This study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K

The research aims to verify the role of the Human Resources Strategic Management (HRSM) in enhancing the strategic success factors for talent (SSFT) in the General Tourism Authority by distributing a questionnaire consisting of (36) paragraphs on an intentional sample represented by the higher departments as it reached (50) and the sample valid for testing was (44) Person and to test the relationships between the two research variables, the researchers used statistical methods represented by (Bartlett test / mean / simple regression coefficient / difference coefficient, alpha- cronbachAch, confirmatory factor Analysis ) through the statistical program (SPSS v.23 & AMOS v.23). In enhancing the factors of success for talent management in the

In this paper, the relationship between urban growth, land use, site availability, and impacts on the general appearance of the city generated by functional characteristics of port cities were analyzed. Various data were used to identify patterns of land use change and city growth and expansion. The research aims to analyze the impact of the port on the growth of the city, study the urban growth of the city of Umm Qasr and predicting the growth trends, and to identify the most influential factors in this growth. The study dealt with the concepts of urban growth and the factors that characterize the growth of port cities and the current situation of the city. The practical part included the mechanisms used by the researcher to analyze the

            This study tests the effect of a large number of independent variables that control the growth of the total productivity, which amounted to 112 variables, gathered from what is mentioned in the specialized theoretical and applied literature. The data for these variables were taken from global reports of sound international organizations and reliable databases covering the period 1991-2016. The data of the dependent variable, the growth of the total factor productivity, were taken from the database of the world development indicators. The study covered 61 countries for which data were available. The study included three regression models to explain

Astronomers have known since the invention of the telescope that atmospheric turbulence affects celestial images. So, in order to compensate for the atmospheric aberrations of the observed wavefront, an Adaptive Optics (AO) system has been introduced. The AO can be arranged into two systems: closedloop and open-loop systems. The aim of this paper is to model and compare the performance of both AO loop systems by using one of the most recent Adaptive Optics simulation tools, the Objected-Oriented Matlab Adaptive Optics (OOMAO). Then assess the performance of closed and open loop systems by their capabilities to compensate for wavefront aberrations and improve image quality, also their effect by the observed optical bands (near-infrared band

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through tha

Today, the science of artificial intelligence has become one of the most important sciences in creating intelligent computer programs that simulate the human mind. The goal of artificial intelligence in the medical field is to assist doctors and health care workers in diagnosing diseases and clinical treatment, reducing the rate of medical error, and saving lives of citizens. The main and widely used technologies are expert systems, machine learning and big data. In the article, a brief overview of the three mentioned techniques will be provided to make it easier for readers to understand these techniques and their importance.

Using the Neural network as a type of associative memory will be introduced in this paper through the problem of mobile position estimation where mobile estimate its location depending on the signal strength reach to it from several around base stations where the neural network can be implemented inside the mobile. Traditional methods of time of arrival (TOA) and received signal strength (RSS) are used and compared with two analytical methods, optimal positioning method and average positioning method. The data that are used for training are ideal since they can be obtained based on geometry of CDMA cell topology. The test of the two methods TOA and RSS take many cases through a nonlinear path that MS can move through that region. The result

Massive multiple-input multiple-output (m-MIMO) is considered as an essential technique to meet the high data rate requirements of future sixth generation (6G) wireless communications networks. The vast majority of m-MIMO research has assumed that the channels are uncorrelated. However, this assumption seems highly idealistic. Therefore, this study investigates the m-MIMO performance when the channels are correlated and the base station employs different antenna array topologies, namely the uniform linear array (ULA) and uniform rectangular array (URA). In addition, this study develops analyses of the mean square error (MSE) and the regularized zero-forcing (RZF) precoder under imperfect channel state information (CSI) and a realist