DC-DC power converters such as buck converters are susceptible to degradation and failure due to operating under conditions of electrical stress and variable power sources in power conversion applications, such as electric vehicles and renewable energy. Some key components such as electrolytic capacitors degrade over time due to evaporation of the electrolyte. In this paper, a model-observer based scheme is proposed to monitor the states of Buck converters and to estimate their component parameters, such as capacitance and inductance. First, a diagnosis observer is proposed, and the generated residual vectors are applied for fault detection and isolation. Second, component condition parameters, such as capacitance and inductance are reconstructed using another novel observer with adaptive feedback law. Additionally, the observer structures and their theoretical performance are analyzed and proven. In contrast to existing reliability approaches applied in buck converters, the proposed scheme performs online-estimation for key parameters. Finally, buck converters in conventional dc-dc step-down and photovoltaic applications are investigated to test and validate the effectiveness of the proposed scheme in both simulation and laboratory experiments. Results demonstrate the feasibility, performance, and superiority of the proposed component parameter estimation scheme.

This paper extends the definition of an exact consensus complex social network to that of a near consensus complex social network. A near consensus complex social network is a social network with nontrivial topological features and steady state values of the decision certitudes of the majority of the nodes being either higher or lower than a threshold value. By using eigen theories, the relationships among the vectors representing the steady state values of the decision certitudes of the nodes, the influence weight matrix and the set of vectors representing the initial state values of the decision certitudes of the nodes that satisfies a given near consensus specification are characterized.

Computer users working with large visual documents, such as large layouts, blueprints, or maps perform tasks that require them to simultaneously access overview information while working on details. To avoid the need for zooming, users currently have to choose between using a sufficiently large screen or applying appropriate visualization techniques. Currently available hi-res "wall-size" screens, however, are cost-intensive, space-intensive, or both. Visualization techniques allow the user to more efficiently use the given screen space, but in exchange they either require the user to switch between multiple views or they introduce distortion.In this paper, we present a novel approach to simultaneously display focus and context information. Focus plus context screens consist of a hi-res display and a larger low-res display. Image content is displayed such that the scaling of the display content is preserved, while its resolution may vary according to which display region it is displayed in. Focus plus context screens are applicable to practically all tasks that currently use overviews or fisheye views, but unlike these visualization techniques, focus plus context screens provide a single, non-distorted view. We present a prototype that seamlessly integrates an LCD with a projection screen and demonstrate four applications that we have adapted so far.