Energy harvesting was and still an important point of research. Batteries have been utilized for a long time, but they are now not compatible with the downsizing of technology. Also, their need to be recharged and changed periodically is not very desirable, therefore over the years energy harvesting from the environment and the human body have been investigated. Three energy harvesting methods which are the Piezoelectric energy harvesters, the Enzymatic Biofuel cells, and Triboelectric nanogenerators (TENGs) are being discussed in the paper. Although Biofuel cells have been investigated for a

This paper presents a comparative study of edge detection algorithms based on integer and fractional order differentiation. A performance comparison of the two algorithms has been proposed. Then, a soft computing technique has been applied to both algorithms for better edge detection. From the simulations, it shows that better performance is obtained compared to the classical approach. The noise performances of those algorithms are analyzed upon the addition of random Gaussian noise, as well as the addition of salt and pepper noise. The performance has been compared to peak signal to noise

The aim of this research is to reduce the gap between manufacture expertise and management expertise by using modern technology like Manufacturing Execution System (MES) via Artificial Intelligence (AI) and Machin Learning (ML). A design of MES has been proposed and implemented on El-Araby Plastic Injection Molding (PIM) factory. This work is based on the International Society of Automation Standard (ISA-S95). A fully automated data management system has been designed and implemented to control data follow between shop floor e.g. (machines and operators) and management floor e.g. (production