Purpose – The aim of this paper is to present a model in which the relationship between Muslims’ involvement with traveling to Islamic destinations and Islamic destination brand equity is investigated. Design/methodology/approach – Based on the existing theoretical and empirical research on involvement and brand equity in tourism marketing and the literature on Muslim tourists’ needs and culture, a conceptual model for Muslim tourists is developed. The model investigates the relationships between Muslims’ psychological motivations for traveling to Islamic destinations and the evaluation of destination Islamic brand. Findings – The study shows that the more Muslims are involved in traveling to Islamic destinations, the more likely they evaluate the key dimensions of destination Islamic brand. This is demonstrated by the influence of Muslims’ involvement on their awareness of Islamic destinations, their image of the Islamic destination attributes, the perceived quality of Islamic offerings, the perceived Islamic value and their loyalty toward Islamic destinations. Practical implications – The study evaluates the Islamic brand equity in the context of Islamic tourism destinations and in relation to Muslims’ interests in traveling to Islamic countries. The study contributes to better understand the Islamic destinations and how to maximize the benefits of their Islamic attributes. It is suggested that Islamic attributes should be highlighted more for Muslim tourists interested in traveling to Islamic countries. Investigating the concepts analyzed will help tourism destinations to integrate marketing and promotional campaigns and build a more powerful Islamic brand in Muslim markets. Originality/value – The relationship between involvement and brand equity has not been yet explored adequately, especially in the context of Islamic branding. This study adds to the previous studies in which the link between personal involvement with a specific destination and destination brand equity was explored. The role of Islamic values in this relationship is highlighted. The study contributes to destination branding studies by being one of the primary works, which applies the concept of brand equity to Islamic destinations.

Overall, the study makes a significant contribution to healthcare organizations, better health outcomes for patients and better quality of life for the community.

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The prediction of heart disease is one of the areas where machine learning can be implemented. Optimization algorithms have the advantage of dealing with complex non-linear problems with a good flexibility and adaptability. In this paper, we exploited the Fast Correlation-Based Feature Selection (FCBF) method to filter redundant features in order to improve the quality of heart disease classification. Then, we perform a classification based on different classification algorithms such as K-Nearest Neighbour, Support Vector Machine, Naïve Bayes, Random Forest and a Multilayer Perception | Artificial Neural Network optimized by Particle Swarm Optimization (PSO) combined with Ant Colony Optimization (ACO) approaches. The proposed mixed approach is applied to heart disease dataset; the results demonstrate the efficacy and robustness of the proposed hybrid method in processing various types of data for heart disease classification. Therefore, this study examines the different machine learning algorithms and compares the results using different performance measures, i.e. accuracy, precision, recall, f1-score, etc. A maximum classification accuracy of 99.65% using the optimized model proposed by FCBF, PSO and ACO. The results show that the performance of the proposed system is superior to that of the classification technique presented above.

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Purpose In particular, this paper aims to systematically analyze a few prominent wireless sensor network (WSN) clustering routing protocols and compare these different approaches according to the taxonomy and several significant metrics. Design/methodology/approach In this paper, the authors have summarized recent research results on data routing in sensor networks and classified the approaches into four main categories, namely, data-centric, hierarchical, location-based and quality of service (QoS)-aware, and the authors have discussed the effect of node placement strategies on the operation and performance of WSNs. Originality/value Performance-controlled planned networks, where placement and routing must be intertwined and everything from delays to throughput to energy requirements is well-defined and relevant, is an interesting subject of current and future research. Real-time, deadline guarantees and their relationship with routing, mac-layer, duty-cycles and other protocol stack issues are interesting issues that would benefit from further research.

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