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Microcapsule-embedded autonomic healing materials have the ability to repair microcracks when they come into contact with the crack by releasing the healing agent. The microcapsules with specific shape and thickness effect in releasing healing agent to the cracked surfaces. Thus, the purpose of this paper is to know the load bearing capacity of the self-healing microcapsules and the stresses developed in the material.

In the present study, self-healing microcapsule is modelled and integrated with the polymer matrix composite. The aim of the present study is to investigate failure criteria of Poly (methyl methacrylate) microcapsules by varying the shell thickness, capsule diameter and loading conditions. The strength of the capsule is evaluated by keeping the shell thickness as constant and varying the capsule diameter. Uniformly distributed pressure loads were applied on the capsule-reinforced polymer matrix composite to assess the failure strength of capsules and composite.

It is observed from the results that the load required to break the capsules is increasing with the increase in capsule diameter. The failure strength of microcapsule with 100 µm diameter and 5 µm thickness is observed as 255 MPa. For an applied load range of 40–160 N/mm² on the capsules embedded composite, the maximum stress developed in the capsules is observed as 308 MPa.

Failure strengths of microcapsules and stresses developed in the microcapsule-reinforced polymer composites were evaluated.

The purpose of this paper is to find out a convenient chemical treatment for seedlac and shellac (semi‐refined and refined commercial forms of natural resin lac, respectively) for preventing degradation during storage at room temperature condition.

Seedlac and shellac are treated with a dilute solution of an antioxidant before storage. This method has not been attempted before. The changes in the physico‐chemical properties of both untreated and treated resins are investigated periodically during storage.

Antioxidant delays the degradation of seedlac and shellac at least by six to eight months during the early period of storage. It is further observed that oxalic acid, used in the trade during conversion of seedlac into shellac by hot filtration for imparting gloss on shellac flakes for attracting buyers), causes rapid polymerisation of shellac resulting in zero value (100 percent decrease) of flow (fluidity) within 30 months of storage, whereas, shellac prepared without treatment of oxalic acid could be stored beyond that period without a significant deterioration in its qualities.

Antioxidants are known to be scavengers of OH groups. Lac resin (shellac and seedlac) contains five hydroxyl groups and one carboxyl group. Thus, only one dilute concentration of antioxidant is used to avoid possible modification of seedlac and shellac.

Consumers of shellac are not aware of the ill effect of oxalic acid treatment being practiced by processors. The results obtained in the present study will help consumers to advise processors suitably before purchase and will be able to store shellac for a longer period if it is not treated with oxalic acid. The consumers may also use an antioxidant to delay degradation of seedlac/shellac.

The results obtained in this paper, regarding the effects of treatments of antioxidant and oxalic acid are not available in any previous publication. These are reported for the first time.

This study aims to provide a systematic review about the Internet of Things (IoT) and its impacts on happiness. It intends to serve as a platform for further research as it is sparse in in-depth analysis.

This systematic review initially observed 2,501 literary articles through the ScienceDirect and WorldCat search engines before narrowing it down to 72 articles based on subject matter relevance in the abstract and keywords. Accounting for duplicates between search engines, the count was reduced to 66 articles. To finally narrow down all the literature used in this systematic review, 66 articles were given a critical readthrough. The count was finally reduced to 53 total articles used in this systematic review.

This paper necessitates the claim that IoT will likely impact many aspects of our everyday lives. Through the literature observed, it was found that IoT will have some significant and positive impacts on people's welfare and lives. The unprecedented nature of IoTs impacts on society should warrant further research moving forward.

While the literature presented in this systematic review shows that IoT can positively impact the perceived or explicit happiness of people, the amount of literature found to supplement this argument is still on the lower end. They also necessitate the need for both greater depth and variety in this field of research.

Since technology is already a pervasive element of most people’s contemporary lives, it stands to reason that the most important factors to consider will be in how we might benefit from IoT or, more notably, how IoT can enhance our levels of happiness. A significant implication is its ability to reduce the gap in happiness levels between urban and rural areas.

Currently, the literature directly tackling the quantification of IoTs perceived influence on happiness has yet to be truly discussed broadly. This systematic review serves as a starting point for further discussion in the subject matter. In addition, this paper may lead to a better understanding of the IoT technology and how we can best advance and adapt it to the benefits of the society.

The purpose of this paper is to investigate the Newtonian heating and slip effect on mixed convective flow near a stagnation point in a porous medium with thermal radiation in the presence of magnetohydrodynamic (MHD), heat generation/absorption and chemical reaction.

The governing nonlinear coupled equations are converted into ordinary differential equations by similarity transformation. These equations are solved numerically using a Runge–Kutta–Fehlberg method with shooting technique and analytically using the homotopy analysis method (HAM).

The effects of different parameters on the fluid flow and heat transfer are investigated. It is found that the velocity and temperature profiles increase on an increase in the Biot number. The velocity and concentration profiles increase on decreasing the chemical reaction parameter.

This paper is helpful to the engineers and scientists in the field of thermal and manufacturing engineering.

The two-dimensional boundary layer flow over a vertical plate with slip and convective boundary conditions near the stagnation-point is analysed in the presence of magnetic field, radiation and heat generation/absorption. This paper is helpful to the engineers and scientists in the field of thermal and manufacturing engineering.

The main aim of the existing study is to assess work-home interaction which is a challenge to human resource management (HRM).

The existing research is primary in nature. The sample size of the study is 285. The responses obtained from structured questionnaire. The qualitative data collected from secondary sources. For quantitative analysis various statistical tools have been applied, namely, Cronbach Alpha test, Correlation analysis and Regression analysis. The variables understudy was work environment, training opportunities, career opportunities, pay structure and technology factors.

As the recent pandemic continues to spread, all institutions should essentially remain alert and adaptable to new circumstances. HRM was essential throughout the pandemic, but now more than ever HR professionals must go above and beyond to meet the demands of organizations. The purpose of this study was to illuminate some of the most significant HR concerns that have surfaced in the aftermath of recent pandemics.

Employees' perspectives on work and life have shifted as a result of the added stress brought on by pandemic. So, businesses should provide crucial care to their workers' spirits and also HR professionals should pay close attention to their concerns and address the same thoughtfully.

The research adds to the current literature by illuminating the additional HR difficulties that have emerged in the wake of the global epidemic. More research may reveal additional significant HR difficulties, but these are a good place to start.

This paper aims that optimization parameters depending on machining processes examine to define for the milling process of AL 6061-T6 aluminum alloy used in the aviation industry.

The Taguchi method was used to study the optimal parameters. Furthermore, the effects of machining parameters on surface roughness were also evaluated by performing variance analysis. Optimum parameter levels were determined by Signal/Noise analysis.

It was determined that the parameter levels that optimize the surface roughness were “4000 rev/min for the rotational speed of the cutting tool, 0.4 mm for the cutting depth and the optimum value for the feedrate 500 mm/min.”

It is limited by the precision of the manufacturing processes, the desired geometry and the exactness of the measurement make the machine productivity valuable in the production of parts.

By improving the optimal production parameters, reducing part production costs and waste amount in aviation has been seen as an important gain.

Improving production methods and optimization parameters in production technologies will ensure the minimization of loss and waste. These developed parameters with optimizing the surface roughness will add value in this context.

It was determined that the parameter levels that optimize the surface roughness of aluminum considering manufacturing processes. Especially as process parameters, optimum feed rate has been developed for effective rotation speed and cutting depth for cutting tools.

Aadhaar card is an innovative step taken by the Government of India to facilitate smooth functioning of government welfare programs among the needy citizens of this country. This chapter deals about the Aadhaar Project of the Central Government, its features, its impact on the welfare schemes of government, etc. Second, it also deals with the challenges and loopholes associated with the Aadhaar scheme which eventually led to the case of Justice K. S. Puttaswamy and Another v. Union of India [Writ Petition (Civil) No. 494 of 2012]. At last, the chapter deals with the potential challenges which the Aadhaar scheme may face even after it has been declared constitutional by the Apex Court in the case of Justice K. S. Puttaswamy and Another v. Union of India [Writ Petition (Civil) No. 494 of 2012].

The aim of continuous learning is to obtain and fine-tune information gradually without removing the already existing information. Many conventional approaches in streaming data classification assume that all arrived new data is completely labeled. To regularize Neural Networks (NNs) by merging side information like user-provided labels or pair-wise constraints, incremental semi-supervised learning models need to be introduced. However, they are hard to implement, specifically in non-stationary environments because of the efficiency and sensitivity of such algorithms to parameters. The periodic update and maintenance of the decision method is the significant challenge in incremental algorithms whenever the new data arrives.

Hence, this paper plans to develop the meta-learning model for handling continuous or streaming data. Initially, the data pertain to continuous behavior is gathered from diverse benchmark source. Further, the classification of the data is performed by the Recurrent Neural Network (RNN), in which testing weight is adjusted or optimized by the new meta-heuristic algorithm. Here, the weight is updated for reducing the error difference between the target and the measured data when new data is given for testing. The optimized weight updated testing is performed by evaluating the concept-drift and classification accuracy. The new continuous learning by RNN is accomplished by the improved Opposition-based Novel Updating Spotted Hyena Optimization (ONU-SHO). Finally, the experiments with different datasets show that the proposed learning is improved over the conventional models.

From the analysis, the accuracy of the ONU-SHO based RNN (ONU-SHO-RNN) was 10.1% advanced than Decision Tree (DT), 7.6% advanced than Naive Bayes (NB), 7.4% advanced than k-nearest neighbors (KNN), 2.5% advanced than Support Vector Machine (SVM) 9.3% advanced than NN, and 10.6% advanced than RNN. Hence, it is confirmed that the ONU-SHO algorithm is performing well for acquiring the best data stream classification.

This paper introduces a novel meta-learning model using Opposition-based Novel Updating Spotted Hyena Optimization (ONU-SHO)-based Recurrent Neural Network (RNN) for handling continuous or streaming data. This is the first work utilizes a novel meta-learning model using Opposition-based Novel Updating Spotted Hyena Optimization (ONU-SHO)-based Recurrent Neural Network (RNN) for handling continuous or streaming data.