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The purpose of this paper is to develop an eco-friendly corrosion inhibitor for mild steel in 1 M HCl.

A pharmaceutical drug acetyl G was investigated for its corrosion inhibition efficiency using weight loss method, potentiodynamic polarisation and electrochemical impedance spectroscopy.

The inhibition efficiency increased with increase in inhibitor concentration. Results from polarisation studies revealed mixed type of inhibition. Impedance studies, scanning electron microscopy and Fourier transform spectroscopy confirm the adsorption of inhibitor on the mild steel surface.

The drug acetyl G has sulphur and nitrogen atoms which effectively block the corrosion of mild steel and is non-toxic and has good inhibition efficiency.

This method provides an excellent, non-toxic and cost-effective material as a corrosion inhibitor for mild steel in acid medium.

Application of this drug as a corrosion inhibitor has not been reported yet in the literature. Replacing the organic inhibitors, this green inhibitor shows excellent inhibition efficiency. This is adsorbed excellently on the mild steel surface due to the presence of long chain and hetero atoms. Thus, the drug retards the corrosion reaction.

The purpose of this paper is to analyze the existence of volatility spillover effect in frontier markets. This study also examines whether any linkages exist among these markets or not.

Monthly data of regional frontier markets, from 2009 to 2016, are analyzed using Multivariate GARCH (BEKK and Dynamic Conditional Correlation (DCC)) models.

The result of cointegration test shows that the sample frontier markets are not linked in long run, and Granger causality test reveals that the markets under consideration do not cause each other even in the short run. BEKK test says that the effect of the arrival of shock from the own market does not last for longer, whereas shock from other markets lasts with the stronger persistence, and according to DCC test, the volatility spillover exists for all the markets.

The results of present study suggest that the frontier markets are not cointegrated in the long run as well as in the short run, which opens the doors for long-term investments in these markets in future, which may lead to decent returns. Long-term investors may draw the benefits from including the financial assets in their portfolios from these non-integrated frontier markets; nevertheless, they have to consider and implement diversification and hedging strategies during the period of financial turmoil, so as to protect themselves against economic and financial distress.

Significant work has been done on developed, developing and emerging markets but frontier markets are not explored much so far. This paper is an attempt to see the status of frontier stock markets as potential financial markets for diversification benefits.

This paper aims to appraise the inhibitory effect of saponins extracted from Gongronema latifolium (SEGL) on mild steel in acid media. This is in a bid to conserve our environment and maintain the integrity of engineering structures and materials.

The corrosion inhibition of SEGL and ethanolic extracts of the leaves of G. latifolium (EEGL) on mild steel was studied by hydrogen evolution technique within a temperature range of 30-60°C in tetraoxosulphate (VI) acid solutions.

The extracts inhibit the corrosion of mild steel, and the inhibition efficiency depends on the concentration of the plant extract, temperature and the period of immersion. SEGL was comparatively more efficient than EEGL. Optimum values of the inhibition efficiency for both the EEGL and SEGL (93.7 and 96.5 per cent, respectively) were obtained at extract concentration of 10 g/L, whereas the least values were obtained at extract concentration of 0.5 g/L.

This paper provides new information on the possible application of isolated SEGL as an environmentally friendly corrosion inhibitor. The possible mechanism of the inhibitive action is also given.

The current investigation is concerned with the Soret effect along with chemical reaction and radiation on flow of an electrically conductive, viscous fluid through a perpendicular plate, which is porous with oscillatory suction. The aim of this study is to investigate the effects of first-order temperature and chemical reaction and the transverse magnetic field characteristics. The closed form of solutions are obtained using the governing equations for concentration, energy and momentum. The perturbation technique was applied to find the result for the velocity field, temperature profiles and concentration distributions. Furthermore, the impact of various nondimensional parameters on fluid flow variables on the temperature field, velocity field and concentration dispersal was analyzed and the results were depicted graphically. Moreover, the skin friction and the rate of mass transfer (local Sherwood number) were analyzed using tables. In this work, an unsteady 2D flow of a laminar, viscid (Newtonian), electrically conducting fluid across a semi-infinite perpendicular permeable plate under motion in its plane (x-axis) embedded in a constant permeable structure was investigated.

In this work, an unstable 2D flow of a laminar, viscid (Newtonian), electrically conducting fluid across a semi-limitless perpendicular permeable plate under motion in its plane (x-axis) embedded in a constant permeable structure was investigated. The medium is considered to be under a transverse magnetic field with concentrated buoyancy effects. Furthermore, it is considered that no voltage is supplied, which indicates that there is no electrical field. The fluid properties are considered to be uniform. The concentration of the imparting species is considered as C′w at the plate; the concentration of the specimens away from the wall, C′8, is considered to be limitlessly less. The first-order chemical reaction is considered to be seen in the flow. Due to the semi-limitless plane surface considerations, the flow parameters are the functions of y′ and the time t′ only. The oscillatory suction velocity of the fluid at the plate normal to it is v′; initially, the plate relocates with the oscillatory velocity u′, in the direction of x that is in its plane. The pressure gradient is toward the x-axis.

The analytical solutions were obtained using the above analytical method for a few values of the governing parameters, such as the magnetic parameter (M), the permeability parameter (K), Schmidt number (Sc), chemical reaction parameter (Kr), Grashoff number for the concentration (Gm), Radiation parameter (N), Prandtl number (Pr), Chemical reaction parameter (Kr), Grashof number for heat transfer (Gr) and Heat source parameter (s). The influence of M, K, Sc, Kr, Gm, N, Pr, Kr, Gr and s on the fluid velocity, temperature and the concentration over the semi-infinite porous plate was obtained. Furthermore, the numerical computation was carried out using MATLAB.

In this chapter, the analysis of a free convective flow of a viscid compact, electrically conductive fluid was discussed during its flow through a plate in permeable condition with oscillatory suction with first-order temperature and chemical reaction and the transverse magnetic field. The problem formulation and the results were discussed. The following chapter explain the Soret effect of mass transfer and radiation with heat source on magnetohydrodynamics oscillatory viscoelastic fluid in a channel filled with porous medium.

Nowadays, the speech emotion recognition (SER) model has enhanced as the main research topic in various fields including human–computer interaction as well as speech processing. Generally, it focuses on utilizing the models of machine learning for predicting the exact emotional status from speech. The advanced SER applications go successful in affective computing and human–computer interaction, which is making as the main component of computer system's next generation. This is because the natural human machine interface could grant the automatic service provisions, which need a better appreciation of user's emotional states.

This paper implements a new SER model that incorporates both gender and emotion recognition. Certain features are extracted and subjected for classification of emotions. For this, this paper uses deep belief network DBN model.

Through the performance analysis, it is observed that the developed method attains high accuracy rate (for best case) when compared to other methods, and it is 1.02% superior to whale optimization algorithm (WOA), 0.32% better from firefly (FF), 23.45% superior to particle swarm optimization (PSO) and 23.41% superior to genetic algorithm (GA). In case of worst scenario, the mean update of particle swarm and whale optimization (MUPW) in terms of accuracy is 15.63, 15.98, 16.06% and 16.03% superior to WOA, FF, PSO and GA, respectively. Under the mean case, the performance of MUPW is high, and it is 16.67, 10.38, 22.30 and 22.47% better from existing methods like WOA, FF, PSO, as well as GA, respectively.

This paper presents a new model for SER that aids both gender and emotion recognition. For the classification purpose, DBN is used and the weight of DBN is used and this is the first work uses MUPW algorithm for finding the optimal weight of DBN model.

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.

This paper aims to provide a prolonging network lifetime and optimizing energy consumption in mobile wireless sensor networks (MWSNs). MWSNs have characteristics of dynamic topology due to the factors such as energy consumption and node movement that lead to create a problem in lifetime of the sensor network. Node clustering in wireless sensor networks (WSNs) helps in extending the network life time by reducing the nodes’ communication energy and balancing their remaining energy. It is necessary to have an effective clustering algorithm for adapting the topology changes and improve the network lifetime.

This work consists of two centralized dynamic genetic algorithm-constructed algorithms for achieving the objective in MWSNs. The first algorithm is based on improved Unequal Clustering-Genetic Algorithm, and the second algorithm is Hybrid K-means Clustering-Genetic Algorithm.

Simulation results show that improved genetic centralized clustering algorithm helps to find the good cluster configuration and number of cluster heads to limit the node energy consumption and enhance network lifetime.

In this work, each node transmits and receives packets at the same energy level throughout the solution. The proposed approach was implemented in centralized clustering only.

The main reason for the research efforts and rapid development of MWSNs occupies a broad range of circumstances in military operations.

The research highly gains impacts toward mobile-based applications.

A new fitness function is proposed to improve the network lifetime, energy consumption and packet transmissions of MWSNs.

For achieving the profitable human activity recognition (HAR) method, this paper solves the HAR problem under wireless body area network (WBAN) using a developed ensemble learning approach. The purpose of this study is,to solve the HAR problem under WBAN using a developed ensemble learning approach for achieving the profitable HAR method. There are three data sets used for this HAR in WBAN, namely, human activity recognition using smartphones, wireless sensor data mining and Kaggle. The proposed model undergoes four phases, namely, “pre-processing, feature extraction, feature selection and classification.” Here, the data can be preprocessed by artifacts removal and median filtering techniques. Then, the features are extracted by techniques such as “t-Distributed Stochastic Neighbor Embedding”, “Short-time Fourier transform” and statistical approaches. The weighted optimal feature selection is considered as the next step for selecting the important features based on computing the data variance of each class. This new feature selection is achieved by the hybrid coyote Jaya optimization (HCJO). Finally, the meta-heuristic-based ensemble learning approach is used as a new recognition approach with three classifiers, namely, “support vector machine (SVM), deep neural network (DNN) and fuzzy classifiers.” Experimental analysis is performed.

The proposed HCJO algorithm was developed for optimizing the membership function of fuzzy, iteration limit of SVM and hidden neuron count of DNN for getting superior classified outcomes and to enhance the performance of ensemble classification.

The accuracy for enhanced HAR model was pretty high in comparison to conventional models, i.e. higher than 6.66% to fuzzy, 4.34% to DNN, 4.34% to SVM, 7.86% to ensemble and 6.66% to Improved Sealion optimization algorithm-Attention Pyramid-Convolutional Neural Network-AP-CNN, respectively.

The suggested HAR model with WBAN using HCJO algorithm is accurate and improves the effectiveness of the recognition.

The research purpose is to explore the diffusion of mobile QR-code payment (MQP) in a coronavirus disease (COVID-19) context by formulating a behavioral response model based on an integration between protection motivation theory (PMT) and unified theory of acceptance and use of technology (UTAUT). This study also investigates the importance of physical distancing norm for behavioral intention toward MQP.

A web-based survey was designed and data were accumulated from 411 validated respondents who have used MQP or tend to utilize it in Vietnam. Statistical analysis was conducted using SPSS and AMOS to verify the hypotheses.

Results illustrated that behavioral intention is motivated by key antecedents of PMT (including perceived severity, perceived susceptibility and self-efficacy) and important factors of UTAUT (including performance expectancy, effort expectancy and social influence), and physical distancing norm. Moreover, perceived severity promotes performance expectancy, whereas self-efficacy boosts effort expectancy in MQP. Lastly, behavioral intention and recommendation were indicators of the diffusion of MQP under COVID-19.

MQP is just in its infant stage in Vietnam; thus, the findings provide managerial implications, which will aid service providers and firms to adopt marketing strategies that enhance consumers' acceptability and recommendation of MQP to the public.

Little is empirically considered the effects of perceived threat-related factors in PMT and physical distancing norm on behavioral intention toward MQP in a salient pandemic setting. Furthermore, the antecedents in UTAUT contribute greatly to behavioral intention. This study enlightens the diffusion of MQP based on behavioral intention and recommendation.

The purpose of the study is to find the effect of convergent and divergent section length on the exit flow characteristics. Converging-diverging (CD) nozzle design can be difficult because of the necessity for precise geometry and an understanding of compressible fluid flow dynamics. To obtain the ideal supersonic speeds, it is challenging to make sure that the flow chokes at the throat, where the Mach number approaches one and then expands appropriately in the diverging region. The design needs to take into consideration things like the relationship between the area and Mach number, the impact of various pressure ratios and the flow’s isentropic interactions.

An ideal thrust production is achieved through the effective acceleration of exhaust gases through proper nozzle design. This paper numerically investigates impact of convergent, divergent length and nozzle pressure ratio on the exit Mach Number of CD nozzle supersonic jet. Exit Mach Number 1.6 convergent-divergent nozzle was used. In total, five cases were taken as the length of the both the convergent-divergent sections were modified with 50% of increment and decrement in its base length. At four different NPR, the analysis was carried out in over-expanded, correctly expanded and under-expanded conditions. The NPR used were 2, 3.2, 4 and 5.

From the results, it is found that the convergent length linearly affects the exit Mach number, while the divergent length variation is not in order. Both the decreased and increased divergent length reduce the supersonic jet exit Mach number. The subsonic region is not majorly affected by the length. There is no rapid change in the flow properties whether the length is reduced or increased. Maximum of 2% to 3% variation is only noticed. On the contrary, a small change in supersonic region or divergent section makes major modification in the flow.

To achieve the desired Mach number, not only the area of the nozzle but also the length affects it. In terms of divergent angle and area ratio, only most of the studies on nozzle have been focused. This study aims to find the impact of convergent length and divergent length on the exit Mach number. This could be used in a wide range of applications, including laser cutting, thermal spraying, gas turbines for power generation, rocket and jet engines, supersonic wind tunnels and turbo chargers in automotive engineering, because of their capacity to accelerate fluids to supersonic speeds.