DSpace at Indian Statistical Institute
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The DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material.2024-03-28T15:21:04ZUnitary Connections and Q-Systems
http://hdl.handle.net/10263/7440
Title: Unitary Connections and Q-Systems
Authors: Ghosh, Mainak
Abstract: In the classification programme of subfactors, the standard invariant plays a quintessential role. In this thesis, we furnish a 2-categorical perspective of the standard invariant of finite-index subfactors and further study algebraic structures (Q-systems) associated with them
Description: This thesis is under the supervision of Dr. Shamindra Kumar Ghosh2023-04-01T00:00:00ZPrice Escalation Verification Report
http://hdl.handle.net/10263/7439
Title: Price Escalation Verification Report
Authors: Economic Research Unit, .
Abstract: At the request of Coal India Limited (CIL) the “Price Escalation Verification
Project” has been undertaken by a team of the Economic Research Unit, Indian
Statistical Institute. The project examines the escalation clause associated with the
price index formula to be used in contract agreements between CIL and Mine
Developers.
The existing formulae for price escalation, both for open cast and underground coal
mining, have been examined and certain modifications along with justification have
been proposed. Using illustrative examples, it is found that the suggested escalation
formulae have significant impact on the final prices.2016-11-01T00:00:00ZEquivariant Homology Decompositions for Projective Spaces and Associated Results
http://hdl.handle.net/10263/7437
Title: Equivariant Homology Decompositions for Projective Spaces and Associated Results
Authors: Karmakar, Aparajita
Abstract: Abstracts
Description: This thesis is under the supervision of Prof Samik Basu2023-12-01T00:00:00ZTFNet: Time and Frequency Modeling for Irregular Multivariate Medical Time Series
http://hdl.handle.net/10263/7436
Title: TFNet: Time and Frequency Modeling for Irregular Multivariate Medical Time Series
Authors: Lakkoju, V S Siva Kumar
Abstract: Time Series Classification (TSC) involves assigning a target label based on features
involving time series data. TSC arises in a variety of domains, like healthcare, finance, process control, weather pattern prediction, etc. This work is focused on
exploiting both frequency and time domains of a time series. Inspired by the
TimesNet proposed in [27], which learns multi-periodic variations, we proposed
Time-Frequency Network (TFNet), a novel Deep Learning model, and applied it
to irregular medical time series data. Earlier methods used either only features
captured in the time domain or in the frequency domain. It is di"cult to learn
both temporal dependencies and understand cyclic or seasonality patterns when
analyzed in a single domain. To tackle these limitations, we extend the TimesNet
model to perform time domain analysis. Our proposed TFNet achieves an improved performance when applied to in-hospital mortality (IHM) prediction based
on 48 hours of ICU stay, on a dataset extracted from Medical Information Mart
for Intensive Care (MIMIC-III)
Description: Dissertation under the supervision of Dr. Swagatam Das2023-06-01T00:00:00Z