The main objective of this project is to develop an application to find the best compression technique to store Muscat College students' photographs in less storage. MATLAB software will be used to develop a Graphical User Interface GUI application and implement two image compression techniques which are lossless compression using the DCT algorithm and lossy compression using the LBG algorithm.  The application shall allow the user to select and test a sample image by applying both these techniques for any student image he\she selects in order to compare the results by display the image after compression and the histogram to find which the most suitable compression technique is. Also, the application shall show the size of images before and after applying the compression process and show the compression ratio and relative data redundancy of compressed image/images. The main functionality is that the application shall allow the user to do bulk processing to apply image enhancement and image compression technique to enhance and compress all the photographs of students and store them in less space.

Palms trees (Phoenix dactylifera L.), Al Nakheel in Arabic are known to have cultural and economic importance to Gulf and Arabic-speaking countries. However, using the traditional method of cultivation, improper use, and depletion of water is perceived as the major challenge as farmers used almost two and a half times the required amount without considering numerous factors. This paper attempts to develop an implementation model of a water management system for Date Palm Trees using Case Based-Reasoning. The said model involves an IoT-based module comprised of NodeMCU, soil moisture, temperature, and humidity sensors that automate the settings of the water amount for the whole year based on palm age, temperature, air humidity, and soil moisture. CBR calculates the amount of water supplied to palm trees (based on initial knowledgebase cited from previous empirical studies) and stores it in a cloud-based database. These data and hardware status can be accessed using a mobile application. When the temperature or soil moisture sensor fails, data trends are retrieved from the database and processed using Linear Regression Analysis. The test results have shown that the proposed model helped in a significant decrease in water consumption compared to the traditional method.