Jyothi N. and Rekha Patil
This study aims to develop a trust mechanism in a Vehicular ad hoc Network (VANET) based on an optimized deep learning for selfish node detection.
Abstract
Purpose
This study aims to develop a trust mechanism in a Vehicular ad hoc Network (VANET) based on an optimized deep learning for selfish node detection.
Design/methodology/approach
The authors built a deep learning-based optimized trust mechanism that removes malicious content generated by selfish VANET nodes. This deep learning-based optimized trust framework is the combination of the Deep Belief Network-based Red Fox Optimization algorithm. A novel deep learning-based optimized model is developed to identify the type of vehicle in the non-line of sight (nLoS) condition. This authentication scheme satisfies both the security and privacy goals of the VANET environment. The message authenticity and integrity are verified using the vehicle location to determine the trust level. The location is verified via distance and time. It identifies whether the sender is in its actual location based on the time and distance.
Findings
A deep learning-based optimized Trust model is used to detect the obstacles that are present in both the line of sight and nLoS conditions to reduce the accident rate. While compared to the previous methods, the experimental results outperform better prediction results in terms of accuracy, precision, recall, computational cost and communication overhead.
Practical implications
The experiments are conducted using the Network Simulator Version 2 simulator and evaluated using different performance metrics including computational cost, accuracy, precision, recall and communication overhead with simple attack and opinion tampering attack. However, the proposed method provided better prediction results in terms of computational cost, accuracy, precision, recall, and communication overhead than other existing methods, such as K-nearest neighbor and Artificial Neural Network. Hence, the proposed method highly against the simple attack and opinion tampering attacks.
Originality/value
This paper proposed a deep learning-based optimized Trust framework for trust prediction in VANET. A deep learning-based optimized Trust model is used to evaluate both event message senders and event message integrity and accuracy.
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João Paulo Augusto Eça, Wilson Tarantin Júnior and Maurício Ribeiro do Valle
This paper aims to analyze whether a relationship exists between the debt structure concentration and investment–cash flow sensitivity of Brazilian companies.
Abstract
Purpose
This paper aims to analyze whether a relationship exists between the debt structure concentration and investment–cash flow sensitivity of Brazilian companies.
Design/methodology/approach
The study is based on a sample of 500 Brazilian firms (337 unlisted and 163 listed) in the 10-year period from 2010 to 2019 analyzed according to the investment–cash flow sensitivity model.
Findings
The results show evidence that companies with more concentrated debt structures tend to have lower investment sensitivity to internal cash flow. In other words, firms with a greater concentration of debts tend to have less investment–cash flow sensitivity. In general, the results are robust to (1) variation of the debt concentration proxy and the independent variable; (2) the control of fixed effects in different dimensions and (3) use of estimator for endogeneity treatment, i.e. two-stage least squares (2SLS) and generalized method of moments (GMM).
Originality/value
Various studies have investigated whether specific financing sources reduce financial constraints, but few have addressed the relationship between debt concentration and these constraints. Besides this, to the best of the authors’ knowledge, no previous study has investigated the mentioned relationship in a sample of unlisted firms. This analysis is relevant since the effects of financial constraints tend to be stronger on companies that have restricted access to the capital market.
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Marta Aurelia Horianski, Juan Manuel Peralta and Luis Alberto Brumovsky
The purpose of this study was to analyze the influence of epichlorohydrin (ECH) concentration and reaction time on the food-grade resistant starch production and its pasting…
Abstract
Purpose
The purpose of this study was to analyze the influence of epichlorohydrin (ECH) concentration and reaction time on the food-grade resistant starch production and its pasting properties by using native cassava starch of Misiones-Argentina origin.
Design/methodology/approach
Cassava starch was modified using ECH (0.30 and 0.15 per cent) during 4 or 8 h. Digestibility was evaluated by determining resistant starch as total dietary fiber. Pasting properties and the cross-linking degree were studied using a micro-viscoamylograph (Brabender).
Findings
Resistant starch content was not influenced by ECH concentration and reaction time. Cross-linking was detected at higher reaction times (8 h) and ECH concentrations (0.30 per cent), where a decrease in viscosity peaks by more than 80 per cent was observed. Both pasting temperature and breakdown were increased, whereas a decrease in retrogradation was detected.
Practical implications
Starches can be suitable for different food applications. This is because of the ability to modify its pasting properties and the invariability of the in vitro digestibility of cassava starch as a result of using ECH (at concentrations approved by local and regional legislation) and reaction times of 4 and 8 h.
Originality/value
Information related to the modification of cassava starch using ECH is scarce or not available nowadays in literature.
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Keywords
Iskandar Waini, Umair Khan, Aurang Zaib, Anuar Ishak and Ioan Pop
This study aims to investigate the micropolar fluid flow through a moving flat plate containing CoFe2O4-TiO2 hybrid nanoparticles with the substantial influence of thermophoresis…
Abstract
Purpose
This study aims to investigate the micropolar fluid flow through a moving flat plate containing CoFe2O4-TiO2 hybrid nanoparticles with the substantial influence of thermophoresis particle deposition and viscous dissipation.
Design/methodology/approach
The partial differential equations are converted to the similarity equations of a particular form through the similarity variables. Numerical outcomes are computed by applying the built-in program bvp4c in MATLAB. The process of flow, heat and mass transfers phenomena are examined for several physical aspects such as the hybrid nanoparticles, micropolar parameter, the thermophoresis particle deposition and the viscous dissipation.
Findings
The friction factor, heat and mass transfer rates are higher with an increment of 1.4%, 2.2% and 1.4%, respectively, in the presence of the hybrid nanoparticles (with 2% volume fraction). However, they are declined because of the rise of the micropolar parameter. The imposition of viscous dissipation reduces the heat transfer rate, significantly. Meanwhile, thermophoresis particle deposition boosts the mass transfer. Multiple solutions are developed for a certain range of physical parameters. Lastly, the first solution is shown to be stable and reliable physically.
Originality/value
As far as the authors have concerned, no work on thermophoresis particle deposition of hybrid nanoparticles on micropolar flow through a moving flat plate with viscous dissipation effect has been reported in the literature. Most importantly, this current study reported the stability analysis of the non-unique solutions and, therefore, fills the gap of the study and contributes to new outcomes in this particular problem.
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Mohanaphriya US and Tanmoy Chakraborty
This research focuses on the controlling irreversibilities in a radiative, chemically reactive electromagnetohydrodynamics (EMHD) flow of a nanofluid toward a stagnation point…
Abstract
Purpose
This research focuses on the controlling irreversibilities in a radiative, chemically reactive electromagnetohydrodynamics (EMHD) flow of a nanofluid toward a stagnation point. Key considerations include the presence of Ohmic dissipation, linear thermal radiation, second-order chemical reaction with the multiple slips. With these factors, this study aims to provide insights for practical applications where thermal management and energy efficiency are paramount.
Design/methodology/approach
Lie group transformation is used to revert the leading partial differential equations into nonlinear ODE form. Hence, the solutions are attained analytically through differential transformation method-Padé and numerically using the Runge–Kutta–Fehlberg method with shooting procedure, to ensure the precise and reliable determination of the solution. This dual approach highlights the robustness and versatility of the methods.
Findings
The system’s entropy generation is enhanced by incrementing the magnetic field parameter (M), while the electric field (E) and velocity slip parameters (ξ) control its growth. Mass transportation irreversibility and the Bejan number (Be) are significantly increased by the chemical reaction rate (Cr). In addition, there is a boost in the rate of heat transportation by 3.66% while 0.05⩽ξ⩽0.2; meanwhile for 0.2⩽ξ⩽1.1, the rate of mass transportation gets enhanced by 12.87%.
Originality/value
This paper presents a novel approach to analyzing the entropy optimization in a radiative, chemically reactive EMHD nanofluid flow near a stagnation point. Moreover, this research represents a significant advancement in the application of analytical techniques, complemented by numerical approaches to study boundary layer equations.
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Ravi Tej D, Sri Kavya Ch K and Sarat K. Kotamraju
The purpose of this paper is to improve energy efficiency and further reduction of side lobe level the algorithm proposed is firework algorithm. In this paper, roused by the…
Abstract
Purpose
The purpose of this paper is to improve energy efficiency and further reduction of side lobe level the algorithm proposed is firework algorithm. In this paper, roused by the eminent swarm conduct of firecrackers, a novel multitude insight calculation called fireworks algorithm (FA) is proposed for work enhancement. The FA is introduced and actualized by mimicking the blast procedure of firecrackers. In the FA, two blast (search) forms are utilized and systems for keeping decent variety of sparkles are likewise all around planned. To approve the presentation of the proposed FA, correlation tests were led on nine benchmark test capacities among the FA, the standard PSO (SPSO) and the clonal PSO (CPSO).
Design/methodology/approach
The antenna arrays are used to improve the capacity and spectral efficiency of wireless communication system. The latest communication systems use the antenna array technology to improve the spectral efficiency, fill rate and the energy efficiency of the communication system can be enhanced. One of the most important properties of antenna array is beam pattern. A directional main lobe with low side lobe level (SLL) of the beam pattern will reduce the interference and enhance the quality of communication. The classical methods for reducing the side lobe level are differential evolution algorithm and PSO algorithm. In this paper, roused by the eminent swarm conduct of firecrackers, a novel multitude insight calculation called fireworks algorithm (FA) is proposed for work enhancement. The FA is introduced and actualized by mimicking the blast procedure of firecrackers. In the FA, two blast (search) forms are utilized and systems for keeping decent variety of sparkles are likewise all around planned. To approve the presentation of the proposed FA, correlation tests were led on nine benchmark test capacities among the FA, the standard PSO (SPSO) and the clonal PSO (CPSO). It is demonstrated that the FA plainly beats the SPSO and the CPSO in both enhancement exactness and combination speed. The results convey that the side lobe level is reduced to −34.78dB and fill rate is increased to 78.53.
Findings
Samples including 16-element LAAs are conducted to verify the optimization performances of the SLL reductions. Simulation results show that the SLLs can be effectively reduced by FA. Moreover, compared with other benchmark algorithms, fireworks has a better performance in terms of the accuracy, the convergence rate and the stability.
Research limitations/implications
With the use of algorithms radiation is prone to noise one way or other. Even with any optimizations we cannot expect radiation to be ideal. Power dissipation or electro magnetic interference is bound to happen, but the use of optimization algorithms tries to reduce them to the extent that is possible.
Practical implications
16-element linear antenna array is available with latest versions of Matlab.
Social implications
The latest technologies and emerging developments in the field of communication and with exponential growth in users the capacity of communication system has bottlenecks. The antenna arrays are used to improve the capacity and spectral efficiency of wireless communication system. The latest communication systems use the antenna array technology which is to improve the spectral efficiency, fill rate and the energy efficiency of the communication system can be enhanced.
Originality/value
By using FA, the fill rate is increased to 78.53 and the side lobe level is reduced to 35dB, when compared with the bench mark algorithms.
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Keywords
Laura Lucantoni, Sara Antomarioni, Filippo Emanuele Ciarapica and Maurizio Bevilacqua
The Overall Equipment Effectiveness (OEE) is considered a standard for measuring equipment productivity in terms of efficiency. Still, Artificial Intelligence solutions are rarely…
Abstract
Purpose
The Overall Equipment Effectiveness (OEE) is considered a standard for measuring equipment productivity in terms of efficiency. Still, Artificial Intelligence solutions are rarely used for analyzing OEE results and identifying corrective actions. Therefore, the approach proposed in this paper aims to provide a new rule-based Machine Learning (ML) framework for OEE enhancement and the selection of improvement actions.
Design/methodology/approach
Association Rules (ARs) are used as a rule-based ML method for extracting knowledge from huge data. First, the dominant loss class is identified and traditional methodologies are used with ARs for anomaly classification and prioritization. Once selected priority anomalies, a detailed analysis is conducted to investigate their influence on the OEE loss factors using ARs and Network Analysis (NA). Then, a Deming Cycle is used as a roadmap for applying the proposed methodology, testing and implementing proactive actions by monitoring the OEE variation.
Findings
The method proposed in this work has also been tested in an automotive company for framework validation and impact measuring. In particular, results highlighted that the rule-based ML methodology for OEE improvement addressed seven anomalies within a year through appropriate proactive actions: on average, each action has ensured an OEE gain of 5.4%.
Originality/value
The originality is related to the dual application of association rules in two different ways for extracting knowledge from the overall OEE. In particular, the co-occurrences of priority anomalies and their impact on asset Availability, Performance and Quality are investigated.
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Latifah Falah Alharbi, Umair Khan, Aurang Zaib, S.H.A.M. Shah, Anuar Ishak and Taseer Muhammad
Thermophoresis deposition of particles is a crucial stage in the spread of microparticles over temperature gradients and is significant for aerosol and electrical technologies. To…
Abstract
Purpose
Thermophoresis deposition of particles is a crucial stage in the spread of microparticles over temperature gradients and is significant for aerosol and electrical technologies. To track changes in mass deposition, the effect of particle thermophoresis is therefore seen in a mixed convective flow of Williamson hybrid nanofluids upon a stretching/shrinking sheet.
Design/methodology/approach
The PDEs are transformed into ordinary differential equations (ODEs) using the similarity technique and then the bvp4c solver is employed for the altered transformed equations. The main factors influencing the heat, mass and flow profiles are displayed graphically.
Findings
The findings imply that the larger effects of the thermophoretic parameter cause the mass transfer rate to drop for both solutions. In addition, the suggested hybrid nanoparticles significantly increase the heat transfer rate in both outcomes. Hybrid nanoparticles work well for producing the most energy possible. They are essential in causing the flow to accelerate at a high pace.
Practical implications
The consistent results of this analysis have the potential to boost the competence of thermal energy systems.
Originality/value
It has not yet been attempted to incorporate hybrid nanofluids and thermophoretic particle deposition impact across a vertical stretching/shrinking sheet subject to double-diffusive mixed convection flow in a Williamson model. The numerical method has been validated by comparing the generated numerical results with the published work.
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The current study aims to investigate the mediating role of executive stock options in the nonlinear relationship between financial constraints and research and development (R&D…
Abstract
Purpose
The current study aims to investigate the mediating role of executive stock options in the nonlinear relationship between financial constraints and research and development (R&D) investment through two measures of financial constraints.
Design/methodology/approach
This study is based on a sample of 90 French firms for the period extending from 2008 to 2020. The authors employ a panel threshold method to analyze whether the impact of financial constraints on R&D investment depends on the level of financial constraints or not.
Findings
Using SA index (Hadlock and Pierce, 2010) and FCP index (Schauer et al., 2019) as measures of financial constraints, the authors demonstrate that the relationship between financial constraints and R&D investment is nonlinear. Moreover, the authors find that executive stock options mediate partially the relationship between financial constraints and R&D investment. More specifically, the authors show that stock options could play two roles depending on the level of the financial constraints; inconsistent mediation for firms with low/medium level of financial constraints and partial mediation for highly constrained firms.
Originality/value
This paper is the first to the best of the authors' knowledge to investigate the nonlinear relationship between financial constraints and R&D investment as well as the mediating role of executive stock option using dynamic panel threshold models.
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Tianjiao Li, Jing Ma, Guangwen Li and Xiaowei Chen
This study aims to replace petroleum-based lubricating oils with sustainable biomaterials, addressing issues associated with existing alternatives, such as poor performance, high…
Abstract
Purpose
This study aims to replace petroleum-based lubricating oils with sustainable biomaterials, addressing issues associated with existing alternatives, such as poor performance, high cost and limited availability.
Design/methodology/approach
The transformation of agricultural waste cardanol, a nonedible vegetable oil that is abundantly available, into green cardanyl acetate (CA) biolubricating ester oil. The potential of CA as a base stock for lubricants is validated by assessing its lubrication performance.
Findings
CA exhibited a higher viscosity index, flash point and thermal stability than commercially available mineral-based (CTL3, coal-to-liquid) and synthetic (PAO2, poly-alpha-olefin) lubricant base stocks. Moreover, CA exhibits excellent anticorrosivity properties as well as PAO2 and CTL3. The tribological properties of CA were evaluated, and the results show that CA exhibits a smaller average wear scar diameter (WSD) of 0.54 mm than that of PAO2 (0.85 mm) and CTL3 (0.90 mm). In extreme pressure tests, acylated CA demonstrated the highest last nonseizure load capacity at 510 N, outperforming commercial CTL3 (491 N) and PAO2 (412 N). All results demonstrate that CA displays an excellent series of base stock properties.
Originality/value
The novelty of this work lies in the utilization of renewable agricultural waste, cashew nut shell liquid, to produce a high-value biolubricant as an alternative to commercial fossil-based lubricants. The renewable nature, low cost, and large-scale availability of raw materials pave a new path for the production and application of biolubricants, showcasing the immense potential of converting agricultural waste into high-value products.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0064/