Surrogate brands - the pull to adopt an 'other' nation; via sports merchandise

A growing number of consumers are choosing to wear sporting merchandise, from an‘other’ nation – whom they have no geographic or ethnic affiliation with. In addition, nation sports branding appears to have scaled pandemic heights; by reaching fever pitch, when actively carrying its message across boarders. Consumer preferences are being driven past simple behavioural characteristics; towards more transient psychographic and emotional constructs. In short, nation branded sporting uniform is no longer viewed as demanding restrictivemonogamous loyalty. Ownership of a uniform largely suggests exclusivity and encouraged competition. However, manufactures, national teams, athletes and sponsors are entering symbiotic brand relationships - where they are actively seeking publics, open to multiple adopted nationalities. This phenomenon draws consumers towards embracing temporal national identities, which are converted into an over-arching cross-border identity; ultimately gifting sports brands more significance. The following paper explores consumers’ entry into relationships with another nation, in preference to their own - in manner that has been likened to a form of surrogacy; by the authors. The aim is to stimulate further thinking in a field; which transcends national and cultural boundaries - in the interests of developing new insight, and to provide a platform for marketers to develop more effective communications.

A meta-heuristic approach to parallel code generation

The efficient generation of parallel code for multi-processor environments, is a large and complicated issue. Attempts to address this problem have always resulted in significant input from users. Because of constraints on user knowledge and time, the automation of the process is a promising and practically important research area. In recent years heuristic approaches have been used to capture available knowledge and make it available for the parallelisation process. Here, the introduction of a novel approach of neural network techniques is combined with an expert system technique to enhance the availability of knowledge to aid in the automatic generation of parallel code.

Surrogate-Based Optimization Using Multifidelity Models with Variable Parameterization and Corrected Space Mapping

Surrogate-based-optimization methods provide a means to achieve high-fidelity design optimization at reduced computational cost by using a high-fidelity model in combination with lower-fidelity models that are less expensive to evaluate. This paper presents a provably convergent trust-region model-management methodology for variableparameterization design models: that is, models for which the design parameters are defined over different spaces. Corrected space mapping is introduced as a method to map between the variable-parameterization design spaces. It is then used with a sequential-quadratic-programming-like trust-region method for two aerospace-related design optimization problems. Results for a wing design problem and a flapping-flight problem show that the method outperforms direct optimization in the high-fidelity space. On the wing design problem, the new method achieves 76% savings in high-fidelity function calls. On a bat-flight design problem, it achieves approximately 45% time savings, although it converges to a different local minimum than did the benchmark.