Manjunatha Gudekote, Rajashekhar Choudhari, Hanumesh Vaidya, Prasad K.V. and Viharika J.U.
The purpose of this paper is to emphasize the peristaltic mechanism of power-law fluid in an elastic porous tube under the influence of slip and convective conditions. The effects…
Abstract
Purpose
The purpose of this paper is to emphasize the peristaltic mechanism of power-law fluid in an elastic porous tube under the influence of slip and convective conditions. The effects of different waveforms on the peristaltic mechanism are taken into account.
Design/methodology/approach
The governing equations are rendered dimensionless using the suitable similarity transformations. The analytical solutions are obtained by using the long wavelength and small Reynold’s number approximations. The expressions for velocity, flow rate, temperature and streamlines are obtained and analyzed graphically. Furthermore, an application to flow through an artery is determined by using a tensile expression given by Rubinow and Keller.
Findings
The principal findings from the present model are as follows. The axial velocity increases with an expansion in the estimation of velocity slip parameter and fluid behavior index, and it diminishes for a larger value of the porous parameter. The magnitude of temperature diminishes with an expansion in the Biot number. The flux is maximum for trapezoidal wave and minimum for the triangular wave when compared with other considered waveforms. The flow rate in an elastic tube increases with an expansion in the porous parameter, and it diminishes with an increment in the slip parameter. The volume of tapered bolus enhances with increasing values of the porous parameter.
Originality/value
The current study finds the application in designing the heart-lung machine and dialysis machine. The investigation further gives a superior comprehension of the peristaltic system associated with the gastrointestinal tract and the stream of blood in small or microvessels.
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Thameem Basha Hayath, Sivaraj Ramachandran, Ramachandra Prasad Vallampati and O. Anwar Bég
Generally, in computational thermofluid dynamics, the thermophysical properties of fluids (e.g. viscosity and thermal conductivity) are considered as constant. However, in many…
Abstract
Purpose
Generally, in computational thermofluid dynamics, the thermophysical properties of fluids (e.g. viscosity and thermal conductivity) are considered as constant. However, in many applications, the variability of these properties plays a significant role in modifying transport characteristics while the temperature difference in the boundary layer is notable. These include drag reduction in heavy oil transport systems, petroleum purification and coating manufacturing. The purpose of this study is to develop, a comprehensive mathematical model, motivated by the last of these applications, to explore the impact of variable viscosity and variable thermal conductivity characteristics in magnetohydrodynamic non-Newtonian nanofluid enrobing boundary layer flow over a horizontal circular cylinder in the presence of cross-diffusion (Soret and Dufour effects) and appreciable thermal radiative heat transfer under a static radial magnetic field.
Design/methodology/approach
The Williamson pseudoplastic model is deployed for rheology of the nanofluid. Buongiorno’s two-component model is used for nanoscale effects. The dimensionless nonlinear partial differential equations have been solved by using an implicit finite difference Keller box scheme. Extensive validation with earlier studies in the absence of nanoscale and variable property effects is included.
Findings
The influence of notable parameters such as Weissenberg number, variable viscosity, variable thermal conductivity, Soret and Dufour numbers on heat, mass and momentum characteristics are scrutinized and visualized via graphs and tables.
Research limitations/implications
Buongiorno (two-phase) nanofluid model is used to express the momentum, energy and concentration equations with the following assumptions. The laminar, steady, incompressible, free convective flow of Williamson nanofluid is considered. The body force is implemented in the momentum equation. The induced magnetic field strength is smaller than the external magnetic field and hence it is neglected. The Soret and Dufour effects are taken into consideration.
Practical implications
The variable viscosity and thermal conductivity are considered to investigate the fluid characteristic of Williamson nanofluid because of viscosity and thermal conductivity have a prime role in many industries such as petroleum refinement, food and beverages, petrochemical, coating manufacturing, power and environment.
Social implications
This fluid model displays exact rheological characteristics of bio-fluids and industrial fluids, for instance, blood, polymer melts/solutions, nail polish, paint, ketchup and whipped cream.
Originality/value
The outcomes disclose that the Williamson nanofluid velocity declines by enhancing the Lorentz hydromagnetic force in the radial direction. Thermal and nanoparticle concentration boundary layer thickness is enhanced with greater streamwise coordinate values. An increase in Dufour number or a decrease in Soret number slightly enhances the nanofluid temperature and thickens the thermal boundary layer. Flow deceleration is induced with greater viscosity parameter. Nanofluid temperature is elevated with greater Weissenberg number and thermophoresis nanoscale parameter.
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Vijaya Prasad Burle, Tattukolla Kiran, N. Anand, Diana Andrushia and Khalifa Al-Jabri
The construction industries at present are focusing on designing sustainable concrete with less carbon footprint. Considering this aspect, a Fibre-Reinforced Geopolymer Concrete…
Abstract
Purpose
The construction industries at present are focusing on designing sustainable concrete with less carbon footprint. Considering this aspect, a Fibre-Reinforced Geopolymer Concrete (FGC) was developed with 8 and 10 molarities (M). At elevated temperatures, concrete experiences deterioration of its mechanical properties which is in some cases associated with spalling, leading to the building collapse.
Design/methodology/approach
In this study, six geopolymer-based mix proportions are prepared with crimped steel fibre (SF), polypropylene fibre (PF), basalt fibre (BF), a hybrid mixture consisting of (SF + PF), a hybrid mixture with (SF + BF), and a reference specimen (without fibres). After temperature exposure, ultrasonic pulse velocity, physical characteristics of damaged concrete, loss of compressive strength (CS), split tensile strength (TS), and flexural strength (FS) of concrete are assessed. A polynomial relationship is developed between residual strength properties of concrete, and it showed a good agreement.
Findings
The test results concluded that concrete with BF showed a lower loss in CS after 925 °C (i.e. 60 min of heating) temperature exposure. In the case of TS, and FS, the concrete with SF had lesser loss in strength. After 986 °C and 1029 °C exposure, concrete with the hybrid combination (SF + BF) showed lower strength deterioration in CS, TS, and FS as compared to concrete with PF and SF + PF. The rate of reduction in strength is similar to that of GC-BF in CS, GC-SF in TS and FS.
Originality/value
Performance evaluation under fire exposure is necessary for FGC. In this study, we provided the mechanical behaviour and physical properties of SF, PF, and BF-based geopolymer concrete exposed to high temperatures, which were evaluated according to ISO standards. In addition, micro-structural behaviour and linear polynomials are observed.
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Pervasive analytics act as a prominent role in computer-aided prediction of non-communicating diseases. In the early stage, arrhythmia diagnosis detection helps prevent the cause…
Abstract
Purpose
Pervasive analytics act as a prominent role in computer-aided prediction of non-communicating diseases. In the early stage, arrhythmia diagnosis detection helps prevent the cause of death suddenly owing to heart failure or heart stroke. The arrhythmia scope can be identified by electrocardiogram (ECG) report.
Design/methodology/approach
The ECG report has been used extensively by several clinical experts. However, diagnosis accuracy has been dependent on clinical experience. For the prediction methods of computer-aided heart disease, both accuracy and sensitivity metrics play a remarkable part. Hence, the existing research contributions have optimized the machine-learning approaches to have a great significance in computer-aided methods, which perform predictive analysis of arrhythmia detection.
Findings
In reference to this, this paper determined a regression heuristics by tridimensional optimum features of ECG reports to perform pervasive analytics for computer-aided arrhythmia prediction. The intent of these reports is arrhythmia detection. From an empirical outcome, it has been envisioned that the project model of this contribution is more optimal and added a more advantage when compared to existing or contemporary approaches.
Originality/value
In reference to this, this paper determined a regression heuristics by tridimensional optimum features of ECG reports to perform pervasive analytics for computer-aided arrhythmia prediction. The intent of these reports is arrhythmia detection. From an empirical outcome, it has been envisioned that the project model of this contribution is more optimal and added a more advantage when compared to existing or contemporary approaches.
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Suman Das and Ambika Prasad Pati
Over the past three decades, financial deregulation and various reforms have significantly transformed the competitive environment for banks in Indonesia. These changes have…
Abstract
Purpose
Over the past three decades, financial deregulation and various reforms have significantly transformed the competitive environment for banks in Indonesia. These changes have introduced new challenges for banks to retain their market power and ensure their survival. In light of this, the article aims to assess the current levels of market power held by Indonesian banks and explore the factors that influence it.
Design/methodology/approach
The paper measured the degree of market power and identified its impacting factors for 22 listed commercial banks using the Adjusted Lerner Index (ALI) and appropriate regression technique over a period of 2011–2023.
Findings
The empirical findings reveal that banks in Indonesia enjoy high market power, and factors such as capitalization, diversification, operational inefficiency, asset quality and GDP growth rate significantly impact banks’ market power. Additionally, the findings contradict the structure-conduct-performance paradigm, which advocates that a concentrated banking system impairs competition.
Research limitations/implications
The study suggests that regulatory authorities should closely monitor the market power levels and promote strategies to enhance competition within the banking sector. Additionally, banks should prioritize implementing measures to reduce operational costs and improve the quality of assets.
Originality/value
This research represents one of the early attempts to gauge the market power of publicly listed conventional commercial banks in Indonesia by employing the Adjusted Lerner Index. Additionally, it introduces “technology adoption” as a novel variable to the analysis alongside other established variables.
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Mansi Yadav and Priyanka Banerji
There has been a great deal of exploratory, conceptual and empirical research on digital financial literacy (DFL) in the fields of finance, economics, business and management. But…
Abstract
Purpose
There has been a great deal of exploratory, conceptual and empirical research on digital financial literacy (DFL) in the fields of finance, economics, business and management. But up until now, there has not been any attempt to provide a thorough scientific mapping of the area. Therefore, by combining various knowledge systems, this study seeks to identify the current research trend.
Design/methodology/approach
A sample of 158 papers was subjected to bibliometric analysis in the areas of DFL or digital finance. Assembling, organising and evaluating are the three phases that make up the bibliometric analysis process derived from the most dependable and genuine sources, the Scopus database, and the Web of Science (WoS) database. This study was done using a scientific search technique on the Scopus and WoS databases for the years 2015 through 2022. The study made use of Biblioshiny, a web-based tool created in R-studio and part of the Bibliometrix package. Prominent journals, authors, nations, articles and themes were identified with the use of the software's automated workflow. “Citation, co-citation, and social network analysis” were also carried out.
Findings
The study' outcomes indicate that, as an interdisciplinary discipline, the themes of digital finance have changed throughout time. Researchers first concentrated on socioeconomic and demographic variables, but over time the subject expanded to include themes like influencing, promoting, and behavioural factors that affect digital financial literacy (DFL). This research shows the conceptual framework of the area in addition to its intellectual and social structure. This study offers crucial insights into subjects that demand more research.
Research limitations/implications
Since the current study is a bibliometric analysis, the usual restrictions on such studies apply. A meta-analysis, a thorough literature review and other methods would be beneficial for future researchers to develop a solid conceptual framework. This current research work's science mapping is restricted to the Scopus and WoS databases because this research includes more high-quality articles and has organised formats that work with the Bibliometrix application.
Practical implications
Present research provides critical insights into saving behaviour, retirement planning, digital finance and the interdependence of these. This research highlights the most prevalent problems in the field and points in the direction of potential areas for further study. Exposing the social and intellectual structure of the domain educates upcoming scholars about the themes, contexts and opportunities for collaboration in this field.
Social implications
The study will be useful for future learning as the study gives broad exposure to the current literature in the field of digital finance. On the other hand, people will also grow aware of the effects of digital finance and make the proper choices as a result. Additionally, the report might offer crucial insights for developing policies on digital finance and literacy.
Originality/value
In the past, a significant number of conceptual and empirical studies were conducted internationally in the research fields of economics, finance, business, management and consumer behaviour. This research makes a significant addition by bringing together disparate literature in the field, highlighting reliable sources, authors and documents, and examining the relationship between digital finance, saving behaviour and retirement planning.
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Emmanuel Bannor B. and Alex O. Acheampong
This paper aims to use artificial neural networks to develop models for forecasting energy demand for Australia, China, France, India and the USA.
Abstract
Purpose
This paper aims to use artificial neural networks to develop models for forecasting energy demand for Australia, China, France, India and the USA.
Design/methodology/approach
The study used quarterly data that span over the period of 1980Q1-2015Q4 to develop and validate the models. Eight input parameters were used for modeling the demand for energy. Hyperparameter optimization was performed to determine the ideal parameters for configuring each country’s model. To ensure stable forecasts, a repeated evaluation approach was used. After several iterations, the optimal models for each country were selected based on predefined criteria. A multi-layer perceptron with a back-propagation algorithm was used for building each model.
Findings
The results suggest that the validated models have developed high generalizing capabilities with insignificant forecasting deviations. The model for Australia, China, France, India and the USA attained high coefficients of determination of 0.981, 0.9837, 0.9425, 0.9137 and 0.9756, respectively. The results from the partial rank correlation coefficient further reveal that economic growth has the highest sensitivity weight on energy demand in Australia, France and the USA while industrialization has the highest sensitivity weight on energy demand in China. Trade openness has the highest sensitivity weight on energy demand in India.
Originality/value
This study incorporates other variables such as financial development, foreign direct investment, trade openness, industrialization and urbanization, which are found to have an important effect on energy demand in the model to prevent underestimation of the actual energy demand. Sensitivity analysis is conducted to determine the most influential variables. The study further deploys the models for hands-on predictions of energy demand.
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Martin Götz and Ernest H. O’Boyle
The overall goal of science is to build a valid and reliable body of knowledge about the functioning of the world and how applying that knowledge can change it. As personnel and…
Abstract
The overall goal of science is to build a valid and reliable body of knowledge about the functioning of the world and how applying that knowledge can change it. As personnel and human resources management researchers, we aim to contribute to the respective bodies of knowledge to provide both employers and employees with a workable foundation to help with those problems they are confronted with. However, what research on research has consistently demonstrated is that the scientific endeavor possesses existential issues including a substantial lack of (a) solid theory, (b) replicability, (c) reproducibility, (d) proper and generalizable samples, (e) sufficient quality control (i.e., peer review), (f) robust and trustworthy statistical results, (g) availability of research, and (h) sufficient practical implications. In this chapter, we first sing a song of sorrow regarding the current state of the social sciences in general and personnel and human resources management specifically. Then, we investigate potential grievances that might have led to it (i.e., questionable research practices, misplaced incentives), only to end with a verse of hope by outlining an avenue for betterment (i.e., open science and policy changes at multiple levels).
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Md Mahdi Hj Abd Latif and Gabriel Y.V. Yong
The coast at Berakas in the Brunei-Muara district of Brunei Darussalam suffers from erosion caused by a combination of fluvial and marine processes. This paper investigates the…
Abstract
The coast at Berakas in the Brunei-Muara district of Brunei Darussalam suffers from erosion caused by a combination of fluvial and marine processes. This paper investigates the rate and pattern of erosion along a 1.8-km stretch of coast to compare the difference between the unprotected and protected sections. We used (i) image and spatial analysis and (ii) field geomorphology. The Digital Shoreline Analysis System (DSAS) in ArcGIS was used to compare the study area using two Google Earth images. The study found that the unprotected section had receded by 4.6 m between 2009 and 2019, while the protected section had advanced by 8.0 m over the same period; intense gullying and slumping of cliff continued at both sections. The detached headland breakwaters in the protected section were effective in stabilizing the coast. A concrete drain installed parallel to the cliff edge appears to be capable of intercepting storm runoff, but its effectiveness was undermined by lack of maintenance. We conclude that terrestrial-fluvial processes continue to erode coastal land and cause slumping of the cliff face at Berakas. However, coastal protection structures that curb the marine process could stabilize the coastline, even where sediment transport is active.