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Showing 2 results for Mansouri

Abdolbasir Hosseinbor, Hesam Aslani, Eshagh Mansouri,
Volume 1, Issue 2 (Spesial Issue 1.2 2018)
Abstract

The rock inscription, which forms the basis of this research, is located in the Pirghar region and was carved on a rock in Deh-Cheshmeh village under the orders of the leaders of the Bakhtiari Constitutional Movement. The current condition of this monument is not optimal; thus, a detailed and accurate study of the inscription, given its historical and cultural significance, is essential for its proper recognition and conservation. Based on topographic and field studies, the inscriptions have been subjected to erosion and deterioration due to surface water flow and frost. Among the most significant surface factors are snow accumulation, precipitation at higher elevations, seasonal flows on sloping surfaces leading to the monument, and frost during cold seasons, which cause erosion, deterioration, and serious damage to the inscriptions. This study is conducted within the framework of a quantitative research approach, utilizing field studies, environmental assessments, and the Geographic Information System (GIS). To this end, the area hosting the inscriptions was identified using field visits and GIS and RS tools, and the obtained data were evaluated based on the direction and extent of damage. Using GIS, the drainage of runoff from the basin, hydrological operations, elevation ratios of each basin, digital elevation model, slope, slope direction, basins, sub-basins, waterway outlets, and water flow direction in the region were determined. These data will contribute to the damage assessment and preventive conservation of the inscriptions.

Talhe Ghodousiyan, Mehdi Razani, Amir Hossein Mehdikhani, Arash Keshtkar, Ali Kh Mirzaie, Alireza Mansouri, Ali Akbar Kiaei , Hossein Shirazi , Mustafa Dehpahlavan, Abdolbasir Hosseinbor,
Volume 7, Issue 3 (11-2024)
Abstract

Artificial intelligence (AI) and machine learning (ML) have emerged as transformative tools in preserving, analyzing, and representing cultural heritage and arts. This article provides a systematic and comprehensive review of AI applications in this domain, exploring their potential to address longstanding challenges such as natural degradation, limited accessibility, and complex documentation. By integrating classical and advanced ML algorithms, we examine case studies including the Time Machine Europe project, the Ithaca model for ancient Greek texts, and metaverse-based heritage digitization. These initiatives demonstrate AI’s capacity to enhance precision, speed, and interactivity in heritage tasks, from virtual reconstruction to multimodal data analysis. However, limitations such as data quality, ethical concerns, and computational complexity pose significant barriers to widespread adoption. Emerging technologies like non-fungible tokens (NFTs), prompt engineering, and quantum AI are highlighted as future directions that promise further innovation. This study underscores the need for interdisciplinary collaboration and ethical frameworks to ensure sustainable advancements, offering a roadmap for researchers and policymakers in the digital era.


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