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To meet the requirements of high-dimensional accuracy and surface finish of various advanced engineering materials for generating intricate part geometries, non-traditional machining (NTM) processes have now become quite popular in manufacturing industries. To explore the fullest machining capability of these NTM processes, it is often required to operate them while setting their different controllable parameters at optimal levels. This paper aims to present a novel approach for selection of the optimal parametric mixes for different NTM processes in order to assist the concerned process engineers.

In this paper, design of experiments (DoE) and technique for order preference by similarity to ideal solution (TOPSIS) are combined to develop the corresponding meta-models for identifying the optimal parametric combinations of two NTM processes, i.e. electrical discharge machining (EDM) and wire electrical discharge machining (WEDM) processes with respect to the computed TOPSIS scores.

For EDM operation on Inconel 718 alloy, lower settings of open circuit voltage and pulse-on time and higher settings of peak current, duty factor and flushing pressure will simultaneously optimize all the six responses. On the other hand, for the WEDM process, the best machining performance can be expected to occur at a parametric combination of zinc-coated wire, lower settings of pulse-on time, wire feed rate and sensitivity and intermediate setting of pulse-off time.

As the development of these meta-models is based on the analysis of the experimental data, they are expected to be more practical, being immune to the introduction of additional parameters in the analysis. It is also observed that the derived optimal parametric settings would provide better values of the considered responses as compared to those already determined by past researchers.

This DoE–TOPSIS method-based approach can be applied to varieties of NTM as well as conventional machining processes to determine the optimal parametric combinations for having their improved machining performance.

The purpose of this paper is to exploit the fullest potential and capability of different non-traditional machining (NTM) processes, it is often recommended to operate them at their optimal parametric combinations. There are several mathematical tools and techniques that have been effectively deployed for identifying the optimal parametric mixes for the NTM processes. Amongst them, grey relational analysis (GRA) has become quite popular due to its sound mathematical basis, ease to implement and apprehensiveness for multi-objective optimization of NTM processes.

In this paper, GRA is integrated with fuzzy logic to present an efficient technique for multi-objective optimization of three NTM processes (i.e. abrasive water-jet machining, electrochemical machining and ultrasonic machining) while identifying their best parametric settings for enhanced machining performance.

The derived results are validated with respect to technique for order preference by similarity to ideal solution (TOPSIS), and analysis of variance is also performed so as to identify the most significant control parameters in the considered NTM processes.

This grey-fuzzy logic approach provides better parametric combinations for all the three NTM processes with respect to the predicted grey-fuzzy relational grades (GFRG). The developed surface plots help the process engineers to investigate the effects of various NTM process parameters on the predicted GFRG values.

The adopted approach can be applied to various machining (both conventional and non-conventional) processes for their parametric optimization for achieving better response values.

The present study aims to determine the proximate and mineral composition of important coldwater food fishes in the North Eastern Indian upland region to assess their nutritional quality.

The paper is of original work and the analyses were performed using AOAC (1990). Data were analyzed by one-way analysis of variance (ANOVA) and determined by Duncan’s Multiple Range Test using SPSS (Version 19).

Crude protein levels ranged from 16-20 per cent, crude fat (CF) 9.60-1.54 per cent and ash 3.5-0.99 per cent. Moisture content was in the range of 71-78 per cent. The lowest moisture content was observed in Semiplotus semiplotus and highest in Labeo dero. Sodium, potassium and calcium content ranged from 92-309, 692-1435, 467-2021 mg/100g, respectively. Maximum concentration of potassium was found in Labeo dero followed by Labeo pangusia. Selenium was most abundant in L. dero, Labeo dyocheilus, Sanguina sanguine, Barilius bendelisis, Garra mullya, L. pangusia and Neolissochilus hexagonolepis. The maximum level of iron was evidenced in Tor tor.

The results obtained revealed that all the ten studied fishes are rich sources of nutrients including protein, macro and micro-minerals, which will be a healthy addition to human diet and will act as a ready reference for the nutritionists and other stakeholders.

The purpose of this paper is to incorporate prior knowledge in the artificial neural network (ANN) model for the prediction of continuous cooling transformation (CCT) diagram of steel, so that the model predictions become valid from materials engineering point of view.

Genetic algorithm (GA) is used in different ways for incorporating system knowledge during training the ANN. In case of training, the ANN in multi-objective optimization mode, with prediction error minimization as one objective and the system knowledge incorporation as the other, the generated Pareto solutions are different ANN models with better performance in at least one objective. To choose a single model for the prediction of steel transformation, different multi-criteria decision-making (MCDM) concepts are employed. To avoid the problem of choosing a single model from the non-dominated Pareto solutions, the training scheme also converted into a single objective optimization problem.

The prediction results of the models trained in multi and single objective optimization schemes are compared. It is seen that though conversion of the problem to a single objective optimization problem reduces the complexity, the models trained using multi-objective optimization are found to be better for predicting metallurgically justifiable result.

ANN is being used extensively in the complex materials systems like steel. Several works have been done to develop ANN models for the prediction of CCT diagram. But the present work proposes some methods to overcome the inherent problem of data-driven model, and make the prediction viable from the system knowledge.

Background: Every so often, one experiences different physically unstable situations which may lead to possibilities of suffering through vicious physiological risks and extents. Dynamic physiological activities are such a key metric that they are perceived by means of measuring galvanic skin response (GSR). GSR represents impedance of human skin that frequently changes based on different human respiratory and physical instability. Existing solutions, paved in literature and market, focus on the direct measurement of GSR by two sensor-attached leads, which are then parameterized against the standard printed circuit board mechanism. This process is sometimes cumbersome to use, resulting in lower user experience provisioning and adaptability in livelihood activities. The purpose of this study is to validate the novel development of the cost-effective GSR sensing system for affective usage for smart e-healthcare.

This paper proposes to design and develop a flexible circuit strip, populated with essential circuitry assemblies, to assess and monitor the level of GSR. Ordinarily, this flexible system would be worn on the back palm of the hand where two leads would contact two sensor strips worn on the first finger.

The system was developed on top of Pyralux. Initial goals of this work are to design and validate a flexible film-based GSR system to detect an individual’s level of human physiological activities by acquiring, amplifying and processing GSR data. The measured GSR value is visualized “24 × 7” on a Bluetooth-enabled smartphone via a pre-incorporated application. Conclusion: The proposed sensor-system is capable of raising the qualities such as adaptability, user experience, portability and ubiquity for possible application of monitoring of human psychodynamics in a more cost-effective way, i.e. less than US$50.

Several novel attributes are envisaged in the development process of the GSR system that made it different from and unique as compared to the existing alternatives. The attributes are as follows: (i) use of reproductive sensor-system fabrication process, (ii) use of flexible-substrate for hosting the system as proof of concept, (iii) use of miniaturized microcontroller, i.e. ATTiny85, (iv) deployment of energy-efficient passive electrical circuitry for noise filtering, (v) possible use case scenario of using CR2032 coin battery for provisioning powering up the system, (vi) provision of incorporation of internet of things (IoT)-cloud integration in existing version while fixing related APIs and (vii) incorporation of heterogeneous software-based solutions to validate and monitor the GSR output such as MakerPlot, Arduino IDE, Fritzing and MIT App Inventor 2.

This paper is a revised version R1 of the earlier reviewed paper. The proposed paper provides novel knowledge about the flexible sensor system development for GSR monitoring under IoT-based environment for smart e-healthcare.

World over, change of base year in the gross domestic product (GDP) is a standard practice of GDP estimation. However, unless a consistent series of GDP is released with respect to the new base for the earlier period, the existence of multiple growth rates creates problems for applied researchers, policymakers and the general public alike. Faced with such a menu of GDP series researchers often try to interpolate a consistent series of GDP. The main purpose of this paper is to analyses the nature of the data generating process of such multiple interpolated series of quarterly growth rates and tries to discern the consistency of such processes.

The present paper tries to look into the statistical implications and complications of such interpolated quarterly GDP/growth series in India in terms of three series of GDP, namely, with 1999–2000, 2004–2005 and 2011–2012 as its bases.

The analysis reveals that as a result of a change of base year, the nature of the data generating process of the old and new GDP series could undergo changes and experience different breakpoints. While all these conclusions seem to be valid for GDP growth at quarterly intervals, taking the data at annual frequency is less problematic.

The observation suggests that in most applied work, researchers may not have the luxury of only working with annual data and certain consistency checks will be necessary to check the veracity of the results based on quarterly data with those based on annual data. Second, moving forward it may be useful for the Authorities to make a transition to a chain-based linking method rather than fixed time-period-based bases as is currently done.

The analysis of Indian GDP in this paper is, perhaps, indicative of the fact that usage of quarterly GDP data is to be handled with caution and it is preferable that any serious empirical analysis uses annual GDP data whenever it is available/feasible. The comparison of GDP growth rates at different frequencies and examining the true nature of the process are quite unique in their contribution towards empirical macroeconomic research.

The purpose of this paper is to conduct a theoretical study on steady fully developed non-linear natural convection and mass transfer flow past an infinite vertical moving porous plate with chemical reaction and thermal diffusion effect. Closed-form expressions for dimensionless velocity, concentration, Sherwood number and skin-friction are obtained by solving the present mathematical model.

The fully developed steady non-linear natural convection and mass transfer flow near a vertical moving porous plate with chemical reaction and thermal diffusion effect is investigated. The non-linear density variation and Soret effect were taken into consideration. The dimensionless velocity, temperature and concentration profiles were obtained in terms of exponential functions, and were used to compute the governing parameters, skin-friction and Sherwood number.

The effect of coefficient of the non-linear density variation with the temperature (NDT) and concentration (NDC) parameter, chemical reaction parameter, thermal diffusion parameter are discussed with the aid of line graphs and tables. The analysis of the result shows that the velocity as well as skin-friction having higher values in the case of non-linear variation of density with temperature and concentration in comparison to linear variation of density with temperature and concentration. It is observed that the velocity and skin-friction increase with an increase in the Soret parameter.

The aim of this paper is to extend the work of Muthucumaraswamy (2002) by incorporating the thermal diffusion (Soret) effect and non-linear density variation with temperature (NDT) and concentration (NDC), on which, to the best knowledge of the authors, no studies have been carried out.

Prisoners are at a higher risk of HIV infection compared to the general population. The purpose of this study is to estimate the prevalence of HIV and related risk behaviours among inmates of the Central Prisons in four states of North India.

The HIV sentinel surveillance was conducted in seven Central Prisons in four states of North India from February to April 2019. Four hundred inmates were included from each prison. The interviews were conducted at the Integrated Counselling and Testing Centre located within the prison premises. The Ethics Committee of the National AIDS Control Organization, New Delhi, granted ethical approval before the start of the surveillance.

Overall, 2,721 inmates were enrolled in this study. The mean (SD) age was 38.9 (13.9) years. One-third of prison inmates had comprehensive knowledge about HIV/AIDS. The proportion of convict (54%) and undertrial (46%) inmates was almost equal. The overall prevalence of HIV infection among inmates was 0.96% (95% CI 0.65–1.40). The odds of being HIV positive were significantly higher in never married inmates, undertrials, inmates who were in the prison for more than three months to one year, inmates incarcerated for multiple times, inmates with history of injecting drug use and inmates with history of intercourse with a commercial sex worker.

The findings from the very first HIV sentinel surveillance in central prisons in North India have been presented in this paper. This has huge implications for future policy decisions.

The purpose of this study is to present the significance of Joule heating, viscous dissipation, magnetic field and slip condition on the boundary layer flow of an electrically conducting Boussinesq couple-stress fluid induced by an exponentially stretching sheet embedded in a porous medium under the effect of the magnetic field of the variable kind. The heat transfer phenomenon is accounted for under thermal radiation, Joule and viscous dissipation effects.

The governing nonlinear partial differential equations are transformed to the nonlinear ordinary differential equations (ODEs) by using some appropriate dimensionless variables and then the consequential nonlinear ODEs are solved numerically by making the use of the well-known shooting iteration technique along with the standard fourth-order Runge–Kutta integration scheme. The impact of emerging flow parameters on velocity and temperature profiles, streamlines, local skin friction coefficient and Nusselt number are described comprehensively through graphs and tables.

Results reveal that the velocity profile is observed to diminish considerably within the boundary layer in the presence of a magnetic field and slip condition. The enhanced radiation parameter is to decline the temperature field. The slip effect is favorable for fluid flow.

Till now, slip effect on Boussinesq couple-stress fluid over an exponentially stretching sheet embedded in a porous medium has not been explored. The present results are validated with the previously published study and found to be highly satisfactory.