Abstract-Eye is a delicate organ of the body which provides organisms a vision. Eye is made up of sensory component such as lens, pupil, retina etc. One of the diseases which affect the human eye is cataract. Cataract occurs due to clouding of lens in the eye. Cataract is an eye disease which is responsible for vision loss and blindness. But earlier cataract detection system can provide a patient to know their condition timely and they can get the treatment accordingly. Using various image processing and classification technique one can detect and classify images. This paper points out different algorithm for detecting cataract in fundus images. This paper mainly involves mainly three steps specially preprocessing of the image, extraction of feature of preprocessed image and the last one is classification of image. In the very first step, image processing technique is applied for processing the image. We have used brightness preserving dynamic fuzzy histogram equalization method for contrast enhancement of image. In second step various feature of optical eye is extracted and the same feature are then used in classifier. For feature extraction statistical texture features such as mean, variance, energy, entropy and kurtosis of the eye is found. Support Vector Machine (SVM). SVM classification accuracy is 89%.
Mobile ad-hoc network (MANET) are self-configuring without any fixed infrastructure. In MANET the challenge of providing QoS support during multimedia application is an open problem. To enhance the network throughput adequate amount of bandwidth is required. Bandwidth management in MANET plays a vital role in improving the networks overall performance. In this paper a systematic study has been carried out about challenging issues associated with bandwidth management during routing in MANET and analysis has been done about different models of bandwidth management.
The quality of service (QoS) component in a mobile ad-hoc network has an active role in the current network scenario. In a dynamic mobile ad hoc network, ensuring optimum QoS with a scarce network resource is a significant challenge. To achieve QoS, it is essential to adopt some effective and efficient mechanisms. We have proposed an adaptive bandwidth manager model (ABMM) which uses a bandwidthsharing concept along with the flexible bandwidth reservation algorithm (FBRA) for an effective, quick and authentic data transfer. During real-time data transfer, to make communication effective, we make use of bandwidth-sharing network design problems and the concept of reserving bandwidth in high-performance networks. In our proposed model we are concentrating on the maximum utilization of resources, and using the scheduling concept to provide the minimum required bandwidth guarantee to QoS flows. Our goal is to reduce the delay in data transfer and enhance the throughput while properly utilizing the system resources. Our simulation result also shows that our model improves the network performance.
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