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Improved production with quality, safety, and security is the biggest challenge of the food industry. Modern technologies, including robotics and automation systems, can help to cope with such issues. This chapter gives a brief view of robotics and automation for the sustainable food industry along with packaging, warehousing, distribution, marketing, and consumer services. It describes the recently implemented solutions of robotic automation in different supply chain operations and various food commodities. The benefits of robotic and automation technology for perishable and semi-perishable items have also been covered. The present research may assist the food industry professionals, supply chain managers, and academicians in implementing automation and robotics in the food industry.

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 chapter aims to provide an overview of the ethical framework and decision-making in clinical dementia research, and to analyze and discuss the ethical challenges and issues that can arise when conducting clinical dementia research.

Informed consent is the most scrutinized and controversial aspect of clinical research ethics. In clinical dementia research, assessing decision-making capacity may be challenging as the nature and progress of each disease influences decision-making capacity in diverse ways. Persons with dementia represent a vulnerable population deserving special attention when developing, implementing, and evaluating the informed consent process. In this chapter, particular attention will be given to vulnerability categories and how these influence decision-making capacity. Ethical frameworks with a pragmatic contour and implication are needed to protect vulnerable patients from potential harms and ensure their optimal participation in clinical dementia research.

In addition, this chapter analyses important ethical challenges and issues in clinical dementia research. If handled thoughtfully, they would not pose insuperable barriers to research. But if they are ignored, they could slow the research process, alienate potential study subjects and cause harm to research participants. Ethical considerations in research involving persons with dementia primarily concern the representation of the interests of the participants with dementia and protection of their vulnerabilities and rights.

A core set of ethical questions and recommendations are drawn to aid researchers, institutional review boards and potential research participants in the process of participating in clinical dementia research.

This paper aims to study the flow and heat transfer inside a wavy enclosure filled with Cu-water nanofluid under magnetic field effect by parallel implemented meshfree approach.

The simulation has been carried out for a two-dimensional model with steady, laminar and incompressible flow of the nanofluid filled inside wavy enclosure in which one of the walls is sinusoidal such that the amplitude (A = 0.15) and number of undulations (n = 2) are fixed. A uniform magnetic field B₀ has been applied at an inclination angle γ. The governing equations for the transport phenomena have been solved numerically by implementing element-free Galerkin method (EFGM) with the sequential as well as parallel approach. The effect of various parameters, namely, nanoparticle volume fraction (φ), Rayleigh number (Ra), Hartmann number (Ha) and magnetic field inclination angle (γ) has been studied on the natural convection flow of nanofluid.

The results are obtained in terms of average Nusselt number calculated at the cold wavy wall, streamlines and isotherms. It has been observed that the increasing value of Rayleigh number results in increased heat transfer rate while the Hartmann number retards the fluid motion. On the other hand, the magnetic field inclination angle gives rise to the heat transfer rate up to its critical value. Above this value, the heat transfer rate starts to decrease.

The implementation of the magnetic field and its inclination has provided very interesting results on heat and fluid flow which can be used in the drug delivery where nanofluids are used in many physiological problems. Another important novelty of the paper is that meshfree method (EFGM) has been used here because the domain is irregular. The results have been found to be very satisfactory. In addition, parallelization of the scheme (which has not been implemented earlier in such problems) improves the computational efficiency.

This paper aims to derive criteria for a strategic selection of learning management system (LMS) after making an analysis of the feedback data collected from learners and academic counselors in open and distance learning (ODL) to evaluate their perceptions. This analysis hints at the need to implement a learning management system (LMS) in ODL. Selecting an appropriate LMS can prove to be a strategic approach for ODL in achieving self-reliance and competitiveness.

Research design includes qualitative design intended to discuss the features, advantages and attributes of different popular LMSs and compare them. In addition, the quantitative design (a questionnaire-based online feedback) to analyze the perceptions of the learners and academic counselors in order to know their e-learning needs has also been used. Results have been exhibited in tabular/graphical formats for easy comprehension and enhanced understanding.

Findings of the study suggest that availability of plethora of LMSs in the market, which also include open source (OS) LMSs, makes the decision- making as regards selection of an appropriate LMS strategically crucial requiring adequate consideration of every aspect such as cost, quality, usage, capacity, budget and most importantly priorities and objectives.

This study will help educational administrators and decision-makers in ODL for building a quality civilized life and empowered society by removing the constraints related to financial problems, disabilities, time, geographical conditions and many others in bringing education to the doorstep of every willing learner. The technical details of LMS, however, were intentionally kept simplified to achieve the objective and provide easy comprehensibility for the reader with little technical background, which might be a limitation of this study.

This study highlights that ODL has tasted success with optimum exploitation of different technological advancements in its transformational expedition from conventional learning to innovative e-learning and to the newest adaptive e-learning system. The huge potential of LMS, in providing learners and educators in ODL with an effective web-based learning system incorporating almost all the academic activities, has attracted organizations for using it not only for imparting education to learners but also for providing appropriate trainings to their human resources.

Purpose: The main purpose of this study is to test the effect of consumers’ readiness level to use new technology on their intention to use mobile payment applications based on the technology readiness and acceptance model (TRAM). In detail, it examines how the dimensions of TR as ‘optimism, innovativeness, discomfort, and insecurity’ affect consumers’ intention to utilise mobile payment applications. Moreover, the effect of the technology-accepting behaviour measured by two major factors as ‘perceived usefulness’ and ‘perceived ease of use’ on the intention to use mobile payment applications is also examined.

Need for the study: The existence of a mobile system alone is not enough to attract consumers with no user experience to these applications. The user-centred attribute in the usage of these applications, which involves the influence of technology readiness (TR), has been largely ignored especially in developing countries. By focussing on this area, it is expected to fill the gap that has not been sufficiently handled in the developing country settings and, particularly in Turkey.

Methodology: The study population consists of the consumers who live in İstanbul who is aged 18 and over and use mobile payment technology at least once. After collecting data, confirmatory factor analysis was applied to validate the measurement model. Afterward, the structural model was tested by the Maximum Likelihood-MI estimation method, and the bootstrap samples were stated as 5,000.

Findings: When the results of the study are examined, it is seen that optimism has a significant influence on the perceived usefulness and perceived ease of use dimensions of the technology acceptance model, while innovativeness is significant only on the perceived ease of use. This study results also show that discomfort and insecurity don’t significantly influence the perception of usefulness and easy-to-use mobile payment applications as perceived by individuals. Perceived ease of use is to positively affect the perceived usefulness. Additionally, the perceived ease of use and the perceived usefulness are strong predictors of intention to use mobile payment applications.

Practical implications: Findings of this study demonstrate the validity of the technology readiness and acceptance model for explaining the intention of using mobile payment applications in Turkey. To improve consumers’ intent in the usage of m-payment apps, their level of technological readiness towards technology should be determined and the factors that affect the formation of insecurity and discomfort attitudes of individuals should be emphasised.

This study proposes an objective assessment model to evaluate the performance of internal and external capabilities of firms. It facilitates firms to invest appropriate resources to cultivate the organizational capability necessary to meet the requirements of the performance indicators.

This study integrates the concepts of resource-based theory, the organizational capability concept, and conduct a performance analysis to the four perspectives of the BSC by implementing the fuzzy set theory and data employment analysis.

The findings show that the appropriate strategies help allocate available resources and capabilities during the different product life cycle, which provides practical guidelines for firms to achieve sustaining competitive advantage.

The selected factors were focused on four resources and capabilities rather than all possible factors.

An objective assessment model was created based on internal and external competitive performance efficiency in this research field. This model facilitates the ability of the top management to make decisions for resource allocation that will enhance firm's performance.

This paper aims to create a better understanding of the challenges posed by work from home (WFH) during the ongoing COVID-19 pandemic, to investigate the public sentiment toward this transition, and to develop a conceptual model incorporating the relationships among the factors that influence the effectiveness of WFH.

This paper uses netnography method to collect data from the Twitter platform and uses Python programming language, Natural Language Processing techniques and IBM SPSS 26 to conduct sentiment analysis and directed content analysis on the data. The findings are combined with an extensive review of the remote work literature to develop a conceptual model.

Results show the majority of tweets about WFH during the pandemic are positive and objective with technology and cyber security as the most repeated topics in the tweets. New challenges to WFH during pandemic include future uncertainty, health concerns, home workspaces, self-isolation, lack of recreational activities and support mechanisms. In addition, exhaustion and technostress mediate the relationship between the antecedents and outcomes of WFH during the ongoing COVID-19 pandemic. Finally, the fear of pandemic and coping strategies moderates these relationships.

This paper is one of the first efforts to comprehensively investigate the challenges of WFH during a crisis and to extend the remote work literature by developing a conceptual model incorporating the moderating effects of fear of pandemic and coping strategies. Moreover, it is the first paper to investigate the tweeting behavior of different user types on Twitter who shared posts about WFH during the ongoing pandemic.

The purpose of this paper is to study the application of entropy based optimized fuzzy logic control for a real-time non-linear system. Optimization of the fuzzy membership function (MF) is one of the most explored areas for performance improvement of the fuzzy logic controllers (FLC). Conversely, majority of previous works are motivated on choosing an optimized shape for the MF, while on the other hand the support of fuzzy set is not accounted.

The proposed investigation provides the optimal support for predefined MFs by using genetic algorithms-based optimization of fuzzy entropy-based objective function.

The experimental results obtained indicate an improvement in the performance of the controller which includes improvement in error indices, transient and steady-state parameters. The applicability of proposed algorithm has been verified through real-time control of the twin rotor multiple-input, multiple-output system (TRMS).

The proposed algorithm has been used for the optimization of triangular sets, and can also be used for the optimization of other fussy sets, such as Gaussian, s-function, etc.

The proposed optimization can be combined with other algorithms which optimize the mathematical function (shape), and a potent optimization tool for designing of the FLC can be formulated.

This paper presents the application of a new optimized FLC which is tested for control of pitch and yaw angles in a TRMS. The performance of the proposed optimized FLC shows significant improvement when compared with standard references.

The primary objective of this investigation is to optimize the constricted arc tungsten inert gas (CA-TIG) welding parameters specifically welding current (WC), arc constriction current (ACC), ACC frequency (ACCF) and CA traverse speed to maximize the tensile properties of thin Inconel 718 sheets (2 mm thick) using a statistical technique of response surface methodology and desirability function for gas turbine engine applications.

The four factor – five level central composite design (4 × 5 – CCD) matrix pertaining to the minimum number of experiments was chosen in this investigation for designing the experimental matrix. The techniques of numerical and graphical optimization were used to find the optimal conditions of CA-TIG welding parameters.

The thin sheets of Inconel 718 (2 mm thick) can be welded successfully using CA-TIG welding process without any defects. The joints welded using optimized conditions of CA-TIG welding parameters showed maximum of 99.20%, 94.45% and 73.5% of base metal tensile strength, yield strength and elongation.

The joints made using optimized CA-TIG welding parameters disclosed 99.20% joint efficiency which is comparatively 20%–30% superior than conventional TIG welding process and comparable to costly electron beam welding and laser beam welding processes. The parametric mathematical equations were designed to predict the tensile properties of Inconel 718 joints accurately with a confidence level of 95% and less than 4.5% error. The mathematical relationships were also developed to predict the tensile properties of joints from the grain size (secondary dendritic arm spacing-SDAS) of fusion zone microstructure.