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Sentiment Analysis is the procedure of computationally deciding if a bit of composing is certain, negative or nonpartisan. It's otherwise called supposition mining, inferring the sentiment or frame of mind of a user. In this paper, an attempt has been made to propose analysis method for sentiment of twitter dataset. In proposed method polarity of each tweet is calculate to distinguish whether tweet is positive or negative. A sentiment polarity is the emotions of user such as angry, sad, happy and joy. The proposed mechanism has been implemented in Python.

A Data Acquisition System (DAQs) is an indispensable part to receive, store and further analysis of data. This paper focuses on Data Acquisition from multiple channels using Dual Data Rate (DDR) techniques. Multiple Channels of data source which are source synchronous are initially configured using Serial Peripheral Interface (SPI) commands. The Proposed technique gives an advantage of storing data received from multiple channels in parallel form. The proposed approach is divided into two parts. First is to acquire data from multiple channels of single data source into XILINX sparten-6 Field Programmable Gate Array (FPGA) followed by storing the same onto high speed storage device such as Static Random Access Memory (SRAM).

DPSO-FOHA I and DPSO-FOHA II algorithms, based on multilevel thresholding are proposed in this paper. Optimal multilevel thresholds for colored images are maximized by using Otsu's between class variance functions. The Darwinian principle has been used to improve the value of fitness function along with the concept of fractional calculus, which optimizes it in lesser number of search iterations. Comparative analysis is presented between existing and proposed algorithms for performance assessment using standard deviation, PSNR, SSIM and computational search time of CPU. Experimental results depict that DPSO-FOHA II outperforms DPSO-FOHA I and another state of art methods in terms of PSNR, SSIM, fitness function and computational time.

Segmentation is the process by which image is divided in to certain parts or regions in such a way that each part and region share a distinct property in common. This paper compare various segmentation approaches applicable to gray scale images. A comprehensive analysis has been done to choose best power and time efficient scheme from available state of art algorithms. SAD approach along with heuristic based segmentation as well as Fuzzy based clustering methods has been used for Depth estimation of stereo images. A case of selective blurring is also introduced that can be applied to remove undesired portion of images.