This research develops a new method based on spectral indices and random forest classifier to detect paddy rice areas and then assess their distributions regarding to urban areas. The classification will be conducted on Landsat OLI images and Landsat OLI/Sentinel 1 SAR data. Consequently, developing a new spectral index by analyzing the relative importance of Landsat bands will be calculated by the random forest. The new spectral index has improved depending on the most three important bands, then two additional indices including the normalized difference vegetation index (NDVI), and standardized difference built-up index (NDBI) have been used to extract paddy rice fields from the data. Several experiments being

In this research study failed Annunciation No. 10 for the fourth phase of the pressure of carbon dioxide of the company for Southern Fertilizers and repeated the failures more than once for the same gospel was a detailed study of the gospel included a series tests for properties Mechanical and Structural addition to the tests microscopic and scanning electron microscope shows m This study parameters and a failure Elal well as the existence of an old internal cracks in the metal of the Annunciation

The UN plans to achieve several development objectives by 2030. These objectives address global warming, a major issue. This method aims to improve sustainable accounting performance (AP). In this circumstance, AI is being applied in various fields, notably in economic, social, and environmental (ESE) domains. This research investigates how sustainable development (SD) influences AI methodologies and AP improvement. The research examined a sample of Iraqi banks listed on the Iraq Stock Exchange from 2014 to 2022. AI was measured by ATM and POS prevalence. A three-dimensional approach examined economic, social, and environmental (ESE) sustainability. Meanwhile, the performance of sustainable accounting was measured through the return on asse

Environmental stress affects the yield of sorghum. This impact can be reduced by seed stimulation technique and determining the appropriate planting date. An experiment was conducted in the spring and fall seasons of 2022. Randomized complete block design with split-plot arrangement in four replications was used. Planting dates (spring season: February 15th, March 1st, 15th, April 1st, 15th; fall season: June 15th, July 1st, 15th, August 1st, 15th) were assigned to the main plots. Seed stimulation treatments (banana peel extract 35% + citric acid 100 mg L-1 and soaking in distilled water only) were applied to the subplots. The interaction treatment of soaking with banana peel extract + citric acid and the planting date of April 15th showed

Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is s