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This study sets out to investigate the elements of the collaborative culture required for the successful implementation and sustainability of programs in schools. It draws on a case study of a student peer-led physical activity (PA) program implemented within the complex and dynamic environment of school communities in New Zealand. The article outlines four key components needed to effectively implement and impact long term sustainability of a program within the school context.

This qualitative case study examines the implementation of a new peer-led PA program introduced across eight New Zealand schools. Data were collected from semi-structured interviews with senior leaders, teachers and parents and analyzed through a complexity theory lens.

Effective and sustainable program implementation requires a strategic, collaborative approach through actively engaging with and resourcing four key interacting components: student choice, voice and agency; collective responsibility; shared understanding of purpose; and curriculum coherence.

This research offers a pragmatic approach to developing collaborative school communities that can effectively implement change by highlighting key areas of focus that policymaker, school leaders and program designers can plan for.

This study aims to comprehensively address the challenge of delineating traffic scenarios in video footage captured by an embedded camera within an autonomous vehicle.

This methodology involves systematically elucidating the traffic context by leveraging data from the object recognition subsystem embedded in vehicular road infrastructure. A knowledge base containing production rules and logical inference mechanism was developed. These components enable real-time procedures for describing traffic situations.

The production rule system focuses on semantically modeling entities that are categorized as traffic lights and road signs. The effectiveness of the methodology was tested experimentally using diverse image datasets representing various meteorological conditions. A thorough analysis of the results was conducted, which opens avenues for future research.

Originality lies in the potential integration of the developed methodology into an autonomous vehicle’s control system, working alongside other procedures that analyze the current situation. These applications extend to driver assistance systems, harmonized with augmented reality technology, and enhance human decision-making processes.