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An abundance of techniques has been presented so forth for waste classification but, they deliver inefficient results with low accuracy. Their achievement on various repositories is different and also, there is insufficiency of high-scale databases for training. The purpose of the study is to provide high security.

In this research, optimization-assisted federated learning (FL) is introduced for thermoplastic waste segregation and classification. The deep learning (DL) network trained by Archimedes Henry gas solubility optimization (AHGSO) is used for the classification of plastic and resin types. The deep quantum neural networks (DQNN) is used for first-level classification and the deep max-out network (DMN) is employed for second-level classification. This developed AHGSO is obtained by blending the features of Archimedes optimization algorithm (AOA) and Henry gas solubility optimization (HGSO). The entities included in this approach are nodes and servers. Local training is carried out depending on local data and updations to the server are performed. Then, the model is aggregated at the server. Thereafter, each node downloads the global model and the update training is executed depending on the downloaded global and the local model till it achieves the satisfied condition. Finally, local update and aggregation at the server is altered based on the average method. The Data tag suite (DATS_2022) dataset is used for multilevel thermoplastic waste segregation and classification.

By using the DQNN in first-level classification the designed optimization-assisted FL has gained an accuracy of 0.930, mean average precision (MAP) of 0.933, false positive rate (FPR) of 0.213, loss function of 0.211, mean square error (MSE) of 0.328 and root mean square error (RMSE) of 0.572. In the second level classification, by using DMN the accuracy, MAP, FPR, loss function, MSE and RMSE are 0.932, 0.935, 0.093, 0.068, 0.303 and 0.551.

The multilevel thermoplastic waste segregation and classification using the proposed model is accurate and improves the effectiveness of the classification.

Road passenger transportation faces a global challenge of reducing environmental pollution and greenhouse gas emissions because of the vehicle weight increases needed to enhance passenger safety and comfort. This paper aims to present a preliminary mechanical design evaluation of the Wikispeed Car (with a focus on body bending, body torsion and body crash) to assess light-weighting implications and improve the vehicle’s environmental performance without compromising safety.

For this research, finite element analysis (FEA) was performed to examine the Wikispeed chassis for light-weighting opportunities in three key aspects of the vehicle’s design, namely, for body bending the rockers (or longitudinal tubes), for body torsion (again on the rockers but also the chassis as a whole) and for crash safety – on the frontal crash structure. A two-phase approach was adopted, namely, in phase one, a 3D CAD geometry was generated and in phase, two FEA was generated. The combination of analysis results was used to develop the virtual model using FEA tools, and the model was updated based on the correlation process.

The research revealed that changing the specified material Aluminium Alloy 6061-T651 to Magnesium EN-MB10020 allows vehicle mass to be reduced by an estimated 110 kg, thus producing a concomitant 10 per cent improvement in fuel economy. The initial results imply that the current beam design made from magnesium would perform worst during a crash as the force required to buckle the beam is the lowest (between 95.2 kN and 134 kN). Steel has the largest bandwidth of force required for buckling and also requires the largest force for buckling (between 317 kN and 540 kN).

This is the first study of its kind to compare and contrast between material substitution and its impact upon Wikispeed car safety and performance.

Blockchain technology (BT) is a relatively new technological innovation in all industries, including the construction industry, that is used to improve supply chain management. Therefore, this study assesses the drivers for the implementation of BT in the construction supply chain management in Nigeria.

This study used a quantitative research approach, with a questionnaire survey administered to professionals in the Nigerian construction industry using the snowball sampling method, yielding 155 respondents. The collected data were analysed using descriptive and exploratory factor analysis (EFA) while Cronbach’s alpha was used to evaluate the reliability.

The analysis revealed that all the identified drivers ranked higher than the average mean item score, with level of awareness of the new technology and data management ranking topmost. The identified drivers were clustered into five categories using EFA: technological driver, social-economic driver, management driver, transparency and security driver and information driver.

This research was carried out in the Southwestern region which is one of the six geo-political zones in Nigeria using a cross-sectional survey method.

The findings will be extremely useful to both professionals and practitioners in the Nigerian construction industry in gaining knowledge about the potential drivers to the implementation of BT in construction supply chain management.

The research categorized the drivers into technological, social-economic, management, transparency and security and information driver. It also identified that level of awareness of BT as the major driver in the implementation of BT in construction supply chain management.

Vehicle weight reduction represents a viable means of meeting tougher regulatory requirements designed to reduce fuel consumption and control greenhouse gas emissions. This paper aims to present an empirical and comparative analysis of lightweight magnesium materials used to replace conventional steel in passenger vehicles with internal combustion engines. The very low density of magnesium makes it a viable material for lightweighting given that it is lighter than aluminium by one-third and steel by three-fourth.

A structural evaluation case study of the “open access” Wikispeed car was undertaken. This included an assessment of material design characteristics such as bending stiffness, torsional stiffness and crashworthiness to evaluate whether magnesium provides a better alternative to the current usage of aluminium in the automotive industry.

The Wikispeed car had an issue with the rocker beam width/thickness (b/t) ratio, indicating failure in yield instead of buckling. By changing the specified material, Aluminium Alloy 6061-T651 to Magnesium EN-MB10020, it was revealed that vehicle mass could be reduced by an estimated 110 kg, in turn improving the fuel economy by 10 per cent. This, however, would require mechanical performance compromise unless the current design is modified.

This is the first time that a comparative analysis of material substitution has been made on the Wikispeed car. The results of such work will assist in the lowering of harmful greenhouse gas emissions and simultaneously augment fuel economy.

This research work aims to determine the maximum load a thermoplastic gear can withstand without the occurrence of extended contact. The extended contact of polymer gears is usually overlooked in basic design calculations, although it considerably affects the gear's load-carrying ability. Although various researchers highlighted the phenomenon, an extensive investigation of the extended contact behaviour is limited. Hence the work aims to investigate the premature and extended contact behaviour of thermoplastic gears and its effect in the gear kinematics, bending stiffness, stresses induced and the roll angle subtended by the gear pair.

The work uses finite element method to perform quasi-static two-dimensional analysis of the meshing gear teeth. The FE model was developed in AutoCAD and analysed using ANSYS 19.1 simulation package. A three-dimensional gear model with all the teeth is computationally intensive for solving a static analysis problem. Hence, planar analysis with a reduced number of teeth is considered to reduce the computational time and difficulty.

The roll angle subtended at the centre by the path of approach is higher than the path of recess because of the increased load sharing. The contact stress profile followed a unique R-F-R-F pattern in the premature and extended contact regions due to the driven tip-driver flank surface contact. A non-dimensional parameter was formulated correlating the young's modulus, the load applied and deflection induced that can be utilised to predict the occurrence of premature and extended contact in thermoplastic gears.

The gear rating standards for polymer gears are formulated from the conventional metal gears which does not include the effect of gear tooth deflection. The work attempts to explain the gear tooth deflection for various standard thermoplastics and its effect in kinematics. Likewise, a new dimensionless number was introduced to predict the extended contact that will help in appropriate selection of load reducing the possibility of wear.

Consumers are increasingly choosing social media over other channels and mechanisms for grievance redressal. However, not all social media grievances elicit a response from businesses. Hence, in this research the authors aim to explore the effect of the complainant's social characteristics and the complaint's social and content characteristics on the likelihood of receiving a response to a grievance from the business on social media.

The authors build a conceptual model and then empirically test it to explore the effect of the complainant's characteristics and the complaint's characteristics on the likelihood of response from a business on social media. The authors use data of consumer grievances received by an Indian airline operator on Twitter during two time periods – the first corresponding to lockdown during Covid-19 pandemic, and the second corresponding to the resumption of business as usual following these lockdowns. The authors use logistic regression and the hazard rate model to model the likelihood of response and the response delay, respectively, for social media customer grievances.

Complainants with high social influence are not more likely to get a response for their grievances on social media. While tagging other individuals and business accounts in a social media complaint has negative effect on the likelihood of business response in both the time periods, the effect of tagging regulatory bodies on the likelihood of response was negative only in the Covid-19 lockdown period. The readability and valence of a complaint were found to positively affect the likelihood of response to a social media grievance. However, the effect of valence was significant only in lockdown period.

This research offers insights on what elicits responses from a service provider to consumers' grievances on social media platforms. The extant literature is a plenty on how firms should be engaging consumers on online media and how online communities should be built, but scanty on grievance redressal on social media. This research is, therefore, likely to be useful to service providers who are inclined to improve their grievance handling mechanisms, as well as, to regulatory authorities and ombudsmen.

The study aims to investigate magnetohydrodynamics thermal convection energy transference and entropy production in an open chamber saturated with ferrofluid having an isothermal solid block.

Analysis of thermal convection phenomenon was performed for an open chamber saturated with a nanofluid having an isothermal solid unit placed inside the cavity with various aspect ratios. The left border temperature is kept at T_c. An external cooled nanofluid of fixed temperature T_c penetrates into the domain from the right open border. The nanofluid circulation is Newtonian, incompressible, and laminar. The uniform magnetic field of strength B at the tilted angle of γ is applied. The finite volume technique is used to work out the non-linear equations of liquid motion and energy transport. For Rayleigh number (Ra=1e+7), numerical simulations were executed for varying the solid volume fractions of the nanofluid (ϕ = 0.01–0.04), the aspect ratios of a solid body (A_s = 0.25–4), the Hartmann number (Ha = 0–100), the magnetic influence inclination angle (γ = 0–π/2) and the non-dimensional temperature drop (Ω = 0.001–0.1) on the liquid motion, heat transference and entropy production.

Numerical outcomes are demonstrated by using isolines of temperature and stream function, profiles of mean Nusselt number and entropy generations. The results indicate that the entropy generation rate and mean Nu can be decreased with an increase in Ha. The inner solid block of A_s = 0.25 reflects the maximum heat transfer rate in comparison with other considered blocks. The addition of nano-sized particles results in a growth of energy transport and mean entropy generations.

An efficient computational technique has been developed to solve natural convection problem for an open chamber. The originality of this research is to scrutinize the convective transport and entropy production in an open domain with inner body. The outcomes would benefit scientists and engineers to become familiar with the investigation of convective energy transference and entropy generation in open chambers with inner bodies, and the way to predict the energy transference strength in the advanced engineering systems.

The purpose of this paper was to present a simple and convenient technology to produce the electronic-grade CuO. The prepared electronic-grade CuO fully meets the demands of industrial production of high density interconnect (HDI).

A new method termed as open-circuit potential-time technology is proposed to measure the dissolution time of CuO in plating solution. X-ray diffraction (XRD) scanning electron microscopy (SEM) and inductively coupled plasma-atomic emission spectroscopy (ICP-AES) were used to characterize the prepared CuO. Solder shock and reflow tests were carried out to examine the Cu deposits.

All aspects of the prepared CuO meet the demands of printed circuit board (PCB) industry.

A simple and convenient technology was presented to produce the electronic-grade CuO. A new method was proposed to determine the dissolution time of CuO in plating solution.

The purpose of this study is to refine the microstructure and improve the corrosion behaviour of aluminium alloy AA5083 by subjecting it to friction stir processing (FSP).

FSP trials are conducted as per central composite design, by varying tool rotation speed, tool traverse speed and shoulder diameter at three levels. The microstructure is examined and the hardness is measured for both the base material and the processed workpieces. The corrosion behaviour of the base material and processed workpieces is studied using potentiodynamic polarization technique for three different testing temperatures, and the corrosion current and corrosion rate are calculated.

The results reveal that FSP refined the grains, dispersed secondary phases, increased the hardness and improved the corrosion resistance of most of the friction stir processed specimens than the base material at all the three testing temperatures. Grain refinement and fine dispersion of ß phase improves the hardness and corrosion resistance of most of the FSPed specimens. However partial dissolution of ß phase decreases the hardness in some of the specimens. Most of the FSPed specimens displayed more positive potential than the base material at all the testing temperatures representing a higher nobility than the base material, as a result of fine dispersion of secondary phase particles in the matrix. Large pits formed on the surface of the base specimen indicating a higher corrosion rate at all three testing temperatures. The SEM image of FSPed specimens reveals the occurrence of very few pits and minimal corrosion products on the surface, which indicates lower corrosion rate.

The corrosion mechanism of the friction stir-processed AA5083 specimens is found to be a combination of activation and concentration polarization.

This study aims to propose and evaluate a simpler technology to reduce harmful emissions from diesel engines by preheating the fuel before injection into the combustion chamber.

A spring-type heater coil with suitable insulation was installed on the high-pressure fuel pipeline to preheat the fuel. Experiments were conducted at a standard injection timing of 23° before top dead center, across 25%, 50%, 75% and 100% of full load. The fuel was preheated to 100°C, 160°C and 220°C for each engine load. Engine performance, emissions and thermal balance were analyzed for preheated and unheated diesel.

This study found that preheated fuel improved combustion characteristics, with higher pressure rise and net heat release rates during diffusion combustion. Brake thermal efficiency increased by 8.75% to 10.58%, and brake-specific fuel consumption decreased by up to 9.18%. Emissions significantly dropped: nitrogen oxides by up to 51%, smoke density by up to 63%, carbon monoxide by up to 67% and hydrocarbon by up to 25%. Thermal balance results showed increased useful work and reduced heat losses, particularly at higher preheating temperatures.

This research presents a novel and simpler approach to enhancing diesel engine performance and reducing emissions by preheating the fuel. The findings demonstrate significant improvements in efficiency and substantial reductions in harmful emissions, highlighting the potential of preheated fuel as a viable solution for cleaner diesel engine operation.