The Fourth Industrial Revolution represents an advanced stage of technological development, characterized by the integration of digital, physical, and biological technologies, with a strong focus on smart connectivity and advanced data analysis. At the core of this revolution stands Artificial Intelligence (AI), which enables the processing of vast amounts of data, decision-making with speed and accuracy, automation of processes, and enhancement of productivity and quality. This research examines the transformative role of AI in the humanities, particularly in archaeological, historical, and geographical studies, where traditional methods face limitations in handling complex and extensive datasets.The study aims to highlight these limitations, explore the potential of AI in analyzing diverse archaeological data to uncover new patterns, examine its role in processing large historical sources, and investigate its application in spatial data analysis for environmental and urban changes. The main hypothesis posits that AI can reveal patterns and insights unattainable by conventional methods, thereby enhancing understanding of past civilizations, historical trends, and geographical dynamics.Using a descriptive-analytical methodology supported by practical examples, the research illustrates AI applications such as satellite image analysis, artifact examination, and archival data processing. The findings indicate that integrating AI with humanities research not only improves data analysis efficiency but also maintains the critical and interpretive framework of the humanities, enabling a deeper understanding of society, history, and collective awareness in the digital era.The study concluded that integrating artificial intelligence into humanities research not only improves the efficiency and speed of data analysis but also contributes to the development of the research methodology itself, by shifting from descriptive to analytical and predictive studies, while preserving the critical and interpretive dimensions of the humanities. The study also recommends strengthening collaboration between researchers in the humanities and computer science, establishing open-source Arabic digital archives, and training researchers in the use of artificial intelligence tools. This will contribute to broadening the horizons of humanities research and connecting the past with the present within an integrated scientific framework that meets the demands of the digital age.
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One hundred forty three of Klebsiellapneumoniae isolates had been collected from some hospitals in Baghdad city. The isolates were taken from different clinical specimens.Antimicrobial susceptibility test was carried out towards fifteen antimicrobial agents by using Vitek2 system with Antimicrobial susceptibility test cards. The results of antibiogram showed that the local isolates were possess highly resistance towards most antimicrobial agents under study. The high resistance wastoAmpicillin while the low resistance was to Imipenem.Two methods were used for detection of Extended Spectrum Beta Lactamases (ESBLs) production; first methods by using of Vitek2 system,thesecondmethods by using of polymerase chain reaction (PCR) technique to dis
... Show MoreThis work revealed the spherical aromaticity of some inorganic E4 cages and their protonated E4H+ ions (E=N, P, As, Sb, and Bi). For this purpose, we employed several evaluations like (0D-1D) nucleus independent chemical shift (NICS), multidimensional (2D-3D) off-nucleus isotropic shielding σiso(r), and natural bond orbital (NBO) analysis. The magnetic calculations involved gauge-including atomic orbitals (GIAO) with two density functionals B3LYP and WB97XD, and basis sets of Jorge-ATZP, 6-311+G(d,p), and Lanl2DZp. The Jorge-ATZP basis set showed the best consistency. Our findings disclosed non-classical aromatic characters in the above molecules, which decreased from N to Bi cages. Also, the results showed more aromaticity in E4 than E4H+
... Show MoreUnderstanding, promoting, and teaching media literacy is an important societal challenge. STEM educators are increasingly looking to incorporate 21st century skills such as media literacy into core subject education. In this paper we investigate how undergraduate Computer Science (CS) students can learn media literacy as a by-product of collaborative video tutorial production. The paper presents a study of 34 third-year CS undergraduates who, as part of their learning, were each asked to produce three video tutorials on Raspberry Pi programming, using a collaborative video production tool for mobile phones (Bootlegger). We provide results of both quantitative and qualitative analysis of the production process and resulting video tutorials,
... Show MoreSensing insole systems are a promising technology for various applications in healthcare and sports. They can provide valuable information about the foot pressure distribution and gait patterns of different individuals. However, designing and implementing such systems poses several challenges, such as sensor selection, calibration, data processing, and interpretation. This paper proposes a sensing insole system that uses force-sensitive resistors (FSRs) to measure the pressure exerted by the foot on different regions of the insole. This system classifies four types of foot deformities: normal, flat, over-pronation, and excessive supination. The classification stage uses the differential values of pressure points as input for a feedforwar
... Show MoreThe issue of penalized regression model has received considerable critical attention to variable selection. It plays an essential role in dealing with high dimensional data. Arctangent denoted by the Atan penalty has been used in both estimation and variable selection as an efficient method recently. However, the Atan penalty is very sensitive to outliers in response to variables or heavy-tailed error distribution. While the least absolute deviation is a good method to get robustness in regression estimation. The specific objective of this research is to propose a robust Atan estimator from combining these two ideas at once. Simulation experiments and real data applications show that the p
... Show MoreAs one type of heating furnaces, the electric heating furnace (EHF) typically suffers from time delay, non-linearity, time-varying parameters, system uncertainties, and harsh en-vironment of the furnace, which significantly deteriorate the temperature control process of the EHF system. In order to achieve accurate and robust temperature tracking performance, an integration of robust state feedback control (RSFC) and a novel sliding mode-based disturbance observer (SMDO) is proposed in this paper, where modeling errors and external disturbances are lumped as a lumped disturbance. To describe the characteristics of the EHF, by using convection laws, an integrated dynamic model is established and identified as an uncertain nonlinear second ord
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