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Sixth-Generation (6G) Mobile Cloud Security and Privacy Risks for AI System Using High-Performance Computing Implementation
The exchange of information from one person to another is called communication. Telecommunication makes it possible with electronic devices and their tools. The scientist Alexander Graham Bell has invented the basic telephone in 1876 in the USA. Telephones now have the new format in the form of mobile phones, which are the primary media for communicating and transmitting data. We are using 5th-generation mobile network standards. Still, there are some requirements for the users that are believed to be solved in the 6th-generation mobile network standards. By 2030, all of the people would be using 6G. The computing model in the cloud is not dependent on either the location or any specific device that would provide the service. It is an on-demand computational service-oriented mechanism. Combining these two technologies as mobile cloud computing provides customized options with more flexible implementations. Artificial intelligence is being used in devices in many fields. AI can be used in mobile network services (MNS) to provide more reliable and customized services to the users, such as network operation monitoring, network operation management, fraud detection, and reduction in mobile transactions and security to the cyber devices. Combining cloud with AI in mobile network services in the 6th generation would improve human beings' lives, such as zero road accidents, advanced level special health care, and zero crime rates in society. However, the most vital needs for sixth-generation standards are the capability to manage large volumes of records and excessive-statistics-fee connectivity in step with gadgets. The sixth-generation mobile network is under development. This generation has many exciting features. Security is the central issue that needs to be sorted out using appropriate forensic mechanisms. There is a need to approach high-performance computing for improved services to the end-user. Considering three-dimensional research methodologies (technical dimension, organizational dimension, and applications hosted on the cloud) in a high-performance computing environment leads to two different cases such as real-time stream processing and remote desktop connection and performance test. By 'narrowing the targeted worldwide audience with a wide range of experiential opportunities,' this paper is aimed at delivering dynamic and varied resource allocation for reliable and justified on-demand services. 2022 Srinivasa Rao Gundu et al. -
Hycons Renewable Private Limited: decision to accept or reject an equity investment
Learning outcomes: This study will help students determine the economic value of a firm particularly in case of a small business. The crux of the case is to help students estimate an enterprise value for a company and figure the actual worth of the company to aid in decision-making. Case overview/Synopsis: This case is about a decision dilemma faced by Shashi Hegde, Director, Hycons Renewable Private Ltd, a company ventured into the production of Bio-CNG. It is about a recent proposal received by the firm from APL Ltd for equity investment with 40% stake in the firm. The case reflects the dilemma faced by small businesses to choose between investment or loss of control. Accepting the proposal will bring in additional funds, whereas the Board loss control on the firm. The case revolves around this dilemma. To help Hegde in this task, he seeks advice from his CFO and his confidant Kumar. Complexity academic level: This case is most appropriate for a core finance class for both under-graduate and graduate programs. Supplementary materials: Teaching notes are available for educators only. Subject code: CSS 1: Accounting and Finance. 2022, Emerald Publishing Limited. -
Yttrium(III) oxide catalyzed facile synthesis of novel hydrazinyl thiazoles by multicomponent approach
A facile and a one-pot procedure for the synthesis of novel hydrazinyl thiazoles by the cyclo condensation reaction between substituted phenacyl bromides, aromatic aldehydes, and semicarbazides using Yttrium(III) oxide as reusable catalyst under acetic acid as a solvent medium is described. The chromatography-free methodology has several benefits such as being facile, atom economic, higher functional group tolerance and provides excellent yield in shorter reaction time. All the synthesized compounds were characterized by 1H NMR, 13C NMR, and HRMS (ESI) analysis. 2021 -
Cattaneo-Christov Theory to model heat flux effect on nanoliquid slip flow over a spinning disk with nanoparticle aggregation and Hall current
The heat transport of a nanoliquid on a spinning disk with velocity slip and thermal jump boundary conditions is modeled. The effects of external magnetism and the aggregation of nanoparticles are analyzed. The Cattaneo-Christov heat flux model and the Joule heating phenomenon are incorporated in the thermal analysis. The central composite design (CCD) of the response surface methodology is implemented to optimize heat transfer in the nanoliquid. The sensitivity of the heat transport is analyzed. The partial differential governing model is converted into a system of ordinary differential equations using a novel von Karmans transformation, the consequent system is solved numerically. The significance of physical operating parameters is analyzed through a detailed parametric study. Optimal levels of Hall parameter, Hartmann number, and Eckert number, that optimize the heat transport are determined. The Lorentz force expands the structure of the thermal layer and subsequently reduces the heat transport of the system. The Hall current improves the thickness of the velocity layer in the radial direction, while the thickness of the thermal layer is reduced. Viscous dissipation improves the thickness of the thermal boundary layer. The isothermal boundary condition causes less heat transport in the system than the temperature jump condition. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Implementation of a Heart Disease Risk Prediction Model Using Machine Learning
Cardiovascular disease prediction aids practitioners in making more accurate health decisions for their patients. Early detection can aid people in making lifestyle changes and, if necessary, ensuring effective medical care. Machine learning (ML) is a plausible option for reducing and understanding heart symptoms of disease. The chi-square statistical test is performed to select specific attributes from the Cleveland heart disease (HD) dataset. Support vector machine (SVM), Gaussian Naive Bayes, logistic regression, LightGBM, XGBoost, and random forest algorithm have been employed for developing heart disease risk prediction model and obtained the accuracy as 80.32%, 78.68%, 80.32%, 77.04%, 73.77%, and 88.5%, respectively. The data visualization has been generated to illustrate the relationship between the features. According to the findings of the experiments, the random forest algorithm achieves 88.5% accuracy during validation for 303 data instances with 13 selected features of the Cleveland HD dataset. 2022 K. Karthick et al. -
Perusal of flexoelectric effect with deformed interface in distinct (PZT-7A, PZT-5A, PZT-6B, PZT-4, PZT-2) piezoelectric materials
The present research article aims to describe that the flexoelectric affects the propagation of Love-type in various piezoelectric (PE) materials bars (PZT-7A, PZT-5A, PZT-6B, PZT-4, PZT-2) that rest over a silicon oxide plate under the presence of a deformed interface. With the help of material properties of these various piezoelectric, this article elucidates the impact of flexoelectric (FE) and piezoelectric (PE) on propagation characteristics of Love-type waves. Before this, the desire dispersion relation in the form of a complex, for both electrically unlocked/locked conditions, have been obtained by using mechanical as well as electrical quantities for the respective medium under suitable boundary and interface conditions. The complex dispersion relation is separated into real and imaginary terms which give Real(c) and Imag(c). Further, the effect of flexoelectric (FE) and piezoelectric (PE) on Real(c) and Imag(c) have been observed. In addition, a comparative study among various types of piezoelectric materials is also performed which serve as a major highlight of the present research work. The outcomes of this study may be very helpful in the specific problems of monitoring structural health system design with the help of simulation and alesser number of elaborate trials. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Examination of thermal and velocity slip effects on the flow of blood suspended with aluminum alloys over a bi-directional stretching sheet: the ternary nanofluid model
The flow of a ternary nanofluid through a bi-directionally distending sheet has been analyzed by employing the Casson model. The ternary nanofluid is formed by suspending the aluminum alloys namely (Formula presented.) and (Formula presented.) along with the oxide (Formula presented.) into blood. The nanoparticles that are suspended in the base fluid are assumed to be in the shape of a blade so that the maximum surface of the nanoparticle will be intact with the base fluid and thus will absorb more heat from the surface. Also, the shape of the nanoparticle helps in faster movement within the nanofluid. The flow is further subjected to velocity and thermal slips. With these assumptions, the mathematical model is framed with the help of partial differential equations considering thermal radiation and heat source/sink to achieve realistic results. These equations are further transformed into non-linear differential equations that are solved using the (Formula presented.) technique. The results of this study are interpreted graphically for various parameters concerning fluid flow. It is observed that the fluid flow velocity is ebbed considerably with the increase in Casson parameter and the slips at the boundary have enhanced the corresponding fluid profiles. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
Effects of variable thermal properties on thermoelastic waves induced by sinusoidal heat source in half space medium
Aim of the present study is to characterize the effects of changing thermal conductivity on the propagation of thermoelastic waves in the half space medium when it is exposed to a periodic heat source. Closed form solutions of all significant physical fields such as conductive temperature, stress and displacement are evaluated in their dimensionless form in the Laplace transform domain. Impact of changing thermal conductivity parameter is exhibited on all field variables with the help of quantitative outcomes in time-domain. Following this pattern, the effects of time parameter is also observed on the field quantities. 2022 -
Intensified geopolitical conflicts and herding behavior: An evidence from selected Nifty sectoral indices during India-China tensions in 2020
The recent India-China geopolitical conflicts have presented enormous uncertainty to the investors in various sectoral indices of the Indian stock market. This empirical study aims to examine the impact of intensified India-China geopolitical conflicts 2020 on investors' herding behavior in the National Stock Exchange sectoral indices. The high-frequency data of three major NIFTY sectoral indices (Auto, Energy, and Pharma) are used in an intensified geopolitical event window to spot precisely the traces of the investors' herding behavior. Furthermore, multifractal detrended fluctuation analysis (MFDFA) is employed to obtain Hurst Exponent values (h(q)) for the NIFTY sectoral indices. The findings reveal that these NIFTY sectoral indices exhibited profound traces of herding behavior on the event day (t = 0) due to the heightened India-China geopolitical clashes. In addition, these indices depicted an overall higher level herding behavior with the (h(q)) values close to 0.72 throughout the intensified geopolitical event window. The study concludes that the sectors highly reliant on the Chinese supplies and with significant trade linkages with China depicted a higher level of herding behavior in their indices. Further, the presence of herding behavior in these sectoral indices is due to the operational and supply-chain risks posed by the geopolitical event. 2022 LLC CPC Business Perspectives. All rights reserved. -
Effect of source-substrate distance on the transparent electrode properties of spray pyrolysed aluminium doped zinc oxide thin films
The wide band gap zinc oxide is a potential metal oxide that has been widely used in optoelectronic applications. The zinc oxide thin films demonstrate excellent conductivity and transparency enabling them for transparent electrode applications. The aluminium doping is an efficient route in further improving the conductivity without compromising the transparency and scalable spray pyrolysis is an effective approach in realizing high quality thin films. Our current study focuses on the effects of distance between the substrate and spray nozzle on the structural, morphological, optical, and electrical properties of aluminium doped zinc oxide. Our results suggests that this spray parameter has appreciable impact on the thin film properties and can be optimized for tuning properties. We explain this in detail backed by the characterization of thin films by X-ray diffraction, Atomic Force Microscopy, UVVis-NIR spectroscopy, Photoluminescence and Hall effect measurements. 2021 -
A Novel Edge-Based Trust Management System for the Smart City Environment Using Eigenvector Analysis
The proposed Edge-based Trust Management System (E-TMS) uses an Eigenvector-based approach for eliminating the security threats present in the Internet of Things (IoT) enabled smart city environment. In most existing trust management systems, the trust aggregation process completely depends on the direct trust ratings obtained from both legitimate and malicious neighboring IoT devices. E-TMS possesses an edge-assisted two-level trust computation approach for ensuring the malicious free trust evaluation of IoT devices. The E-TMS aims at removing the false contribution on aggregated trust data. It utilizes the properties of the Eigenvector for identifying compromised IoT devices. The Eigenvector Analysis also helps to avoid false detection. The analysis involves a comparison of all the contributed trust data about every single connected device. A spectral matrix will be generated corresponding to the contributions and the received trust will be scaled based on the obtained spectral values. The absolute sum of obtained values will contain only true contributions. The accurate identification of false data will remove the effect of malicious contributions from the final trust value of a connected IoT device. Since the final trust value calculated by the edge node contains only the trustworthy data, the prediction about the malicious nodes will be accurate. Eventually, the performance of E-TMS has been validated. Throughput and network resilience are higher than the existing system. 2022 G. Nagarajan et al. -
Social Inclusion, Equality, Leadership, and Diversity to Attain Sustainable Development Goal 5 in the Indian Banking Industry
The UN SDG 5 aspires to end all kinds of bigotry and abuse of women, although gender bias still exists in India. Most bank employees are men; few women hold senior positions in Indias banking industry because of the countrys early history of limiting chances for women to enter the profession. The solution to this is to hire women in leadership positions from international locations if the banking sector opens. The development of the banking industry in India relies on the best talent. The banking sector must open its position for multinational expatriates to maintain diversity and bring forth the inclusivity of a multi-talented global workforce. The concept of liberalization, privatization, and globalization in the Indian context is limited. Privatization and globalization can only be anticipated if they have a multicultural workforce within the country and globally. 2022 -
m-quasi-?-Einstein contact metric manifolds
The goal of this article is to introduce and study the characterstics of m-quasi-?-Einstein metric on contact Riemannian manifolds. First, we prove that if a Sasakian manifold admits a gradient m-quasi-?-Einstein metric, then M is ?-Einstein and f is constant. Next, we show that in a Sasakian manifold if g represents an m-quasi-?-Einstein metric with a conformal vector field V, then V is Killing and M is ?-Einstein. Finally, we prove that if a non-Sasakian (?, )-contact manifold admits a gradient m-quasi-?-Einstein metric, then it is N(?)-contact metric manifold or a ?-Einstein. Kumara H.A., Venkatesha V., Naik D.M., 2022. -
Capturing non-financial information in integrated reporting
In the contemporary business scenario, integrated reporting is a transformational form of corporate reporting. Integrated reporting provides material and substantial information about an entitys prospects, governance, strategy and actions that serve as a reflection of social and commercial viability within the holistic environment in which it operates (IIRC, 2013). Thus, in integrated reports, along with financial information the critical non-financial aspects that affect the reputation, performance and sustainability of the firm are also required to be reported by companies. While regulations are instituted for compulsory divulgence of non-financial information as part of annual reports, there is a lot of ambiguity regarding the non- financial items to be included and the manner of reporting. This paper delineates the non-financial capital components for disclosure in integrated reports. It also discusses the current practices of integrated reporting world over, which will help organisations gain clarity in presenting the non-financial items under different heads of non-financial capitals. Copyright 2022 Inderscience Enterprises Ltd. -
A Component Selection Framework of Cohesion and Coupling Metrics
Component-based software engineering is concerned with the development of software that can satisfy the customer prerequisites through reuse or independent development. Coupling and cohesion measurements are primarily used to analyse the better software design quality, increase the reliability and reduced system software complexity. The complexity measurement of cohesion and coupling component to analyze the relationship between the component module. In this paper, proposed the component selection framework of Hexa-oval optimization algorithm for selecting the suitable components from the repository. It measures the interface density modules of coupling and cohesion in a modular software system. This cohesion measurement has been taken into two parameters for analyzing the result of complexity, with the help of low cohesion and high cohesion. In coupling measures between the component of inside parameters and outside parameters. The final process of coupling and cohesion, the measured values were used for the average calculation of components parameter. This paper measures the complexity of direct and indirect interaction among the component as well as the proposed algorithm selecting the optimal component for the repository. The better result is observed for high cohesion and low coupling in component-based software engineering. 2022 CRL Publishing. All rights reserved. -
Cat Swarm Optimization Algorithm Tuned Multilayer Perceptron for Stock Price Prediction
Due to the nonlinear and dynamic nature of stock data, prediction is one of the most challenging tasks in the financial market. Nowadays, soft and bio-inspired computing algorithms are used to forecast the stock price. This article assesses the efficiency of the hybrid stock prediction model using the multilayer perceptron (MLP) and cat swarm optimization (CSO) algorithm. The CSO algorithm is a bio-inspired algorithm inspired by the behavior traits of cats. CSO is employed to find the appropriate value of MLP parameters. Technical indicators calculated from historical data are used as input variables for the proposed model. The model's performance is validated using historical data not used for training. The model's prediction efficiency is evaluated in terms of MSE, MAPE, RMSE and MAE. The model's results are compared with other models optimized by various bio-inspired algorithms presented in the literature to prove its efficiency. The empirical findings confirm that the proposed CSO-MLP prediction model provides the best performance compared to other models taken for analysis. 2022 Polish Academy of Sciences. All rights reserved. -
Optimal procurement and pricing policy for deteriorating items with price and time dependent seasonal demand and permissible delay in payment
In practice, items like food, nursery plants, medicines, etc. are seasonal and deteriorating in nature. For this type of products, permissible delay in payment is a common business policy, which is used to increase in the sell volume and to develop trust in buyer-seller relationship. In this paper, we developed an inventory model for time dependent deteriorating seasonal items with the permission of delay in payment. Shortages are permitted and partially back ordered. Our aim is to find optimal selling price and ordering quantity simultaneously. Concavity of profit function with respect to decision variables has been discussed analytically. A solution procedure followed by a numerical example and sensitivity analysis along with managerial insights are provided. Numerical analysis predicts that delay in payment profit policy is a better decision in order to maximise the profit or in order to get more profit. 2022 Inderscience Enterprises Ltd. -
On ion transport during the electrochemical reaction on plane and GLAD deposited WO3 thin films
Tungsten oxide thin films were deposited on FTO and Corning glass substrates on Plane and GLAD (75) using DC magnetron sputtering and characterized using SEM, XRD, UVVis spectrophotometer, and Electrochemical analyzer systematically. Further, a comparative analysis was carried out in which it was observed that the result of surface morphology for plane showed the denser and GLAD showed nanopillars deposition. The amorphous nature of the sample was evident from XRD analysis. Optical transmittance was between 87% and 81% for both plane and GLAD. The Electrochemical studies showed the diffusion coefficient of H+ ions are more compared to Li+ ions for both plane and GLAD and Coloration efficiency was calculated at the scan rates of 10, 30, and 50 mV/s at the wavelength of 500 to 600 nm. 2021 -
Molecular level investigation on the impact of geometric isomers as fluorinated ligands in SIFSIX MOF for natural gas sweetening
In natural gas (NG), significant amounts of hydrogen sulfide (H2S) and carbon dioxide (CO2) are the most menacing contaminants that cause degradation of the purity of fuel. We considered fluorine-functionalized MOFs and employed cheaper and faster computational simulation techniques to understand the adsorption process. Hence, this includes structural optimization of newly designed fluorine-functionalized MOF with Density Functional Theory (DFT) and further Grand Canonical Monte Carlo (GCMC) simulation at room temperature on those MOFs for understanding in detail the adsorptive separation process on sour gases. However, the main emphasis has been made on the adsorptive separation of H2S gas from sour gas. Eventually, the fluorination of organic ligand in [(SiF6)Ni(1,2-di(pyridin-4-yl)ethyne)2] MOF has resulted in an excellent H2S/CO2 separation performance from NG because of the different geometrical isomers. The cis isomer of 1,2-di(pyridin-4-yl)ethyne as ligand in MOF, i.e., SIFSIX-Ni-dpe-3-cis, shows a high CO2 affinity than H2S; on the contrary, the trans isomer of 1,2-di(pyridin-4-yl)ethyne as ligand in MOF, i.e., SIFSIX-Ni-dpe-3-trans, has H2S selective over CO2 and CH4. So, the resulting affinity variation indicates that structural variation by the stereochemistry of ligands in MOF plays a significant role in NG purification, which is further validated through detailed molecular simulation analysis. 2022 Taylor & Francis Group, LLC. -
Significance of aggregation of nanoparticles, activation energy, and Hall current to enhance the heat transfer phenomena in a nanofluid: a sensitivity analysis
The mechanisms involved in the heat transport enhancement due to suspended nanoparticles are still unclear. Many studies have shown that nanoparticle aggregation is a key aspect of increasing nanofluid thermal conductivity. Nevertheless, the fractal dimension of nanoparticle aggregation will have a substantial impact on the nanofluids thermal conductivity. Therefore, the present study examines the influence of nanoparticle aggregation and Hall current on the nanoliquid flow past a spinning disk. The importance of Arrhenius activation energy is also investigated. A revised correlation for the aggregation mechanism is attained using the modified Krieger-Dougherty model (KD-model) and the Maxwell-Bruggeman model (MB-model). A similarity technique and finite difference method are used to construct the numerical solutions for the boundary value problem. The 2D plots and 3D surface plots are shown to investigate how different key parameters impact the velocity, temperature, and concentration fields. The study highlights that the Hall current has a beneficial effect on the fluid flow field. Higher activation energy leads to a productive chemical reaction which, improves the concentration layer. The thermal boundary for NPs aggregationis superior than to that withoutNPs aggregation, and the suspension of nanoparticles will have a favorable impact on the thermal layer. 2022 Informa UK Limited, trading as Taylor & Francis Group.