The article discusses the spatial analysis of the chemical soil properties that is a key component of the agriculture ecosystem based on satellite images. The main objective of the present study is to measure the chemical soil properties (total dissolved salts (TDS), Electrical conductivity (EC), PH, and) and the ​spatial variability. On 13 November 2020 (wet season), a total of 12 soil samples were collected in the field through random sampling in the Sanam mountain-Al Zubair region south of Basra province, to contain its soil samples components of minerals and precious elements such as silica and sulfur. From experimental results, the soil sample in the sixth position has the highest concentration of TDS values, reached (5798.4

Activated carbon (AC) is a highly important adsorbent material, as it is a solid form of pure carbon that boasts a porous structure and a large surface area, making it effective for capturing pollutants. Thanks to its exceptional features, AC is widely used for purifying water that is contaminated with odors and removing dyes in a cost-effective manner. A variety of carbonic materials have been employed to prepare AC, and this study aimed to evaluate the suitability of utilizing waste mango and avocado seeds for this purpose, followed by testing their efficacy in removing dye from aqueous solutions. The results indicate that using waste mango and avocado as AC is technically feasible, achieving dye removal percentages of 98% and 93%,

The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

Wireless Body Area Network (WBAN) is a tool that improves real-time patient health observation in hospitals, asylums, especially at home. WBAN has grown popularity in recent years due to its critical role and vast range of medical applications. Due to the sensitive nature of the patient information being transmitted through the WBAN network, security is of paramount importance. To guarantee the safe movement of data between sensor nodes and various WBAN networks, a high level of security is required in a WBAN network. This research introduces a novel technique named Integrated Grasshopper Optimization Algorithm with Artificial Neural Network (IGO-ANN) for distinguishing between trusted nodes in WBAN networks by means of a classifica