This research aims to study the contribution of social costs contribution to achieving social luxury in Al-Furat General Chemical Industries company that has considered second largest contamination in the area after the invasive power  to deal with chemicals in manufacturing and very dangerous to individual society and environment ,this is first to play an effective role by the senior parties related to sense of social responsibility of the internal and external environment of the company to identify costs that are preventing ,reduced and treating damage caused and achieving sustainable development ,to achieve this goal  and what they reached are the difficulty of accounting for the environment and social costs from final accou

ABSTRACT

Impkact  of  Knowledge  sharing  on  organizational  innovation  Impriscal  study in Arabic company . 

of  Knowledge Management is  the  main  component  Knowledge  sharing  system, it mean the exchange if  Knowledge, ideas, and good  practice with  another  individual . Knowledge sharing between persons, then its values can growth .

It is vry important because it can provide us with the contention between virus peoples . the interaction among the people can pass all kind of Knowledge among them. the connection and interaction and interaction enabl

Field experiment was conducted to test the effect of saline water and fertilizers rate on Pisum sativum L. plants . Treatments of the experiment included two levels of water salinity (2, 7 dSm-1) as a main plot and three levels of potash fertilization K2SO4 (44%K) namely 150 control, 300 and 450 kg/Donum as a sub plot. Results indicated that irrigation of plant with saline water 7 dSm-¹ caused a significant decrease in K and P contents specially in the upper parts of the plants , the percentage of the K increased (2.80%) under 2 dSm-¹of irrigation water and 300 kg/ donum fertilizer rate in the upper leaves, However K decreased(1.10%) in lower leaves under 7 dSm-¹ and 300 kg/donum fertilizer. while P increased in pods und

The research team seeks to study the phenomena of random housing in Iraqi society in general and Baghdad city in particular by standing on the causes behind this phenomena and its relation with security situation in Baghdad. The researchers adopted a theoretical and practical framework. The main objective is to diagnose the risks caused by the escalation of slums in Baghdad city. 

Digital tampering identification, which detects picture modification, is a significant area of image analysis studies. This area has grown with time with exceptional precision employing machine learning and deep learning-based strategies during the last five years. Synthesis and reinforcement-based learning techniques must now evolve to keep with the research. However, before doing any experimentation, a scientist must first comprehend the current state of the art in that domain. Diverse paths, associated outcomes, and analysis lay the groundwork for successful experimentation and superior results. Before starting with experiments, universal image forensics approaches must be thoroughly researched. As a result, this review of variou

The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz

The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz