Browsing by Author "Roy, A."

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A study on dimensional analysis modeling of crater size during wire electrical discharge turning process by using Buckingham Pi theorem
(Elsevier Ltd, 2022) Naik, G.M.; Hipparagi, M.A.; Bellubbi, S.; Roy, A.; Anjan, B.N.; Ramesh, S.; Narendranath, S.
The investigation on material removal by thermal erosion of discrete spark and vaporization in wire electrical discharge turning process was made to understand the crater size variation on turned components. In this study the modelling is done to establish the relationship between dependent and independent variables through Buckingham's Pi-theorem, to predict the variations of crater diameter depending on physical and thermal properties, subsequently the dimensional model was validated by conducting experiments on wire-electrical discharge turning process for two distinct density variant materials such as Aluminium 6061 and INCONEL 718 super alloys. The density, enthalpy of vaporization, radius of spark, specific heat and other quantities effect on crater diameter have been discussed in this research paper. Â© 2022
A Survey ofÂ Hyperparameter Selection Methods forÂ Weather Forecasting Using State-of-the-Art Machine Learning Algorithms
(Springer Science and Business Media Deutschland GmbH, 2025) Sen, A.; Sen, U.; Paul, M.; Sutradhar, A.; Vankala, T.N.; Mallick, C.; Mallik, A.; Roy, A.; Sai, S.; Roy, S.
Weather forecasting is an important aspect across various sectors, but the intricate dynamics of weather systems pose a challenge for conventional statistical models to forecast accurately. Besides auto-regressive time forecasting models like ARIMA, deep learning architectures like ANNs, LSTMs, and GRU networks have been shown to enhance the accuracy of forecasts by considering temporal dependencies. This paper studies various machine learning models like XGBoost, SVR, KNN Regressor, Random Forest Regressor and the application of metaheuristic algorithms, like Genetic Algorithm (GA), Differential Evolution (DE), and Particle Swarm Optimization (PSO), on some deep learning model architectures like ANNs, LSTMs and GRUs, to automate the process of finding the best hyperparameters for the models. Furthermore, this paper explores the Quantum LSTM (QLSTM) network and novel QLSTM Ensemble models. We conduct a comparative study of these model structures, evaluating their effectiveness in weather prediction using measures such as Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE). The findings underscore the capabilities of metaheuristic algorithms and innovative quantum methods in enhancing the precision of weather forecasts. Â© The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
Active feedback supported CMOS LNA blended with coplanar waveguide-fed antenna for Wi-Fi networks
Roy, A.; Gunjan Mittal; Dwari; Santanu; Kanaujia; Binod Kumar; Kumar; Sandeep; Song; Hanjung
This study presents integration of complementary CMOS active feedback low noise amplifier with coplanar waveguide fed patch antenna for Wi-Fi networks. The LNA design-I, involves a cascode amplifier followed by active feedback common source amplifier offering wideband impedance matching with lowered parasitic losses. The inductor-less feedback mechanism is used to nullify noise effect with extended bandwidth in the range of 2.2 to 5.8 GHz and a peak forward gain of 22.5 dB. It is implemented on agilent's advance design system using 45 nm CMOS process. The noise figure (NF) is approximately 2 dB while the stability factors mu and mu prime are well above 1 dB with IIP3 of about 15 dBm. The chip area is 0.57 x 0.57 mm(2) under dc power supply of 1V while power consumption of 0.8 mW. A CPW fed antenna design-II, achieves a wide band response similar to the bandwidth of LNA. The size of the fabricated antenna is calculated as 40 x 40 mm(2). The peak gain is approximately 4.1 dBi at 3.9 GHz. The codesign-III, proposes a receiver achieving a much wider band of 1.6 to 6 GHz with a gain of 16.5 dB and NF of 2.59 dB at 2.06 GHz. The codesign improves the system integration by reducing overall chip area and offers saving in the effective cost.
Active feedback supported CMOS LNA blended with coplanar waveguide-fed antenna for Wi-Fi networks
Roy, A.; Gunjan Mittal; Dwari; Santanu; Kanaujia; Binod Kumar; Kumar; Sandeep; Song; Hanjung
This study presents integration of complementary CMOS active feedback low noise amplifier with coplanar waveguide fed patch antenna for Wi-Fi networks. The LNA design-I, involves a cascode amplifier followed by active feedback common source amplifier offering wideband impedance matching with lowered parasitic losses. The inductor-less feedback mechanism is used to nullify noise effect with extended bandwidth in the range of 2.2 to 5.8 GHz and a peak forward gain of 22.5 dB. It is implemented on agilent's advance design system using 45 nm CMOS process. The noise figure (NF) is approximately 2 dB while the stability factors mu and mu prime are well above 1 dB with IIP3 of about 15 dBm. The chip area is 0.57 x 0.57 mm(2) under dc power supply of 1V while power consumption of 0.8 mW. A CPW fed antenna design-II, achieves a wide band response similar to the bandwidth of LNA. The size of the fabricated antenna is calculated as 40 x 40 mm(2). The peak gain is approximately 4.1 dBi at 3.9 GHz. The codesign-III, proposes a receiver achieving a much wider band of 1.6 to 6 GHz with a gain of 16.5 dB and NF of 2.59 dB at 2.06 GHz. The codesign improves the system integration by reducing overall chip area and offers saving in the effective cost.
An optimized fault diagnosis method for reciprocating air compressors based on SVM
(2011) Verma, N.K.; Roy, A.; Salour, A.
Fault diagnosis in reciprocating air compressors is essential for continuous monitoring of their performance and thereby ensuring quality output. Support Vector Machines (SVMs) are machine learning tools based on structural risk minimization principle and have the advantageous characteristic of good generalization. For this reason, four well-known and widely used SVM based methods, one-against-one (OAO), oneagainst-all (OAA), fuzzy decision function (FDF), and DDAG have been used here and an optimized SVM based technique is proposed for classification based fault diagnosis in reciprocating air compressors. The results obtained through implementation of all five techniques are thus compared as per their accuracy rate in percentages and the performance of the proposed method with 98.03 percent accuracy rate was found to be better than all other classification methods. With the compressor datasets being complex natured, proposed method is found to be of vital importance for classification based fault diagnosis pertaining to reciprocating air compressors. Â© 2011 IEEE.
Castelnuovo–Mumford regularity of the closed neighborhood ideal of a graph
(Springer, 2025) Chakraborty, S.; Joseph, A.P.; Roy, A.; Singh, A.
Let G be a finite simple graph, and let NI(G) denote the closed neighborhood ideal of G in a polynomial ring R. We show that if G is a forest, then the Castelnuovo–Mumford regularity of R/NI(G) is the same as the matching number of G, thus proving a conjecture of Sharifan and Moradi in the affirmative. We also show that the matching number of G provides a lower bound for the Castelnuovo–Mumford regularity of R/NI(G) for any G. Furthermore, we prove that if G contains a simplicial vertex, then NI(G) admits a Betti splitting, and consequently, we show that the projective dimension of R/NI(G) is also bounded below by the matching number of G, if G is a forest or a unicyclic graph. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.
Circuit Complexity in Z2 EEFT
(MDPI, 2023) Adhikari, K.; Choudhury, S.; Kumar, S.; Mandal, S.; Pandey, N.; Roy, A.; Sarkar, S.; Sarker, P.; Shariff, S.S.
Motivated by recent studies of circuit complexity in weakly interacting scalar field theory, we explore the computation of circuit complexity in (Formula presented.) Even Effective Field Theories ((Formula presented.) EEFTs). We consider a massive free field theory with higher-order Wilsonian operators such as (Formula presented.), (Formula presented.), and (Formula presented.) To facilitate our computation, we regularize the theory by putting it on a lattice. First, we consider a simple case of two oscillators and later generalize the results to N oscillators. This study was carried out for nearly Gaussian states. In our computation, the reference state is an approximately Gaussian unentangled state, and the corresponding target state, calculated from our theory, is an approximately Gaussian entangled state. We compute the complexity using the geometric approach developed by Nielsen, parameterizing the path-ordered unitary transformation and minimizing the geodesic in the space of unitaries. The contribution of higher-order operators to the circuit complexity in our theory is discussed. We also explore the dependency of complexity on other parameters in our theory for various cases. © 2022 by the authors.
Development and Surface Engineering of TiNi Shape Memory Alloy
(Springer Science and Business Media B.V., 2020) Soni, H.; Narendranath, S.; Mashninini, P.M.; Roy, A.; Sebin Binoy, T.; Jyothi, K.; Rojina, J.; Krishnan, A.
Shape memory alloys are currently replacing many conventional materials due to their various useful properties. Besides shape recovery above austenitic temperature and pseudo-elasticity, high strength and good corrosion properties are one of the many mentionable properties of these alloys. Due to their intriguing properties, aerospace, biomedical and automotive industries are leading the research frontier for these smart materials. This chapter presents the results of an experimental investigation conducted on development of Ti rich shape memory alloy by arc melting and hot rolling, and its surface study when machined by wire-EDM. The developed and machined specimens of TiNi alloys were also tested. Tensile study of the specimens showed that material rigidity has decreased due to intensive rolling process. Scan electron microscopic analysis of the fractured surface confirmed that the mode of failure of the rolled specimen was ductile in nature. Characteristic properties like necking, dimple formation, cracks which are related to ductile failure of metallic materials are clearly visible in the SEM micrographs. Micro hardness test revealed that micro hardness of the rolled specimens are much higher than as cast TiNi alloy and less along the edge of the fracture surface compared to bulk rolled material. © 2020, Springer Nature Switzerland AG.
Effect of peak current and peak voltage on machined surface morphology during WEDM of TiNiCu shape memory alloys
(Korean Society of Mechanical Engineers, 2020) Roy, A.; Narendranath, S.; Pramanik, A.
This study considers the effect of wire electro discharge machining (WEDM) parameter peak current (Ip) and pulse peak voltage (Vp) on the machined surface morphology of TiNiCu shape memory alloys. Various defects of machined surfaces were identified and correlated with parameter values and measured average surface roughness (Ra) and average surface depth (Rz). It was found that the nature of the machined surface is highly influenced by the nature of sparking, which is dictated by levels of peak current and peak voltage used during machining. Distinctions between machining parameters resulting in “rough-cut” and “trim-cut” machining are reported along with deviations in output responses, which counters the trend reported in the literature. © 2020, The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature.
Effect of spark gap voltage and wire electrode feed rate on machined surface morphology during Wire EDM process
(2018) Roy, A.; Narendranath, S.
Nature of machined surface morphology during wire electro discharge machining (Wire EDM) process depends on input process parameters like pulse on duration (Ton), pulse off duration (Toff), spark gap voltage (SV) and wire electrode feed rate (WF). After initial experimentation, duty factor (Ton/Ton+Toff = 120/150) was decided to be 0.8 based on suitable material removal rate. Afterwards effect of spark gap voltage and wire electrode feed rate on machined surface morphology was investigated. It was found that at lower spark gap voltage re-solidification and accumulation of debris on machined surface is more which reduces with increasing spark gap voltage. Debris size increases with increasing spark gap voltage and higher wire electrode feed rate leads to sparse accumulation of debris on machined surface. � 2018 Elsevier Ltd. All rights reserved.
Effect of spark gap voltage and wire electrode feed rate on machined surface morphology during Wire EDM process
(Elsevier Ltd, 2018) Roy, A.; Narendranath, S.
Nature of machined surface morphology during wire electro discharge machining (Wire EDM) process depends on input process parameters like pulse on duration (Ton), pulse off duration (Toff), spark gap voltage (SV) and wire electrode feed rate (WF). After initial experimentation, duty factor (Ton/Ton+Toff = 120/150) was decided to be 0.8 based on suitable material removal rate. Afterwards effect of spark gap voltage and wire electrode feed rate on machined surface morphology was investigated. It was found that at lower spark gap voltage re-solidification and accumulation of debris on machined surface is more which reduces with increasing spark gap voltage. Debris size increases with increasing spark gap voltage and higher wire electrode feed rate leads to sparse accumulation of debris on machined surface. Â© 2018 Elsevier Ltd. All rights reserved.
Energy harvesting by foot-propelled battery charger using shoe-model
(2012) Verma, N.K.; Singla, P.; Roy, A.
This paper proposes an effective and convenient mechanism to transform and utilize biomechanical energy to electrical energy by presenting a self-powered shoe-model in order to tap the energy obtained for charging mobile phone battery. While walking in general, negative work is done by every human being in every single step taken. This negative work can be converted into electrical energy using a dc machine. The resulting energy could serve as ancillary source of energy for charging the batteries. The proposed self-powered shoe-model contains a permanent magnet DC machine, rack and pinion section and a signal conditioning circuit for charging mobile phone battery. The designed shoe-model has been successfully tested on Li-ion battery of a mobile phone from a reputed brand. � (2012) Trans Tech Publications.
Energy harvesting by foot-propelled battery charger using shoe-model
(2012) Verma, N.K.; Singla, P.; Roy, A.
This paper proposes an effective and convenient mechanism to transform and utilize biomechanical energy to electrical energy by presenting a self-powered shoe-model in order to tap the energy obtained for charging mobile phone battery. While walking in general, negative work is done by every human being in every single step taken. This negative work can be converted into electrical energy using a dc machine. The resulting energy could serve as ancillary source of energy for charging the batteries. The proposed self-powered shoe-model contains a permanent magnet DC machine, rack and pinion section and a signal conditioning circuit for charging mobile phone battery. The designed shoe-model has been successfully tested on Li-ion battery of a mobile phone from a reputed brand. Â© (2012) Trans Tech Publications.
Entanglement in interacting quenched two-body coupled oscillator system
(American Physical Society, 2022) Choudhury, S.; Gharat, R.M.; Mandal, S.; Pandey, N.; Roy, A.; Sarker, P.
In this work, we explore the effects of a quantum quench on the entanglement measures of a two-body coupled oscillator system having quartic interaction. We use the invariant operator method, under a perturbative framework, for computing the ground state of this system. We give the analytical expressions for the total and reduced density matrix of the system having non-Gaussian, quartic interaction terms. Using this reduced density matrix, we show the analytical calculation of two entanglement measures viz., Von Neumann entanglement entropy using replica trick and Renyi entanglement entropy. Further, we give a numerical estimate of these entanglement measures with respect to the dimensionless parameter (t/δt) and show its behavior in the three regimes, i.e., late time behavior, around the quench point and the early time behavior. We comment on the variation of these entanglement measures for different orders of coupling strength. The variation of Renyi entropy of different orders has also been discussed. © 2022 authors. Published by the American Physical Society.
Experimental investigation on variation of output responses of as cast TiNiCu shape memory alloys using wire EDM
(ModTech Publishing House office@hotelfloramamaia.ro, 2017) Roy, A.; Narendra Nath, S.; Nedelcu, D.
The present research study is emphasized on investigation of machining characteristics of TiNiCu shape memory alloys using Wire EDM and analyzes the effect of input process parameters on the quality of the machined surfaces. Complications associated with the machining process results in degradation of surface quality which notably is not avoidable. But proper optimization of the process parameters may help to achieve the desired or near-perfect quality of these machined products. Experiments were conducted as per Taguchi’s L16 orthogonal array considering four input parameters at four levels of operation for Ti50Ni40Cu10, Ti45Ni45Cu10 and Ti40Ni50Cu10 shape memory alloys. Zinc coated brass wire is used as the wire electrode in this study. Material removal rate (MRR) and surface roughness (SR) of the machined samples are considered as the output responses of these alloys. Optimum MRR and SR achieved while machining these alloys are 6.9431 mm3/min and 1.060 µm respectively for Ti50Ni40Cu10. Keeping in mind the productivity of the machining process, formation of recast layer of these alloys are also studied for optimum material removal rate, which led us to the conclusion that Ti45Ni45Cu10 alloy exhibits a surprising aversion towards formation of recast layer as compared to its counterparts. Also, Ti45Ni45Cu10 displayed least average recast layer thickness (RLT) of 9.16 µm compared to 23.93 µm and 21.65 µm for Ti50Ni40Cu10 and Ti40Ni50Cu10 respectively. Pulse on time (120 µs) and wire feed (10 m/min) are found as the most influential Wire EDM process parameters against pulse off time and wire feed for an optimum material removal rate and for a better surface finish, pulse on time (100 µs) and pulse off time (30 µs) against servo voltage and wire feed respectively. © 2017, ModTech Publishing House. All rights reserved.
Impact of variation in wire electro discharge machining responses of homologous TiNiCu shape memory alloys for smart applications: An experimental investigation
(Institute of Physics Publishing helen.craven@iop.org, 2018) Roy, A.; Narendranath, S.
In this study, three distinct TiNiCu alloys were processed using wire electro discharge machining. These alloys are potential materials for smart applications owing to their fast actuation response resulting from suitable martensitic transformation temperatures. Due to differences in their physical property (thermal conductivity in this case), these alloys exhibit variation in machining response during wire electro discharge machining. Based on wire electro discharge machining responses of these alloys, order of thermal conductivity of these alloys are concluded in this study. This investigation aims at addressing the variation in terms of kerf width, recast layer thickness and machined surface microhardness to form the basis for production of intricate components. Ti50Ni40Cu10 alloy exhibited diverging machining response compared to its counterparts. Influential parameter for a given machining response changes depending on thermal property of the workpiece which makes it vital to investigate and choose the parameters in a more sensible manner while machining such materials. It was found that kerf width decreases with increasing servo voltage whereas recast layer thickness (mostly influenced by pulse off duration) increases with increasing pulse off duration. Microhardness of the machined surface (mostly influenced by pulse on duration) increases at higher discharge energy levels owing to presence of oxides formed during spark erosion process. Microhardness of Ti40Ni50Cu10 was found to be high (approximately 560 Hv) compared to its counterparts which was due to presence of Ni rich and ?-CuTi precipitates which also affected its phase transformation temperatures. © 2018 IOP Publishing Ltd.
Influence of dielectric flushing conditions during WEDM of TiNiCu shape memory alloys
(ICE Publishing subscriptions@icepublishing.com, 2019) Roy, A.; Yellappa, N.S.
In this study, the effect of dielectric flushing pressure and direction on the machining responses of wire electrodischarge machining (WEDM) was investigated. Vacuum-melted titanium-nickel-copper (TiNiCu) shape memory alloy Ti50Ni25Cu25, homogenized at 500°C, was used as the workpiece material. The flushing pressure was varied from 0.5 to 1.5 kg/cm2 along with pulse-on time (T on), pulse-off time (T off), servo voltage and wire feed rate for Taguchi's L27 experiments. Cutting rate (CR) and kerf width were selected as major WEDM responses, and at optimal CR, the effect of the flushing direction on surface characteristics was studied. It was found that the surface morphology depended mainly on process parameter values and was greatly affected by the flushing pressure. Also, the amount of molten and resolidified debris on samples, machined with the upward-direction flow, was much higher compared with that for the downward-direction flow. © 2019 ICE Publishing: All rights reserved.
Medical image segmentation using improved mountain clustering technique version-2
(2010) Verma, N.K.; Roy, A.; Vasikarla, S.
This paper proposes Improved Mountain Clustering version-2 (IMC-2) based medical image segmentation. The proposed technique is a more powerful approach for medical image based diagnosing diseases like brain tumor, tooth decay, lung cancer, tuberculosis etc. The IMC-2 based medical image segmentation approach has been applied on various categories of images including MRI images, dental X-rays, chest X-rays and compared with some widely used segmentation techniques such as K-means, FCM and EM as well as with IMC-1. The performance of all these segmentation approaches is compared on widely accepted validation measure, Global Silhouette Index. Also, the segments obtained from the above mentioned segmentation approaches have been visually evaluated. � 2010 IEEE.
Medical image segmentation using improved mountain clustering technique version-2
(2010) Verma, N.K.; Roy, A.; Vasikarla, S.
This paper proposes Improved Mountain Clustering version-2 (IMC-2) based medical image segmentation. The proposed technique is a more powerful approach for medical image based diagnosing diseases like brain tumor, tooth decay, lung cancer, tuberculosis etc. The IMC-2 based medical image segmentation approach has been applied on various categories of images including MRI images, dental X-rays, chest X-rays and compared with some widely used segmentation techniques such as K-means, FCM and EM as well as with IMC-1. The performance of all these segmentation approaches is compared on widely accepted validation measure, Global Silhouette Index. Also, the segments obtained from the above mentioned segmentation approaches have been visually evaluated. Â© 2010 IEEE.
An optimized fault diagnosis method for reciprocating air compressors based on SVM
(2011) Verma, N.K.; Roy, A.; Salour, A.
Fault diagnosis in reciprocating air compressors is essential for continuous monitoring of their performance and thereby ensuring quality output. Support Vector Machines (SVMs) are machine learning tools based on structural risk minimization principle and have the advantageous characteristic of good generalization. For this reason, four well-known and widely used SVM based methods, one-against-one (OAO), oneagainst-all (OAA), fuzzy decision function (FDF), and DDAG have been used here and an optimized SVM based technique is proposed for classification based fault diagnosis in reciprocating air compressors. The results obtained through implementation of all five techniques are thus compared as per their accuracy rate in percentages and the performance of the proposed method with 98.03 percent accuracy rate was found to be better than all other classification methods. With the compressor datasets being complex natured, proposed method is found to be of vital importance for classification based fault diagnosis pertaining to reciprocating air compressors. � 2011 IEEE.