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 l

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 l

Steady natural convection in a square enclosure with wall length (L= 20 cm) partially filled by saturated porous medium with same fluid (lower layer) and air (upper layer) is investigated. The conceptual study of the achievements of the heat transfer is performed under effects of bottom heating by constant heat flux (q=150,300,450,600W/m2 ) for three heaters size (0.2,0.14,0.07)m with symmetrically cooling with constant temperature on two vertical walls and adiabatic top wall. The relevant filled studied parameters are four different porous medium heights (Hp=0.25L,0.5L, 0.75L, L), Darcey number (Da1) 3.025×10-8 and (Da2) 8.852×10-4 ) and Rayleigh number range (60.354 - 241.41), (1.304×106 – 5.2166×106 ) for Da1 and Da2 cases respecti

The current research aims to investigate the impact of the LEAD strategy on teamwork skills among second-year intermediate school students in government day schools. Umm Al-Mu'minin School, affiliated with the First Education Directorate of Al-Koura/Qom Abi Urayb, was intentionally selected as the research site for the academic year (2026- 2025). The researcher selected one of two classes as the experimental group, which studies according to the LEAD strategy, and the other as the control group, which studies according to the traditional method. The two research groups were compared in a number of variables, including (chronological age in months, intelligence test, prior knowledge, and a teamwork skills scale). The results showed that the

The study aims at finding out the effect of the lead time strategy on the first intermediate class pupils' achievement in geography The partial experimental design of two groups, experimental and control, with pre-post tests is used. The sample is represented in (73) female pupils. The sample is divided into two groups (37) experimental group and (36) control one. The sam ple is selected from first intermediate class pupils ( Al Batol intermediate school for girls) Baghdad Al-karkh-3, for academic year 2015-2016 The researcher has equalized the two groups in several variables: the previous achievement tests, intelligence, age in months, the scores of geography test of first course

Credit risk assessment has become an important topic in financial risk administration. Fuzzy clustering analysis has been applied in credit scoring. Gustafson-Kessel (GK) algorithm has been utilised to cluster creditworthy customers as against non-creditworthy ones. A good clustering analysis implemented by good Initial Centres of clusters should be selected. To overcome this problem of Gustafson-Kessel (GK) algorithm, we proposed a modified version of Kohonen Network (KN) algorithm to select the initial centres. Utilising similar degree between points to get similarity density, and then by means of maximum density points selecting; the modified Kohonen Network method generate clustering initial centres to get more reasonable clustering res