Abstract
Social networks have an evolving characteristic due to the continuous interaction between users, with nodes associating and disassociating with each other as time flies. The analysis of such networks is especially challenging, because it needs to be performed with an online approach, under the one-pass constraint of data streams. Such evolving behavior leads to changes in the network topology that can be investigated under different perspectives. In this work we focus on the analysis of nodes position evolution—a node-centric perspective. Our goal is to spot change-points in an evolving network at which a node deviates from its normal behavior. Therefore, we propose a change detection model for processing evolving network streams which employs three different aggregating mechanisms for tracking the evolution of centrality metrics of a node. Our model is space and time efficient with memory less mechanisms and in other mechanisms at most we require the network of current time step T only. Additionally, we also compare the influence on different centralities’ fluctuations by the dynamics of real-world preferences. Consecutively, we apply our model in the user preference change detection task, reaching competitive levels of accuracy on Twitter network. © 2019, Springer International Publishing AG, part of Springer Nature.

Abstract

Abstract
In this study, a non-probabilistic program is proposed to a trading framework for demand response (DR) aggregators. Both sides of the aggregator, including upper side and down side of this entity, have been taken into account. In the down-side of the aggregator, two popular programs are considered such as reward-based program and time-of-use (TOU) program, where DR is obtained from these resources. The acquired DR is being sold to the purchasers in the other side of the aggregator through DR options and fixed DR contracts. To the aim of increasing the desired target profit of risk-seeker aggregator, an opportunity function of information-gap decision theory (IGDT) is used to handle the uncertainty, which is solved in General Algebraic Modeling System (GAMS) software. This model is implemented in a realistic case study.

Abstract
The fabrication of optical waveguides with femtosecond laser direct writing is reported in two materials, Suprasil1 and Eagle2000. The influence of typical fabrication parameters, such as pulse energy and scan velocity, on the waveguide's spectral characteristics is explored from 500 to 1700 nm. Tests conducted in Suprasil1 evidence a strong presence of Rayleigh scattering, hindering the production of low-loss waveguides at short wavelengths. On the other hand, optical waveguides fabricated in Eagle2000 exhibited lower insertion losses at short wavelengths, enabling the fabrication of low-loss broadband optical waveguides with a two order of magnitude higher scan velocity when compared with Suprasil1.

Abstract

Abstract
This article proposes the optimal coordination problem of protective relays within a hybrid optimisation framework which is presented based on integer coded genetic algorithm (ICGA) and non-linear programming (NLP). The optimal coordination problem of directional overcurrent relays (DOCRs) is implemented while aimed at finding the optimal plug setting multiplier (PSM) and time dial setting (TDS). In this respect, PSM is a function of the current transformer (CT) size and the tap of the relay which is discrete in nature. TDS is a function of the operating time of the relay for different short-circuit currents at different locations of the system. Here, the variables of the problem are decomposed into continuous and discrete variables. The first stage of the problem uses the ICGA to determine the size of CTs considering the permitted tap of relays while the second stage utilises the NLP method to evaluate the feasibility and optimality. The presented framework is then simulated on an 8-bus test system. The obtained results verify the effectiveness and the applicability of the optimisation technique to find the optimal settings of DOCRs.