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Health-care ontologies and their terminologies play a vital role in knowledge representation and data integration for health information. In health-care systems, Internet of Technology (IoT) technologies provide data exchange among various entities and ontologies offer a formal description to present the knowledge of health-care domains. These ontologies are advised to assure the quality of their adoption and applicability in the real world.

Ontology assessment is an integral part of ontology construction and maintenance. It is always performed to identify inconsistencies and modeling errors by the experts during the ontology development. A smart health-care ontology (SHCO) has been designed to deal with health-care information and IoT devices. In this paper, an integrated approach has been proposed to assess the SHCO on different assessment tools such as Themis, Test-Driven Development (TDD)onto, Protégé and OOPs! Several test cases are framed to assess the ontology on these tools, in this research, Themis and TDDonto tools provide the verification for the test cases while Protégé and OOPs! provides validation of modeled knowledge in the ontology.

As of the best knowledge, no other study has been presented earlier to conduct the integrated assessment on different tools. All test cases are successfully analyzed on these tools and results are drawn and compared with other ontologies.

The developed ontology is analyzed on different verification and validation tools to assure the quality of ontologies.

This paper proposed a bi-level mathematical model for location, routing and allocation of medical centers to distribution depots during the COVID-19 pandemic outbreak. The developed model has two players including interdictor (COVID-19) and fortifier (government). Accordingly, the aim of the first player (COVID-19) is to maximize system costs and causing further damage to the system. The goal of the second player (government) is to minimize the costs of location, routing and allocation due to budget limitations.

The approach of evolutionary games with environmental feedbacks was used to develop the proposed model. Moreover, the game continues until the desired demand is satisfied. The Lagrangian relaxation method was applied to solve the proposed model.

Empirical results illustrate that with increasing demand, the values of the objective functions of the interdictor and fortifier models have increased. Also, with the raising fixed cost of the established depot, the values of the objective functions of the interdictor and fortifier models have raised. In this regard, the number of established depots in the second scenario (COVID-19 wave) is more than the first scenario (normal COVID-19 conditions).

The results of the current research can be useful for hospitals, governments, Disaster Relief Organization, Red Crescent, the Ministry of Health, etc. One of the limitations of the research is the lack of access to accurate information about transportation costs. Moreover, in this study, only the information of drivers and experts about transportation costs has been considered. In order to implement the presented solution approach for the real case study, high RAM and CPU hardware facilities and software facilities are required, which are the limitations of the proposed paper.

The main contributions of the current research are considering evolutionary games with environmental feedbacks during the COVID-19 pandemic outbreak and location, routing and allocation of the medical centers to the distribution depots during the COVID-19 outbreak. A real case study is illustrated, where the Lagrangian relaxation method is employed to solve the problem.

This paper aims to propose a novel computational framework called EvoPOL (EVOlving POLicies) to support governmental policy analysis in restricting recruitment of smokers. EvoPOL is a fuzzy inference‐based decision support system that uses an evolutionary algorithm (EA) to optimize the if‐then rules and its parameters. The performance of the proposed method is compared with a fuzzy inference method adapted using neural network learning technique (neuro‐fuzzy).

EA is a population‐based adaptive method, which may be used to solve optimization problems, based on the genetic processes of biological organisms. The Takagi‐Sugeno fuzzy decision support system was developed based on three sub‐systems: fuzzification, fuzzy knowledge base (if‐then rules) and defuzzification. The fine‐tuning of the fuzzy rule base and membership function parameters is achieved by using an EA.

The proposed EvoPOL technique is simple and efficient when compared to the neuro‐fuzzy approach. However, EvoPOL attracts extra computational cost due to the population‐based hierarchical search process. When compared to neuro‐fuzzy model the error values on the test sets have improved considerably. Hence, when policy makers require more accuracy EvoPOL seems to be a good solution.

When policy makers require more accuracy EvoPOL seems to be a good solution. For complicated decision support systems involving more input variables, EvoPOL would be an excellent candidate for framing if‐then rules with precise decision scores that could help the government representatives as to what extent to concentrate on available social regulation measures in restricting the recruitment of smokers.

Introduction: Decision making is always based on several factors which may affect the possible outcomes, especially in financial markets. Instead of having many criteria which may be required for decision making, “Multiple Criteria Decision Making” (MCDM) models might be used as a tool to reduce all criteria into a single one.

Purpose: The aim of this study is to measure the financial performance of commercial banks listed on Borsa Istanbul (BIST) by the MCDM.

Method: To this end, data from 15 different financial ratios from 11 commercial banks were used between the periods of 2002 and 2018. Both TOPSIS and gray relational analysis (GRA) models were used, which are commonly used in the literature for detecting the financial performance of listed banks in BIST based on their consolidated financial statements.

Results: According to the TOPSIS method, while the best bank is QNB Finansbank, HALKB, a public bank, was determined as the best bank using the GRA method. There is no significant correlation between financial performance indicators and market returns obtained by either method, with exceptions. There is no generally significant correlation detected between financial ratios and market returns. Accordingly, it is concluded that the bank stock prices in the study are shaped by the influence of external factors and expectations. The study results include information that can be used for different purposes among bank managers, academics and financial investors.

With over-the-top (OTT) streaming services rapidly transforming the media industry and saturating the market, the authors' study seeks to enrich the goal-directed behaviour model by exploring how perceived risks and descriptive norms influence OTT consumption.

Survey data from OTT subscribers were collected online to assess their risk behaviours. The 353 responses obtained were analysed with SmartPLS, validating the structural equation modelling (SEM) through structural and measurement model verification.

The authors' findings illustrate that descriptive norm, perceived behavioural control, as well as positive and negative anticipated emotion (NEM) and attitude, contribute positively to the desire to engage with OTT streaming services. Interestingly, the authors' study contradicts common assumptions, revealing that subjective norms do not significantly impact the propensity to utilise OTT services. This counterintuitive finding necessitates a reconsideration of prevalent theories and contributes to a nuanced understanding of OTT adoption determinants.

The data gathering for this study were conducted from the perspective of a single nation. Therefore, caution must be exercised when generalising this study's results.

The practical ramifications of this research are vast, providing OTT service providers and marketers with actionable insights to maximise user engagement and navigate perceived risks related to OTT service adoption and consumption.

This study's exploration of perceived risks and descriptive norms enhances the goal-directed behaviour model's breadth, facilitating a holistic comprehension of the constructs shaping OTT consumption behaviours. It would be the first attempt to combine perceptual, affective and behavioural factors and perceived risks to understand the user's predisposition to engage in OTT streaming services.

The purpose of this paper is to identify antecedents and consequences of customers’ value co-creation behaviour (VCB). VCB as a means to facilitate value realisation processes is gaining importance in service research and practice. Encouraging such enactments can be challenging, but can also offer competitive advantages.

We empirically investigate a conceptual model by converging three contemporary concepts of co-creation research – embeddedness, VCB and value-in-context – and examining the interdependencies between them. Data were collected in an online forum of a leading international weight-management firm.

Results suggest that customers’ embeddedness is a key antecedent of customers’ VCB in a service system. The three embeddedness dimensions – structural, relational and cultural – have a differential impact on customers’ VCB. Furthermore, findings illustrate that customers’ VCB has a significant impact on their object-oriented, self-oriented and brand-oriented social value-in-context outcomes.

This study contributes by empirically investigating and validating antecedents and consequences of VCB in a service system. In doing so, the study highlights the significance of the nature of customer’s social constellations to develop contexts where value outcomes are actualised. Understanding the factors that shape VCB offers insights for firms to recognise how and where value propositions can be deployed that drives on-going co-creation processes.

This study is the first empirical research to offer insights into important pre-conditions and subsequent outcomes concurrently to illustrate how customers’ VCB can be managed and nurtured for sustainable value co-creation processes within service systems. This research further advances mid-range theorizing and microfoundational perspectives in marketing.

The power sector needs frontline employees (FLEs) who are adaptable to the dynamic and complex business environments. There is yet to be a study that defines FLE adaptability as a lived in experience. The main purpose of this study is to explore the dimensions of FLE adaptability in power sector.

FLE adaptability being multifaceted and context based, the research is conducted as a qualitative research in an attempt to identify FLE adaptability dimensions. FLE's working in three power utilities in Western, India participated through purposeful sampling frame. Data were collected using interviews, group discussions and open-ended questionnaire and analyzed in line with grounded theory.

The analysis revealed seven dimensions of FLE adaptability. The dimensions being interpersonal aspect of adaptability, service offering aspect adaptability, political aspects of adaptability, social aspects of adaptability, physical aspects of adaptability, group aspect of adaptability and organizational aspect of adaptability.

Given the authors' exploratory qualitative approach and small sample size, these findings should be interpreted with caution until they have been replicated in a variety of settings and with multiple methodologies. Participants in this study were drawn from power sector organizations located in Western, India. This may delimit generalizations. Substantial research needs to be carried out in order to fully develop a complete understanding of this important FLE adaptability construct.

Power sector is one of the major parameters for the development of country. FLEs are one of the main cogs in the efficient management of power sector. This research stresses the need for FLE for adapting to the social fabric of society especially for services which are essential in nature. The new term coined by the researchers is social consciousness which depicts employee social orientation.

There is academic scarcity on research that defines FLE adaptability as a lived in experience. In the previous research on employee adaptability, there was a consistent divide between the setting (laboratory vs field), construct dimensionality (uni- vs multidimensional), assessment format (objective task scores vs subjective ratings), and sample (military vs non-military setting). Thus, the previous research on adaptability could not be generalized on the adaptability spectrum of FLEs; hence, this study revisits the attributes of FLE adaptability.

This research presents an ontological model, to communicate the impact of dynamic preconditions for peri-urban communities. As such, this paper approaches perturbation communities as social-complex-adaptive-systems.

Previous assessment of dynamic preconditions have typically been based on top-down approaches. Through the lens of social-complex-adaptive and systemic design approaches (requiring a range of different disciplines), this work focuses on providing a broader view towards periurban research. The methodological approach involved academic literature, fieldwork observations, in-depth discussions with community, government, experts and research groups, focusing on a region called “Xochimilco” on the outskirts of Mexico City, a unique pre-Hispanic, Aztec ecosystem. This evolving man made agricultural/ecological structure of island plots, still provides environmental services to Mexico City. This region provides the basis of the research and subsequent ontological model. Ontology, in this instance, refers to the nature of being within a range of constraining dynamic forces relating to resilient behaviors of the current Xochimilco perturbation ecosystem.

Xochimilco can be considered as a longitudinal phenomenon that contributed to the understanding of observable resilient and precondition elements between the past and present of a living complex-adaptive-system.

The research has provided a better understanding of community resilience through preconditions, contributing towards preparation of environmental change and future urbanization. To this end, the research focused on visualizing key dynamics elements for communities attempting to absorb new urban conditions (being continuously pushed into it).

The outcomes of this research have provided specific systemic, bottom up approaches with ontological modeling to assist with visualizing and understanding intangible dynamic conditions that impact high complex areas of perturbation regions.

This study aims to characterize the properties of natural cellulose fiber from the pseudo-stems of the curcuma zedoaria plant.

The fiber was extracted using the biological retting process (cold-water retting). The intrinsic fiber properties obtained were used to evaluate the possibility of using fiber for textile applications.

The average length of a curcuma zedoaria fiber was 34.77 cm with a fineness value of 6.72 Tex. A bundle of curcuma zedoaria fibers was comprised of many elementary fibers. Curcuma zedoaria had an irregular cross-section, with the lumen having a varied oval shape. Curcuma zedoaria fibers had tenacity and elongation value of 3.32 gf/denier and 6.95%, respectively. Curcuma zedoaria fibers had a coefficient of friction value of 0.46. Curcuma zedoaria fibers belong to a hygroscopic fiber type with a moisture regain value of 10.29%.

Extraction and Characterization of Curcuma zedoaria Pseudo-stems Fibers for Textile Application.