The paper discusses novel image retrieval methods based on shape features extracted using gradient operators and slope magnitude technique with Block Truncation Coding (BTC). Four variations of proposed "Mask-Shape-BTC" image retrieval techniques are proposed using gradient masks like Robert, Sobel, Prewitt and Canny. The proposed image retrieval techniques are tested on generic image database with 1000 images spread across 11 categories. In all 55 queries (5 from each category) are fired on the image database. The average precision and recall of all queries are computed and considered for performance analysis. In all the considered gradient operators for shape extraction, "Mask-Shape-BTC" CBIR techniques outperform the "Mask-Shape" CBIR techniques. The performance ranking of the masks for proposed image retrieval methods can be listed as Robert (best performance), Prewitt, Sobel and lastly the Canny.

The paper discusses novel image retrieval methods based on edge texture of images extracted using morphological operators. The existing CBIR techniques are based on the feature vectors extracted from morphological edge extraction techniques such as simple morphological edge extraction technique, Top-Hat transform and Bottom-Hat transform. The proposed CBIR techniques are using the morphological edge extraction techniques with block truncation coding (BTC). The proposed techniques are tested on generic image database with 1000 images spread across 11 categories. In all 55 queries (5 from each category) are fired on the image database. The average precision and recall of all queries are computed and considered for performance analysis. The experimental results show that use of BTC over morphological shape images for feature extraction improves the performance of image retrieval with reduced computational complexity for query execution. In all BTC with simple morphological edge extraction based CBIR method (SMBTC) gives best performance.

The paper discusses novel image retrieval methods based on edge texture of images extracted using gradient operators and slope magnitude technique with image transforms. Twenty eight variations of proposed image retrieval techniques using seven image transforms and four gradient operators like Roberts, Sobel, Prewitt and Canny are considered here. The proposed image retrieval techniques are tested on generic image database with 1000 images spread across 11 categories. In all 55 queries (5 from each category) are fired on the image database. The average precision and recall of all queries are computed and considered for performance analysis. The various "Mask-Shape-Transform" CBIR techniques [1] are compared with each other and each of the proposed "Mask-Shape-Transform" CBIR methods. The "Mask-Shape-Transform" is found to be better than the "Mask-Shape" Technique. In all Roberts-Kekre-Transform based CBIR gives best performance followed by Sobel-Slant-Transform and Sobel-Hartley-Transform.

Impact Investing is a community of investors willing to create social and environmental impact along with financial returns by investing either directly with Base of Pyramid[1] (BoP) enterprises or indirectly through enterprises that help in creating impact by investing in BoP organizations. Adoption of SDGs[2] quantified the expectation paradigm of the global community for social, environmental and economic achievable and projected/targeted achievement of SDGs by 2030 made the governments, businesses, institutions daunted with the task in hand hence, it is imperative for investing community to contribute its share as well. With high social need and underserved population India has become a test bed for impact investing. However, with increasing impact investing, Impact Measurement and Management (IMM) gains significant importance as it allows investors to evaluate impact and channelize fund to most effective solutions. The present study conducted for year 2019 not only attempts to explore impact investing landscape in India and its future dimension but it simultaneously does content analysis of impact report of investors using impact value chain[3] and indicators developed on the basis of SDGs targets and indicators. The analysis aims to establish a link between developed indicators and impact, the link once established, developed indicators will provide agile, cost effective, quantifiable and measurable basis to impact that has worldwide acceptance. [1]Base of Pyramid refers to the poorest two-third of the economic human pyramid living in abject poverty. [2]SDGs, adopted in 2015 by all UN member states, are universally accepted goals and targets under goals to guide sustainable development and create a sustainable world for all. [3]Impact Value chain is a tool build on theory of change to illustrate how enterprise activities lead to desired outcome and impact by setting a relationship between activities, output, outcome and impact.