Vehicular Ad-hoc Network (VANET) is the extended version of Mobile Ad-hoc Network (MANET). Both share similar characteristics except VANET is utilizing the vehicles instead of mobiles. However; the high speed of the vehicles, the rapidly change of VANET topology, and the city environment characteristics, has become today's issues in terms of wireless communication using vehicles. In terms of routing protocols, there are so many protocols that could be used by VANETs. However; these protocols are not capable enough to achieve the communication. Position-based or geographical-based routing is one of the examples that we will cover in this paper. Our main focus is to make comparison of geographical-based routing protocols. For example, qualitative comparison of protocols that are used for packages' carrying and forwarding such as some Delay Tolerant Network (DTN) and non-DTN geographic routing protocols. Finally, each protocol has its own advantages and disadvantages. So it is important to have an idea about them in order to guidance the researcher. Depends on this comparison it is observed that hybrid DTN and non-DTN will perform better since it will take the advantages of all DTN and non-DTN.
Diabetic retinopathy is a severe complication retinal disease caused by advanced diabetes mellitus. Long suffering of this disease without threatment may cause blindness. Therefore, early detection of diabetic retinopathy is very important to prevent to become proliferative. One indication that a patient has diabetic retinopathy is the existence of hard exudates besides other indications such as microaneurysms and hemorrhages. In this study, the existence of hard exudates is applied to classify the moderate and severe grading of non-proliferative diabetic retinopathy in retinal fundus images. The hard exudates are segmented using K-means clustering. The segmented regions are extracted to obtain a feature vector which consists of the areas, the perimeters, the number of centroids and its standard deviation. Using three different classifiers, i.e. soft margin Support Vector Machine, Multilayer Perceptron, and Radial Basis Function Network, we achieve the accuracy of 89.29%, 91.07%, and 85.71% respectively, for 56 training data and 56 testing data of retinal images.
Vehicular Ad-hoc Networks (VANETs) are an extension of Mobile Ad-hoc Networks (MANETs). However, many routing protocols of MANETs do not perform very well in VANETs due to their unique characteristics such as moving at high speed and road patterned movement. Thus, routing protocols and the other issues must be adapted to those VANETs characteristics. Moving at high speed causes links to be broken easily, which is not a good situation for real-time applications that need stable and reliable connection. Thus, in order to support those kinds of applications, we introduced probabilistic relay to improve the performance of routing protocols in VANETs.In this paper, we implemented probabilistic relay into OLSR and AODV protocols and compared their performance with the original ones using a computer simulation with realistic scenarios in VANETs. We evaluated those protocols under different metrics such as vehicle mobility and road segment length. We showed that probabilistic relay could provide a significant improvement in routing protocols' performance especially in packet delivery ratio.
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