Mobility and active ageing in suburban environments : findings from in-depth interviews and person-based GPS tracking

Background. Governments face a significant challenge to ensure that community environments meet the mobility needs of an ageing population. Therefore, it is critical to investigate the effect of suburban environments on the choice of transportation and its relation to participation and active ageing. Objective. This research explores if and how suburban environments impact older people’s mobility and their use of different modes of transport. Methods. Data derived from GPS tracking, travel diaries, brief questionnaires, and semistructured interviews were gathered from thirteen people aged from 56 to 87 years, living in low-density suburban environments in Brisbane, Australia. Results. The suburban environment influenced the choice of transportation and out-of-home mobility. Both walkability and public transportation (access and usability) impact older people’s transportation choices. Impracticality of active and public transportation within suburban environments creates car dependency in older age. Conclusion. Suburban environments often create barriers to mobility, which impedes older people’s engagement in their wider community and ability to actively age in place. Further research is needed to develop approaches towards age-friendly suburban environments which will encourage older people to remain active and engaged in older age.

How do older adults respond to Active Australia physical activity questions? Lessons from cognitive interviews

The aim of this study was to examine older adults’ understanding and interpretation of a validated questionnaire for physical activity surveillance, the Active Australia Survey (AAS). To address this aim, cognitive interviewing techniques were used during face-to-face semi-structured interviews with 44 adults aged 65-89 years. Qualitative data analysis revealed that participants were confused with questionnaire phrasing, misunderstood the scope of activities to include in answers, and misunderstood the time frame of activities to report. They also struggled to accurately estimate the frequency and duration of their activities. Our findings suggest that AAS questions may be interpreted differently by older adults than intended by survey developers. Findings also suggest that older adults use a range of methods for calculating PA frequency and duration. The issues revealed in this study may be useful for adapting AAS for use in older community-dwelling adults.

Active versus passive screen time for young children

In this paper, we report some initial findings from our investigations into the Australian Government’s Longitudinal Study of Australian Children dataset. It is revealed that the majority of Australian children are exceeding the government’s Screen Time recommendations and that most of their screen time is spent as TV viewing, as opposed to video game play or computer use. In light of this finding,we review the body of research surrounding children’s engagement in Screen Time activities and the associated positive and negative effects. Based on existing evidence,we define two categories of Screen Time—Active Screen Time and Passive Screen Time. It is proposed that this distinction provides a more accurate classification of Screen Time and a more informative lens through which to consider the associated benefits and detrimental effects for young children.

Assessment bias : physical activity questionnaire assessment inadvertently influences patients’ desire to be ‘more physically active’

Evaluating physical activity is important for public health population research and evaluating lifestyle interventions among targeted groups. Self-reported questionnaires are frequently used to evaluate physical activity in a variety of contexts where resource or pragmatic limitations prohibit the use of more sophisticated approaches. However, prior research in the use of other patient reported outcomes in healthcare settings has highlighted that simply completing a questionnaire may change a patients’ behaviour or responses to subsequent questions. This methodology study aimed to examine whether completing a standard physical activity questionnaire altered patients responses to two related questions a) whether they are ‘sufficiently physically active’ and b) whether they desire ‘to be more physically active.’

The predictors of active ageing of older Australians : the triple a study

The concept of older adults contributing to society in a meaningful way has been termed ‘active ageing’. Active ageing reflects changes in prevailing theories of social and psychological aspects of ageing, with a focus on individuals' strengths as opposed to their deficits or pathology. In order to explore predictors of active ageing, the Australian Active Ageing (Triple A) project group undertook a national postal survey of participants over the age of 50 years recruited randomly through their 2004 membership of a large Australia-wide senior's organisation. The survey comprised 178 items covering paid and voluntary work, learning, social, spiritual, emotional, health and home, life events and demographic items. A 45% response rate (2655 returned surveys) reflected an expected balance of gender, age and geographic representation of participants. The data were analysed using data mining techniques to represent generalizations on individual situations. Data mining identifies the valid, novel, potentially useful and understandable patterns and trends in data. The results based on the clustering mining technique indicate that physical and emotional health combined with the desire to learn were the most significant factors when considering active ageing. The findings suggest that remaining active in later life is not only directly related to the maintenance of emotional and physical health, but may be significantly intertwined with the opportunity to engage in on-going learning activities that are relevant to the individual. The findings of this study suggest that practitioners and policy makers need to incorporate older peoples' learning needs within service and policy framework developments.

Active text perception for mobile robots

Our everyday environment is full of text but this rich source of information remains largely inaccessible to mobile robots. In this paper we describe an active text spotting system that uses a small number of wide angle views to locate putative text in the environment and then foveates and zooms onto that text in order to improve the reliability of text recognition. We present extensive experimental results obtained with a pan/tilt/zoom camera and a ROS-based mobile robot operating in an indoor environment.

Active and reactive power control of synchronous generator for the realization of a virtual power plant

This paper presents a novel power control strategy that decouples the active and reactive power for a synchronous generator connected to a power network. The proposed control paradigm considers the capacitance of the transmission line along with its resistance and reactance as-well. Moreover the proposed controller takes into account all cases of R-X relationships, thus allowing it to function in Virtual Power Plant (VPP) structures which operate at both medium voltage (MV) and low voltage (LV) levels. The independent control of active and reactive power is achieved through rotational transformations of the terminal voltages and currents at the synchronous generator's output. This paper details the control technique by first presenting the mathematical and electrical network analysis of the methodology and then successfully implementing the control using MATLAB-SIMULINK simulation.

Designing a new robust on-line secondary path modeling technique for feedforward active noise control systems

Several approaches have been introduced in the literature for active noise control (ANC) systems. Since the filtered-x least-mean-square (FxLMS) algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of the FxLMS algorithm, as a first novelty. In many ANC applications, an on-line secondary path modeling method using white noise as a training signal is required to ensure convergence of the system. As a second novelty, this paper proposes a new approach for on-line secondary path modeling on the basis of a new variable-step-size (VSS) LMS algorithm in feed forward ANC systems. The proposed algorithm is designed so that the noise injection is stopped at the optimum point when the modeling accuracy is sufficient. In this approach, a sudden change in the secondary path during operation makes the algorithm reactivate injection of the white noise to re-adjust the secondary path estimate. Comparative simulation results shown in this paper indicate the effectiveness of the proposed approach in reducing both narrow-band and broad-band noise. In addition, the proposed ANC system is robust against sudden changes of the secondary path model.

A self-tuning feedforward active noise control system

This paper proposes a self-tuning feedforward active noise control (ANC) system with online secondary path modeling. The step-size parameters of the controller and modeling filters have crucial rule on the system performance. In literature, these parameters are adjusted by trial-and-error. In other words, they are manually initialized before system starting, which require performing extensive experiments to ensure the convergence of the system. Hence there is no guarantee that the system could perform well under different situations. In the proposed method, the appropriate values for the step-sizes are obtained automatically. Computer simulation results indicate the effectiveness of the proposed method.

An efficient online secondary path estimation for feedback active noise control systems

In practical cases for active noise control (ANC), the secondary path has usually a time varying behavior. For these cases, an online secondary path modeling method that uses a white noise as a training signal is required to ensure convergence of the system. The modeling accuracy and the convergence rate are increased when a white noise with a larger variance is used. However, the larger variance increases the residual noise, which decreases performance of the system and additionally causes instability problem to feedback structures. A sudden change in the secondary path leads to divergence of the online secondary path modeling filter. To overcome these problems, this paper proposes a new approach for online secondary path modeling in feedback ANC systems. The proposed algorithm uses the advantages of white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the algorithm and to prevent the instability effect of the white noise. In this approach, instead of continuous injection of the white noise, a sudden change in secondary path during the operation makes the algorithm to reactivate injection of the white noise to correct the secondary path estimation. In addition, the proposed method models the secondary path without the need of using off-line estimation of the secondary path. Considering the above features increases the convergence rate and modeling accuracy, which results in a high system performance. Computer simulation results shown in this paper indicate effectiveness of the proposed method.

A variable step-size FxLMS algorithm for feedforward active noise control systems based on a new online secondary path modelling technique

Several approaches have been introduced in literature for active noise control (ANC) systems. Since FxLMS algorithm appears to be the best choice as a controller filter, researchers tend to improve performance of ANC systems by enhancing and modifying this algorithm. This paper proposes a new version of FxLMS algorithm. In many ANC applications an online secondary path modelling method using a white noise as a training signal is required to ensure convergence of the system. This paper also proposes a new approach for online secondary path modelling in feedfoward ANC systems. The proposed algorithm stops injection of the white noise at the optimum point and reactivate the injection during the operation, if needed, to maintain performance of the system. Benefiting new version of FxLMS algorithm and not continually injection of white noise makes the system more desirable and improves the noise attenuation performance. Comparative simulation results indicate effectiveness of the proposed approach.

A new online secondary path modelling method for feedforward active noise control systems

An online secondary path modelling method using a white noise as a training signal is required in many applications of active noise control (ANC) to ensure convergence of the system. Not continually injection of white noise during system operation makes the system more desirable. The purposes of the proposed method are two folds: controlling white noise by preventing continually injection, and benefiting white noise with a larger variance. The modelling accuracy and the convergence rate increase when a white noise with larger variance is used, however larger the variance increases the residual noise, which decreases performance of the system. This paper proposes a new approach for online secondary path modelling in feedfoward ANC systems. The proposed algorithm uses the advantages of the white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the system. Comparative simulation results shown in this paper indicate effectiveness of the proposed approach in controlling active noise.

Benefiting white noise in developing feedforward active noise control systems

In many applications of active noise control (ANC), an online secondary path modelling method using a white noise as a training signal is required to ensure convergence of the system. The modelling accuracy and the convergence rate increase when a white noise with larger variance is used, however larger the variance increases the residual noise, which decreases performance of the system. The proposed algorithm uses the advantages of the white noise with larger variance to model the secondary path, but the injection is stopped at the optimum point to increase performance of the system. In this approach, instead of continuous injection of the white noise, a sudden change in secondary path during the operation makes the algorithm to reactivate injection of the white noise to adjust the secondary path estimation. Comparative simulation results shown in this paper indicate effectiveness of the proposed method.