Weather forecasting has become an indispensable application to predict the state of the atmosphere for a future time based on cloud cover identification. But it generally needs the experience of a well-trained meteorologist. In this paper, a novel method is proposed for automatic cloud cover estimation, typical to Indian Territory Speeded Up Robust Feature Transform(SURF) is applied on the satellite images to obtain the affine corrected images. The extracted cloud regions from the affine corrected images based on Otsu threshold are superimposed on the artistic grids representing latitude and longitude over India. The segmented cloud and grid composition drive a look up table mechanism to identify the cloud cover regions. Owing to its simplicity, the proposed method processes the test images faster and provides accurate segmentation for cloud cover regions.

This research paper proposes an improved feature reduction and classification technique to identify mild and severe dementia from brain MRI data. The manual interpretation of changes in brain volume based on visual examination by radiologist or a physician may lead to missing diagnosis when a large number of MRIs are analyzed. To avoid the human error, an automated intelligent classification system is proposed which caters the need for classification of brain MRI after identifying abnormal MRI volume, for the diagnosis of dementia. In this research work, advanced classification techniques using Support VectorMachines based on Particle Swarm Optimisation and Genetic algorithm are compared.Feature reduction by wavelets and PCA are analysed.From this analysis, it is observed that the proposed classification of SVM based PSO is found to be efficient than SVM trained with GA and wavelet based feature reduction technique yields better results than PCA.

Web 3.0 is an evolving extension of the current web environme bnt. Information in web 3.0 can be collaborated and communicated when queried. Web 3.0 architecture provides an excellent learning experience to the students. Web 3.0 is 3D, media centric and semantic. Web based learning has been on high in recent days. Web 3.0 has intelligent agents as tutors to collect and disseminate the answers to the queries by the students. Completely Interactive learner's query determine the customization of the intelligent tutor. This paper analyses the Web 3.0 learning environment attributes. A Maximum spanning tree model for the personalized web based collaborative learning is designed.

This paper presents a Generalized Power Allocation (GPA) scheme for different users in Non-Orthogonal Multiple Access (NOMA) based wireless communication system.The power allocation to the users becomes complex with the increased number of users.There are some conventional schemes for power allocation in NOMA but they have to optimize some parameters arbitrarily.In this paper, a simple but effective power allocation scheme has been formulated and tested by simulations.The proposed GPA scheme does not need any parameter adjustment.Theoretical power distribution to different users of NOMA has been calculated using the proposed GPA technique.The calculated powers of individual users with the proposed scheme are different and more distributed than the arbitrary power allocation scheme which satisfies the basic condition of NOMA.The total of calculated powers with GPA scheme shows only 01% variation with the arbitrary power allocation scheme which shows the consistency of GPA scheme with other schemes.The performance of NOMA based wireless communication system with GPA scheme has been simulated under various conditions using Matlab.The simulated BER performance for NOMA based wireless communication system using different modulation techniques show similar results with other conventional schemes which validates the formulation of GPA scheme.