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As the number of devices that connect to the Internet of Things (IoT) has grown, privacy and security issues have come up. Because IoT devices collect so much sensitive information, like user names, locations, phone numbers and even how they usually use energy, it is very important to protect users' privacy and security. IoT technology will be hard to use on the client side because IoT-enabled devices do not have clear privacy and security controls.

IoT technology would be harder to use on the client side if the IoT did not offer enough well-defined ways to protect users’ privacy and security. The goal of this research is to protect people's privacy in the IoT by using the oppositional artificial flora optimization (EGPKC-OAFA) algorithm to generate the best keys for the ElGamal public key cryptosystem (EGPKC). The EGPKC-OAFA approach puts the most weight on the IEEE 802.15.4 standard for MAC, which is the most important part of the standard. The security field is part of the MAC header of this standard. In addition, the MAC header includes EGPKC, which makes it possible to make authentication keys as quickly as possible.

With the proliferation of IoT devices, privacy and security have become major concerns in the academic world. Security and privacy are of the utmost importance due to the large amount of personally identifiable information acquired by IoT devices, such as name, location, phone numbers and energy use. Client-side deployment of IoT technologies will be hampered by the absence of well-defined privacy and security solutions afforded by the IoT. The purpose of this research is to present the EGPKC with optimum key generation using the EGPKC-OAFA algorithm for the purpose of protecting individual privacy within the context of the IoT. The EGPKC-OAFA approach is concerned with the MAC standard defined by the IEEE 802.15.4 standard, which includes the security field in its MAC header. Also, the MAC header incorporates EGPKC, which enables the fastest possible authentication key generation. In addition, the best methodology award goes to the OAFA strategy, which successfully implements the optimum EGPKC selection strategy by combining opposition-based (OBL) and standard AFA ideas. The EGPKC-OAFA method has been proved to effectively analyze performance in a number of simulations, with the results of various functions being identified.

In light of the growing prevalence of the IoT, an increasing number of people are becoming anxious about the protection and confidentiality of the personal data that they save online. This is especially true in light of the fact that more and more things are becoming connected to the internet. The IoT is capable of gathering personally identifiable information such as names, addresses and phone numbers, as well as the quantity of energy that is used. It will be challenging for customers to adopt IoT technology because of worries about the security and privacy of the data generated by users. In this work, the EGPKC is paired with adversarial artificial flora, which leads in an increase to the privacy security provided by EGPKC for the IoT (EGPKC-OAFA). The MAC security field that is part of the IEEE 802.15.4 standard is one of the areas that the EGPKC-OAFA protocol places a high focus on. The Authentication Key Generation Protocol Key Agreement, also known as EGPKCA, is used in MAC headers. The abbreviation for this protocol is EGPKCA. The OAFA technique, also known as the combination of OBL and AFA, is the most successful method for selecting EGPKCs. This method is recognized by its acronym, OAFA. It has been shown via a variety of simulations that the EGPKC-OAFA technique is a very useful instrument for carrying out performance analysis.

In this chapter, I explore two media texts, Imtiaz Ali's Highway and Alankrita Shrivastava's Netflix original series Bombay Begums (2021). I contend that recent filmmakers have begun to arguably reframe the narratives of rape victim-survivors and disrupting the cultural of silence described above. They offer progressive and multi-faceted representations of these experiences, such that there is an opportunity for a dialogue within both private and public spheres. What I mean when I say that they are ‘progressive representations’ is that the rape victim-survivors are not merely reduced to helpless women in distress, nor painted as vengeful, aggressive characters. Instead, their characterisation shows that they have agency and autonomy, but at the same time struggle with the repercussions of speaking out against their perpetrators in a society that does not support them wholly.

Using the extant literature review, this paper aims to explore the relationship between gender, entrepreneurial education (EE) and entrepreneurial intention (EI) in the Indian context, which the authors believe is a novel approach to this research stream. The authors also use career preparedness as a control variable to examine this relationship.

Data were collected from 368 undergraduate students across four Indian universities (one exclusively for female students) through a standard structured questionnaire. Additionally, rather than examining, EI has been treated as a monolithic construct; however, the authors conceptualize it as comprising three different dimensions that include grand vision and risk-taking ability; opportunity exploitation; and ability to persevere. An additional analysis was conducted for the students who reported higher scores for “being well prepared for their careers” through their institutes’ academic programs and communities of entrepreneurs. The authors also interviewed some entrepreneurship instructors, who confirmed the present findings through their observations.

The findings indicate that, essentially, there is a positive relationship between EE and EI. The authors find that male students scored higher for the first two dimensions of EI but not the third. Additionally, the authors used career preparedness as a control variable for additional analysis. The authors observed that students with higher “career preparedness” reported a positive relationship between EE and EI, independent of gender, for all three dimensions of EI. Thus, it may be assumed that if a community of entrepreneurs needs to be developed in India, a focus on career preparedness is critical.

First, given that the present survey reflected a single moment in linking EE to EI (which may be considered a limitation of the study), future researchers might focus on a longitudinal approach. Second, all the respondents are attending urban universities (and, as such, very likely belong to the upper middle class of Indian society). The financial divide between urban and rural India is well known; as such, the results might be different if the sample was drawn from rural and poor India.

The salience/value of this study lies in the conceptualization of EI comprising three sub-constructs to understand the impact of formal EE (with three sub-constructs) on EI. The focus on career preparedness for a female student is a new direction of inquiry with respect to entrepreneurial intention.

This paper aims to propose fuzzy-regression-particle swarm optimization (PSO) based hybrid optimization approach for getting maximum weld quality in terms of weld strength and bead depth of penetration.

The prediction of welding quality to achieve best of it is not possible by any single optimization technique. Therefore, fuzzy technique has been applied to predict the weld quality in terms of weld strength and weld bead geometry in combination with a multi-performance characteristic index (MPCI). Then regression analysis has been applied to develop relation between the MPCI output value and the input welding process parameters. Finally, PSO method has been used to get the optimal welding condition by maximizing the MPCI value.

The predicted weld quality or the MPCI values in terms of combined weld strength and bead geometry has been found to be highly co-related with the weld process parameters. Therefore, it makes the process easy for setting of weld process parameters for achieving best weld quality, as there is no need to finding the relation for individual weld quality parameter and weld process parameters although they are co-related in a complicated manner.

In this paper, a new hybrid approach for predicting the weld quality in terms of both mechanical properties and weld geometry and optimizing the same has been proposed. As these parameters are highly correlated and dependent on the weld process parameters the proposed approach can effectively analyzing the ambiguity and significance of each process and performance parameter.

This study aims to explore the interrelationships among human-related lean practices, lean production shop floors, process quality, inventory management, operational productivity and business productivity.

This study used a cross-sectional survey approach, and quantitative data were collected from 324 Indian auto-component manufacturing firms. Confirmatory factor analysis was used, followed by structural equation modelling techniques for the conceptual model, which incorporated a complete set of 11 hypotheses.

The results confirmed that human-related lean practices trigger lean production shop floors and improve process quality. Furthermore, the study revealed the positive impact of a lean production shop floor on process quality and inventory management and the positive impact of process quality on both operational and business productivity. Finally, inventory management is of the utmost importance in achieving better operational and business productivity, and operational productivity positively leads to business productivity.

The findings of this study can benefit auto-component manufacturing firms by elucidating the complex relationships between human-related lean practices, lean production shop floors, process quality, inventory management, operational productivity and business productivity. Better knowledge of these relationships will enable firms to enhance efficiency levels, reduce costs and resource wastage and improve their overall performance. This study provides a good understanding of the interplay between lean and quality factors and their influence on inventory management and business performance.

In this study, the authors assess the current state of lean product development and the lean production shop floor, along with the impact of the former on process quality and the latter on product quality and customer complaint reduction. The interplay between process and product quality and customer complaint reduction is assessed, along with their impacts on business performance.

Data were collected from 377 managers working at auto-component manufacturing firms in India. Confirmatory factor analysis was used for scale validation, and structural equation modelling was employed to test the research hypotheses.

The results of the statistical analyses reveal the positive influence of a lean production shop floor on process quality and lean product development on product quality and customer complaint reduction, and thereby on business performance.

The findings of this research provide insights into the interplay between lean and quality factors and their influence on customer complaint reduction and business performance. Practitioners can use the proposed model to strategically design unique products and improve the efficiency and effectiveness of the production shop floor, which can help enhance the product and process quality. This can reduce customer dissatisfaction and improve the business performance.

Few studies have simultaneously investigated the influence of lean product development and lean production shop floors in the Indian manufacturing context. To the best of our knowledge, this study is one of the first attempts to include customer complaint reduction as a construct in a lean model. It helps identify and prioritise the enablers of business performance and provides valuable insights for practitioners to strengthen lean implementation to attain a competitive edge.

The main purpose of this study is to provide a comprehensive review and critical insights of the application of fuzzy methods in modeling, assessing and understanding the various aspects of green and sustainable supply chains (SSCs).

The present study conducts a systematic literature review (SLR) and bibliometric analysis of 252 research articles. This study employs various tools such as VOSviewer version 1.6.10, Publish or Perish, Mendeley and Excel that aid in descriptive analysis, bibliometric analysis and network visualization. These tools have been used for performing citation analysis, top authors' analysis, co-occurrence of keywords, cluster and content analysis.

The authors have divided the literature into seven application areas and discussed detailed insights. This study has observed that research in the social sustainability area, including various issues like health and safety, labor rights, discrimination, etc. is scarce. Integration of the Industry 4.0 technologies like blockchain, big data analytics, Internet of Things (IoT) with the sustainable and green supply chain (GSC) is a promising field for future research.

The authors' contribution primarily lies in providing the integrated framework which shows the changing trends in the use of fuzzy methods in the sustainability area classifying and consolidating green and sustainable supply chain management (SSCM) literature in seven major areas where fuzzy methods are predominantly applied. These areas have been obtained after the analysis of clusters and content analysis of the literature presenting key insights from the past and developing the conceptual framework for future research studies.

The purpose of this study is to present a systematic review of the online service failure (OSF) literature and conduct an exhaustive analysis of academic research on this emerging research area.

The current study has adopted a structured systematic literature review approach to synthesize and assess the OSF literature. Further, the study uses the Theory-Context-Characteristics-Methodology (TCCM) framework to propose future research directions in the OSF domain.

This systematic review shows that OSF research is still developing and remains mainly incoherent. Further, the study develops a conceptual framework integrating the frequently reported antecedents, mediators, moderator and consequences in the extant literature. This review also synthesizes the theoretical perspectives adopted for this domain.

The study followed specific inclusion and exclusion criteria to shortlist articles. Further, articles published only in the English language were considered. Hence, the findings of this review cannot be generalized to all OSF literature.

This systematic review has classified antecedents into customers' and service providers' roles which will enable online service providers to understand all sets of factors driving OSF. It also synthesizes and presents service recovery strategies and emphasizes the role of online customer support to fix OSF.

The OSF literature is still developing and remains highly incoherent, suggesting that a synthesized review is needed. This study has systematically reviewed and synthesized the OSF literature to study its development over time and proposes a framework which provides a comprehensive understanding of OSF.