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This paper deals with active and reactive power control of a three phase grid connected photovoltaic system. Maximum power point tracking (MPPT) algorithm is used to track the MPP. The MPPT algorithm uses the IPV and VPV of the PV array and gives the MPP and a Vdc,ref. This voltage is then passed on to the inverter and then further to the three-phase grid. The behaviour of the active and reactive power of the grid which is supplied by the PV array is investigated. The various currents such as inverter current, grid current and load currents are also investigated. MATLAB/simulink has been used to carry out the simulations. The proposed work has also been experimentally verified.

Nowadays, image compression is very important for efficient data storage and transmission. This paper presents a dictionary-based intra-prediction framework for image compression using sparse representation, with the construction of trained over-complete dictionaries. The intra-prediction residuals selected from different images and K-SVD algorithm are used to train over-complete dictionaries. The trained dictionaries are integrated into the intra-prediction framework for efficient image compression. In this proposed method, first, intra-prediction is applied over an image and then prediction residuals of the image are encoded using sparse representation. Sparse approximation algorithm and trained dictionaries are employed for encoding of prediction residuals of the image. The coefficients obtained from sparse representation are used for encoding. For efficient sparse representation with fewer dictionary coefficients, an adaptive sparse image partitioning method is introduced. Simulation result demonstrates that the proposed image compression method yields improved encoding efficiency as compared to existing schemes.

In this paper, solar array current is estimated and observed with a sliding mode observer instead of having a sensor, the observer is based on sliding-mode control and is constructed from the dynamic equations of the considered system vis. a single phase grid connected photovoltaic system that has a photovoltaic module and a single-phase H-bridge inverter. The solar array current is observed by the known values or measured values of the array voltage and inductor current. The current estimation is governed by the sliding mode observer gain, with decrease in the value of the gain, chattering problems become reduce. Observer gain has been varied from 100% of designed value to 6.25% of its value. A compromise has been made between estimation accuracy and chattering, to get an effective result at 12.5% of the designed value of observer gain. The estimated value almost follows the original current and hence, is used to track the MPP rapidly. Methodology of grid integration of distributed photovoltaic systems is explored and simulated using MATLAB/Simulink. The simulation results prove the effectiveness of the proposed method for efficient grid integration.

Our objective is to develop new geometric eight-point model for cervical spine vertebra that provides sufficient information for diagnosis. A subset of cervical spine images from National Institutes of Health digitised X-rays database is selected for our study. As angles at anterior corners of spine vertebra appear meaningful features for detection of anterior osteophytes, three variants of the geometric eight-point model are proposed to find the best estimate of these angles. Algorithms have been proposed to automatically locate the said eight contour points. The proposed models are uniform for all (normal and abnormal) vertebrae, not biased by human experts and thus free from ambiguity. The angle-based features derived using the proposed models discriminate the normal and abnormal spine vertebrae reasonably well. These models can be used to represent the spine vertebrae shape in lower dimensional feature space and may be useful for indexing and retrieval of cervical spine images.

The objective of the proposed approach is to narrow down the semantic gap between the query and retrieval primitives in a spine image retrieval system. The proposed retrieval technique is based on a geometric eight-point model to enable formation of semantic query. The geometric eight-point model is uniform for all vertebrae, not biased by human experts and thus free from ambiguity. The features are extracted after automatically locating contour points of eight-point geometric model of spine vertebra. Then, vertebra is represented in feature space using region-based shape features, indicative of pathology (at two anterior corners). The proposed retrieval scheme uses Euclidean distance as similarity measure in feature space. It yields better result than an existing whole shape-based matching method for retrieval of spine images that uses Procrustes metric, in term of accuracy and parsimony of model. The approach is simple and computationally efficient.