298 resultados para Reverse self-control problem
Resumo:
We reviewed the effect of behavioural telehealth interventions on glycaemic control and diabetes self-management in patients with type 2 diabetes. The databases CINAHL, Medline and psychINFO were searched in August 2012. Journal articles were selected that had been published in English with a randomized controlled trial design using a usual care comparison group, and in which the primary intervention component was delivered by telehealth. Relevant outcome measures were glycaemic control and one or more of the following diabetes self-care areas: diet, physical activity, blood glucose self-monitoring (BGSM) or medication adherence. Interventions were excluded if they were primarily based on telemonitoring. The search retrieved 1027 articles, from which 49 were selected based on their title and abstract. Fourteen articles (reporting 13 studies) met the eligibility criteria for inclusion. Four studies reported significant improvements in glycaemic control. Five of eight studies on dietary adherence reported significant treatment effects, as did five of eight on physical activity, four of nine on blood glucose self-monitoring, and three of eight on medication adherence. Overall, behavioural telehealth interventions show promise in improving the diabetes self-care and glycaemic control of people with type 2 diabetes.
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Brief interventions are effective for problem drinking and reductions are known to occur in association with screening and assessment. The present study sought to assess, among participants (N=202) in a clinical trial, how much change occurred between baseline assessment and a one-session brief intervention (S1), and the predictors of early change. The primary focus was on changes in the Beck Depression Inventory Fast Screen scores and alcohol consumption (standard drinks per week) prior to random allocation to nine further sessions addressing either depression, alcohol, or both problems. There were large and clinically significant reductions between baseline and S1, with the strongest predictors being baseline scores in the relevant domain and change in the other domain. Client engagement was also predictive of early depression changes. Monitoring progress in both domains from first contact, and provision of empathic care, followed by brief intervention appear to be useful for this high prevalence comorbidity.
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We conducted a randomized controlled trial to test whether a Brief Mobile Treatment (BMT) intervention could improve outcomes relative to usual care among suicide attempters. The intervention included training in problem solving therapy, meditation, a brief intervention to increase social support as well as advice on alcohol and other drugs, and mobile phone follow-up. The effect of the intervention was measured in terms of a reduction in suicidal ideation, depression and self-harm at Baseline, six and 12 months. A wait-list control group received usual care. A total of 68 participants was recruited from a Sri Lankan hospital following a suicide attempt. Participants who received the intervention were found to achieve significant improvements in reducing suicidal ideation and depression than those receiving usual care. The BMT group also experienced a significant improvement of social support when compared to the control group. However, the BMT group did not demonstrate a significant effect in reducing actual self-harm and most substance use, and differential effects on alcohol use were restricted to men. Although the present study was limited in revealing which component of the intervention was more effective in preventing suicide, it showed its efficacy in reducing suicide as a whole.
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Proxy reports from parents and self-reported data from pupils have often been used interchangeably to identify factors influencing school travel behaviour. However, few studies have examined the validity of proxy reports as an alternative to self-reported data. In addition, despite research that has been conducted in a different context, little is known to date about the impact of different factors on school travel behaviour in a sectarian divided society. This research examines these issues using 1624 questionnaires collected from four independent samples (e.g. primary pupils, parent of primary pupils, secondary pupils, and parent of secondary pupils) across Northern Ireland. An independent sample t test was conducted to identify the differences in data reporting between pupils and parents for different age groups using the reported number of trips for different modes as dependent variables. Multivariate multiple regression analyses were conducted to then identify the impacts of different factors (e.g. gender, rural–urban context, multiple deprivations, and school management type, net residential density, land use diversity, intersection density) on mode choice behaviour in this context. Results show that proxy report is a valid alternative to self-reported data, but only for primary pupils. Land use diversity and rural–urban context were found to be the most important factors in influencing mode choice behaviour.
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This study investigated the association between outdoor work and response to a behavioural skin cancer early detection intervention among men 50 years or older. Overall, 495 men currently working in outdoor, mixed or indoor occupations were randomised to a video-based intervention or control group. At 7 months post intervention, indoor workers reported the lowest proportion of whole-body skin self-examination (wbSSE; 20%). However, at 13 months mixed workers engaged more commonly in wbSSE (36%) compared to indoor (31%) and outdoor (32%) workers. In adjusted analysis, the uptake of early detection behaviours during the trial did not differ between men working in different settings. Outdoor workers compared to men in indoor or mixed work settings were similar in their response to an intervention encouraging uptake of secondary skin cancer prevention behaviours during this intervention trial.
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This paper is concerned with the unsupervised learning of object representations by fusing visual and motor information. The problem is posed for a mobile robot that develops its representations as it incrementally gathers data. The scenario is problematic as the robot only has limited information at each time step with which it must generate and update its representations. Object representations are refined as multiple instances of sensory data are presented; however, it is uncertain whether two data instances are synonymous with the same object. This process can easily diverge from stability. The premise of the presented work is that a robot's motor information instigates successful generation of visual representations. An understanding of self-motion enables a prediction to be made before performing an action, resulting in a stronger belief of data association. The system is implemented as a data-driven partially observable semi-Markov decision process. Object representations are formed as the process's hidden states and are coordinated with motor commands through state transitions. Experiments show the prediction process is essential in enabling the unsupervised learning method to converge to a solution - improving precision and recall over using sensory data alone.
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A new control method for battery storage to maintain acceptable voltage profile in autonomous microgrids is proposed in this article. The proposed battery control ensures that the bus voltages in the microgrid are maintained during disturbances such as load change, loss of micro-sources, or distributed generations hitting power limit. Unlike the conventional storage control based on local measurements, the proposed method is based on an advanced control technique, where the reference power is determined based on the voltage drop profile at the battery bus. An artificial neural network based controller is used to determine the reference power needed for the battery to hold the microgrid voltage within regulation limits. The pattern of drop in the local bus voltage during power imbalance is used to train the controller off-line. During normal operation, the battery floats with the local bus voltage without any power injection. The battery is charged or discharged during the transients with a high gain feedback loop. Depending on the rate of voltage fall, it is switched to power control mode to inject the reference power determined by the proposed controller. After a defined time period, the battery power injection is reduced to zero using slow reverse-droop characteristics, ensuring a slow rate of increase in power demand from the other distributed generations. The proposed control method is simulated for various operating conditions in a microgrid with both inertial and converter interfaced sources. The proposed battery control provides a quick load pick up and smooth load sharing with the other micro-sources in a disturbance. With various disturbances, maximum voltage drop over 8% with conventional energy storage is reduced within 2.5% with the proposed control method.
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Whole-body computer control interfaces present new opportunities to engage children with games for learning. Stomp is a suite of educational games that use such a technology, allowing young children to use their whole body to interact with a digital environment projected on the floor. To maximise the effectiveness of this technology, tenets of self-determination theory (SDT) are applied to the design of Stomp experiences. By meeting user needs for competence, autonomy, and relatedness our aim is to increase children's engagement with the Stomp learning platform. Analysis of Stomp's design suggests that these tenets are met. Observations from a case study of Stomp being used by young children show that they were highly engaged and motivated by Stomp. This analysis demonstrates that continued application of SDT to Stomp will further enhance user engagement. It also is suggested that SDT, when applied more widely to other whole-body multi-user interfaces, could instil similar positive effects.
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This paper presents a shared autonomy control scheme for a quadcopter that is suited for inspection of vertical infrastructure — tall man-made structures such as streetlights, electricity poles or the exterior surfaces of buildings. Current approaches to inspection of such structures is slow, expensive, and potentially hazardous. Low-cost aerial platforms with an ability to hover now have sufficient payload and endurance for this kind of task, but require significant human skill to fly. We develop a control architecture that enables synergy between the ground-based operator and the aerial inspection robot. An unskilled operator is assisted by onboard sensing and partial autonomy to safely fly the robot in close proximity to the structure. The operator uses their domain knowledge and problem solving skills to guide the robot in difficult to reach locations to inspect and assess the condition of the infrastructure. The operator commands the robot in a local task coordinate frame with limited degrees of freedom (DOF). For instance: up/down, left/right, toward/away with respect to the infrastructure. We therefore avoid problems of global mapping and navigation while providing an intuitive interface to the operator. We describe algorithms for pole detection, robot velocity estimation with respect to the pole, and position estimation in 3D space as well as the control algorithms and overall system architecture. We present initial results of shared autonomy of a quadrotor with respect to a vertical pole and robot performance is evaluated by comparing with motion capture data.
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A long-running issue in appetite research concerns the influence of energy expenditure on energy intake. More than 50 years ago, Otto G. Edholm proposed that "the differences between the intakes of food [of individuals] must originate in differences in the expenditure of energy". However, a relationship between energy expenditure and energy intake within any one day could not be found, although there was a correlation over 2 weeks. This issue was never resolved before interest in integrative biology was replaced by molecular biochemistry. Using a psychobiological approach, we have studied appetite control in an energy balance framework using a multi-level experimental system on a single cohort of overweight and obese human subjects. This has disclosed relationships between variables in the domains of body composition [fat-free mass (FFM), fat mass (FM)], metabolism, gastrointestinal hormones, hunger and energy intake. In this Commentary, we review our own and other data, and discuss a new formulation whereby appetite control and energy intake are regulated by energy expenditure. Specifically, we propose that FFM (the largest contributor to resting metabolic rate), but not body mass index or FM, is closely associated with self-determined meal size and daily energy intake. This formulation has implications for understanding weight regulation and the management of obesity.
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Modern mobile computing devices are versatile, but bring the burden of constant settings adjustment according to the current conditions of the environment. While until today, this task has to be accomplished by the human user, the variety of sensors usually deployed in such a handset provides enough data for autonomous self-configuration by a learning, adaptive system. However, this data is not fully available at certain points in time, or can contain false values. Handling potentially incomplete sensor data to detect context changes without a semantic layer represents a scientific challenge which we address with our approach. A novel machine learning technique is presented - the Missing-Values-SOM - which solves this problem by predicting setting adjustments based on context information. Our method is centered around a self-organizing map, extending it to provide a means of handling missing values. We demonstrate the performance of our approach on mobile context snapshots, as well as on classical machine learning datasets.
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The ultimate goal of an access control system is to allocate each user the precise level of access they need to complete their job - no more and no less. This proves to be challenging in an organisational setting. On one hand employees need enough access to the organisation’s resources in order to perform their jobs and on the other hand more access will bring about an increasing risk of misuse - either intentionally, where an employee uses the access for personal benefit, or unintentionally, through carelessness or being socially engineered to give access to an adversary. This thesis investigates issues of existing approaches to access control in allocating optimal level of access to users and proposes solutions in the form of new access control models. These issues are most evident when uncertainty surrounding users’ access needs, incentive to misuse and accountability are considered, hence the title of the thesis. We first analyse access control in environments where the administrator is unable to identify the users who may need access to resources. To resolve this uncertainty an administrative model with delegation support is proposed. Further, a detailed technical enforcement mechanism is introduced to ensure delegated resources cannot be misused. Then we explicitly consider that users are self-interested and capable of misusing resources if they choose to. We propose a novel game theoretic access control model to reason about and influence the factors that may affect users’ incentive to misuse. Next we study access control in environments where neither users’ access needs can be predicted nor they can be held accountable for misuse. It is shown that by allocating budget to users, a virtual currency through which they can pay for the resources they deem necessary, the need for a precise pre-allocation of permissions can be relaxed. The budget also imposes an upper-bound on users’ ability to misuse. A generalised budget allocation function is proposed and it is shown that given the context information the optimal level of budget for users can always be numerically determined. Finally, Role Based Access Control (RBAC) model is analysed under the explicit assumption of administrators’ uncertainty about self-interested users’ access needs and their incentives to misuse. A novel Budget-oriented Role Based Access Control (B-RBAC) model is proposed. The new model introduces the notion of users’ behaviour into RBAC and provides means to influence users’ incentives. It is shown how RBAC policy can be used to individualise the cost of access to resources and also to determine users’ budget. The implementation overheads of B-RBAC is examined and several low-cost sub-models are proposed.
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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.
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This study examined the effects of personal and social resources, coping strategies and appraised stress on employees' levels of anxiety and depression. In relation to the effects of resources and coping strategies, two different models were tested. The main effects model proposes that, irrespective of the level of stress, coping resources and coping strategies have direct effects on well-being. In contrast, the buffering model predicts that the buffering effects of coping resources and strategies are only evident at high levels of stress. One hundred lawyers completed a structured self-administered questionnaire that measured their personal and social resources, use of problem-focused and emotion-focused coping strategies, and appraisals of the stressfulness of the situation. Results revealed generally strong support for the main effects model in the prediction of employee levels of anxiety and depression. Lower levels of anxiety were linked to judgements of lower levels of organizational change, greater self-confidence, greater internality of control beliefs and less use of emotion-focused coping strategies. Lower levels of depression in employees were also linked to judgements of lower levels of organizational change, greater use of resources and less appraised stress. There was only limited support for the buffering effects model. Due to the small size of the sample, the findings need to be explored further in other contexts.
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Past work has clearly demonstrated that numerous commonly used metallic materials will support burning in oxygen, especially at higher pressures. An approach to rectify this significant safety problem has been successfully developed and implemented by applying the concept of Situational Non-Flammability. This approach essentially removes or breaks one leg of the conceptual fire triangle, a tool commonly used to define the three things that are required to support burning; a fuel, an ignition source and an oxidizer. Since an oxidiser is always present in an oxygen system as are ignition sources, the concept of Situational Non-Flammability essentially removes the fuel leg of the fire triangle by only utilising materials that will not burn at the maximum pressure, for example, that the control valve is to be used in. The utilisation of this approach has lead to the development of a range of oxygen components that are practically unable to burn while in service at their design pressure thus providing an unparalleled level of first safety while not compromising on the performance or endurance required in the function of these components. This paper describes the concept of Situational Non-Flammability, how it was used to theoretically evaluate designs of components for oxygen service and the outcomes of the actual development, fabrication and finally utilisation of these components in real oxygen systems in a range of flow control devices.