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The aim of this paper is to study the effect of the parametric sensitivity of all critical parameters of feed water and other operating variables on the corrosion rate and oxide scale deposition on economizer tubes of a typical coal-fired 250-MW boiler.

In this paper, a multilayer perceptron-based artificial neural network (ANN) model has been developed to envisage the corrosion rate and oxide scale deposition rate in economizer tubes of a coal-fired boiler. The neural network architecture has been optimized using an efficient gradient-based network optimization algorithm to minimize the training and testing errors rapidly during simulation runs.

The parametric sensitivity of all critical parameters of feed water and other operating variables on the corrosion rate and oxide scale deposition activities has been investigated. It has been observed that dissolved oxygen, dissolved copper content, residual hydrazine content and pH of the feed water have a relatively predominant influence on the corrosion rate, whereas dissolved iron content, silica content, pH and temperature of the feed water have a moderately major influence on oxide scale deposition phenomenon. There has been very good agreement between ANN model predictions and the measured values of corrosion rate and oxide scale deposition rate substantiated by the regression fit between these values.

This paper details the development of an alternative model to accurately predict corrosion rate and deposition rate on the inner surface of economizer tubes of a boiler over first principle-based kinetic model.

This paper aims to propose an efficient artificial neural network (ANN) model using multi-layer perceptron philosophy to predict the fireside corrosion rate of superheater tubes in coal fire boiler assembly using operational data of an Indian typical thermal power plant.

An efficient gradient-based network training algorithm has been used to minimize the network training errors. The input parameters comprise of coal chemistry, namely, coal ash and sulfur contents, flue gas temperature, SOX concentrations in flue gas, fly ash chemistry (Wt.% Na₂O and K₂O).

Effects of coal ash and sulfur contents, Wt.% of Na₂O and K₂O in fly ash and operating variables such as flue gas temperature and percentage excess air intake for coal combustion on the fireside corrosion behavior of superheater boiler tubes have been computationally investigated and parametric sensitivity analysis has been undertaken.

Quite good agreement between ANN model predictions and the measured values of fireside corrosion rate has been observed which is corroborated by the regression fit between these values.

The contribution of women toward entrepreneurial activities has gained significant attention in recent years because of economic and social concerns, government support and initiatives and increased education and awareness. Women’s entrepreneurial activity has increased and women-owned businesses can today be found in every sector of the economy, irrespective of region. In India, government bodies such as the Ministry of Micro, Small and Medium Enterprises (MSMEs) and several other organizations (private and NGOs) have adopted considerable measures to promote women entrepreneurship (WE). To improve WE, the critical factors of WE adoption need to be identified and evaluated. The purpose of this paper is to identify, prioritize and evaluate the critical success factors of WE adoption in Indian MSMEs.

This paper proposes a methodology based on fuzzy analytical hierarchal process to prioritize the critical success factors of WE adoption. A numerical analysis of Indian MSMEs is presented to demonstrate the use of the proposed method. This proposed method considered fuzzy framework, which can handle impreciseness and uncertainty. Sensitivity analysis is also performed to test the robustness of the proposed model.

Potential critical success factors are identified from relevant literature and validated by industry experts. This research finalize the critical success factors of WE adoption in Indian MSMEs under seven dimensions, so prioritization of identified critical success factors can be developed and insights relationship of factors would be explored. The results of the study found that individual, management and government dimensions take paramount importance while women aim to become entrepreneurs in Indian MSMEs.

This study is limited to identifying evaluation factors; other factors have not been identified and categorized. Evaluation is one by experts in this area so it is natural that views of decision-makers may be subjective and vary with regard to industry-type, priorities, resources, etc.

This study will help industry to identify, evaluate and prioritize factors for successful implementation of women entrepreneurship. MSMEs could device these factors by applying the outcome of the study in their decisions with higher priority to implement women entrepreneurship culture.

Potential factors are identified from relevant literature and validated by industry experts. Indian MSMEs could device these factors by applying the outcome of the study in their decisions with higher priority to adopt women entrepreneurship.

This paper aims to study the impediments and difficulties that prevent Indian women from becoming entrepreneurs.

Data were obtained through a survey involving 15 experts. Based on the feedback provided by the experts, ten relevant barriers in the context of Indian micro small and medium enterprises (MSMEs) were chosen. A structured questionnaire was used to gather data. These ten barriers create obstruction for Indian women as entrepreneurs. These barriers were ranked, and causal relationships among them established using interpretive structural modeling and Matrice d’Impacts croises-multiplication appliqúean classment (cross-impact matrix multiplication applied to classification) (ISM–MICMAC) approach.

This study identifies, on the basis of extant literature and experts’ opinion, ten barriers to female entrepreneurship. These barriers were ranked, and causal relationships among them established using the ISM–MICMAC approach. On the basis of ranking, women can move forward in MSMEs after removing these obstacles and it will have good results.

In this research, with literature reviews and experts opinion, ten barriers have been identified for women’s entrepreneurship and have been used to build the model.

To bring Indian women forward in the field of entrepreneurship, both the society and the government should work together, and efforts should be made to overcome the obstacles coming in the way of entrepreneurs.

Female entrepreneurship in India faces many problems including negative attitude of authorities and society toward women. The society and authorities have no format or model for Indian women to move forward in the entrepreneurship sector.

This study seeks to identify, on the basis of a thorough review of literature and expert opinion, major barriers to female entrepreneurship in the context of Indian MSMEs.

The paper aims to evaluate how progressive stakeholders view the adoption of contemporary techniques such as virtual technology in driving sustainable quality in an emerging economy context.

The authors adopted a systematic literature review to develop the theoretical framework for virtual reality (VR) technology adoption in sustaining quality in agriculture production. The framework was refined after discussion with a panel of academic experts. The refined theoretical framework was further empirically validated using Partial Least Square Structure Equation Modelling.

The study focuses on the future perspective of the perception for progressive farming with the adoption of VR technology in an emerging economy. The data were collected from the stakeholders (farmers, collectives, cooperative, etc.), for their future perspectives for the adoption of VR technology and sustainable quality agriculture production. The study may help build up VR technology in emerging economies which may take years to be established.

The perception of the future perspective of VR technology study conducted has limitations. The findings are well established on technology adoption; however, the technology used will take many extra years to find its application in the agriculture sector. The study offers insightful theoretical, managerial and policy implications for sustainable quality in agriculture production through the adoption of virtual reality (VR) technology. The authors found very few works that focused on VR technology adoption.

The study discusses VR, which has an impact on sustaining the quality of agriculture production. The study has notable managerial and policy implications that suggest the future perspective for VR technology in agriculture production. The study is an unexplored area that needs research to capture future perspectives.

The study aims at evaluating the most appropriate transport project which is one of the critical concerns of transport infrastructure scheduling. This process will be applied considering a set of criteria and discussed alternatives with sustainable perspectives.

In this paper, a complex proportional assessment (COPRAS) framework is discussed to handle the sustainable transport investment project (STIP) assessment problem within a single-valued neutrosophic set (SVNSs). To form the procedure more useful in handling with uncertain features, a SVNS is applied as a valuable procedure to handle uncertainty. First, a new discrimination measure for SVNSs is introduced and discussed some elegant properties to determine the significance degree or weight values of criteria with the sustainabality perspectives. Second, an integrated approach is introduced based on the discrimination measure and the COPRAS method on SVNSs and named as SVN-COPRAS.

A case study of an STIP evaluation problem is used to confirm the practicality and effectiveness of the SVN-COPRAS framework. Lastly, comparative discussion and sensitivity investigation are illustrated to prove the strength and solidity of the proposed framework.

The SVNSs enrich the essence of linguistic information when a decision expert (DE) vacillates among different linguistic values (LVs) to measure a sustainable transport project alternative problem. The utilization of SVNSs provides a more stable procedure to describe DEs' evaluations. So, an elegant methodology is developed to incorporate the DEs' awareness and experience for electing the desired STIPs. The introduced methodology has higher operability than the single-valued neutrosophic set technique for order preference by similarity to an ideal solution (SVN-TOPSIS) procedure during the larger numbers of attribute(s) or option(s). For the SVN-COPRAS methodology, there is no need to estimate the single-valued neutrosophic ideal solution (SVN-IS) and single-valued neutrosophic anti-ideal solution (SVNA-IS). The outcomes are calculated with handling the realistic data, which elucidates that the introduced model can tackle more intricate and realistic multi-criteria decision-making issues.

The purpose of this paper is to investigate the effect of corrugation, wave number, initial stress and the heterogeneity of the media on the phase velocity of the Love-type wave. Moreover, the paper aims to have a comparative study of the presence and absence of anisotropy, heterogeneity, corrugation and initial stress in the half-space, which serve as a focal theme of the study.

The present paper modelled the propagation of the Love-type wave in a corrugated heterogeneous monoclinic layer lying over an initially stressed heterogeneous transversely isotropic half-space. The method of separation of variables is used to procure the dispersion relation.

The closed form of dispersion relation is obtained and found to be in well agreement to the classical Love wave equation. Neglecting the corrugation at either of the boundary surfaces, expressions of the phase velocity of the Love-type wave are deduced in closed form as special cases of the problem. It is established through the numerical computation of the obtained relation that the concerned affecting parameters have significant impact on the phase velocity of the Love-type wave. Also, a comparative study shows that the anisotropic case favours more to the phase velocity as comparison to the isotropic case.

Although many attempts have been made to study the effect of corrugated boundaries on reflection and refraction of seismic waves, but the effect of corrugated boundaries on the dispersion of surface wave (which are dispersive in nature) propagating through mediums pertaining various incredible features still needs to be investigated.

This paper aims to review the recent advances in processing and utilization of Madhuca longifolia flowers to address its potential as an industrial ingredient.

The paper analyzes the harvesting practices of flowers and recent works on the value addition.

Mahua flowers are rich source of natural sugars (glucose, fructose, sucrose, etc.) and hence are deliberately used for liquor production by tribal besides various food products, namely, Mahua ladoo, barfi, kheer, sweet puri and as grain staple. Mahuain medicine has been curing people since ages such as in rakhtpitta, diarrhoea and skin diseases and as aphrodisiac, galactagogue, carminative, antihelmenthic, antibacterial and antioxidant. Mahua candy, cake, ready to serve beverages, toffee, squash, ladoo, bars, etc. have been developed as value-added products. However, such a wonderful nature’s gift remains underused due to post harvest spoilage.

Improvement in storage facilities and processing of flowers after harvesting and drying will lead to enhanced availability of flowers for industrial purposes for food, feed and fodder. More value-added products can be prepared by the preparation of flower-juice concentrate, as well as efforts are made to produce powder from the flowers.

Post-harvest spoilage of Mahua flowers due to improper collection and handling practices, and filthy storage conditions is the major limitation of Mahua flowers to be used as a potential industrial ingredient. An improvement in collection, handling and pre-processing practices can diversify its use from liquor production to various value-added and functional food products at an industrial scale.

This paper aims to delve into the critical aspect of supplier selection in the healthcare sector, emphasizing the significance of strategic sourcing in enhancing operational efficiency and quality of services. The primary aim is to develop a comprehensive framework for supplier evaluation that aligns with the unique requirements of hospitals, ultimately improving procurement processes and patient care outcomes.

The study leverages the renowned Carter’s 7 C model as a foundational framework for supplier assessment, supplemented by insights gathered from interviews with experts in the New Product Introduction, Purchasing and Procurement departments of a leading hospital in India. Data collection involved a combination of primary interactions through Google Forms and secondary data extraction from Purchase Inquisition Brochures and Hospital Information Systems. The weighted average method was employed to determine the significance of various criteria based on expert recommendations, ensuring a fair and consensus-driven evaluation process.

Through the synthesis of expert inputs and data analysis, the study unveils a nuanced set of criteria weights that guide supplier selection decisions in the healthcare setting. The research highlights the dynamic nature of supplier evaluation criteria, underscoring the importance of tailoring assessments to suit the specific needs of each hospital. By emphasizing effective communication, technological advancements and collaborative supplier relationships, the study underscores the potential for strategic supplier selection to optimize supply chains, drive innovation and enhance patient care delivery in the healthcare sector.

The framework for supplier selection in the healthcare sector has limitations, including limited generalizability, subjectivity in expert opinions and a static framework. The framework assumes the constant importance of selection criteria over time, which could be affected by dynamic changes in the industry. Its focus on the healthcare sector may require adaptation to other sectors.

For hospitals, it also supports cost optimization by focusing on critical variables like cost efficiency and quality. For suppliers, the framework provides clear expectations, performance benchmarking and collaborative growth. It encourages performance benchmarking and encourages collaboration between the hospital and its supply chain partners. The framework is a replicable model that can be adapted by other hospitals or organizations to optimize supplier selection processes. It promotes standardization in supplier evaluation, fostering consistency across the sector. For patients, the framework improves care delivery by ensuring reliable access to high-quality supplies and services.

This research intends to provide a novel framework for the classification of suppliers in the healthcare sector for operational excellence which enhances the strategic sourcing decision in the domain.