Recently Genetic Algorithms (GAs) have frequently been used for optimizing the solution of estimation problems. One of the main advantages of using these techniques is that they require no knowledge or gradient information about the response surface. The poor behavior of genetic algorithms in some problems, sometimes attributed to design operators, has led to the development of other types of algorithms. One such class of these algorithms is compact Genetic Algorithm (cGA), it dramatically reduces the number of bits reqyuired to store the poulation and has a faster convergence speed. In this paper compact Genetic Algorithm is used to optimize the maximum likelihood estimator of the first order moving avergae model MA(1). Simulation results

 Data Driven Requirement Engineering (DDRE) represents a vision for a shift from the static traditional methods of doing requirements engineering to dynamic data-driven user-centered methods. Data available and the increasingly complex requirements of system software whose functions can adapt to changing needs to gain the trust of its users, an approach is needed in a continuous software engineering process. This need drives the emergence of new challenges in the discipline of requirements engineering to meet the required changes. The problem in this study was the method in data discrepancies which resulted in the needs elicitation process being hampered and in the end software development found discrepancies and could not meet the need

     Evolutionary algorithms (EAs), as global search methods, are proved to be more robust than their counterpart local heuristics for detecting protein complexes in protein-protein interaction (PPI) networks. Typically, the source of robustness of these EAs comes from their components and parameters. These components are solution representation, selection, crossover, and mutation. Unfortunately, almost all EA based complex detection methods suggested in the literature were designed with only canonical or traditional components. Further, topological structure of the protein network is the main information that is used in the design of almost all such components. The main contribution of this paper is to formulate a more robust E

In this paper, the construction of Hermite wavelets functions and their operational matrix of integration is presented. The Hermite wavelets method is applied to solve nth order Volterra integro diferential equations (VIDE) by expanding the unknown functions, as series in terms of Hermite wavelets with unknown coefficients. Finally, two examples are given

In this study, we investigate the behavior of the estimated spectral density function of stationary time series in the case of missing values, which are generated by the second order Autoregressive (AR (2)) model, when the error term for the AR(2) model has many of continuous distributions. The Classical and Lomb periodograms used to study the behavior of the estimated spectral density function by using  the simulation.

Incremental Sheet Metal Forming (ISMF) is a modern sheet metal forming technology which offers the possibility of manufacturing 3D complex parts of thin sheet metals using the CNC milling machine. The surface quality is a very important aspect in any manufacturing process. Therefore, this study focuses on the resultant residual stresses by forming parameters, namely; (tool shape, step over, feed rate, and slope angle) using Taguchi method for the products formed by single point incremental forming process (SPIF). For evaluating the surface quality, practical experiments to produce pyramid like shape have been implemented on aluminum sheets (AA1050) for thickness (0.9) mm. Three types of tool shape used in this work, the spherical tool ga

The sensitive and important data are increased in the last decades rapidly, since the tremendous updating of networking infrastructure and communications. to secure this data becomes necessary with increasing volume of it, to satisfy securing for data, using different cipher techniques and methods to ensure goals of security that are integrity, confidentiality, and availability. This paper presented a proposed hybrid text cryptography method to encrypt a sensitive data by using different encryption algorithms such as: Caesar, Vigenère, Affine, and multiplicative. Using this hybrid text cryptography method aims to make the encryption process more secure and effective. The hybrid text cryptography method depends on circular queue. Using circ

This study investigates asset returns within the Iraq Stock Exchange by employing both the Fama-MacBeth regression model and the Fama-French three-factor model. The research involves the estimation of cross-sectional regressions wherein model parameters are subject to temporal variation, and the independent variables function as proxies. The dataset comprises information from the first quarter of 2010 to the first quarter of 2024, encompassing 22 publicly listed companies across six industrial sectors. The study explores methodological advancements through the application of the Single Index Model (SIM) and Kernel Weighted Regression (KWR) in both time series and cross-sectional analyses. The SIM outperformed the K