The aim of the current research is to identify the impact of the SWOT strategy on developing systemic intelligence among students of the Ibn Rushd College of Education for Human Sciences University of Baghdad / College of Education Ibn Rushd for Human Sciences. The current research community consists of (8590) male and female students, divided into (7) departments. The current research relied on one of the partial control designs, which is the design of non-random groups: experimental group and a control group with a pre and post-test. As for the research tool, It was represented by Tourmanin’s Systemic Intelligence Scale (2012) of (50) items that measure the eight components of systemic intelligence. The results of the Mann Whitney te

Study Purpose. highlighting the origins of the sport's philosophy. Studying the development of the sport of kendo across different historical periods and its adaptation to societal and cultural changes. Identifying the establishment of the most prominent organizations and federations that contributed to its development, and exploring the sport's basic tools and rules and its most prominent championships. Materials and Methods. The historical approach was adopted in studying the historical process of the development of kendo, as it is appropriate to the nature of the problem. The information has been simplified and presented in a sequential manner that presents the development of the sport of kendo, starting from the origins of its p

The sale of facial features is a new modern contractual development that resulted from the fast transformations in technology, leading to legal, and ethical obligations. As the need rises for human faces to be used in robots, especially in relation to industries that necessitate direct human interaction, like hospitality and retail, the potential of Artificial Intelligence (AI) generated hyper realistic facial images poses legal and cybersecurity challenges. This paper examines the legal terrain that has developed in the sale of real and AI generated human facial features, and specifically the risks of identity fraud, data misuse and privacy violations. Deep learning (DL) algorithms are analyzed for their ability to detect AI genera

In recent years, the steady stream of artificial intelligence into economic systems has become a torrent. It is changing how we generate wealth and grow anew. Manufacturing, finance, health care energy, agriculture and education are just a few of the areas where AI may result in dramatic increases in productivity as well as innovation and sustainability. Predictive analytics, AI, robotics and natural language processing have significantly contributed in the improvement of resource allocation mechanisms and decision making as well as reaching SDGs. The concept of Artificial Humanity is also introduced in the paper. It shows how AI could become a global cognitive network to foster knowledge. By comparison and references of the literature, thi

Many stone tools were found on a hill south of the Hor Al-Dalmaj which is located in the central part of the alluvial plain of Mesopotamia, between the Tigris and Euphrates Rivers. The types of rocks from which the studied stone tools were made are not found in the alluvial plain, because it consists of friable sand, silt, and clay. All existing sediments were precipitated in riverine environments such as point bar, over bank, and floodplain sediments. The collected stone tools were described with a magnifying glass (10 x) and a polarized microscope after they were thin sectioned. Microscopic analysis showed that these stone tools are made of sedimentary, volcanic igneous and metamorphic rocks, such as: sandstones, limestones, chert, con

A total of 589 fishes, belonging to 23 species were collected from eight different localities
in north and mid Iraq during 1993. The parasitological inspection of such fishes revealed the
presence of 59 parasite species and two fungi. Among such parasites, five monogenetic
trematodes were recorded on the gills of some fishes for the first time in Iraq. These
included:- Ancyrocephalus vanbenedenii on Liza abu from Tigris river at Al-Zaafaraniya,
south of Baghdad; Dactylogyrus anchoratus on Cyprinus carpio from Tigris river at Al –
Zaafaranya D. minutus on C. carpio from both Tigris river at Al-Zaafaraniya and Euphrates
river at Al-Qadisiya dam lake; Discocotyle sagittata on L. abu from both the drainage system
at

   Predicting permeability is a cornerstone of petroleum reservoir engineering, playing a vital role in optimizing hydrocarbon recovery strategies. This paper explores the application of neural networks to predict permeability in oil reservoirs, underscoring their growing importance in addressing traditional prediction challenges. Conventional techniques often struggle with the complexities of subsurface conditions, making innovative approaches essential. Neural networks, with their ability to uncover complicated patterns within large datasets, emerge as a powerful alternative. The Quanti-Elan model was used in this study to combine several well logs for mineral volumes, porosity and water saturation estimation. This model goes be

With the fast-growing of neural machine translation (NMT), there is still a lack of insight into the performance of these models on semantically and culturally rich texts, especially between linguistically distant languages like Arabic and English. In this paper, we investigate the performance of two state-of-the-art AI translation systems (ChatGPT, DeepSeek) when translating Arabic texts to English in three different genres: journalistic, literary, and technical. The study utilizes a mixed-method evaluation methodology based on a balanced corpus of 60 Arabic source texts from the three genres. Objective measures, including BLEU and TER, and subjective evaluations from human translators were employed to determine the semantic, contextual an