Abstract: Israel formulated its security theory, which it established on the "pretext of war", meaning converting any Arab action that Israel deems a threat to its security, into a pretext to ignite the fuse of war, considering this a violation of an existing situation, and then it initiates preventive and pre-emptive attacks, then immediately turns into transfer the war to the enemy's land, to achieve a quick solution by (destroying the enemy), occupying its lands, and benefiting of the advantage of working on (internal lines against an enemy) working on external lines, and ending the war quickly, before the major powers intervene to impose a ceasefire

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

Construction and operation of (2 m) parabolic solar dish for hot water application were illustrated. The heater was designed to supply hot water up to 100 oC using the clean solar thermal energy. The system includes the design and construction of solar tracking unit in order to increase system performance. Experimental test results, which obtained from clear and sunny day, refer to highly energy-conversion efficiency and promising a well-performed water heating system.

Moment invariants have wide applications in image recognition since they were proposed.