Using Network Analysis to Understand and Advance Falls Prevention Services and Programs

The purpose of this study was to understand referral linkages that exist among falls prevention agencies in a southern Ontario region using network analysis theory. This was a single case study which included fifteen individual interviews. The data was analyzed through the constant comparative approach. Ten themes emerged and are classified into internal and external factors. Themes associated with internal factors are: 1) health professionals initiating services; 2) communication strategies; 3) formal partnerships; 4) trust; 5) program awareness; and 6) referral policies. Themes associated with external factors are: 1) client characteristics; 2) primary and community care collaboration; 3) networking; and 4) funding. Recommendations to improve the referral pathway are: 1) electronic database; 2) electronic referral forms; 3) educating office staff; and 4) education days. This study outlined the benefit of using network analysis to understand referral pathways and the importance of implementing strategies that will improve falls prevention referral pathways.

Passive Solar Building Design Using Genetic Programming

Passive solar building design is the process of designing a building while considering sunlight exposure for receiving heat in winter and rejecting heat in summer. The main goal of a passive solar building design is to remove or reduce the need of mechanical and electrical systems for cooling and heating, and therefore saving energy costs and reducing environmental impact. This research will use evolutionary computation to design passive solar buildings. Evolutionary design is used in many research projects to build 3D models for structures automatically. In this research, we use a mixture of split grammar and string-rewriting for generating new 3D structures. To evaluate energy costs, the EnergyPlus system is used. This is a comprehensive building energy simulation system, which will be used alongside the genetic programming system. In addition, genetic programming will also consider other design and geometry characteristics of the building as search objectives, for example, window placement, building shape, size, and complexity. In passive solar designs, reducing energy that is needed for cooling and heating are two objectives of interest. Experiments show that smaller buildings with no windows and skylights are the most energy efficient models. Window heat gain is another objective used to encourage models to have windows. In addition, window and volume based objectives are tried. To examine the impact of environment on designs, experiments are run on five different geographic locations. Also, both single floor models and multi-floor models are examined in this research. According to the experiments, solutions from the experiments were consistent with respect to materials, sizes, and appearance, and satisfied problem constraints in all instances.