MATLAB

Artificial intelligence (AI) has the potential to revolutionize the field of archaeology by enabling researchers to analyze large amounts of data quickly and accurately. In this article, we have tried to implement some methods and algorithms in image processing on the image of ancient artifacts. We implemented the algorithms on two historical models as examples, one of which is the image of a coin decorated with the image of Farkhan the Great and the other is the coin with the image of Khursheed Daboui to obtain the details of these works from the images on the computer. We used Edge Detection, Hough Transform, imcontour, and Filter Images Using Predefined Filters algorithms in MATLAB software, each of these algorithms is used for specific purposes in image processing. By using digital image analysis techniques, researchers can gain a deeper understanding of the objects and sites they are studying and can make new and important discoveries about the history and culture of ancient civilizations.

Score for exposure factor is the sum of scores for the five criteria of precipitation, temperature, wind, weather phenomena, and horizontal visibility. Hourly data on precipitation, temperature, relative humidity, weather condition codes, and horizontal visibility obtained at 23 synoptic stations in the Province, and from those located in an area within a radius of 100 kilometers from the borders of it, since the time they were established up to the end of 2012, was first received from Iran Meteorological Organization. Those stations were then selected that had data related to eight daily measurements in the interval 1990-2010. Based on this, data processing was carried out for nine stations (five in Kermanshah Province and four in neighboring Provinces) within MATLAB environment. The scores for exposure factors for climate change in two five-year intervals were calculated to assess climate vulnerability of Kermanshah Province. In the next stage, the study period was divided into three intervals: the base interval (from 23, 9, 1990 to 21, 9, 2000), the first interval (from 22, 9, 2000 to 22, 9, 2005), and the second interval (from 23, 9, 2005 to 22, 9, 2010). Following that, exposure criteria and markers were determined. It was then necessary to define and measure a broad range of markers because of the temporal-spatial non-uniformity in the climate of Kermanshah Province that results from land location and variety in this Province. In the present research, climatic data was processed in the framework of five criteria that included 29 markers. In general, it was found that Kermanshah Province is faced with increased hazards resulting from current changes in climate.