A Signature-based Clustering Approach for Record Matching from Multiple Databases
Prabhjyot Juneja and Urjita Thakar

Abstract
Various business analytics depend on collection and analysis of large volumes of data. Data from multiple sources may need to be integrated and examined to draw fruitful results. Lack of a global unique identifier and other data inconsistencies pose challenges in linking such data. Existing record linkage approaches set certain prerequisites in form of either training data or known match status of databases under consideration. These approaches rely particularly on the problem datasets and are practically infeasible for large volumes of disparate real-world data. The proposed signature-based clustering approach generates multiple signatures of each record and clusters similar records together using affinity propagation clustering technique. Each set of clustered records is then represented by its representative feature.
High performance of the proposed algorithm on various real-world and synthetic datasets indicates its efficiency over existing approaches. The proposed system generates matching results with an average 92% accuracy. Representation of each set of similar records by a single representative feature greatly reduces the number of overall comparisons and memory requirements of the matching process, thereby improving the matching quality.
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Strategy for the Separation of Azeotropic Mixture by Pressure Swing Distillation
Seema Kakade, Rajendra Ugwekar and Sanjay Shirsat

Abstract
Pressure swing distillation (PSD) is a technique coming forward as a strong alternative to the conventional separation methods for separating azeotropes. The conventional pressure swing distillation involves two columns operated at two different pressures. This work puts forward a new three column oressure swing distillation strategy for the separation of azeotropic Isobutyl Alcohol (IBA) - Isobutyl Acetate (IBAc) mixture. Two of the columns are operated at atmospheric pressure while third at a lower pressure. CHEMCAD (version 6.5) software is used to perform the simulations to get the optimized configuration which gives minimum energy requirements. The proposed process comes out to be more energy efficient when compared to the conventional two column techniques.
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Re-Engineering the Global Supply Chain Network for Importing Knitwear Capital Goods in India
Baba Gnanakumar P.

Abstract
Due to increase in the exports of Knitted garments, the Knitting exporting units decided to re-engineer the capital goods. The domestic suppliers are unable to satisfy the demand of the capital goods in time and the import of machinery from other countries are cheaper. In this context, the research has motivated to find out the supply chain reference model required to upgrade the technology in Knitting units. The study is conducted among 121 Export oriented units located in Tirupur, which is considered as the hub for knitwear units in India. The result indicates that technology upgradation is the main factor in deciding capital goods. Hence, the Supply chain reference model has been designed based on the technology upgradation mapping system..
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Role of Behavioural Finance in Stock Market Investment by Retail Indian Investor’s
Shobana Swamynathan

Abstract
Financial system plays an important role in the economic growth of a country. Financial system allows exchange of money between savers and borrowers. Various financial institutions, markets, instruments and services work in the complexly knit financial system and paves for the smooth transfer and allocation of funds efficiently and effectively. Indian stock market is one of the vital area of market economy were investors park their funds and thereby claim to be the owners of the company. Behavioural finance deals with psychological influence of investor’s behaviour with respect to financial decision making and its impact on the markets. The main aim of this research is to identify Indian investor’s investment objective to invest in Indian stock market.
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