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The purpose of this paper is to provide simulation modelling for bulk arrival bulk service queueing system involved in a textile industry and analyze the performance metrics.

This paper describes the simulation modelling of a bulk queueing system with limited number of admissions and multiple vacations. The model is developed for the proposed queueing system using Flexsim 2017, and it is explained through an application observed in a textile industry involving the process of cone winding.

In this paper, the simulation model has been developed to study the behaviour of queues at different resources in a production system. Various performance measures such as average components, average waiting time, total number of inputs and outputs, processing time and idle time involved in a textile industry are evaluated using simulation and justified through numerical illustration.

The proposed simulation model may be used in various scenarios wherever a real time situation exists related to bulk queueing system. The results produced in this paper can be used by the manufacturing industries to enhance the need-based accuracy. It is worth pointing out that the findings are of direct practical relevance and can be successfully used for a number of industrial applications.

The approach suggested in this paper attempts to deal with the queueing system involved in a textile industry and provides numerical results in less time with less computer resources. It provides a reasonably good approximation for simple and complex queueing models where it is difficult to find closed form of theoretical results.

The purpose of this paper is to find the droplets impact on the airplane wing structure. Two kinds of characteristics of the droplet at different velocity and viscosity are assumed. The droplet is assumed to be spherical cubic form and it is injected from the convergent divergent nozzle with a passive control.

This paper presents the results of a numerical simulation of droplet impact on the horizontal surface. The effects of impact parameters are studied. The splash effect of the droplet also visualized. The results are presented in form of stress, strain, displacement magnitude of the droplet.

Crosswire is used as passive control. The behavior of the droplet impact is observed based on the kinetic energy and the gravitational forces.

The results predict that smooth particle hydrodynamic designed droplet not only depend on the equation of state of the droplet but also the injection velocity from the nozzle. It also determined that droplet velocity is depending on the viscosity of the fluid.

The paper seeks to determine whether different aspects of migrant pre‐migration characteristics (human capital and motivation to migrate) and post‐migration behaviour (social integration and career self‐management) predict migrants' post‐migration career success.

The research employed a survey questionnaire applied to a sample of 210 migrants who had migrated from Sri Lanka to New Zealand. Twenty‐three independent and three dependent (career success – objective and subjective) variables were measured. Sequential multiple regression analysis was applied, mirroring the time‐sequenced theory of career development.

Overall, migrants' occupational status had declined markedly following migration. Variables representing human capital, social integration and career self‐management perspectives all contributed substantially to explaining variances in career success, especially objective career success, but motivation to migrate did not. Human capital variables were especially influential in determining pre‐migration success, acculturation in the host country and education in the host country in post‐migration success. Effects of career self‐management behaviours on success were relatively small.

A limitation is the cross‐sectional design, and possible non‐generalisability beyond a single migrant group and host country.

The paper discusses implications for migrants, policy makers and future research.

Migration, and interest in research on migrants' careers, is growing. This paper applies a wide range of predictor variables and a logical causal model to predicting migrant career success, indicates significant effects, and points to positive actions that may be taken by government, organisations and migrants.

The purpose of this paper is to find the pressure and the knocking phenomena. To get the pressure values, the butterworth bandpass filter was used and the potential of knocking was found by using peak-to-peak pressure values and also the species concentration. Cooled exhaust gas recirculation was the method used to minimize the knocking occurrence in the engine. Moreover, the effect of premixed methanol and start of engine (SOI) on knocking were also determined.

This paper deals with the compression ignition engine to investigate the unfavorable knocking behavior. The tests were carried out with the 3D model of engine fueled with waste cooking oil blended with TiO2. A number of tests were taken to find the pressure variation and the species concentration at eight different locations in the computational model.

In doing the tests, the positive intended outcome was achieved. From results, it is clear that the SOI and premixed methanol mitigated the knocking process.

The species concentration and pressure in the form of filtered signal were proved to be the ideal methods for evaluating the knocking event in the engine.

Purpose: In addition to the liberalisation policy, big data has revolutionised the level of awareness among customers about the quality and prices of insurance products. The rationale behind this study is to underline the issues in managing product portfolios in a disruptive environment, where a sudden and unexpected situation like COVID-19 pandemic is going to challenge the traditional models and insurance covers of organisations as well as individuals.

Methodology: The study is based on secondary data. The scope of the study will only be confined to the top two general insurance companies in India based on year of registration and market share to compare their product portfolios during pre- and post-liberalisation periods ranging from 1985–1986 to 2000–2001 and 2001–2002 to 2018–2019, respectively.

Findings: There is a lack of a balanced product portfolio for fulfilling the varying needs of customers. The insurance companies needed to set up different portfolios and should provide separate covers for natural catastrophes such as floods, earthquakes, landslides, tsunami, and the occurrence of new pandemics like COVID-19.

Significance: The study highlights that the outbreak of COVID-19 and similar pandemics or global emergencies need special preparation from the insurance sector.

The online users’ characteristic information can provide decision support for policy-designing and construction of public strategies. Hence, this paper aims to conduct online public opinion mining on the recovery policy stimulating the economies stroked by COVID-19 epidemic. Also, sentimental analysis is performed to uncover the posters’ emotion towards the target policy.

This paper adopts bidirectional encoder representations from transformers (BERT) as classifier in classification tasks, including misinformation detection, subject analysis and sentimental analysis. Meanwhile, latent Dirichlet allocation method and sentiment formulations are implemented in topic modelling and sentiment analysis.

The experimental results indicate that public opinion is mainly non-negative to the target policy. The positive emotions mainly focus on the benefits that the recovery policy might bring to stimulate economy. On the other hand, some negative opinions concerned about the shortcomings and inconvenience of the target policy.

The authors figured out the key factors focused by the public opinion on the target recovery policy. Also, the authors indicated pros and cons of the recovery policy by analysing the emotion and the corresponding topics of the public opinion on social media. The findings of the paper can be generalized in other countries theoretically to help them design recovery policy against COVID-19.

The paper aims to investigate the impact of economic policy uncertainty (EPU) (i.e. uncertainty due to government policies) on fine wine prices.

The paper uses the Baker et al. (2016) monthly news-based measure of EPU for the leading wine markets: the USA, the UK, France, Germany and China in conjunction with monthly fine wine pricing data from the London International Vintners Exchange (Liv-ex). The wine sub-indices used are the Liv-ex 500 (Bordeaux), Burgundy 150, Champagne 50, Rhone 100, Italy 100, California 50, Port 50 and Rest of the World 50. The Prais–Winsten and Cochrane–Orcutt regressions are used for our analyses to correct for effects of serial correlation. Time lags are chosen based on the appropriate information criterion.

Changes in EPU levels negatively impact changes in the Liv-ex 500 index for all our leading wine markets except France, the Champagne 50 index for the UK and the Burgundy 150 and the Rhone 100 indices for Germany, with the effects being significant for at least up to a quarter before EPU is detected. The authors did not find significant results for the EPU of France.

The paper aims to provide insights into whether EPU creates opportunities or threats for investors and wineries.

A forward-looking news-based EPU measure is used to gain insights into how the different Liv-ex sub-indices react to increases in uncertainty centered around government policies across a sample of different countries.

The depletion of fossil fuel and emissions of harmful gases forced the pioneers in search of alternate energy source. The purpose of this study is to present an effective use of hydrogen fuel for turbojet engines based on its exergetic performance.

This study was performed to measure the assessment of exergetic data of turbojet engines. Initially, the test was carried out on the Jet A-1 fuel. Then, a series of similar tests were carried out on turbojet engines with hydrogen fuel to measure their performance results. Finally, the exergetic values of both were compared with each other.

The introduction of hydrogen fuel reduced the exergy efficiency, and a 10 per cent reduction was observed in exergy efficiency. Simultaneously, the waste exergy rate increased by 9 per cent. However, because of the high specific fuel exergy, hydrogen fuel was better than Jet A-1 fuel. Note that parameters such as environmental effect factor and ecological effect witnessed an increase in their index owing to the addition of hydrogen.

Introduction of alternative blends is necessary for achieving lower emission of gases such as CO, NOx and CO₂ from gas turbine engines without compromising on performance. The Jet A fuels were replaced by blends to obtain better emission characteristics.

The use of hydrogen in turbojet engines showed an adverse effect on exergetic performance. However, it was very impressive to see a 200 per cent reduction in emissions. From the comparison of exergy efficiency results of inlet, combustion and nozzle, it is evident that the combustion chamber has the largest values of exergy ratio, waste exergy ratio, cost flow, ecological factor, environmental factor and fuel ratio owing to irreversibility in the combustion process.

This study aims to explore dietary diversity (DD) and nutritional status of adolescents among rural farm households in Southwestern Nigeria. It analyses whether higher commercialization levels of farm households translate to better nutrition.

This study was conducted in Ogun and Oyo States of Southwestern Nigeria, using primary data from 352 farm households with a total of 160 adolescent members. The individual version of dietary diversity score (DDS) of nine food groups was used to calculate adolescent DDS over a 24-h recall period. World Health Organization AnthroPlus software was used in analyzing adolescents’ anthropometric data (height-for-age z-score and body mass index-for-age z-score) while household crop commercialization index (CCI) was estimated for each farm household. Separate logit models were used to examine the drivers of adolescents’ DD and malnutrition.

The study findings indicated that 100% of the adolescents consumed starchy staples while 0%, 3.1% and 12.5% consumed organ meat, milk/milk products and eggs, respectively. Results revealed that 74.1% and 21.2% of boys were stunted and thin while the prevalence in adolescent girls was 50.7% and 9.3%, respectively. Prevalence of stunting was found to be very high (60%–83%) in all the four CCI levels’ households indicating that belonging to highly commercialized households (CCI 3–4) may not necessarily translate to better nutrition of adolescent members. Food expenditure (p < 0.01) and access to piped water (p < 0.01) negatively influenced adolescents’ stunting mainly because of lower expenditure on food items and lower percent of household having access to piped water, respectively, while education (p < 0.01) had positive effects on adolescents’ DD.

Previous studies have contributed to the body of knowledge concerning the link between agricultural commercialization and nutrition using under-five children of the households. However, to the best of the authors’ knowledge, this is the first study that investigated the influence of CCI on DDS and nutritional status of adolescent members of farm households in Nigeria. This study fills this existing knowledge gap in investigating adolescents’ DD and malnutrition among smallholder farm households.

Artificial intelligence (AI)-based human capital management (HCM) software solutions represent a potentially effective way to leverage and streamline a bank’s human resources. However, despite the attractiveness of AI-based HCM solutions to improve banks’ effectiveness, to the best of the authors’ knowledge, there are no current studies that identify critical success factors (CSFs) for adopting AI-based HCM in the banking sector. This study aims to fill this gap by investigating CSFs for adopting AI-based HCM software solutions in the banking sector.

Full consistency method methodology and technology–organization–environment, economic and human framework are used for categorizing and ranking CSFs.

The study identifies the technological and environmental dimensions as the most and least important dimensions for AI-based HCM adoption in banks. Among specific CSFs, compatible technology facilities, sufficient privacy and security and relative advantages of technology over competing technologies were identified as the most important. Implementation of AI-based HCM solutions requires significant outlays of resources, both human and financial, for banks.

The study provides bank administrators a set of objective parameters and criterion to evaluate the feasibility of adopting a particular AI-based HCM solution in banks.