Faculty Publications

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Publications by NITK Faculty

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Author: search.filters.author.Jose, N.

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    Solid-State Fermentation vs Submerged Fermentation for the Production of L-Asparaginase
    (Academic Press Inc. apjcs@harcourt.com, 2016) Doriya, K.; Jose, N.; Gowda, M.; Kumar, D.S.
    L-Asparaginase, an enzyme that catalyzes L-asparagine into aspartic acid and ammonia, has relevant applications in the pharmaceutical and food industry. So, this enzyme is used in the treatment of acute lymphoblastic leukemia, a malignant disorder in children. This enzyme is also able to reduce the amount of acrylamide found in carbohydrate-rich fried and baked foods which is carcinogenic to humans. The concentration of acrylamide in food can be reduced by deamination of asparagine using L-Asparaginase. L-Asparaginase is present in plants, animals, and microbes. Various microorganisms such as bacteria, yeast, and fungi are generally used for the production of L-Asparaginase as it is difficult to obtain the same from plants and animals. L-Asparaginase from bacteria causes anaphylaxis and other abnormal sensitive reactions. To overcome this, eukaryotic organisms such as fungi can be used for the production of L-Asparaginase. L-Asparaginase can be produced either by solid-state fermentation (SSF) or by submerged fermentation (SmF). SSF is preferred over SmF as it is cost effective, eco-friendly and it delivers high yield of enzyme. SSF process utilizes agricultural and industrial wastes as solid substrate. The contamination level is substantially reduced in SSF through low moisture content. Current chapter will discuss in detail the chemistry and applications of L-Asparaginase enzyme and various methods available for the production of the enzyme, especially focusing on the advantages and limitations of SSF and SmF processes. © 2016 Elsevier Inc.
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    Findings of the Shared Task on Offensive Language Identification in Tamil, Malayalam, and Kannada
    (Association for Computational Linguistics (ACL), 2021) Chakravarthi, B.R.; Priyadharshini, R.; Jose, N.; Anand Kumar, M.; Mandl, T.; Kumaresan, P.K.; Ponnusamy, R.; LekshmiAmmal, R.L.; Mccrae, J.P.; Sherly, E.
    Detecting offensive language in social media in local languages is critical for moderating user-generated content. Thus, the field of offensive language identification for under-resourced languages like Tamil, Malayalam and Kannada is of essential importance. As user-generated content is often code-mixed and not well studied for under-resourced languages, it is imperative to create resources and conduct benchmark studies to encourage research in under-resourced Dravidian languages. We created a shared task on offensive language detection in Dravidian languages. We summarize the dataset for this challenge which are openly available at https://competitions.codalab.org/competitions/27654, and present an overview of the methods and the results of the competing systems. ©2021 Association for Computational Linguistics
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    Implementation of PWM Speed control for SRM drive using TMS320F28069 Microcontroller
    (Institute of Electrical and Electronics Engineers Inc., 2023) Manaswi, K.; Jose, N.; Bhaktha, S.; Balasubramanian, B.; Gangadharan, K.V.
    Switched reluctance motors (SRMs) are a promising alternative to conventional motors in various variable speed applications due to their simple design, low production costs, high starting torque, wide speed range, high reliability, and efficiency. However, they suffer from high torque ripple and system noise, which can be minimized by selecting appropriate control methods and converter topologies. Due to the intricate nature of the control, motor drives may employ digital systems by utilizing high-speed digital signal processors (DSPs) or microcontrollers (MCUs) to achieve superior results which offers the flexibility to implement complex control algorithms with high precision and accuracy. Therefore, this study proposes the implementation of a Voltage PWM control strategy for a Switched Reluctance Motor (SRM) on a compact high-speed microcontroller (TMS320F28069) using Code Composer Studio. This study demonstrates how MCUs can aid in the precise control of SRMs. © 2023 IEEE.
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    Methodology for Modelling a Custom SRM Configuration Using MATLAB/Simulink
    (Institute of Electrical and Electronics Engineers Inc., 2024) Jose, N.; Jayaraman, A.; Bhaktha, S.; Sarma, S.; Balasubramanian, B.; Gangadharan, K.V.
    Switched Reluctance Motors (SRMs) have gained significant attention in recent years due to their simplicity, robustness, and energy efficiency, making them suitable for various applications such as electric vehicles. However, the development of custom configurations for SRMs presents challenges due to limited options in existing simulation platforms like MATLAB/Simulink. This paper presents a comprehensive methodology for modelling and simulating a custom SRM configuration, specifically a 4-phase, 8/18 Multi-Teeth (MT) SRM, using MATLAB/Simulink. The methodology involves estimating Look-Up Tables (LUTs) using electromagnetic static Finite Element Analysis (FEA), developing mathematical models for phase current and torque, and integrating them into a Simulink model. After that, a closed loop speed control simulation using Hysteresis Current Control (HCC) and Anti-windup PID is applied to the created model. The simulation results demonstrate the effectiveness of the proposed methodology in accurately predicting the motor's performance. Additionally, a comparison with FEA results highlights the model's ability to closely replicate real-world behaviour, despite minor discrepancies attributed to differences in handling mutual phase coupling effects. © 2024 IEEE.
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    Driving Cycle-Based Design Optimization and Experimental Verification of a Switched Reluctance Motor for an E-Rickshaw
    (Institute of Electrical and Electronics Engineers Inc., 2024) Bhaktha, B.S.; Jose, N.; Vamshik, M.; Pitchaimani, J.; Gangadharan, K.V.
    This article deals with the design and optimization of a 2 kW switched reluctance motor (SRM) for an electric rickshaw (E-rickshaw). Previously published research on SRM optimization has mostly focused on the optimization of their design and control variables only at the rated conditions. In electric vehicle (EV) applications, the load operating points (LOPs) of a traction motor are dynamic and spread widely across the torque speed envelope. To enhance their overall performance, it is vital to include them in the design optimization process; therefore, in this article, a novel procedure for implementing the multiobjective design optimization (MODO) of an SRM based on a driving cycle has been demonstrated. Higher starting torque and torque density with reduced electromagnetic losses throughout the driving cycle are established as the design objectives, subject to practical restrictions on current density and slot fill factor. The design objectives have been accurately evaluated through transient finite element analysis (FEA) and a computationally efficient SRM drive model (developed in MATLAB/Simulink) with consideration of the excitation control parameters. Kriging models have been constructed to reduce the computation cost of FEA during the optimization process. Then, a nondominated sorting genetic algorithm II (NSGA II) based multiobjective optimization coupled with the constructed Kriging models is conducted to generate a Pareto front. An optimal design that offers the best balance between the design objectives is selected from the Pareto-optimal set, and the dimensions of corresponding design variables are used to build a prototype. Finally, the static and dynamic performance of the SRM prototype are experimentally evaluated and validated with the FEA simulations. © 2024 IEEE.
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    Vibration reduction and intelligent control in SRM using optimised two stage commutation
    (Inderscience Publishers, 2025) Wilson, V.; Latha, P.G.; Jose, N.; Bhaktha, S.
    Switched reluctance motors (SRMs) have grown in popularity in a variety of industrial applications due to their inherent benefits such as high fault-tolerance, simplicity, affordability, and rare-earth free nature. However, the generation of undesirable vibrations due to radial force variations remains a significant challenge. Two stage commutation based on active vibration cancellation (AVC) is an effective method to reduce these vibrations. The focus of this paper is to address the major limitation with two stage commutation, namely the extended tail current causing increased copper loss. This is accomplished with optimal commutation parameters employing particle swarm optimisation (PSO) method. A MATLAB/Simulink model of SRM with vibration signal is developed and is used for demonstrating vibration cancellation. An intelligent control is also implemented which can track the dynamic changes in speed-load conditions. This paper showcases that this approach is an effective solution to reduce the vibrations issues in SRM, thereby improving the overall performance of the motor for industrial applications. © © 2025 Inderscience Enterprises Ltd.