Abstract

Abstract
The analysis of sentiments, emotions and opinions in texts is increasingly important in the current digital world. The existing lexicons with emotional annotations for the Portuguese language are oriented to polarities, classifying words as positive, negative or neutral. To identify the emotional load intended by the author it is necessary also to categorize the emotions expressed by individual words. EmoSpell is an extension of a morphological analyzer with semantic annotations of the emotional value of words. It uses Jspell as the morphological analyzer and a new dictionary with emotional annotations. This dictionary incorporates the lexical base EMOTAIX.PT, which classifies words based on three di erent levels of emotions – global, specific and intermediate. This paper describes the generation of the EmoSpell dictionary using three sources, the Jspell Portuguese dictionary and the lexical bases EMOTAIX.PT and SentiLex-PT. Also, this paper details the web application and web service that exploit this dictionary. It presents also a validation of the proposed approach using a corpus of student texts with di erent emotional loads. The validation compares the analyses provided by EmoSpell with the mentioned emotional lexical bases on the ability to recognize emotional words and extract the dominant emotion from a text. © Maria Inês Maia and José Paulo Leal

Abstract
The optimized dispatch of different distributed generations (DGs) in stand-alone microgrid (MG) is of great significance to the operation's reliability and economy, especially for energy crisis and environmental pollution. Based on controllable load (CL) and combined cooling-heating-power (CCHP) model of micro-gas turbine (MT), a multi-objective optimization model with relevant constraints to optimize the generation cost, load cut compensation and environmental benefit is proposed in this paper. The MG studied in this paper consists of photovoltaic (PV), wind turbine (WT), fuel cell (FC), diesel engine (DE), MT and energy storage (ES). Four typical scenarios were designed according to different day types (work day or weekend) and weather conditions (sunny or rainy) in view of the uncertainty of renewable energy in variable situations and load fluctuation. A modified dispatch strategy for CCHP is presented to further improve the operation economy without reducing the consumers' comfort feeling. Chaotic optimization and elite retention strategy are introduced into basic particle swarm optimization (PSO) to propose modified chaos particle swarm optimization (MCPSO) whose search capability and convergence speed are improved greatly. Simulation results validate the correctness of the proposed model and the effectiveness of MCPSO algorithm in the optimized operation application of stand-alone MG.

Abstract
Motivate students is one of the biggest challenges that teachers have to face, in general and in particular in programming courses. In this article two techniques, aimed at supporting the teaching of programming, are discussed: program animation, and automatic evaluation of programs. Based on the combination of these techniques and their currently available tools, we will describe two possible approaches to increase motivation and improve the success. The conclusions of a first experiment conducted in the classroom will be presented. PEP, a Web-based tool that implements one of the approaches proposed, will be introduced.

Abstract

Abstract
If we want robots to engage effectively with humans in service applications or in collaborative work scenarios they have be endowed with the capacity to perceive the passage of time and control the timing of their actions. Here we report result of a robotics experiment in which we test a computational model of action timing based on processing principles of neurodynamics. A key assumption is that elapsed time is encoded in the consistent buildup of persistent population activity representing the memory of sensory or motor events. The stored information can be recalled using a ramp-to-threshold dynamics to guide actions in time. For the experiment we adopt an assembly paradigm from our previous work on natural human-robot interactions. The robot first watches a human executing a sequence of assembly steps. Subsequently, it has to execute the steps from memory in the correct order and in synchrony with an external timing signal. We show that the robot is able to efficiently adapt its motor timing and to store this information in memory using the temporal mismatch between the neural processing of the sensory feedback about executed actions and the external cue. © 2017 IEEE.