attack. Genetic Algorithm (GA) and Ant Colony Optimization (ACO) which are used for attacking one of the nonlinear cryptosystems called "shrinking generator" using different lengths of cipher text and different lengths of combined LFSRs. GA and ACO proved their good performance in finding the initial values of the combined LFSRs. This work can be considered as a warning for a stream cipher designer to avoid the weak points, which may be f

A simple, sensitive and rapid method was used for the estimate of: Propranolol with Bi (III) to prove the efficiency, reliability and repeatability of the long distance chasing photometer (NAG-ADF-300-2) using continuous flow injection analysis. The method is based on a reaction between propranolol and Bi (III) in an aqueous medium to obtain a yellow precipitate. Optimum parameters were studied to increase the sensitivity for the developed method. A linear range for calibration graph was 0.1-25 mmol/L for cell A and 1-40 mmol/L for cell B, and LOD 51.8698 ng/200 µL and 363.0886 ng /200 µL , respectively to cell A and cell B with correlation coefficient (r) 0.9975 for cell A, 0.9966 for cell B, RSD% was lower than 1%, (n = 8) for the

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

Media and communication's research are varied in accordance to research approaches' variety which seeks to reach convergent social, psycholo

Phonological metathesis can be defined as an alternation in the normal sequence of two sounds under certain conditions. The present paper is intended to give a detailed synchronic description of phonological metathesis in Iraqi Arabic dialect. For data collection, the researchers have adopted two naturalistic techniques, viz., observation and notes taking. A synchronic analysis is carried out to provide some evidence that describe the sequential change of phonological metathesis in the dialect under investigation. Such sequential changes of metathesized sounds are presented and tabulated. The study concludes with the following finding that this process is not limited to cases where two consonant sounds are transposed, but three consonant

Although the Arabic haiku has its roots in Japanese poetry structure, it frequently deviates from conventional Arabic prosody, showing only sporadic adherence to its guidelines. Arab poets have made an effort to use the haiku form while adhering to the prosody and linguistic limitations of Arabic. In spite of these efforts, the haiku usually exhibits a noticeable defiance of the limitations of conventional Arabic prosody in its Arabic form. It is crucial to critically analyze this non-conforming structure because of its origins in Japanese religious incantations. Arab poets have modified the haiku through a process of reinterpretation, essentially changing its original form into a concise form of modern poetry expression. This rese

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

It is not often  easy to identify a certain group of words as a lexical bundle, since the same set of words can be, in different situations, recognized as idiom,  a collocation, a lexical phrase or a lexical bundle. That is, there are many cases where the overlap among the four types is plausible. Thus, it is important to extract the most identifiable and distinguishable characteristics with which a certain group of words, under certain conditions, can be recognized as a lexical bundle, and this is the task of this paper.

In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri