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Brain tumor segmentation and classification is the interesting area for differentiating the tumorous and the non-tumorous cells in the brain and classifies the tumorous cells for identifying its level. The methods developed so far lack the automatic classification, consuming considerable time for the classification. In this work, a novel brain tumor classification approach, namely, harmony cuckoo search-based deep belief network (HCS-DBN) has been proposed. Here, the images present in the database are segmented based on the newly developed hybrid active contour (HAC) segmentation model, which is the integration of the Bayesian fuzzy clustering (BFC) and the active contour model. The proposed HCS-DBN algorithm is trained with the features obtained from the segmented images. Finally, the classifier provides the information about the tumor class in each slice available in the database. Experimentation of the proposed HAC and the HCS-DBN algorithm is done using the MRI image available in the BRATS database, and results are observed. The simulation results prove that the proposed HAC and the HCS-DBN algorithm have an overall better performance with the values of 0.945, 0.9695 and 0.99348 for accuracy, sensitivity and specificity, respectively.

The proposed HAC segmentation approach integrates the properties of the AC model and BFC. Initially, the brain image with different modalities is subjected to segmentation with the BFC and AC models. Then, the Laplacian correction is applied to fuse the segmented outputs from each model. Finally, the proposed HAC segmentation provides the error-free segments of the brain tumor regions prevailing in the MRI image. The next step is to extract the useful features, based on scattering transform, wavelet transform and local Gabor binary pattern, from the segmented brain image. Finally, the extracted features from each segment are provided to the DBN for the training, and the HCS algorithm chooses the optimal weights for DBN training.

The experimentation of the proposed HAC with the HCS-DBN algorithm is analyzed with the standard BRATS database, and its performance is evaluated based on metrics such as accuracy, sensitivity and specificity. The simulation results of the proposed HAC with the HCS-DBN algorithm are compared against existing works such as k-NN, NN, multi-SVM and multi-SVNN. The results achieved by the proposed HAC with the HCS-DBN algorithm are eventually higher than the existing works with the values of 0.945, 0.9695 and 0.99348 for accuracy, sensitivity and specificity, respectively.

This work presents the brain tumor segmentation and the classification scheme by introducing the HAC-based segmentation model. The proposed HAC model combines the BFC and the active contour model through a fusion process, using the Laplacian correction probability for segmenting the slices in the database.

This paper aims to determine the implications of Covid-19 on the livelihood of marine fishermen. It gives a concrete picture of how vulnerable communities like marine fishermen are affected due to the lockdown policies. The paper examines these communities' present status and the extent of vulnerability during the post-Covid period.

The study uses an exploratory research design to find the solution to the research problem. 298 samples were collected and analysed within a sustainable livelihood theoretical framework. The scope of the study is limited to marine fishermen in Kerala, residing in six districts out of the nine coastal districts. The impact of the lockdown on income was analysed using paired t-test and results linked with the theory.

The study has done an empirical analysis for three periods: before lockdown, lockdown and after lockdown, to identify the impact of lockdown on marine fishermen. The study's significant findings are that these fishermen's livelihood is at risk during the post-lockdown period, and many families are moving into a “debt-trap”.

Policymakers can develop appropriate policy strategies to enhance the livelihood assets of vulnerable communities to include them in a sustainable framework.

Only a few studies are highlighting the impact of Covid-19 on vulnerable communities in India. The effects of climate change on the marine ecosystem are already endangering marine fisher folks' livelihoods. In this light, it is vital to study the extent of the impact of income shock on the livelihood assets of marine fishermen due to the lockdown policy implemented in the State to prevent the spread of Covid-19.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-03-2023-0192

In this article, the elementary notions and aggregation operations of single-valued neutrosophic parameterized complex fuzzy hypersoft set (sv-NPCFHSS) are characterized initially. Then by using matrix version of sv-NPCFHSS, a decision-support system is constructed for the evaluation of real estate residential projects by observing various risk factors.

Two approaches are utilized in this research: set-theoretic approach and algorithmic approach. The first approach is used to investigate the notions of sv-NPCFHSS and its some aggregations whereas the second approach is used to propose an algorithm for designing its decision-support system by using the aggregation operations like reduced fuzzy matrix, decision matrix, etc. of sv-NPCFHSS. The adopted algorithm is validated in real estate scenario for the selection of residential project by observing various risk factors to avoid any expected investment loss.

The proposed approach is more flexible and reliable as it copes with the shortcomings of literature on sv-neutrosophic set, sv-neutrosophic soft set and other fuzzy soft set-like structures by considering hypersoft setting, complex setting and neutrosophic setting collectively.

It has limitations for complex intuitionistic fuzzy hypersoft set, complex neutrosophic hypersoft set and other complex neutrosophic hypersoft set-like models.

The scope of this research may cover a wide range of applications in several fields of mathematical sciences like artificial intelligence, optimization, MCDM, theoretical computer science, soft computing, mathematical statistics etc.

The proposed model bears the characteristics of most of the relevant existing fuzzy soft set-like models collectively and fulfills their limitations.

The objective of this paper is to understand the relationships between service quality, perceived value and satisfaction because several studies endeavored to model these linkages. It is important to test these relationships with loyalty and word-of-mouth (WOM). Thus, it is important to test these relationships in the insurance sector since the relationship between these variables and WOM has not been studied in insurance.

This investigation proposes a theoretical model tested using structural equation modeling (SEM). A questionnaire survey was developed to explore the relationships among service quality, perceived value, satisfaction, loyalty and WOM. For this study, 744 valid questionnaires were collected from a sample of Portuguese car insurance holders.

The results revealed that service quality has a direct relationship with perceived value and satisfaction. In turn, perceived value has a direct relationship with satisfaction. Perceived value and satisfaction influence loyalty and WOM. Finally, loyalty influences WOM.

This investigation examines the mediating role of perceived value and satisfaction in the relationship between service quality (facility and interactive) and loyalty and WOM in the insurance industry. It fills a gap in the literature by exploring the variables that lead to positive WOM in the insurance industry; the authors do not know any study that links these variables with WOM. Also, the relationship between loyalty and WOM has been poorly studied, although it is well known that in services, loyal customers speak well of the companies. Thus, the authors try to fill this gap in the academic literature by analyzing these relationships.

This study, rooted in affordance-actualization theory and communication theory, aims to critically examine how ChatGPT influences users’ transition from new adopters to loyal advocates within the context of travel decision-making. It incorporates constructs including communication quality, personalization, anthropomorphism, cognitive and emotional trust (ET), loyalty and intention to adopt into a comprehensive model.

This study used quantitative methods to analyze data from 477 respondents, collected online through a self-administered questionnaire by Embrain, a leading market research company in South Korea. Lavaan package within R studio was used for evaluating the measurement model through confirmatory factor analysis and using structural equation modeling to examine the proposed hypotheses.

The findings reveal a pivotal need for enhancing ChatGPT’s communication quality, particularly in terms of accuracy, currency and understandability. Personalization emerges as a key driver for cognitive trust, while anthropomorphism significantly impacts ET. Interestingly, the study unveils that in the context of travel recommendations, users’ trust in ChatGPT predominantly operates at the cognitive level, significantly impacting loyalty and subsequent adoption intentions.

The findings of this research provide valuable insights for improving Generative AI (GenAI) technology and management practices in travel recommendations.

As one of the few empirical research papers in the burgeoning field of GenAI, this study proposes a highly explanatory model for the process from affordance to actualization in the context of using ChatGPT for travel recommendations.

Induction heating applications aided by power electronic control have become very attractive in the recent past. For cooking applications, power electronics circuits are very suitable to feed power to multi loads with an appropriate control technique. The purpose of this paper is to develop a three leg inverter to feed power to three loads simultaneously and independently.

Pulse density modulation control technique is used to control the output power independently with constant switching frequency.

Multi-load handling converter with independent power control is achieved with reduced number of switching devices (two switches/per load) with simple control strategy.

The proposed system is simulated in MATLAB/Simulink, and the thermal analysis is carried out in COMSOL multi-physics software. The hardware realisation is performed for a 1 kW prototype with 20 kHz switching frequency and 10 kHz pulse density modulation frequency. PIC16F877A microcontroller is used to validate the experimental results for various values of control signals (D_PDM). The simulation and experimental results are in good agreement and validates the developed system.

The conflicting results on the corrosion characteristics of aluminium matrix composites reinforced with agrarian waste have stimulated an investigation on the hardness and corrosion rate of sugar palm fibre ash (SPFA) reinforced LM26 Al/alloy composite by varying the SPFA from 0 to 10 wt% in an interval of 2 wt%. This paper aims to discuss the aforementioned issue.

The composites were produced via stir-casting and the hardness was determined using a Vickers hardness testing machine, corrosion rate was examined through the weight loss method by immersion in 0.5, 1.0 and 1.5 M hydrochloric acid (HCl) at temperatures of 303, 318, and 333 K for the maximum duration of 120 h. The morphological study was conducted using a scanning electron microscope (SEM) on the samples before and after immersion in HCl.

The incorporation of SPFA improved the hardness of the alloy from 58.22 to 93.62 VH after 10 wt% addition. The corrosion rate increases with increased content of SPFA, the concentration of HCl and temperature. The least corrosion rate of 0.0272 mpy was observed for the LM26 Al alloy in 0.5 M after 24 h while the highest corrosion rate of 0.8511 mpy was recorded for LM26 Al/10 wt% SPFA in 1.5 M HCl acid after 120 h. The SEM image of corroded samples revealed an increased number of pits with increased SPFA content.

The work is limited to SPFA up to 10 wt% as reinforcement in LM26 Al alloy, the use of HCl as corrosion medium, temperatures in the range of 303–333 K, and a weight loss method were used to evaluate the corrosion rate.

The corrosion rate was determined for LM26 Al/SPFA composites with various amounts of SPFA in 0.5, 1.0 and 1.5 M HCl at 303, 318 and 333 K and compared with the matrix alloy.

The purpose of this paper is to illustrate an Inclusive Digital Literacy Framework for vulnerable populations in rural areas under the Digital India program. Key challenges include addressing multiple literacies such as health literacy, financial literacy and eSafety for low-literate learners in low-resource settings with low internet bandwidth, lack of ICT facilities and intermittent electricity.

This research implemented an educational model based on the proposed framework to train over 1,000 indigenous people using an integrated curriculum for digital literacies at remote settlements. The model uses mobile technology adapted for remote areas, context enabled curriculum, along with flexible learning schedules.

The education model exemplifies a viable strategy to overcome persistent challenges by taking tablet-based digital literacies directly to communities. It engages different actors such as existing civil societies, schools and government organizations to provide digital literacy and awareness thereby improving both digital and life skills. It demonstrates the potential value of a comprehensive Digital Literacy framework as a powerful lever for Digital Inclusion.

Policy makers can use this transformational model to extend the reach and effectiveness of Digital Inclusion through the last mile enhancing existing training and service centers that offer the traditional model of Digital Literacy Education.

This innovative mobile learning model based on the proposed Digital Framework for Inclusion instilled motivation, interest and confidence while providing effective digital training and conducting exams directly in the tribal settlements for low-literate learners in remote settings. Through incorporating multiple literacies, this model serves to empower learners, enhance potential, improve well-being and reduce the risk of exploitation.

The purpose of this paper is to develop an economic model, which could determine the acceptance sampling plan that minimizes the quality cost for batch manufacturing.

The authors propose a variable sampling plan based on one-sided capability indices for dealing with the quality cost requirement.

The total quality cost is much more sensitive to process capability indices and inspected cost than internal and external failure costs.

The experimental data were randomly generated instead of real world ones.

The proposed model is specifically designed for manufacturing industries with high sampling cost.

The one-sided capability indices were utilized for the first time to be suitable for the purpose.

This paper aims to automate the welding operation that motion control, sensor integration and coordination with the welding power source. Therefore, there is a need for sophisticated technologies to control precisely the process in terms of positioning the welding torch, and controlling the welding parameters through the use of correct devices which are aided by appropriate control tools and techniques.

A new seam tracking methodology, named sewing technique, has been introduced for the welded joints available in computer-aided design (CAD) environment. This methodology gives the seam path by drawing a line through the adjacent centroids of curve fitted in the weld joint volume. Obtained geometric path and kinematic constraints are given as input to the modeled robot for performing welding operation followed by desired trajectory.

In this investigation, a novel and efficient weld seam technique has been developed to produce uniform welded joints. The key feature of this approach is that the initial and end positions of the weld seams can be obtained easily. Because of this, the robot can be controlled flexibly during welding operation.

This investigation deals with the development of an automated seam tracking methodology for the welded joints available in CAD environment. Validation of the developed methodology has been done through simulation results while performing welding operations for different weld profiles.