Recently, interest in volunteerism focused on environmental sustainability has grown dramatically due to the alarming environmental issues such as global warming, foreign waste and greenhouse gases effects. A greenery club, namely Kelab Bumi Hijau (KBH) which consists of volunteering students led by Majlis Felow Kolej Tuanku Canselor (MFKTC), Universiti Teknologi Malaysia (UTM) has been set up in 2017 to monitor and improve the greenery particularly within Kolej Tuanku Canselor (KTC). Several activities have been carried out by KBH such as picking up litter, clearing unwanted shrubs and planting trees. This study is carried out to evaluate the relevance of KBH to the greenery of KTC. In addition, the challenges faced by KBH and their future plans are also highlighted. The results show that the greenery club namely KBH has not only enhanced the greenery and environment of KTC, but also cultivated volunteerism among the students. Although the data presented apply only to KTC, we believe that the volunteerism to sustain the greenery should be carried out in all residential college in UTM.
<span>The excellent quality of color fundus photograph is crucial for the ophthalmologist to process the correct diagnosis and for convolutional neural network (CNN) models to optimize output classification. As a result of main causes as acquire devises efficiency and experience of a physician most fundus photographs can have uneven illuminance, blur, and bad contrast, in addition to micro-features of retinal diseases, which need to force their contrast. Fundus photograph quality assessment method is proposed to find out the perfect enhanced color fundus Technique in fundoscopy photographs-based CNN model. Five photograph quality measurements, in addition to five CNN metrics, were used as standard in this study. In this research innovative approach combining photograph quality measurement and CNN metrics analysis is proposed to find out the best enhance method that is set for the multiclass CNN model. The contrast enhancement techniques are evaluated using 267 color fundus photographs divided into three retina diseases cases were downloaded from the open-source database “FIGSHARE”. The study outcome showed that the presented system (single-CNN) can determine well the contrast enhancement method, as well as the low-quality fundus photograph then it can boost CNN metrics to achieve superior.</span>
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