Implementation of TSFS (Transposition, Substitution, Folding, and Shifting) algorithm as an encryption algorithm in database security had limitations in character set and the number of keys used. The proposed cryptosystem is based on making some enhancements on the phases of TSFS encryption algorithm by computing the determinant of the keys matrices which affects the implementation of the algorithm phases. These changes showed high security to the database against different types of security attacks by achieving both goals of confusion and diffusion.

Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall

This paper introduces a non-conventional approach with multi-dimensional random sampling to solve a cocaine abuse model with statistical probability. The mean Latin hypercube finite difference (MLHFD) method is proposed for the first time via hybrid integration of the classical numerical finite difference (FD) formula with Latin hypercube sampling (LHS) technique to create a random distribution for the model parameters which are dependent on time [Formula: see text]. The LHS technique gives advantage to MLHFD method to produce fast variation of the parameters’ values via number of multidimensional simulations (100, 1000 and 5000). The generated Latin hypercube sample which is random or non-deterministic in nature is further integ

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

Abstract 

For sparse system identification,recent suggested algorithms are  -norm Least Mean Square (  -LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named  -ZA-LMS, 

This paper aims to add to the growing body of cognitive translation studies that deal with the translation of emotions and the factors of evaluating the translation process-oriented. Cognitive appraisal is one of the tokens that includes three paradigms of assessing the performance of translation, it can be addressed from the perspective of emotions, intuitions, and individual styles of the SL and the method of transfer into TL. The study hypothesized that translators create a similar emotional charge due to their mental capability to build the same emotional effect in the TL audience. The study also proposed that the applicability of cognitive appraisal is a valuable method of evaluating the translation process, as pertinent to TPR. The

This study is an attempt to investigate the conceptual metaphor of UP and DOWN commonly used in Iraqi community. Some of the metaphorical expressions in Iraqi colloquial Arabicarewidely used by Iraqi speakers in everyday language. Ithas been analyzed by following the cognitive theory of metaphor (Lakoff& Johnson,1980).The study indicates that the Iraqi speakerexperiences more of the metaphorical expressions of UP and DOWN to referto many of the abstract concepts that shape his/her impression of everyday life situations.

The present paper is a qualitative descriptive study. It aims to examine the macro-cultural schemata addressing the concept of violence against women in Iraq from a cognitive linguistic point of view. To meet this objective, a number of Iraqi social caricatures have been selected from two popular and active Iraqi caricaturists, Odeh Al-Fahdawi and Nasser Ibrahim. The selection and the analysis of data have been achieved following the validity and reliability procedures and the ethical considerations. To meet this objective, Sharifian’s Model (2011) of Cultural Schemata has been adopted in data analysis. The study has concluded that the macro-cultural schemata regarding the concept of violence in the selected panels reveals that violenc

Objective: this search aims to test the correlation between job complexity and psychological detachment then stats how the burnout can affect in this relationship and dose the burnout can contribute in development of this relationship.   Theoretical framework: the research adopted some questions like how can psychological detachment can make the employee keeping away from work and isolates himself from work environment and how can the job complexity enhance this behavior for employee ,and how can the burnout increase the correlation between job complexity and psychological detachment ?, then trying to extraction some of recommendations may contributes in enhancing practicing and adopting these three variables (job complexity, psych