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With the advancements in photo editing software, it is possible to generate fake images, degrading the trust in digital images. Forged images, which appear like authentic images, can be created without leaving any visual clues about the alteration in the image. Image forensic field has introduced several forgery detection techniques, which effectively distinguish fake images from the original ones, to restore the trust in digital images. Among several forgery images, spliced images involving human faces are more unsafe. Hence, there is a need for a forgery detection approach to detect the spliced images.

This paper proposes a Taylor-rider optimization algorithm-based deep convolutional neural network (Taylor-ROA-based DeepCNN) for detecting spliced images. Initially, the human faces in the spliced images are detected using the Viola–Jones algorithm, from which the 3-dimensional (3D) shape of the face is established using landmark-based 3D morphable model (L3DMM), which estimates the light coefficients. Then, the distance measures, such as Bhattacharya, Seuclidean, Euclidean, Hamming, Chebyshev and correlation coefficients are determined from the light coefficients of the faces. These form the feature vector to the proposed Taylor-ROA-based DeepCNN, which determines the spliced images.

Experimental analysis using DSO-1, DSI-1, real dataset and hybrid dataset reveal that the proposed approach acquired the maximal accuracy, true positive rate (TPR) and true negative rate (TNR) of 99%, 98.88% and 96.03%, respectively, for DSO-1 dataset. The proposed method reached the performance improvement of 24.49%, 8.92%, 6.72%, 4.17%, 0.25%, 0.13%, 0.06%, and 0.06% in comparison to the existing methods, such as Kee and Farid's, shape from shading (SFS), random guess, Bo Peng et al., neural network, FOA-SVNN, CNN-based MBK, and Manoj Kumar et al., respectively, in terms of accuracy.

The Taylor-ROA is developed by integrating the Taylor series in rider optimization algorithm (ROA) for optimally tuning the DeepCNN.

Ohmic heating generates temperature with the help of electrical current and resists the flow of electricity. Also, it generates heat rapidly and uniformly in the liquid matrix. Electrically conducting biofluid flows with Ohmic heating have many biomedical and industrial applications. The purpose of this study is to provide the significance of the effects of Ohmic heating and viscous dissipation on electrically conducting Casson nanofluid flow driven by peristaltic pumping through a vertical porous channel.

In this analysis, the non-Newtonian properties of fluid will be characterized by the Casson fluid model. The long wavelength approach reduces the complexity of the governing system of coupled partial differential equations with non-linear components. Using a regular perturbation approach, the solutions for the flow quantities are established. The fascinating and essential characteristics of flow parameters such as the thermal Grashof number, nanoparticle Grashof number, magnetic parameter, Brinkmann number, permeability parameter, Reynolds number, Casson fluid parameter, thermophoresis parameter and Brownian movement parameter on the convective peristaltic pumping are presented and thoroughly addressed. Furthermore, the phenomenon of trapping is illustrated visually.

The findings indicate that intensifying the permeability and Casson fluid parameters boosts the temperature distribution. It is observed that the velocity profile is elevated by enhancing the thermal Grashof number and perturbation parameter, whereas it reduces as a function of the magnetic parameter and Reynolds number. Moreover, trapped bolus size upsurges for greater values of nanoparticle Grashof number and magnetic parameter.

There are some interesting studies in the literature to explain the nature of the peristaltic flow of non-Newtonian nanofluids under various assumptions. It is observed that there is no study in the literature as investigated in this paper.

The purpose of this paper is to investigate the behavior of a non-Newtonian nanofluid caused by peristaltic waves along an asymmetric channel. Additionally considered is the production of thermal radiation and activation energy.

The equations of momentum, mass and temperature of Sutterby nanofluids are obtained for long wavelength. By taking into account the velocity, temperature and concentration, the formulation is further finished.

Analyses of the physical variables influencing flow features are represented graphically. The present investigation shows that an enhancement in the temperature ratio parameter results in an increase in both the temperature and concentration. The investigation also shows that the dimensionless reaction rate significantly raises the kinetic energy of the reactant, which permits more particle collisions and as a result, raises the temperature field.

Due to their importance in the treatment of cancer, activation energy and thermal radiation as a route of heat transfer are crucial and exciting phenomena for researchers. So, the cancer cells are killed, and tumors are reduced in size with heat and making hyperthermia therapy a cutting-edge cancer treatment.

Web users rely heavily on online content make decisions without assessing the veracity of the content. The online content comprising text, image, video or audio may be tampered with to influence public opinion. Since the consumers of online information (misinformation) tend to trust the content when the image(s) supplement the text, image manipulation software is increasingly being used to forge the images. To address the crucial problem of image manipulation, this study focusses on developing a deep-learning-based image forgery detection framework.

The proposed deep-learning-based framework aims to detect images forged using copy-move and splicing techniques. The image transformation technique aids the identification of relevant features for the network to train effectively. After that, the pre-trained customized convolutional neural network is used to train on the public benchmark datasets, and the performance is evaluated on the test dataset using various parameters.

The comparative analysis of image transformation techniques and experiments conducted on benchmark datasets from a variety of socio-cultural domains establishes the effectiveness and viability of the proposed framework. These findings affirm the potential applicability of proposed framework in real-time image forgery detection.

This study bears implications for several important aspects of research on image forgery detection. First this research adds to recent discussion on feature extraction and learning for image forgery detection. While prior research on image forgery detection, hand-crafted the features, the proposed solution contributes to stream of literature that automatically learns the features and classify the images. Second, this research contributes to ongoing effort in curtailing the spread of misinformation using images. The extant literature on spread of misinformation has prominently focussed on textual data shared over social media platforms. The study addresses the call for greater emphasis on the development of robust image transformation techniques.

This study carries important practical implications for various domains such as forensic sciences, media and journalism where image data is increasingly being used to make inferences. The integration of image forgery detection tools can be helpful in determining the credibility of the article or post before it is shared over the Internet. The content shared over the Internet by the users has become an important component of news reporting. The framework proposed in this paper can be further extended and trained on more annotated real-world data so as to function as a tool for fact-checkers.

In the current scenario wherein most of the image forgery detection studies attempt to assess whether the image is real or forged in an offline mode, it is crucial to identify any trending or potential forged image as early as possible. By learning from historical data, the proposed framework can aid in early prediction of forged images to detect the newly emerging forged images even before they occur. In summary, the proposed framework has a potential to mitigate physical spreading and psychological impact of forged images on social media.

This study focusses on copy-move and splicing techniques while integrating transfer learning concepts to classify forged images with high accuracy. The synergistic use of hitherto little explored image transformation techniques and customized convolutional neural network helps design a robust image forgery detection framework. Experiments and findings establish that the proposed framework accurately classifies forged images, thus mitigating the negative socio-cultural spread of misinformation.

The aim of the present paper is to investigate the homogeneous and heterogeneous reactions on Prandtl fluid flow at a stretching sheet with an induced magnetic field and slip boundary conditions.

The governing equations include the continuity, induced magnetic field, momentum, energy and homogeneous–heterogeneous equations. Initially, with suitable similarity variables, the governing partial differential equations and converted into a system of ordinary differential equations. Then, the nonlinear ordinary differential equations are solved by a shooting technique with the help of the BVC5C Matlab package.

The results of the present investigation are presented through graphs for different values of the various parameters. The authors observed that the large values of the stretching ratio and the induced magnetic parameters are moderate magnetic field, velocity and temperature primarily. Also, the authors found the more velocity and temperatures by boosting the slip parameters.

In addition, the values of the skin friction and the rate of heat transfer for various values of physical parameters are tabulated and deliberated in detail.

The present work explores the influence of Hall and Ohmic heating effects on the convective peristaltic flow of a conducting Jeffrey nanofluid in an inclined porous asymmetric channel with slip. Also, the authors investigated the impact of viscous dissipation, thermal radiation, heat generation/absorption and cross diffusion effects on the flow. Peristaltic flow has many industrial and physiological applications and most of the biofluids show the non-Newtonian fluid behaviour. Further, in a living body, several biofluids flow through different kinds of systems that are not symmetric, horizontal or vertical. The purpose of this paper is to address these issues.

The authors considered the flow of Jeffrey fluid which is generated by a sinusoidal wave propagating on the walls of an inclined asymmetric channel. The flow model is developed from the fixed frame to the wave frame. Finally, yield the nonlinear governing equations by applying the non-dimensional quantities with the assumptions of lengthy wave and negligible Reynolds number. The exact solution has been computed for the velocity and pressure gradient. The solutions for temperature and concentration are obtained by the regular perturbation technique.

Graphical analysis is made for the present results for different values of emerging parameters and explained clearly. It is noticed that the magnetic field enriches the temperature where it drops the fluid velocity. This work describes that the temperature field is decreasing due to the radiation but it is a rising function of temperature slip parameter. The temperature profile declines for growing values of the Hall parameter. The flow velocity diminishes for boosting values of the Darcy parameter. Further, the authors perceived that the concentration field reduces for large values of the chemical reaction parameter.

The authors validated and compared the results with the existing literature. This investigation will help to study some physiological systems, and heat transfer in peristaltic transport plays key role in medical treatments, so we ensure that these results are applicable in medical treatments like cancer therapy, drug delivery, etc.

The purpose of this paper is to evaluate the impact of extended waiting time on patients’ perceptions of provider communication skills and in-clinic satisfaction, in three major cities in India.

In total, 625 patients were interviewed. The multivariate general linear model was used to determine the causality and relationship between the independent and the dependent variable. A moderation analysis was also conducted to assess waiting time role as a potential moderator in doctor-patient communication.

Results show that patients with higher waiting time were less satisfied with health care quality. Male patients and patients of male providers were more affected by extended waiting time than female patients and patients of female providers. The advanced regression analysis, however, suggests weak support for waiting time and its effect on overall satisfaction with clinic quality. Waiting time did not moderate the relationship between satisfaction with dominant communication style, and overall satisfaction at the outpatient clinic.

A cross-sectional study does not easily lend itself to explaining causality with certainty. Thus, sophisticated techniques, such as structural equation modelling may also be utilized to assess the influence of extended waiting time on satisfaction with healthcare at outpatient clinics.

Findings are relevant for providers as the onus is on them to ensure patient satisfaction. They should initiate a workable waiting time assessment model at the operational level.

There has been a relatively lesser focus on patient waiting time in patient-provider satisfaction studies. In India, this aspect is still vastly unexplored especially in the context of outpatient clinics. Gender wise pattern of patient satisfaction and waiting time is also missing in most studies.

Entering a new era of digital transformation, Industry 4.0 (I 4.0) promises to revolutionize the way business has been done, providing unprecedented opportunities and challenges. This study aims to investigate empirically and comparatively analyse the benefits, challenges and critical success factors (CSFs) of Industry 4.0 across four continents and developing and developed economies.

This study used an online survey to explore the benefits, challenges and CSFs of developed and developing economies. In order to ensure the validity of the survey, a pilot test was conducted with 10 respondents. A total of 149 participants with senior managerial, vice-presidential and directorial positions from developed and developing economies spanning four continents were invited to take part in the survey.

The study ranks benefits, challenges and CSFs across economies and continents. Further, the benefit of Industry 4.0 helping to achieve organizational efficiency and agility differed across the developing and developed economies. Furthermore, the benefit improves customer satisfaction significantly differed across continents; in terms of challenges, Employee resistance to change had a higher proportion in developing economies. The future viability of I 4.0 also differed across the continents. Regarding CSFs, there was no difference across the developing and developed economies. Finally, change management and project management vary across the continents.

This study contributes to a balanced understanding of I 4.0 by providing empirical evidence for comparative analysis. Moreover, it extends the concept of resource dependence theory to explain how organizations in developing economies and developed economies deploy resources to manage external condition uncertainties to implement I 4.0. Furthermore, this study provides a structural framework to understand the specific benefits, challenges and CSFs of implementing I 4.0, which can be utilized by policymakers to promote I 4.0 in their economies or continents.

To the best of the authors’ knowledge, no studies have empirically demonstrated the comparative analysis of benefits, challenges and CSFs across economies and continents and distinguish an original contribution of this work.

The main purpose of this paper is to study the effect of heat transfer on the peristaltic flow of a magnetohydrodynamic Walters B fluid through a porous medium in an inclined asymmetric channel.

The approximate analytical solutions of the governing partial differential equations are obtained using the regular perturbation method by taking wave number as a small parameter. The solutions for the pressure difference and friction forces are evaluated using numerical integration.

It is noticed that the pressure gradient and pressure difference are increasing functions of inclination angle and Grashof number. The temperature and heat transfer coefficients both increase with increase in inclination angle, Darcy number, Grashof number and Prandtl number. Increase in Hartmann number and phase difference decreases the size of trapped bolus.

The problem is original, as no work has been reported on the effect of magnetohydrodynamics on the peristaltic flow of a Walters B fluid through a porous medium in an inclined asymmetric channel with heat transfer.

The purpose of this paper is to report the impact of thermophoresis and Brownian moment on MHD two-dimensional forced convection flow of nanofluid past a permeable stretching sheet in the presence of thermal diffusion.

The flow governing PDEs are reduced to ODEs by utilizing pertinent transmutations and then resolved by employing a fourth-order Runge-Kutta-based shooting technique. The energy and diffusion equations are incorporated with Brownian motion, thermophoresis and Soret parameters. The velocity, thermal and concentration attributes along with skin friction factor, local Nusselt and Sherwood number are discussed under the influence of sundry pertinent parameters and presented with the assistance of graphical and tabular values.

The results infer that Sherwood number is accelerated by Soret parameter but it controls the thermal transport rate. And also, Brownian and thermophoresis play a vital role in enhancing heat conduction process.

Considering the industrial applications of flow of magnetic nanofluid over a stretching surface, this paper presents the solution of the flow problem considering thermophoresis, Brownian motion, magnetic field and thermal diffusion effects. In addition, the aim and objectives of this paper fills a gap in the industry.