Abstract
We consider the problem of determining the optimal aggregate power consumption of a population of thermostatically controlled loads such as air conditioners. This is motivated by the need to synthesize the demand response for a load serving entity (LSE) catering a population of such customers. We show how the LSE can opportunistically design the aggregate reference consumption to minimize its energy procurement cost, given day-ahead price, load forecast, and ambient temperature forecast, while respecting each individual load's comfort range constraints. The resulting synthesis problem is intractable when posed as a direct optimization problem after Euler discretization of the dynamics, since it results in a mixed-integer linear programming problem with number of variables typically of the order of millions. In contrast, in this paper, we show that the problem is amenable to continuous-time optimal control techniques. Numerical simulations elucidate how the LSE can use the optimal aggregate power consumption trajectory thus computed, for the purpose of demand response.

Abstract
Analysis of student concentration can help to enhance the learning process. Emotions are directly related and directly reflect students’ concentration. This task is particularly difficult to implement in an e-learning environment, where the student stands alone in front of a computer. In this paper, a prototype system is proposed to figure out the concentration level in real-time from the expressed facial emotions during a lesson. An experiment was performed to evaluate the prototype system that was implemented using a client-side application that uses the C# code available in Microsoft Azure Emotion API. We have found that the emotions expressed are correlated with the concentration of the students, and devised three distinct levels of concentration (high, medium, and low). © Springer Nature Switzerland AG 2019.

Abstract
Readability is a linguistic feature that indicates how difficult it is to read a text. Traditional readability formulas were made for the English language. This study evaluates their adequacy to the Portuguese language. We applied the traditional formulas in 10 parallel corpora. We verified that the Portuguese language had higher grade scores (less readability) in the formulas that use the number of syllables per words or number of complex words per sentence. Formulas that use letters by words instead of syllables by words output similar grade scores. Considering this, we evaluated the correlation of the complex words in 65 Portuguese school books of 12 schooling years. We found out that the concept of complex word as a word with 4 or more syllables, instead of 3 or more syllables as originally used in traditional formulas applied to English texts, is more correlated with the grade of Portuguese school books. In the end, for each traditional readability formula, we adapted it to the Portuguese language performing a multiple linear regression in the same dataset of school books. © Springer Nature Switzerland AG 2019.

Abstract
This paper investigates who wins and who loses when firms depart from a mass advertising/uniform pricing strategy (bench-mark model) to a targeted advertising/price discrimination one. Considering a duopoly market in which firms simultaneously compete in prices and advertising decisions, we examine the competitive and welfare effects of personalized pricing with targeted advertising by comparing equilibrium outcomes under customized advertising/ pricing decisions to the results arising under mass advertising and uniform pricing. We show that, when both firms compete in both market segments, all segment consumers are expected to pay higher average prices under the personalized advertising/pricing strategy. We also show that, in the context of our simultaneous game, targeted advertising with price discrimination might boost firms' profits in comparison to the case of mass advertising and uniform prices. The overall welfare effects of the personalized strategy are ambiguous. However, even when the personalized strategy boosts overall welfare, consumers might all be worse-off. Thus the paper gives support to concerns that have been raised re-garding the firms' ability to adopt personalized strategies to boost profits at the expense of consumers.

Abstract
Current approaches for risk management in energy market participation mostly refer to portfolio optimization for long-term planning, and stochastic approaches to deal with uncertainties related to renewable energy generation and market prices variation. Risk assessment and management as integrated part of actual market negotiation strategies is lacking from the current literature. This paper addresses this gap by proposing a novel model for decision support of players' strategic participation in electricity market negotiations, which considers risk management as a core component of the decision-making process. The proposed approach addresses the adaptation of players' behaviour according to the participation risk, by combining the two most commonly used approaches of forecasting in a company's scope: the internal data analysis, and the external, or sectorial, data analysis. The internal data analysis considers the evaluation of the company's evolution in terms of market power and profitability, while the sectorial analysis addresses the assessment of the competing entities in the market sector using a K-Means-based clustering approach. By balancing these two components, the proposed model enables a dynamic adaptation to the market context, using as reference the expected prices from competitor players, and the market price prediction by means of Artificial Neural Networks (ANN). Results under realistic electricity market simulations using real data from the Iberian electricity market operator show that the proposed approach is able to outperform most state-of-the-art market participation strategies, reaching a higher accumulated profit, by adapting players' actions according to the participation risk.

Abstract
The ANTAREX project relies on a Domain Specific Language (DSL) based on Aspect Oriented Programming (AOP) concepts to allow applications to enforce extra functional properties such as energy-efficiency and performance and to optimize Quality of Service (QoS) in an adaptive way. The DSL approach allows the definition of energy-efficiency, performance, and adaptivity strategies as well as their enforcement at runtime through application autotuning and resource and power management. In this paper, we present an overview of the key outcome of the project, the ANTAREX DSL, and some of its capabilities through a number of examples, including how the DSL is applied in the context of the project use cases.