University of Calcutta (informally known as Calcutta University or CU) is a collegiate public state university located in Kolkata, West Bengal, India.&nbsp;Within India it is recognized as a &quot;Five-Star University&quot; and accredited &quot;A&quot; Grade by National Assessment and Accreditation Council.

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The University of Calcutta has secured the Fifth position among the Universities of India in the prestigious &quot;Indian University Ranking 2019&quot; list, released by the NIRF of the Ministry of Human Resource Development, Government of India.

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It was established on 24 January 1857, and was one of the first institutions in Asia to be established as a multidisciplinary and Western-style university. Its alumni and faculty include several heads of state, heads of government, social reformers, prominent artists, only academy award winner and Dirac medal winner in India, many Fellows of the Royal Society and five Nobel laureates as of 2019 which is highest in South Asia.

University Of Calcutta

Disbursement of loan is an important decision-making process for the corporate like banks and NBFC (Non-banking Finance Corporation) those offers loans. The business involves several parameters and the data which are associated to these parameters are generated from heterogeneous data sources and also belong to different business verticals. Henceforth the decision-making on loan scenarios are critical and the outcome involve solving the issues like whether to grant the loan or not, if sanctioned what is highest amount, etc. In this paper we consider the traditional parameters of loan sanction process along with these we identify one special case of Indian credit lending scenario where the people having old loans with good repayment history get priority. This limits the business opportunities for Bank/NBFC or other loan disbursement organizations as potential good customers having no loan history are treated with less priority. In this research work we propose a data warehouse model which integrates the existing parameters of loan disbursement related decisions and also incorporates the newly identified concepts to give the priorities to the customers who don’t have any old credit history. © Springer Nature Singapore Pte Ltd. 2019.

Geology

GENERAL

Advances in Intelligent Systems and Computing

A data warehouse based schema design on decision-making in loan disbursement for Indian advance sector

This study serves as a first investigation report of benthic foraminifera from Chandipur, east coast of the Indian subcontinent. It concerns the microhabitats of the intertidal living foraminiferal population of Chandipur coast. Three short core samples of 20 cm each were collected from various sub-environments of the Chandipur coast (mud flat, estuary mouth and intertidal flat) and investigated for benthic foraminifera. Eleven genera of foraminifera have been identified, consisting both calcareous and agglutinated forms. The calcareous foraminifera are comprised of Ammonia spp., Haynesina spp., Asterorotalia sp. and Quinqueloculina sp.; with minor occasional occurences of Cribroelphidium sp. and the agglutinated species are Trochammina spp., Miliammina sp. and Haplophragmoides sp. The living foraminiferal count reduces drastically down the cores and shows one or more maxima deeper in the sediment. These different types of vertical distribution are reflections of the tolerance or preference levels of taxa with respect to one or more abiotic parameters. Food availability and dissolved oxygen might play a role in determining the lower downcore maxima. Bioturbation can also actively transport foraminifera to deeper sediment layers, and cause accidental occurrence of taxa that are usually found at the sediment surface. The living population consisted mainly of Haynesina germanica, Haynesina depressula and Ammonia tepida. Abundance of living populations of Haynesina spp. suggests a fluvial influence and higher clay percentages of this area. This also corroborates with good abundance of Ammonia tepida, indicating fluvial influence and lower percentages of sand. Good abundance of Asterorotalia trispinosa indicates high sedimentation rates.