522 citations · 566 across the 11 of their papers we have counts for
12 papers
The State of Lithium-Ion Battery Health Prognostics in the CPS Era
Gaurav Shinde, Rohan Mohapatra, Pooja Krishan +5
Lithium-ion batteries (Li-ion) have revolutionized energy storage technology, becoming integral to our daily lives by powering a diverse range of devices and applications. Their hi…
Large-scale End-of-Life Prediction of Hard Disks in Distributed Datacenters
Rohan Mohapatra, Austin Coursey, Saptarshi Sengupta
On a daily basis, data centers process huge volumes of data backed by the proliferation of inexpensive hard disks. Data stored in these disks serve a range of critical functional n…
Integration of a machine learning model into a decision support tool to predict absenteeism at work of prospective employees
Gopal Nath, Antoine Harfouche, Austin Coursey +3
Purpose - Inefficient hiring may result in lower productivity and higher training costs. Productivity losses caused by absenteeism at work cost U.S. employers billions of dollars e…
Remaining Useful Life Estimation of Hard Disk Drives using Bidirectional LSTM Networks
Austin Coursey, Gopal Nath, Srikanth Prabhu +1
Physical and cloud storage services are well-served by functioning and reliable high-volume storage systems. Recent observations point to hard disk reliability as one of the most p…
Data-Driven Optimization of Public Transit Schedule
Sanchita Basak, Fangzhou Sun, Saptarshi Sengupta +1
Bus transit systems are the backbone of public transportation in the United States. An important indicator of the quality of service in such infrastructures is on-time performance…
A Review of Deep Learning with Special Emphasis on Architectures, Applications and Recent Trends
Saptarshi Sengupta, Sanchita Basak, Pallabi Saikia +5
Deep learning has solved a problem that as little as five years ago was thought by many to be intractable - the automatic recognition of patterns in data; and it can do so with acc…
Chaotic Quantum Double Delta Swarm Algorithm using Chebyshev Maps: Theoretical Foundations, Performance Analyses and Convergence Issues
Saptarshi Sengupta, Sanchita Basak, Richard Alan Peters
Quantum Double Delta Swarm (QDDS) Algorithm is a new metaheuristic algorithm inspired by the convergence mechanism to the center of potential generated within a single well of a sp…
Mechanisms for Integrated Feature Normalization and Remaining Useful Life Estimation Using LSTMs Applied to Hard-Disks
Sanchita Basak, Saptarshi Sengupta, Abhishek Dubey
With emerging smart communities, improving overall system availability is becoming a major concern. In order to improve the reliability of the components in a system we propose an…
QDDS: A Novel Quantum Swarm Algorithm Inspired by a Double Dirac Delta Potential
Saptarshi Sengupta, Sanchita Basak, Richard Alan Peters
In this paper a novel Quantum Double Delta Swarm (QDDS) algorithm modeled after the mechanism of convergence to the center of attractive potential field generated within a single w…
Learning to track on-the-fly using a particle filter with annealed- weighted QPSO modeled after a singular Dirac delta potential
Saptarshi Sengupta, Richard Alan Peters
This paper proposes an evolutionary Particle Filter with a memory guided proposal step size update and an improved, fully-connected Quantum-behaved Particle Swarm Optimization (QPS…
Particle Swarm Optimization: A survey of historical and recent developments with hybridization perspectives
Saptarshi Sengupta, Sanchita Basak, Richard Alan Peters
Particle Swarm Optimization (PSO) is a metaheuristic global optimization paradigm that has gained prominence in the last two decades due to its ease of application in unsupervised,…
Data Clustering using a Hybrid of Fuzzy C-Means and Quantum-behaved Particle Swarm Optimization
Saptarshi Sengupta, Sanchita Basak, Richard Alan Peters
Fuzzy clustering has become a widely used data mining technique and plays an important role in grouping, traversing and selectively using data for user specified applications. The…