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The purpose of this paper is to investigate the performance of cultural algorithms (CAs) over a complete range of optimization problem complexities, from fixed to chaotic and specifically observing whether there is a given homogeneous agent topology within a culture which can dominate across all complexities.

In order to apply the CA overall complexity classes it was necessary to generalize on its co‐evolutionary nature to keep the variation in the population across all complexities. First, previous CA approaches were reviewed. Based on this the existing implementation was extended to produce a more general one that could be applied across all complexity classes. As a result a new version of the cultural algorithms toolkit, CAT 2.0, was produced, which supported a variety of co‐evolutionary features at both the knowledge and population levels. The system was applied to the solution of a 150 randomly generated problems ranging from simple to chaotic complexity classes.

No homogeneous social fabric tested was dominant over all categories of problem complexity; as the complexity of problems increased so did the complexity of the social fabric that was need to deal with it efficiently. A social fabric that was good for fixed problems might be less adequate for periodic problems, and chaotic ones.

The paper presents experimental evidence that social structure of a cultural system can be related to the frequency and complexity type of the problems that presented to a cultural system.

The purpose of this paper is to gather stakeholder tacit knowledge to design new product concepts with optimal product attributes for new health promoting food products for the ageing population.

This research employed a qualitative research method. A total of 16 in-depth interviews were carried out to identify key product design attributes. These attributes were used to design health promoting foods for the ageing population.

Age-related conditions affect and alter the design of health promoting foods targeted at the ageing population. Providing the ageing consumer segment with access to health promoting foods facilitates positive ageing intervention. The integration of affordability and convenience elements into ageing food design attributes is important for product acceptance. The multi-level demands and heterogeneity of ageing consumers result in the need for a variety of nutritionally tailored food formats. A dairy-based beverage was considered to be the optimal product concept for the ageing population.

The inclusion of stakeholders from the food industry could result in levels of food industry bias. The sample size of stakeholders was limited to 16 participants. One interview guide was used throughout all interviews to ensure consistency levels. A more flexible instrument may have captured more specific stakeholder information.

During the early stages of the new product development process, a market-oriented research methodology can help to optimise product design in terms of product attributes that drive consumer acceptance.

This paper provides important insights into the significance of stakeholder tacit knowledge generation throughout the need identification stage of the NPD process. Specifically this paper provides stakeholder tacit knowledge on the optimal design of health promoting foods for the ageing population. This knowledge has the ability to provide market-oriented information on health promoting food concepts which can be valuable for food manufacturers to maximise NPD performance, create value and develop competitive advantage within their marketplace. Finally, design templates of health promoting foods for the ageing population are of high strategic importance to food manufacturers, governments, health professionals and medical professionals.

Current research about American Indians of all ages is in short supply, yet design and allocation of public services and resources are increasingly guided by ‘evidence’ provided by research. The health and wellness of this population is persistently poorer than that of other marginalized populations. American Indian tribes have been beset progressively since the earliest arrival of European settlers by both malevolent and well-intentioned assaults on their cultures and peoples. This long history of cultural and physical genocide continues into the present and undermines the effectiveness of Eurocentric processes for research that have been shaped by values and beliefs antithetical to those of most tribes (e.g. individualism, proprietary ownership, science as the way of knowing). Individual and collective historical trauma is present in all of the more than 500 federally recognized tribes in the United States of America, and a lack of trust further compromises the validity and positive impact of most research. This chapter describes the roots and foundations of flawed and successful research and identifies practical resources and approaches that are valid and beneficial for conducting research with indigenous people. The processes described in this chapter are grounded in the experiences of tribes in the United States of America; however, parallel experiences of indigenous populations that have a continuing legacy of trauma are found in many other countries (such as in Brazil and New Zealand) and the insights and approaches found in this chapter may be applicable to some degree.

The purpose of this paper is to find a novel optimization selection method for hyper‐parameter of support vector classification (SVC), responsible for the classification of datasets from the UCI machine learning database repository.

A novel two‐stage optimization selection method for hyper‐parameters is proposed. It makes use of explicit information derived from issues and implicit knowledge extracted from the evolution process so as to improve the performance of classifier. In the first stage, the search extent of each hyper‐parameter is determined according to the requirements of issues. In the second stage, optimal hyper‐parameters are obtained by adaptive chaotic culture algorithm in the above search extent. Adaptive chaotic cultural algorithm uses implicit knowledge extracted from the evolution process to control mutation scale of chaotic mutation operator. This algorithm can ensure the diversity of population and exploitation in the latter evolution.

The rationality of the above optimization selection method is proved by the binary classification problem. Final confirmation of this approach is the classification results compared with other methods.

This optimization selection method can effectively avoid premature convergence and lead to better computation stability and precision. It is not related on the structure of functions. SVC model corresponding to optimal hyper‐parameters by this method has better generalization.

Considering the importance of knowledge, attitudes and practice (KAP) in communities toward COVID-19 and the acceptance of COVID-19 vaccination in the control of this disease, this study aims to evaluate and compare the KAP level toward COVID-19 and the acceptance rate of COVID-19 vaccination between the Afghan immigrant population and Iranians

This cross-sectional descriptive study was conducted in 2021 on Afghan immigrants, Afghan-neighboring Iranians and Afghan nonneighboring Iranians. Of the 885 people who participated in the survey, 295 from each group were randomly selected. Data collection tools were the following questionnaires: KAP toward COVID-19 and acceptance and attitude toward COVID-19 vaccination.

A total of 837 participants were included for data analysis. According to the findings, the KAP score on COVID-19 in Afghan immigrants was lower than the group of Iranians. Compared with Iranians, the score of nonneighboring Iranians was higher than the neighboring Iranians with Afghan immigrants. This difference in the mean scores suggests a statistically significant difference in the three groups (p < 0.0001). Among demographic data, the relationship between gender, education, type of job, income level and age with KAP indicated a significant difference in the total population studied. In the group of Afghan immigrants, the most likely reason for accepting the vaccination was the employer’s recommendation (55.63%). In comparison, the neighboring and nonneighboring Iranian groups with Afghan immigrants stated that they would receive the vaccine as soon as possible (49.22% and 63.22%, respectively).

Considering the low KAP score in the immigrant population in this study, these people are more vulnerable to the health and socioeconomic effects of COVID-19; therefore, the host countries have more challenges and responsibilities to protect these populations.

Agriculture is a major generator of wealth and employment in Australia. However, it faces a range of economic and environmental challenges which require substantial community support. The purpose of this paper is to examine Australian adults’ Australian knowledge of, and attitudes towards, Australian agriculture.

Online questionnaire survey of 1,026 adults conducted nationwide during August 2012.

Most respondents had little knowledge of even the basic aspects of the industry but they approved of farmers’ performance of their roles. Latent class analysis showed that there are two groups of consumers with low and lower levels of knowledge. The respondents’ age, rural residence and universalist values were positive predictors of agricultural knowledge.

This was a cross-sectional, quota-based survey which examined only some aspects of agriculture. However, the findings suggest that more communication with the general public about the industry is required in order to build on the positive sentiment that exists within the community.

More education about agriculture in schools and higher education is indicated.

The poor state of knowledge of agriculture threatens the social contract upon which agricultural communities depend for survival.

The study highlights the poor state of general knowledge about agriculture in Australia. The findings could be used as a baseline against which the efficacy of future education programmes could be assessed.

This paper aims to establish a systematic cognition to alleviate the supply–demand contradiction in rural financial markets from an integrated perspective of knowledge management and proposes the concept of rural financial knowledge ecosystem (RFKE) to encourage multifaceted solutions.

The authors qualitatively describe the process that the knowledge management dilemmas cause the supply–demand contradiction in the rural finance and further summarize a systematic methodology from three dimensions: the knowledge subject, the knowledge environment and the knowledge ecology.

The authors list four types of knowledge management dilemmas leading to the supply–demand contradiction in the rural finance, i.e. the weak knowledge sharing, the poor knowledge flow, the slow knowledge updating and the imperfect knowledge environment. Meanwhile, the RFKE model consisting of the ecological subject, the ecological environment and the ecological regulation is also presented.

The role of knowledge management in improving the allocation of financial resources to various rural financial market participants (government, rural financial institutions, farmers, agricultural enterprises, etc.).

The authors creatively give the RFKE model, which complements and enriches the theory of knowledge management. Meanwhile, relevant management practices are urgently needed under the macro circumstance of the COVID-19 pandemic and the rural revitalization in China.

This study aims to examine the association between nurses’ ageism and their knowledge about aging and socio-demographic and professional characteristics in recent international nursing research studies.

An extensive search of seven databases covering papers since 2000 was undertaken and Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed.

Ageism among nurses is still poorly understood. It is evident that ageism is associated with poor nurses’ level of knowledge about aging. A range of nurses’ demographical and professional characteristics have been examined as potential predictors of ageism, but they were inconsistent with positive, negative and neutral associations.

There is a lack of robustly designed studies investigating the association of nurses’ level of knowledge about aging and their socio-demographical and professional characteristics to ageism. Future descriptive-correlational and interventional studies are recommended to understand and target ageism in health-care settings.