Abstract

Abstract
The estimation of the tail index is a central topic in extreme value analysis. We consider a geometric-type estimator for the tail index and study its asymptotic properties. We propose here two asymptotic equivalent bias-corrected geometric-type estimators and establish the corresponding asymptotic behaviour. We also apply the suggested estimators to construct asymptotic confidence intervals for this tail parameter. Some simulations in order to illustrate the finite sample behaviour of the proposed estimators are provided.

Abstract
Transmission congestion management plays a key role in deregulated energy markets. To correctly model and solve this problem, power system voltage and transient stability limits should be considered to avoid obtaining a vulnerable power system with low stability margins. Congestion management is modeled as a multi-objective optimization problem in this paper. The proposed scheme includes the cost of congestion management, voltage stability margin and transient stability margin as its multiple competing objectives. Moreover, a new effective Multi-objective Mathematical Programming (MMP) solution approach based on normalized normal constraint (NNC) method is presented to solve the multi-objective optimization problem of the congestion management, which can generate a well-distributed and efficient Pareto frontier. The proposed congestion management model and MMP solution approach are implemented on the New-England's test system and the obtained results are compared with the results of several other congestion management methods. These comparisons verify the superiority of the proposed approach.

Abstract
Wireless sensor networks are being widely used to support time-critical applications, even knowing that previous versions of the IEEE 802.15.4 standard have a limited capacity to ensure a timely communication service. Its main limitation is the reduced number of available GTS slots. More recently, the IEEE 802.15.4e LLDN mode has been released to address this issue. It provides static TDMA-based communication, with a larger number of available slots to support time-critical communication. However, it does not provide any guidelines on how to allocate slots, in order to guarantee the message real-time requirements. In this paper, we propose a methodology to allocate LLDN slots based on the traffic load imposed by the supported message streams. The proposed allocation scheme is able to handle message streams with periodicities that are not multiple of the beacon interval, and also to support static and dynamic prioritizing of message streams.

Abstract
The recent interest in the smart grid vision and the technological advancement in the communication and control infrastructure enable several smart applications at different levels of the power grid structure, while specific importance is given to the demand side. As a result, changes in load patterns due to demand response (DR) activities at end-user premises, such as smart households, constitute a vital point to take into account both in system planning and operation phases. In this study, the impact of price-based DR strategies on smart household load pattern variations is assessed. The household load datasets are acquired using model of a smart household performing optimal appliance scheduling considering an hourly varying price tariff scheme. Then, an approach based on artificial neural networks (ANN) and wavelet transform (WT) is employed for the forecasting of the response of residential loads to different price signals. From the literature perspective, the contribution of this study is the consideration of the DR effect on load pattern forecasting, being a useful tool for market participants such as aggregators in pool-based market structures, or for load serving entities to investigate potential change requirements in existing DR strategies, and effectively plan new ones.

Abstract
Multimedia content has the potential for significant impact on users’ emotions, their sense of presence and engagement experiencing the service, application or information being provided, in immersive environments. The evolution of technology, user expectations and results from research activities have led to an enormous increase in the amount of content delivered in different formats, via a number of heterogeneous communication networks, to a range of devices, many of them portable and offering tremendous opportunities for immersion, user participation and personalization. New paradigms for media production, distribution and consumption have been emerging, introducing different sensory modalities and audio-visual surround effects, for an increased sense of presence, and also enabling participation and social interaction in the media chain, thus increasing the sense of belonging and contributing to the success of the services being provided