In horticultural industry, conventional harvesting is done by ‘handpicking’ methods to remove hundreds of fruits such as citrus fruits in random spatial locations on the individual fruit trees. It is well known that harvesting fruits in a large scale is still inefficient and not cost effective. To solve this challenging task, mechanical harvesting systems have been investigated and practiced to enhance profitability and efficiency of horticultural businesses. However they often damage fruits in the harvesting process. Development of efficient fruit removal methods are required to maintain the fruits quality. This paper reviews fruit harvesting systems from purely mechanical based systems in which operator involvement is still required, to automatic robotic harvesting systems which require minimal or no human intervention in their operation. The researches on machine vision system methodologies used in the automatic detection, inspection and the location of fruits for harvesting are also included. The review is focused on the citrus fruits due to the fact that the research on citrus fruit harvesting mechanism is a bit more advanced than others. Major issues are addressed in the camera sensor and filter designs and image segmentation methods used to identify the fruits within the image. From this review, the major research issues are addressed as future research directions

The objective of this study was to design a non-invasive system for the observation of respiratory rates and detection of apnoea using analysis of real time image sequences captured in any given sleep position and under any light conditions (even in dark environments). A Microsoft Kinect sensor was used to visualize the variations in the thorax and abdomen from the respiratory rhythm. These variations were magnified, analyzed and detected at a distance of 2.5 m from the subject. A modified motion magnification system and frame subtraction technique were used to identify breathing movements by detecting rapid motion areas in the magnified frame sequences. The experimental results on a set of video data from five subjects (3 h for each subject) showed that our monitoring system can accurately measure respiratory rate and therefore detect apnoea in infants and young children. The proposed system is feasible, accurate, safe and low computational complexity, making it an efficient alternative for non-contact home sleep monitoring systems and advancing health care applications.

Bearing retainer instability is one of the major causes of failure in the ball bearings used in spacecraft systems. These bearing failures lead to mission failure or performance degradation of the spacecraft. The instability is characterized by intermittent torque fluctuations and severe audible noise in both low- and high-speed bearings. It also generates severe transient forces that result in high cage wear or fracture. A series of retainer designs was made and the possibility of instability under various operating conditions of a momentum/reaction wheel used in a spacecraft was studied. Various tests such as run-in test, temperature test, and overlubrication test were conducted to study the instability and select a design that is stable under all operating conditions. The study results showed that square pocket retainers are more stable compared to circular pocket retainers.