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The paper aims to advance methodologies to optimize fuzzy logic controller parameters via neural network and use the neuro‐fuzzy scheme to control two cooperating robots.

The paper presents a special neural network architecture that can be converted to fuzzy logic controller. Concepts of model predictive control (MPC) have been used to generate optimal signal to be used to train the neural network via backpropagation. Subsequently, a trained neural network is used to obtain fuzzy logic controller parameters.

The proposed neuro‐fuzzy scheme is able to precisely learn the control relation between input‐output training data generated by the learning algorithm. From the experiments performed on the industrial grade robots at Robotics and Manufacturing Automation (RAMA) Laboratory, it was found that the neuro‐fuzzy controller was able to learn fuzzy logic rules and parameters accurately.

The backpropagation method, used in this research, is extremely dependent on initial choice of parameters, and offers no mechanism to restrict the parameters within specified range during training. Use of alternative learning mechanisms, such as reinforcement learning, needs to be investigated.

The neuro‐fuzzy scheme presented can be used to develop controller for plants for which it is difficult to obtain analytical model or sufficient information about input‐output heuristic relation is not available.

The paper presents the neural network architecture and introduces a learning mechanism to train this architecture online.

The purpose of this paper is to elucidate the methodology of total interpretive structural modeling (TISM) in order to provide interpretation for direct as well as significant transitive linkages in a directed graph.

This study begins by unfolding the concepts and advantages of TISM. The step-by-step methodology of TISM is exemplified by employing it to analyze the mutual dependence among inhibitors of smartphone manufacturing ecosystem development (SMED). Cross-impact matrix multiplication applied to the classification analysis is also performed to graphically represent these inhibitors based on their driving power and dependence.

This study highlights the significance of TISM over conventional interpretive structural modeling (ISM). The inhibitors of SMED are explored by reviewing existing literature and obtaining experts’ opinions. TISM is employed to classify these inhibitors in order to devise a five-level hierarchical structure based on their driving power and dependence.

This study facilitates decision makers to take required actions to mitigate these inhibitors. Inhibitors (with strong driving power), which occupy the bottom level in the TISM hierarchy, require more attention from top management and effective monitoring of these inhibitors can assist in achieving the organizations’ goals.

By unfolding the benefits of TISM over ISM, this study is an endeavor to develop insights toward utilization of TISM for modeling inhibitors of SMED. This paper elaborates step-by-step procedure to perform TISM and hence makes it simple for researchers to understand its concepts. To the best of the authors’ knowledge, this is the first study that analyzes the inhibitors of SMED by utilizing TISM approach.

Significant advances have been made in the field of healthcare service delivery across the world; however, health coverage particular for the poor and disadvantaged still remains a distant dream in developing world. In large developing countries like India, disparities in access to healthcare are pervasive. Despite recent progress in ensuring improved access to health care in past decade or so, disparities across gender, geography and socioeconomic status continue to persist. Fragmented and scattered health records and lack of integration are some of the primary causes leading to uneven healthcare service delivery. The devised framework is intended to address these challenges. The paper aims to discuss these issues.

In view of such challenges, in this research a Big Data and blockchain anchored integrative healthcare framework is proposed focusing upon providing timely and appropriate healthcare services to every citizen of the country. The framework uses unique identification number (UID) system as formalized and implemented by the Government of India for identification of the patients, their specific case histories and so forth.

The key characteristic of our proposed framework is that it provides easy access to secure, immutable and comprehensive medical records of patients across all treatment centers within the country. The model also ensures security and privacy of the medical records based upon the incorporation of biometric authentication by the patients for access of their records to healthcare providers.

A key component of our evolved framework is the Big Data analytics-based framework that seeks to provide structured health data to concerned stakeholders in healthcare services. The model entails all pertinent stakeholders starting from patients to healthcare service providers.

This paper aims to identify, analyze and evaluate the major enablers for the sustainable public distribution system (PDS) supply chain in India in lessening food insecurity by distributing essentials food grains at a subsidized rate.

The major enablers for the sustainable PDS supply chain were explored by conducting the literature survey and discussion with academic and warehouse experts. Then, the fuzzy-DEMATEL (decision-making trial and evaluation laboratory) technique was applied to develop a causal model that analyses the interaction among the identified enablers.

This study recognizes fifteen enablers through literature survey and experts' opinions. The present work concludes that “proper identification of the PDS beneficiaries” and “willingness and commitment of the top management and policymaker” are the two major enablers for the sustainable PDS supply chain.

This work would be helpful for profoundly understanding the major enablers, and how they are affecting the entire PDS supply chain. The study would be beneficial for the general people and the entire society straightforwardly by providing suggestions for food security.

Identifying and analyzing the major enablers for the sustainable PDS supply chain helps to visualize the problem more effectively and efficiently. Besides, the causal model explains a comprehensive perspective on the identified enablers.

The purpose of this paper is to explore the barriers to sustainable tourism management (STM) implementation in a protected area (PA) of a developing country, India, by taking a case study of National Chambal Sanctuary (NCS).

This study develops a framework to analyse the interaction among a set of barriers of STM using the interpretive structural modelling approach.

In this study, 16 relevant barriers responsible for the failure of STM in Indian scenario have been selected. The lack of coordination among various stakeholders and the lack of government incentives are found as the most significant barriers among the selected barriers of STM implementation in the sanctuary.

This study provides most influencing barriers and how these barriers hinder the sustainability efforts in NCS. The study’s main limitation is its generalisation. The problems in implementing sustainable practices may differ with the region.

This study provides strong practical inferences to both practitioners as well as academicians. The practitioners are suggested to focus on identified barriers and formulating strategies to achieve sustainability in the tourism sector. Academicians may propose the solutions and necessary interventions for identified barriers.

Identification and presentation of barriers to STM implementation in the context of a PA are rare to find in literature.

This paper aims to investigate the in-company training according to the technologically demanding and safety-critical feature of the aircraft industry. This study addresses to the tension between the structured and the more incidental part of in-company learning in their training and learning environment.

Against the background of concepts of workplace learning from vocational training research and concepts of the safety management system from safety research, aircraft companies from England and Germany were visited. Data from interviews with training managers and trainees as well as non-participant observations are analysed.

The findings show that workplace vocational learning in this industry is guided by different measures to design the learning environment to prevent purely incidental and informal knowledge acquisition. However, the formalisation of informal learning process leads to a high expenditure of material, personnel and time resources. The findings show that trainers and training managers working together internationally creatively manage different training systems. The training activities are designed to convey the values of safety culture like responsibility, accuracy, transparent communication and reporting. The requirements of the safety management system are also met through the training.

Challenges and tensions in the actual implementation of the training activities could not be identified. The people interviewed were selected by the companies, so there is a risk that certain perceptions are over-represented.

The results show that the safety-critical industry needs its own pedagogical approach to workplace learning, which is not based on independent work processes in the workplace. Insights can be drawn for in-company training in other safety-critical industries too. However, to enable effective in-company learning, which at the same time strengthens the safety culture of the company, many resources must be used. The companies must consider all dimensions of work from the individual level to the work structure level.

This paper discusses the tension between formal and informal learning and shows the specific design of this tension on the basis of a concrete industry for the specific needs of this industry. The results lead to the realisation that the general discussion about workplace learning must be viewed in a differentiated way depending on the industry.