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Focusing on a user's quality-of-experience (QoE) has become important, because of the growing space of sensor-dependent applications and low-cost sensor design. QoE is typically affected by two quantities: the quality-of-information (QoI) received and the lifetime-of-service. Therefore, QoE is defined as a sensor network's ability to consistently offer assured QoI for an expected lifetime when operating on a limited energy resource, such as a battery. However, dynamic factors, such as varying user requirements, unpredictable sensor environment, unreliable network conditions, and limited energy resource, affecting both QoI and lifetime-of-service, make it challenging to achieve a good QoE. In our previous work, we presented a SNR-based QoI metric which addresses the impact of several of these factors on QoI. In this paper, we design a QoE metric that quantifies the relationship between energy conservation, QoI received by a user, and an application's quality expectation. Further, we develop an adaptive sleep schedule mechanism to demonstrate the usefulness of this metric. Finally, simulation results presented show the effectiveness of our mechanism in achieving QoE improvement.

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Structural vulnerability of buildings to damage needs to be identified during the time of earthquake for reliable seismic design. Conventional linear elastic design methods cease to predict seismic damages in buildings. Pushover analysis is a popular displacement-based nonlinear structural analysis procedure employed to predict the seismic behaviour of structures. Generally, buildings are designed based on the assumption that they are fixed at their base, without considering the foundation as well as soil. But in reality, when a structure is subjected to an earthquake excitation, it interacts with the soil, influencing the structural response. In this study, a multi-bay building with different heights are modelled and analysed, duly considering Soil-Structure Interaction (SSI). The study can form foundation for rigorous performance-based seismic design procedure, considering the effect of soil beneath the structure.

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