The thirties and the early forties and the at end of the World War II of the last century
witnessed several attempts carried out by the Public Health Directorate and by the Iraqi
Ministry of Foreign Affairs to persuade the Rockefeller Foundation to fund Iraq with its
health program which is carried out in several regions in the world to promote the health and
social situations since Iraq during that period in history was badly in need to such plans and
programs because of this lack of financial and technical possibilities necessary for the
advancement of health and social dire situation.
The details of these attempts are deposited in the documents of the diplomatic mail
records of the United States of America , and documents of the Middle East, Iraq 1925- 1944
saved in the Iraqi National Library and Archive. We were able to obtain unique information
and it was a catalyst for us to fathom there where were no signs of this information here and
there.
Overall, these documents are a correspondence conducted between the Iraqi Ministry
of Foreign Affairs and the Rockefeller Foundation for charity by the US Office in Baghdad.
The research finds out that the view that Iraq was largely hopeful to be included in the
Rockefeller Foundation for charity programs for the advancement of its own health
deteriorated situation , and it seems that the global economic crisis that hit the United States
of America in the thirties of the last century had the impact on the Rockefeller Foundation for
charity and its preoccupation with the activities of supporting the US military in the years of
World war II , as well as a the engagement of the foundation with the implementation of the
Foundation charitable projects in various regions of the world has hampered the inclusion of
Iraq to their programs in the health field operations.
Explainable Artificial Intelligence (XAI) techniques enable transparency and trust in automated visual inspection systems by making black-box machine learning models understandable. While XAI has been widely applied, prior reviews have not addressed the specific demands of industrial and medical inspection tasks. This paper reviews studies applying XAI techniques to visual inspection across industrial and medical domains. A systematic search was conducted in IEEE Xplore, Scopus, PubMed, arXiv, and Web of Science for studies published between 2014 and 2025, with inclusion criteria requiring the application of XAI in inspection tasks using public or domain-specific datasets. From an initial pool of studies, 75 were included and categorized in
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