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The purpose of this paper is to study the fault diagnosis of internal combustion (IC) engine gearbox using vibration signals with signal processing and machine learning (ML) techniques.

Vibration signals from the gearbox are acquired for healthy and induced faulty conditions of the gear. In this study, 50% tooth fault and 100% tooth fault are chosen as gear faults in the driver gear. The acquired signals are processed and analyzed using signal processing and ML techniques.

The obtained results show that variation in the amplitude of the crankshaft rotational frequency (CRF) and gear mesh frequency (GMF) for different conditions of the gearbox with various load conditions. ML techniques were also employed in developing the fault diagnosis system using statistical features. J48 decision tree provides better classification accuracy about 85.1852% in identifying gearbox conditions.

The proposed approach can be used effectively for fault diagnosis of IC engine gearbox. Spectrum and continuous wavelet transform (CWT) provide better information about gear fault conditions using time–frequency characteristics.

In this paper, experiments are conducted on real-time running condition of IC engine gearbox while considering combustion. Eddy current dynamometer is attached to output shaft of the engine for applying load. Spectrum, cepstrum, short-time Fourier transform (STFT) and wavelet analysis are performed. Spectrum, cepstrum and CWT provide better information about gear fault conditions using time–frequency characteristics. ML techniques were used in analyzing classification accuracy of the experimental data to detect the gearbox conditions using various classifiers. Hence, these techniques can be used for detection of faults in the IC engine gearbox and other reciprocating/rotating machineries.

The purpose of this paper is to study the thermal and mechanical disturbances in a piezo-electric microstretch thermoelastic medium due to the presence of ultra-short laser pulse as input heat source.

The medium is subjected to normal force, tangential force and thermal source. The solution of the problems is developed in terms of normal modes. Mathematical expressions have been obtained for normal stress, tangential stress, microstress, dielectric displacement vector and temperature change.

The numerically computed results are shown graphically. The effect of time and laser radius on temperature distribution is also shown graphically and comparison to theoretical results has been discussed. A mathematical model has been developed for the system of equations and various stress quantities have been analyzed. Some computer programs have also been written for this study. Two particular cases are also derived from the present investigation.

The effect of laser heat source is studied in piezo-electric microstretch thermoelastic medium. It is observed from the figures that the laser heat source has significant role on the values of coupled tangential stress.

The purposes of this paper are (1) to explore the overall development of AI technologies and applications that have been demonstrated to be fundamentally important in the healthcare industry, and their related commercialized products and (2) to identify technologies with promise as the basis of useful applications and profitable products in the AI-healthcare domain.

This study adopts a technology-driven technology roadmap approach, combined with natural language processing (NLP)-based patents analysis, to identify promising and potentially profitable existing AI technologies and products in the domain of AI healthcare.

Robotics technology exhibits huge potential in surgical and diagnostics applications. Intuitive Surgical Inc., manufacturer of the Da Vinci robotic system and Ion robotic lung-biopsy system, dominates the robotics-assisted surgical and diagnostic fields. Diagnostics and medical imaging are particularly active fields for the application of AI, not only for analysis of CT and MRI scans, but also for image archiving and communications.

This study is a pioneering attempt to clarify the interrelationships of particular promising technologies for application and related products in the AI-healthcare domain. Its findings provide critical information about the patent activities of key incumbent actors, and thus offer important insights into recent and current technological and product developments in the emergent AI-healthcare sector.

The purpose of this study is to study the mechanical, tribological and electrical properties of the copper-graphene (Cu-Gn) composites fabricated by a novel rapid tooling technique consist of three-dimensional printing and ultrasonic-assisted pressureless sintering (UAPS).

Four different Cu-Gn compositions with 0.25, 0.5, 1 and 1.5 per cent of graphene were fabricated using an amalgamation of three-dimensional printing and UAPS. The polymer 3d printed parts were used to prepare mould cavity and later the UAPS process was used to sinter Cu-Gn powder to acquire free-form shape. The density, hardness, wear rate, coefficient of friction and electrical conductivity were evaluated for the different compositions of graphene and compared with the pure copper. Besides, the comparison was performed with the conventional method.

Cu-Gn composites revealed excellent wear properties due to higher hardness, and the lubrication provided by the graphene. The electrical conductivity of the fabricated Cu-Gn composites started increasing initially but decreased afterwards with increasing the content of graphene. The UAPS fabricated composites outperformed the conventional method manufactured samples with better properties such as density, hardness, wear rate, coefficient of friction and electrical conductivity due to homogeneous mixing of metal particles and graphene.

The fabrication of Cu-Gn composite freeform shapes was found to be difficult using conventional methods. The novel technique using a combination of polymer three-dimensional printing and UAPS as rapid tooling was introduced for the fabrication of freeform shapes of Cu-Gn composites and mechanical, tribological and electrical properties were studied. The method can be used to fabricate optimized complex Cu-Gn structures with improved wear and electrical applications.

The purpose of this paper is to deal with the study of plane waves and fundamental solution in a modified couple stress generalized thermoelastic solid with three-phase-lag (TPL) model of thermoelasticity.

It is found that for two-dimensional model, there exists two longitudinal waves, namely, longitudinal wave (P-wave), thermal wave (T-wave), and a set of coupled transverse waves (SV1 and SV2 waves). In addition, the fundamental solution for the system of differential equations for steady oscillations in terms of elementary functions has been constructed. Some properties of fundamental solution are also established. Various particular cases of interest are also deduced from the present investigations and compared with the known results.

The phase velocity, attenuation coefficient, specific loss and penetration depth are computed numerically and presented graphically to see the effect of TPL model, dual-phase-lag (DPL) model and GN-III model in the presence of couple stress parameter.

The results are compared with couple stress TPL model, couple stress DPL model and GN-III model.

The authors examine network features such as connectivity, centrality, adjacency matrices, closeness and betweenness measures through a variety of indicators. The results of the study indicate that over time there is a tendency for markets to integrate and segment due to various factors such as pandemics, financial crises, global trade relations and international investments.

This paper employs a visualized network technique to study the dynamics of integration and comovements in global equity markets of emerging economies. Daily closing prices of stock market indices of 24 countries from January 2013 to July 2020 are used to construct a minimum spanning tree network (MSTN) and graph network (GN).

The authors identify India and China as global power hubs and clusters among the emerging economies. India and Bangladesh serve as bridging countries connecting to various other clusters. Bosnia serves as a center in the European region owing to Bosnia's trade relations with neighboring countries. Although Brazil has witnessed the worst recession in the early years of the decade, Brazil has risen to be a central cluster among the Latin American countries. Finally, the authors find that African countries tend to form links with the rest of the world rather than with economies within the Africa continent.

This is the pioneering study that uses network models such as MSTN and GN supplemented with measures of centrality and connectivity to study financial market integration in emerging countries. Against this backdrop, this paper aims to work on a network visualization strategy to examine global stock market integration. The authors also try to use graphs and the spanning trees instead of the correlation models to understand the association between the markets, avoiding the downsides of the existing models. The authors' approach tries to visualize the network integration to examine the interconnectedness in the global stock market.

The purpose of this paper is to propose a new aerodynamic parameter estimation methodology based on neural network and output error method, while the output error method is improved based on particle swarm algorithm.

Firstly, the algorithm approximates the dynamic characteristics of aircraft based on feedforward neural network. Neural network is trained by extreme learning machine, and the trained network can predict the aircraft response at (k + 1)th instant given the measured flight data at kth instant. Secondly, particle swarm optimization is used to enhance the convergence of Levenberg–Marquardt (LM) algorithm, and the improved LM method is used to substitute for the Gauss Newton algorithm in output error method. Finally, the trained neural network is combined with the improved output error method to estimate aerodynamic derivatives.

Neither depending on the initial guess of the parameters to be estimated nor requiring numerical integration of the aircraft motion equation, the proposed algorithm can be used for unstable aircraft and is successfully applied to extract aerodynamic derivatives from both simulated and real flight data.

The proposed method requires iterative calculation and can only identify parameters offline.

The proposed method is successfully applied to estimate aircraft aerodynamic parameters and can also be used as a new algorithm for other optimization problems.

In this study, the output error method is improved to reduce the dependence on the initial value of parameters and expand its application scope. It is applied in aircraft aerodynamic parameter identification together with neural network.

The purpose of this paper is to study two-dimensional deformations in a nonlocal, homogeneous, isotropic, rotating thermoelastic medium with temperature-dependent properties under the purview of the Green-Naghdi model II of generalized thermoelasticity. The formulation is subjected to a mechanical load.

The normal mode analysis technique is adopted to procure the exact solution of the problem.

For isothermal and insulated boundaries, discussions have been made to highlight the influences of rotational speed, nonlocality, temperature-dependent properties and time on the physical quantities.

The exact expressions for the displacement components, stresses and temperature field are obtained in the physical domain. These are also calculated numerically for a magnesium crystal-like material and depicted through graphs to observe the variations of the considered physical quantities. The present study is useful and valuable for the analysis of problems involving mechanical shock, rotational speed, nonlocal parameter, temperature-dependent properties and elastic deformation.

The purpose of this paper is to analyse the certified emission reduction (CERs) disclosure and reporting practices followed by Indian firms.

The study is based on all 131 Indian firms who received the CERs under the CDM of UNFCCC. The content analysis is being used to examine the recognition, measurement, presentation and disclosure of CERs within the financial statements.

The study found that there is generally no uniformity of accounting for CERs. The firms adopted a diversity of accounting practices. More specifically, majority of companies (40.46 per cent) recognised CERs as the other income; a very high non-disclosure rate (91.60 per cent) for valuation of CERs inventories was found as only four companies (3.05 per cent) provided accounting treatment for CERs inventories at lower of cost or net realisable value followed by three companies (2.29 per cent) accounted for these inventories at Net realisable value at the end of the reporting period; similarly, a very high non-disclosure rate (92.36 per cent) for how companies account for expenses incurred in earning these credits was found.

The study will be useful for a wide array of audiences ranging from accounting standard setter to the auditors. The present analysis is based on secondary data, as we examined only annual reports of the sample companies to know how they recognise their earned CERs within the financial statements. So, we did not cover the opinions of various key persons of companies like an accountant, auditors etc. which could be a limitation of this study in validating CERs disclosure practices followed by the Indian firms.

To the best of the author's knowledge, the present study is a first of its kind to analyse the carbon credit disclosure practices in the context of a developing country.

The purpose of this paper is to study the transient thermoelastic interactions in a nonlocal rotating magneto-thermoelastic medium with temperature-dependent properties. Three-phase-lag (TPL) model of generalized thermoelasticity is employed to study the problem. An initial magnetic field with constant intensity acts parallel to the bounding plane. Therefore, Maxwell's theory of electrodynamics has been effectively introduced and the expression for Lorentz's force is obtained with the help of modified Ohm's law.

The normal mode technique has been adopted to solve the resulting non-dimensional coupled field equations to obtain the expressions of physical field variables.

For uniformly distributed thermal load, normal displacement, temperature distribution and stress components are calculated numerically with the help of MATLAB software for a copper material and the results are illustrated graphically. Some particular cases of interest are also deduced from the present study.

Influences of nonlocal parameter, rotation, temperature-dependent properties, magnetic field and time are carefully analyzed for mechanically stress free boundary and uniformly distributed thermal load. The present work is useful and valuable for analysis of problem involving thermal shock, nonlocal parameter, temperature-dependent elastic and thermal moduli.