Material handling is a necessary, but expensive activity in factories. Autonomous robot technology can help reduce the cost and relax humans from the exhaustive job of driving forklifts. In this paper, we describe the mechatronics design and implementation of an autonomous forklift. The robot can perceive the 3D dynamic world and can plan its motion autonomously to lift materials from a source to target locations. Dynamic map of the world is built using data from a Microsoft Kinect head and readings from wheel encoders, thus enabling the robot to avoid obstacles and reach target locations safely. Experiments showed success of the robot to move and load the cargo to target locations.

Solar photovoltaic (PV) arrays in remote applications are often related to the rapid changes in the partial shading pattern. Rapid changes of the partial shading pattern make the tracking of maximum power point (MPP) of the global peak through the local ones too difficult. An essential need to make a fast and efficient algorithm to detect the peaks values which always vary as the sun irradiance changes. This paper presents two algorithms based on the improved particle swarm optimization technique one of them with PID controller (IPSO-PID), and the other one with Brain Emotional Learning Based Intelligent Controller (IPSO-BELBIC). These techniques improve the maximum power point (MPP) tracking capabilities for photovoltaic (PV) system under partial shading circumstances. The main aim of these improved algorithms is to accelerate the velocity of IPSO to reach to (MPP) and increase its efficiency. These algorithms also improve the tracking time under complex irradiance conditions. Based on these conditions, the tracking time of these presented techniques improves to 2 msec, with an efficiency of 100%.

This paper describes a new digital image processing algorithm which is concerned with the automatic detection and measurement of the foveal avascular zone (FAZ) in.Fundus Fluorescein Angiographies (FFA). FFA is used in ophthalmic practice to evaluate vascular retinopathies and choroidopathies. In the proposed algorithm, projection in the horizontal and vertical directions will be applied to determine the location of the dark regions in the test image that represents the region of interest (FAZ). Then. image is segmented based on its gray level values by using thresholding techniques. Morphological operators and Sobel edge detector are then used to detect and localize the contour of the FAZ.

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