Faculty Publications
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Publications by NITK Faculty
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Item Mechanical and Microstructural Properties of Multi-Axially Forged LM6 Aluminium Alloy(Pleiades journals, 2019) Sajjan, S.S.; Kulkarni, M.V.; Ramesh, S.; Sharath, P.C.; Rajesh, R.; Kumar, V.In the present investigation, commercially available light metal aluminium LM6 alloy was processed by Multi-axial forging (MAF) at ambient temperature. MAF was carried out to an equivalent strain in 0.83, 1.66 and 2.4 i.e., 6 passes, 12 passes and 18 passes, respectively. The mechanical properties like tensile test, compression test, hardness and microstructural characterization were studied in processed and unprocessed samples. Ultimate tensile strength (UTS) and ductility improved from 137 to 185 MPa and 3 to 6.2% for as-received to processed samples, respectively. After 18 passes of MAF, the compression strength (CS) has improved from 342 to 530 MPa. Hardness increased as the number of forging passes increases as compared to unprocessed samples. Optical microscopy images were used to study microstructure observations, the average grain size is reduced from 60 to 2 μm for as-received to processed samples, respectively. Strength and hardness increased because of the grain refinement for the processed samples and the introduction of the high amount of dislocation density into the material during the MAF process. Fracture study was conducted by utilizing scanning electron microscopy, dimples on tensile fracture surfaces revealed that ductile mode of fracture. © 2019, Springer Nature Singapore Pte Ltd.Item Review on inorganic ion exchange membranes for diverse applications(Elsevier, 2023) Vijesh, A.M.; Isloor, A.M.; Kumar, V.Ion exchange membranes (IEMs) are extensively employed in many separation processes, especially in water treatment and fuel cells. Separation using IEMs makes the process more environment friendly, greener, and energy efficient. It is also useful in recovering some components of the effluents otherwise that are being left as waste and significantly contributes to the sustainable growth of the society. Inorganic IEMs are superior to the organic IEMs in various aspects. This review chapter addresses the recent developments in the inorganic IEMs in consideration with their preparation and potential applications. © 2024 Elsevier Inc. All rights reserved.Item Advances of membrane technology in wastewater treatment(Elsevier, 2024) Deepthi, P.V.; Viji, K.; Vijesh, A.M.; Isloor, A.M.; Kumar, V.Pure water scarcity is becoming a real threat to the modern world. Rapid growth in the textile, paper, and printing industries has caused the production of large quantities of dye effluents, and they must be treated before passing to the water bodies or lands to minimize pollution and environmental impacts. Polymeric membrane-based filtration has been established as an optimal and greener approach for removing hazardous dyes from polluted water. Superior thermal, chemical, and mechanical properties and convenient modifiability made polysulfone (PSF), polyethersulfone (PES), and polyphenylsulfone (PPSU) ideal for the production of membranes for the treatment of dye effluents from industries. This chapter emphasizes the recent developments in modified PSF, PES, and PPSU membranes and their dye rejection properties. © 2025 Elsevier Inc. All rights reserved.Item Automatic Optic Disc segmentation using maximum intensity variation(2013) Kumar, V.; Sinha, N.Optic disc (OD) segmentation is an important step in automating eye screening for pathological conditions. In this paper, we propose an intensity-based approach to detect the OD boundary, given OD center. OD center is utilized to crop the sub-image that encloses the OD, within which candidate contour points are obtained. Points of maximum intensity variation, both horizontally and vertically, are chosen as candidate contour points. Iterative curve fitting is carried out, incorporating smoothness constraints. The area within the contour is checked for values of mean intensity, variance and compactness. The algorithm is applied on 152 images taken from two public datasets, DIARETDB1 and MESSIDOR. The validation criteria used are common area overlapping between automated segmentation and true OD region (score), sensitivity and Mean Distance to Closest Point (MDCP). The algorithm renders, on an average, a score value of 90%, sensitivity of 93% and MDCP of 8.3 pixels. © 2013 IEEE.Item Multi-label annotation of music(Institute of Electrical and Electronics Engineers Inc., 2015) Ahsan, H.; Kumar, V.; Jawahar, C.V.Automatic annotation of an audio or a music piece with multiple labels helps in understanding the composition of a music. Such meta-level information can be very useful in applications such as music transcription, retrieval, organization and personalization. In this work, we formulate the problem of annotation as multi-label classification which is considerably different from that of a popular single (binary or multi-class) label classification. We employ both the nearest neighbour and max-margin (SVM) formulations for the automatic annotation. We consider K-NN and SVM that are adapted for multi-label classification using one-vs-rest strategy and a direct multi-label classification formulation using ML-KNN and M3L. In the case of music, often the signatures of the labels (e.g. instruments and vocal signatures) are fused in the features. We therefore propose a simple feature augmentation technique based on non-negative matrix factorization (NMF) with an intuition to decompose a music piece into its constituent components. We conducted our experiments on two data sets - Indian classical instruments dataset and Emotions dataset [1], and validate the methods. © 2015 IEEE.Item Handheld electrochemical workstation for serum albumin measurement(Institute of Electrical and Electronics Engineers Inc., 2016) Hebbar, S.; Kumar, V.; Bhat, M.S.; Bhat, N.This paper presents a novel handheld electrochemical workstation for serum albumin measurement. The system consists of a multi-path potentiostat module which performs electrochemical measurements on disposable test strip. The strip provides a port for applying blood sample. The test strip consists of 3 electrochemical cells for redundancy and parallel testing. The 3 sets of 3 electrodes (Working, Reference and Counter electrodes) are screen printed on a Polyethylene Terephthalate (PET) substrate. The system provides the unique capability of performing Cyclic Voltammetry and Chrono Amperometry measurements in three parallel paths. The system is very generic and flexible, with user defined inputs for voltage, sweep rate and time through 5 inch capacitive touch screen. The experimental results can be stored on micro SD card and the data is accessible with USB or Bluetooth interface. This paper reports an extensive characterization of system through several tests conducted on standard redox solution. The system is then validated for human serum albumin measurement, using clinical samples. This is the first ever point of care handheld diagnostic device in the world for human serum albumin measurement. © 2016 IEEE.Item TCP Kay: An end-to-end improvement to TCP performance in lossy wireless networks using ACK-DIV technique and FEC(Institute of Electrical and Electronics Engineers Inc., 2016) Krishnaprasad, K.; Tahiliani, M.P.; Kumar, V.Wireless networks have evolved considerably in the last decade and the world has seen an exponential increase in the number of mobile device users. The performance of the wireless networks has become a critical factor and researchers nowadays are trying to bring out even the slightest increase in network performance wherever possible. TCP, which is the most dominant transport protocol of the Internet, fails to perform well in lossy wireless networks because it cannot differentiate congestion losses from non-congestion losses. This paper aims to improve the performance of TCP in lossy wireless networks and the resulting protocol is termed as TCP Kay. The major contributions of TCP Kay are: (1) it uses a modified ACK-DIV (Acknowledgment Division) technique for combating the loss of acknowledgement packets (ACKs) on the reverse path and (2) it combines the modified ACK-DIV technique with FEC to further enhance the robustness of data transmission in lossy wireless networks. The performance of TCP Kay has been studied using ns-2 and the same has been compared with TCP Reno with SACK (TCP SACK) and TCP Westwood+ (TCPW+). Results show that TCP Kay outperforms other TCPs in terms of goodput, received/sent ratio and packet drop rate in various wireless scenarios with up to 5% packet error rate. © 2015 IEEE.Item Soil classification using airborne hyperspectral data employing various approaches(Asian Association on Remote Sensing Sh1939murai@nifty.com, 2017) George, J.K.; Kumar, V.; Tarun, B.; Kumar, S.; Senthil Kumar, A.S.Hyperspectral remote sensing technology is one of the advance technology for detailed land cover feature extraction. Hyperspectral datasets contain large number of contiguous spectral bands with a narrow spectral bandwidth which enables identification of peculiar absorption features for distinguishing different type of soils. The potential of Airborne Visible Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) data was tested for distinguishing black and red soils in the ICRISAT area near Hyderabad, Telangana. The AVIRIS-NG data captured in 432 narrow contiguous bands (346–2505 nm) with spectral sampling of 5 nm bandwidth and a 4m ground pixel size was used in this study. The dataset was first spectrally subsetted by identification and removal of bad bands and was atmospherically corrected by converting it to surface reflectance using FLAASH. The data was finally georeferenced using the Internal Geometry Module (IGM) parameters. Optimal spectral bands from the reflectance data were selected on the basis of different characteristics of various soils. Data dimensionality reduction technique Minimum Noise Fraction (MNF) was also performed to extract noise free components. Total five classes including red and black soils were considered for land cover classification. Pixel based classification techniques such as Spectral Angle Mapper(SAM) and Support Vector Machine (SVM) were performed on the reflectance as well as MNF transformed data. SVM was also performed on data containing noise free MNF components and the selected optimal spectral bands. In the resultant classified output of reflectance data, SVM classifier provided higher accuracy and was able to classify black and red soil in a better way than SAM technique. The results also suggested that use of MNF components and specific spectral bands altogether improvised the classification of black and red soil. © 2017 ACRS. All rights reserved.Item Smart handheld platform for electrochemical bio sensors(Institute of Electrical and Electronics Engineers Inc., 2017) Hebbar, S.; Kumar, V.; Bhat, M.S.; Bhat, N.In this paper we present a smart handheld system for point of care biosensors. The system consists of a novel multi-path potentiostat module which performs electrochemical measurements on disposable test strip. The strip provides a port for applying bio-sample such as blood or urine. The analyte port on the disposable strip is designed with 3 sets of 3 electrodes (Working, Reference and Counter electrodes) screen printed on a Polyethylene Terephthlate (PET) substrate. The system provides the unique capability of performing Cyclic Voltametry and Chrono Amperometry measurements in three parallel paths, facilitating simultaneous measurement of three bio-analytes. The system is very generic and flexible, with user defined inputs for voltage, sweep rate and time through 5 inch capacitive touch screen. The experimental results can be stored on micro SD card and the data is accessible with USB or Bluetooth interface. © 2016 IEEE.Item Risk aware portfolio construction using deep deterministic policy gradients(Institute of Electrical and Electronics Engineers Inc., 2018) Hegde, S.; Kumar, V.; Singh, A.Allocation of liquid capital to the financial instruments in a portfolio is typically done using a two-step process. In the first step, predictive techniques are used to determine the future risk and rewards for the instrument. In the subsequent step, a quadratic optimization problem is solved to obtain the allocation that maximizes a relevant measure of the portfolio performance computed using a combination of the risks and the rewards. Deep Reinforcement Learning (DRL) eliminates the need for a two step process to find the allocation across the instruments that will optimize a measure of portfolio performance obtained from the market. DRL based portfolio construction autonomously adjusts to a change in the environment unlike traditional machine learning algorithms used in prediction. The existing DRL methods suffer from the challenges of stability, and do not lend themselves well to the portfolio construction problem that has a continuous action space. Proposed in 2015, Deep Deterministic Policy Gradients (DDPG) is a type of actorcritic DRL algorithm that provides support for continuous action space which is encountered in portfolio construction. This paper evaluates the use of DDPG to solve the problem of risk aware portfolio construction. Simulations are done on a portfolio of twenty stocks and the use of both Rate of Return and Sortino ratio as a measure of portfolio performance are evaluated. Results are presented that demonstrate the effectiveness of DDPG for risk aware portfolio construction. The simulation results presented in this paper show that having a risk-aware measure of portfolio performance such as Sortino ratio give a portfolio with superior return and lower variance. © 2018 IEEE.