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The final properties of ductile iron are decided by the inoculant processing while pouring the melt. The shape and size of nodules generated during solidification are of paramount importance in solidification of ductile cast iron. The purpose of this study is to examine the effect of different inoculant addition on the solidification of ductile cast iron melt through thermal analysis.

Thermal analysis has recently grown as a tool for modeling the solidification behavior of ductile cast irons. Iron properties will be predicted by analyzing the cooling curve patterns of the melts and predicting the related effectiveness of inoculant processing. In this study, thermal analysis is used to evaluate the need for inoculation.

The amount and type of inoculation will affect the amount of undercooling during the solidification of ductile cast iron. It is found that the addition of 0.1 to 0.4 Wt.% inoculant lowers the austenite dendrite formation starting temperature while increasing the eutectic freezing temperature. Microstructure analysis revealed that the addition of inoculation increases the nodule count from 103 to 242 nodules. The beneficial effects of inoculation are sustained by an improved graphitization factor, which shows the formation of graphite nodules in the second phase of the eutectic reaction.

The inoculation treatment has improved metallurgical occurrences such as carbide to graphite conversion, graphite microstructure control, graphite nodule count at the start of solidification and the last stage of solidification, which determines the soundness of casting. The foundry industry can follow these steps for monitoring the solidification of ductile iron castings.

This paper aims to evaluate the effects of inulin (3 per cent), chitosan (1 per cent) and carrageenan (0.5 per cent) addition on the physico-chemical, sensory and textural attributes of restructured goat meat products. Health conscious consumers are much more interested in product with added health benefit. Keeping this in mind, this study was undertaken to find out effective ingredient for low fat restructured goat meat product.

Formulation for restructured goat meat blocks was optimized and four different formulation containing different ingredients, namely, control, inulin (3 per cent), chitosan (1 per cent) and carrageenan (0.5 per cent), were used to find out best ingredient for healthier goat meat product and various physicochemical and sensory properties of the product were evaluated.

Results showed that addition of carrageenan improved (p < 0.01) the product yield (86.0 per cent) significantly. The proximate composition, expressible water and water activity were similar. The moisture retention percentage was significantly (p < 0.01) reduced (86.0 per cent) due to addition of inulin. Carrageenan significantly (p < 0.05) increased the lightness (42.4) and yellowness (10) values. Significantly (p < 0.05) lower shear force values were observed in inulin (0.5) and chitosan (0.4) containing samples than control (0.7 kg/1.5 cm²). Hardness values were significantly (p < 0.05) lower in restructured product containing chitosan (56.1 N/cm²) and carrageenan (59.4 N/cm²). Similarly, springiness values were significantly (p < 0.05) lower (0.7 vs 0.8 cm) in carrageenan containing product. Inulin, chitosan and carrageenan did not significantly influence the sensory attributes of restructured goat meat product. It is concluded that inulin, chitosan and carrageenan could be used to improve technological and functional attributes of the healthier restructured goat meat product.

Future research may benefit from efforts to modify shelf life of the product by modifying packaging condition.

The healthier meat-based restructured goat meat product has been developed, and the effect on its quality characteristics have been extensively examined, limited research has focused on this aspect.

The purpose of this paper is to describe a participatory qualitative research project using the Delphi consensus technique aided by Internet technology for successful transition of academic endeavors during and the post COVID era. The study aimed to derive a holistic competency matrix for an optometry program for transformation of the program to competency-based education.

This study combined a scoping review of literature for developing a baseline competency framework, along with derivation of an E-Delphi consensus within a panel of diverse stakeholders to achieve the objective of plotting a detailed competency matrix.

The involvement of all stakeholders of educational system in Delphi study resulted in a valid and all-inclusive competency framework with 18 competency units and 97 competency elements. This framework provided a strong base for redesigning pedagogy and assessment methods during COVID-19 crisis.

The paper highlights the feasibility and utility of adopting a participatory approach during COVID-19 outbreak. The Delphi technique aided by Internet technology was employed to develop a competency-based curriculum.

The paper narrates a suitable, feasible and scientific method for rapid transition in academia, following the restrictions and social distancing norms imposed during the COVID-19 outbreak.

Although there is good evidence for use of the Delphi technique in curriculum development, this paper adds value by focusing on a participatory approach in using it. The suggested method here shows ways to gain optimum scientific output with minimum resources in constrained situations such as COVID-19 crisis.

In today’s digital world, real-time health monitoring is becoming a most important challenge in the field of medical research. Body signals such as electrocardiogram (ECG), electromyogram and electroencephalogram (EEG) are produced in human body. This continuous monitoring generates huge count of data and thus an efficient method is required to shrink the size of the obtained large data. Compressed sensing (CS) is one of the techniques used to compress the data size. This technique is most used in certain applications, where the size of data is huge or the data acquisition process is too expensive to gather data from vast count of samples at Nyquist rate. This paper aims to propose Lion Mutated Crow search Algorithm (LM-CSA), to improve the performance of the LMCSA model.

A new CS algorithm is exploited in this paper, where the compression process undergoes three stages: designing of stable measurement matrix, signal compression and signal reconstruction. Here, the compression process falls under certain working principle, and is as follows: signal transformation, computation of Θ and normalization. As the main contribution, the theta value evaluation is proceeded by a new “Enhanced bi-orthogonal wavelet filter.” The enhancement is given under the scaling coefficients, where they are optimally tuned for processing the compression. However, the way of tuning seems to be the great crisis, and hence this work seeks the strategy of meta-heuristic algorithms. Moreover, a new hybrid algorithm is introduced that solves the above mentioned optimization inconsistency. The proposed algorithm is named as “Lion Mutated Crow search Algorithm (LM-CSA),” which is the hybridization of crow search algorithm (CSA) and lion algorithm (LA) to enhance the performance of the LM-CSA model.

Finally, the proposed LM-CSA model is compared over the traditional models in terms of certain error measures such as mean error percentage (MEP), symmetric mean absolute percentage error (SMAPE), mean absolute scaled error, mean absolute error (MAE), root mean square error, L1-norm and L2-normand infinity-norm. For ECG analysis, under bior 3.1, LM-CSA is 56.6, 62.5 and 81.5% better than bi-orthogonal wavelet in terms of MEP, SMAPE and MAE, respectively. Under bior 3.7 for ECG analysis, LM-CSA is 0.15% better than genetic algorithm (GA), 0.10% superior to particle search optimization (PSO), 0.22% superior to firefly (FF), 0.22% superior to CSA and 0.14% superior to LA, respectively, in terms of L1-norm. Further, for EEG analysis, LM-CSA is 86.9 and 91.2% better than the traditional bi-orthogonal wavelet under bior 3.1. Under bior 3.3, LM-CSA is 91.7 and 73.12% better than the bi-orthogonal wavelet in terms of MAE and MEP, respectively. Under bior 3.5 for EEG, L1-norm of LM-CSA is 0.64% superior to GA, 0.43% superior to PSO, 0.62% superior to FF, 0.84% superior to CSA and 0.60% better than LA, respectively.

This paper presents a novel CS framework using LM-CSA algorithm for EEG and ECG signal compression. To the best of the authors’ knowledge, this is the first work to use LM-CSA with enhanced bi-orthogonal wavelet filter for enhancing the CS capability as well reducing the errors.

The purpose of this study is to present a novel approach for the evaluation of tribological properties of brake friction materials (BFM).

In this study, a BFM was newly formulated with 16 different ingredients and produced using an industrial hot compression molding process. Experimentation was carried out on the brake tester, which was developed for this purpose according to SAE J661 standards. The braking applications, sliding speed and braking pressure were considered as performance parameters, whereas coefficient of friction (CoF) and wear rate as output parameters. The influence of the performance parameters on the output was studied using response surface plots. Analysis of variance and regression analysis was accomplished for post-experimental evaluation of results. Multi-criteria decision-making (MCDM) and multi-objective genetic algorithm (MOGA) were applied for estimating the most critical performance parameter combination to evaluate the BFM.

The present experimental model was significant and effectively used to predict the performance. MCDM generates the optimal values for the parameters braking applications, braking pressure (Bar) and sliding speed (rpm) as 1000, 30 and 915, whereas MOGA as 1008, 10.503 and 462.8202, respectively.

An efficient model for performance evaluation of the BFM considering maximum CoF and minimum wear rate was experimentally presented and statistically verified. Also, the two multi-objective optimization methodologies were implemented and compared. A comparison between the results of MCDM and MOGA reveals that MOGA yields 30% better results than MCDM.

The purpose of this paper is to evaluate experimentally the influence of different surface roughness of the contacting disc on tribological performance of the non-asbestos brake friction material (BFM).

Taguchi method was applied to design an experiment using three different discs of gray cast iron with different surface roughness, which is measured using optical profilometer. These discs were subjected to sliding against pins prepared with the developed non-asbestos BFM, using pin on disc friction and wear monitor.

The experimental results shows that the disc 2 (Ra = 3.77 µm) gives wear of 22.78 µm and coefficient of friction of 0.462, which is recommended for extreme brake performance. Analysis of Taguchi design revealed that the disc surface was most significant parameter among the parameters under study.

During braking, continuous sliding between the BFM and brake disc or drum not only results into wear of BFM but also changes the surface finish of the brake drum or disc. This leads to variation in surface topography of the drum or disc surface with application of brakes, which further affects the characteristics of the BFM.

The tribological performance of BFM depends upon the topography of the surface on which it was sliding. To get best performance of the non-asbestos friction materials, disc having moderate surface finish is recommended. Scanning electron microscope micrographs had shown the different plateaus formed and energy-dispersive X-ray spectroscopy spectra identified presence of different chemical elements prior to sliding of the pins surface over different discs surface topography.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2020-0120/

The purpose of this article is to evaluate revenue efficiency performance of life insurance companies in India. The study also compares if private or public insurance sector is more “revenue efficient”. Furthermore, the study determines the nature of return to scale (RTS) and identifies the leaders and laggards amongst insurance companies operating in India.

Revenue efficiency is calculated by employing data envelopment analysis – a non-parametric approach, on a data set of 24 insurance companies over the period 2013–2014 to 2017–2018.

The empirical results suggest that life insurance companies in India could generate only 34.4% of revenue, which is very less than what these are expected to generate from the same inputs. Majority of life insurance companies operating in India are operating at decreasing return to scale (DRS). There is a reduction in leaders and the highest proportion of companies is falling in the category of laggards.

As per the best knowledge of researchers, no empirical work has been carried out with respect to measuring the revenue efficiency of Indian insurance companies. The current study appropriately fills the gap by not only calculating the revenue efficiency scores of insurance companies in India but also provides insights into the causes of revenue inefficiencies. It also gives implications for efficient and effective management of insurance companies.

Holy cities in India are seeing tremendous gentrification. This study aims to investigate the effect of the changing lifestyle of people towards spirituality and the changing lifestyle's impact on consumer buying behavior on properties in Indian holy cities which has not been studied anecdotally.

The research is exploratory in nature. A questionnaire has been sent to collect primary data through SurveyMonkey. Simple random sampling was used to collect a sample of 450 respondents which was also verified using G* software. The data were analyzed using descriptive statistics and partial least square–structured equation modeling (PLS-SEM).

Findings obtained through the structural model using bootstrapping technique suggest that intrinsic and extrinsic factors are attracting tourists leading to an increase in the demand for real estate in holy cities.

The research findings may vary as per the cultural differences and belief in spirituality, which is subject to perceptual biases in different holy cities.

The traditional determinants of property buying behavior are considered inadequate to attract real estate investments. The inclusion of these behavioral aspects – intrinsic and extrinsic factors may improve the investment inflows in India.

Spirituality connects to the concept of behavioral real estate, where the decision to buy property is largely affected by the emotional attachment of people.

This research adds value to fill the gap by finding out the latent determinant – emotional reasons impacting transnational gentrification in India.

This research article aims to prioritize the risks associated with the implementation of the project-based learning (PBL) concept in engineering institutions and develop possible strategies for risk management.

In this research article, various risks associated with the implementation of the PBL concept in engineering institutions are discovered by taking inputs from academicians and performing a literature survey of peer-reviewed journal articles. Then, identified risks are prioritized by using the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) method. Finally, the risk mitigation strategies are developed.

From the literature survey, 11 risks associated with the implementation of the PBL concept are identified. The TOPSIS method resulted in group dynamics risk and faculty training risk as the top two risks in the implementation of the PBL concept, whereas anxiety risk and poor prior learning experience risk are relatively low-ranked risks.

The outcome of the research is based on the responses received through questionnaires. There are other methods also available for risk analysis, which are beyond this study.

The outcome of this research work will help the implementer of the PBL concept to effectively deal with the risks involved in implementing the PBL concept in engineering institutions by adopting strategies.

This research paper gives an idea about risks associated with the PBL implementation in engineering institutions. Also, this paper uses TOPSIS method for ranking of identified risks.