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The purpose of this paper is to provide a way to analyze satellite images using various clustering algorithms and refined bitplane methods with other supporting techniques to prove the superiority of RIFCM.

A comparative study has been carried out using RIFCM with other related algorithms from their suitability in analysis of satellite images with other supporting techniques which segments the images for further process for the benefit of societal problems. Four images were selected dealing with hills, freshwater, freshwatervally and drought satellite images.

The superiority of the proposed algorithm, RIFCM with refined bitplane towards other clustering techniques with other supporting methods clustering, has been found and as such the comparison, has been made by applying four metrics (Otsu (Max-Min), PSNR and RMSE (40%-60%-Min-Max), histogram analysis (Max-Max), DB index and D index (Max-Min)) and proved that the RIFCM algorithm with refined bitplane yielded robust results with efficient performance, reduction in the metrics and time complexity of depth computation of satellite images for further process of an image.

For better clustering of satellite images like lands, hills, freshwater, freshwatervalley, drought, etc. of satellite images is an achievement.

The existing system extends the novel framework to provide a more explicit way to analyze an image by removing distortions with refined bitplane slicing using the proposed algorithm of rough intuitionistic fuzzy c-means to show the superiority of RIFCM.

In recent times, there has been a lot of research focused on performance measurement (PM) in project-based sectors. However, there are very few studies that were reported on the significance of PM in the construction sector. Keeping track of an organization in achieving organizations goals and objectives seems an important way. One of the major challenges faced by the industry is unavailable of an appropriate PM system for assessing organizational performance. Most of the PM approaches consider the traditional project triangle assessment of project success. Based on the limitations identified in existing PM models, the purpose of this paper is to develop a comprehensive PM model, i.e. Modified Project Quarter Back Rating (MPQR) applicable for construction projects.

A detailed list of performance areas as a method for PM is analyzed in the construction industry context. Also, industry-specific professionals conducted semi-structured interviews to assess whether these performance areas are sufficient to measure and understand the PM systems.

The research finding focuses on developing the MPQR model that considers both financial and non-financial areas for performance assessment to provide a holistic assessment of project performance.

MPQR model provides an opportunity to set the benchmark for overall performance for construction organizations.

The findings of the study are expected to provide guidelines to construction professionals for implementing the performance model that will improve performance in the construction industry.

Gives a bibliographical review of the finite element methods (FEMs) applied for the linear and nonlinear, static and dynamic analyses of basic structural elements from the theoretical as well as practical points of view. The range of applications of FEMs in this area is wide and cannot be presented in a single paper; therefore aims to give the reader an encyclopaedic view on the subject. The bibliography at the end of the paper contains 2,025 references to papers, conference proceedings and theses/dissertations dealing with the analysis of beams, columns, rods, bars, cables, discs, blades, shafts, membranes, plates and shells that were published in 1992‐1995.

The purpose of this paper is to analyze various properties of anatase titanium dioxide (TiO₂) nanoparticles. Further, it proposes to implement Linear Combinations of Atomic Orbitals (LCAO) basis set under the framework of density functional theory and outline how LCAO is able to provide improved results in terms of various mechanical properties rather than plane wave and other theoretical results.

This paper provides an exploratory study on anatase TiO₂ by implementing OLCAO–DFT–LDA–LBFGS–EOS–PZ algorithms to find out various ground-level properties. The data so obtained are complemented by various analysis using mathematical expressions, description of internal processes occurred and comparison to others’ analytical results.

The paper provides some empirical insights on how mechanical properties of anatase TiO₂ improved by implementing LCAO methodology. From the analysis of electronic properties, it is seen that the anatase TiO₂ supports the inter band indirect transition from O-2p in valence region to Ti-3d in the conduction region.

Most of the electronic properties are underestimated because a single exchange-correlation potential is not continuous across the gap. This gap can be enhanced by implementing Green’s function in place of DFT and the other way is to implement self-interaction correction.

The use of anatase TiO₂ is primarily used for catalytic applications. This is also used to enhance the quality of paper in the paper industry. Additionally, this is used as a prime ingredient in cosmetic industry.

This paper fulfills an identified need to study how LCAO, another basis set, plays an important role in improving material properties.

The purpose of this paper is to develop a qualitative framework for the selection of the most appropriate optimization algorithm for the multi-objective trade-off problem (MOTP) in construction projects based on the predefined performance parameters.

A total of 6 optimization algorithms and 13 performance parameters were identified through literature review. The experts were asked to indicate their preferences between each pair of optimization algorithms and performance parameters. A multi-criteria decision-making tool, namely, consistent fuzzy preference relation was applied to analyze the responses of the experts. The results from the analysis were applied to evaluate their relative weights which were used to provide a ranking to the algorithms.

This study provided a qualitative framework which can be used to identify the most appropriate optimization algorithm for the MOTP beforehand. The outcome suggested that non-dominated sorting genetic algorithm (NSGA) was the most appropriate algorithm whereas linear programming was found to be the least appropriate for MOTPs.

The devised framework may provide a useful insight for the construction practitioners to choose an effective optimization algorithm tool for preparing an efficient project schedule aiming toward the desired optimal improvement in achieving the various objectives. Identification of the absolute best optimization algorithm is very difficult to attain due to various problems such as the inherent complexities and intricacies of the algorithm and different class of problems. However, the devised framework offers a primary insight into the selection of the most appropriate alternative among the available algorithms.

The research aims to establish importance scheme of geospatial factors for land valuation activities that may serve as an eye-opener and aid the concerned government agencies in drafting land valuation policies and guidelines to achieve a sound land governance and administration. It specifically identifies and weighs geospatial valuation factors to establish their importance.

The research involves discussions and survey questionnaires given to land experts (i.e. appraisers, environmental planners, land economist, geodetic engineers and assessors) who indicated their opinions on influence of geospatial factors on land value. The analytic hierarchy process (AHP) is then used to weigh the factors in terms of its importance.

The result was then compared with the multiple regression analysis (MRA) taking into consideration the standardized regression coefficient of the 15 factors. The AHP method found out the major road accessibility and slope direction as the most and least influential factors, respectively, while surprisingly MRA found major road accessibility not significant at p < 0.05 level of significance.

The research generally reflects the sub-urban type of study area; hence, inclusion of other road types such as express ways and subways and performing sensitivity analysis of AHP are suggested in future studies.

The findings of the study will provide information of concerned government agencies in improving valuation activities, as well as to update values regularly based on the geospatial factors.

To the best of the authors’ knowledge, this study is the first effort to rank geospatial factors with analytic hierarchy analytic process that further considered both their negative and positive influences on land value. The approach surmounts the flaw and shortcomings of empirical methods of identifying importance of factors.

This study aims to evaluate the role of personality in digital library systems (DLS) adoption intention among Generation Z (Gen-Z) students. The study uses the unified theory of acceptance and use of technology-2 and the five-factor model to investigate personality’s influence on Gen-Z’s DLS adoption intention.

The study is a descriptive causal investigation based on primary data collected through a self-administered survey using pre-validated tools. The study uses structural equation modeling to investigate personality dimensions’ direct and moderating effect on the dependent, independent variables and their relation.

The study results indicate that personality has no significant influence on Gen-Z’s DLS adoption, suggesting the ubiquity and inevitability of technology in current times. Also, only performance expectancy had a considerable impact on DLS adoption among Gen-Z going to college – a deviation from past studies where multiple independent variables have influenced DLS adoption when examined from different technology adoption model angles.

The current research is done on Gen-Z, and thus the results are ideographic to the cohort.

The results of the study can be used to effectively design and communicate technology-enabled information solutions among the Cohort.

The results of the study help better understand the factors affecting the technology adoption intentions of Gen-Z. Such understanding can help in better design and implementation of technology-enabled solutions for the cohort, maximizing such system adoption and its effective and efficient utilization.

The study explores the impact of personality on DLS adoption intentions, hitherto unexplored. The research also focuses on Gen-Z – a cohort born in a technology-enabled world whose attitude and preferences towards technology might differ. The study’s findings will help understand the influence of personality on DLS adoption among the Gen-Z and can be used to design, promote and evaluate such systems.

The purpose of the paper is to highlight the role of Artificial Intelligence (AI) in the healthcare industry through the Ayushman Bharat health protection scheme by analyzing various technologies being integrated to improve the customer service and experiences in India. The key focus lies on the understanding of the influence of AI in the healthcare system services, the clinical treatment, and the facilities to progress with accurate and precise health screening in India.

A systematic study on the emerging technologies of AI and the applications in the healthcare sector is presented in the form of a viewpoint.

AI certainly enhances experiential services; however, it cannot surpass the human touch which is an essential determinant of experiential healthcare services. AI acts as an effective complementary dimension to the future of healthcare.

This viewpoint discusses the applications and role of AI with the help of relevant examples. It highlights the different technologies being applied and how they will be used in the future focusing upon the Ayushman Bharat health protection scheme in India.

The study aims to examine the customers' revisit intention toward the green restaurants after service failure based upon service failure attributions. The study further intends to investigate the moderating effect of green self-identity on customers' post-service failure behavioral intentions.

A self-administered questionnaire was distributed to 327 participants who had experienced service failure while dining in green restaurants. The study draws upon the prevailing literature to examine the relationship among the constructs using structural equation modeling (SEM).

The findings of the study have confirmed that service failure has an adverse effect on customers' revisit intention toward the green restaurants. However, customers with green self-identity appear less anxious about service failure as findings indicate customers revisit green restaurant even after service failure.

The study provides a clear indication to the managers of the green restaurants that a better understanding of service failure attributions may facilitate in preventing service failure in a prompt and reasonable manner. It will not only contribute to building the brand reputation, but also ensure that customers stay with the brand for a longer duration.

The study is unique in a way that it is the first of its type to establish a relationship between service failure attributions and customer satisfaction in the emerging South Asian market, such as India in the context of green restaurants. Besides, this is the only study to use green self-identity as a moderator between the relationships of customer satisfaction and revisit intention.

Advanced bibliometric methods have emerged as key tools in mapping the history and trends of a discipline. This paper aims to demonstrate on applying various bibliometric methods to track a journal’s impact and review its knowledge contribution. In doing so, the authors take the case of IIMB Management Review (IMR) journal focused on management discipline, in consideration of its 10 years of publication presence.

Using bibliometric and Scopus metric methods, the authors map and analyze the productivity of IMR Journal and map its knowledge contributions.

The authors identify the IMR journal’s impact, its growth, the most prolific authors/affiliations, key research hotspots, cross-country collaboration and emerging trends over the past decade.

A 10-year longitudinal review helps the target group identify the main themes. It also provides key empirical insights to the journal editorial board and library managers for future planning and growth of the journal.