The research outcomes support the value of community-based health promotion programmes in rural areas, incorporating a multidisciplinary health team and culturally competent materials to help the elder rural inhabitants with diabetes enjoy better health and quality of life.

Abstract-Driving always involves risk. Various means have been proposed to reduce the risk. Critical motion detection of nearby moving vehicles is one of the important means of preventing accidents. In this paper, a computational model, which is referred to as the dynamic visual model (DVM), is proposed to detect critical motions of nearby vehicles while driving on a highway. The DVM is motivated by the human visual system and consists of three analyzers: 1) sensory analyzers, 2) perceptual analyzers, and 3) conceptual analyzers. In addition, a memory, which is called the episodic memory, is incorporated, through which a number of features of the system, including hierarchical processing, configurability, adaptive response, and selective attention, are realized. A series of experimental results with both single and multiple critical motions are demonstrated and show the feasibility of the proposed system.Index Terms-Assembly of adaptive-resonance-theory (ART) neural networks, driver-assistance system (DAS), dynamic visual model (DVM), fuzzy integral, spatiotemporal attention (STA) neural network.

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Background: The increasing prevalence of type 2 diabetes mellitus (T2DM) poses a major public health challenge throughout the world. It is a major healthcare issue among the elderly. This study was to identify the association between the health promoting behaviors and the diabetic control of type 2 diabetes mellitus (T2DM) patients. Methods: Cross sectional and descriptive research designs were used in this study. Participants were enrolled from three medical centers in northern, central and southern Taiwan during August, 2010 and June, 2011. The instruments encompassed biochemical indicators, and the preliminary developed scale of diabetes mellitus and health promotion (DMHP). Results: A total of 323 participants with T2DM were included in this study. The results showed 1) a high percentage of the participants used cigarette smoking, alcohol drinking and betel nut chewing, which were not conducive to adopting health promoting behaviors; 2) a high percentage of patients showed abnormal blood glucose, dyslipidemia, and elevated blood pressure; 3) few of the participants practiced ideally health promoting behaviors; and 4) practicing health-promoting behavior was positively associated with fasting blood glucose (FBG) and HbA1c levels. Conclusions: Patients with higher health promotion scores had better diabetic control. Less physical activity was found among those addicted to cigarette, alcohol and betel nut consumption. The findings suggest that health care providers should assess health promoting behaviors first for each diabetic patient.

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