2019
Autores
Martins, MPG; Miguéis, VL; Fonseca, DSB; Alves, A;
Publicação
Advances in Intelligent Systems and Computing
Abstract
The present study puts forward a regression analytic model based on the random forest algorithm, developed to predict, at an early stage, the global academic performance of the undergraduates of a polytechnic higher education institution. The study targets the universe of an institution composed of 5 schools rather than following the usual procedure of delimiting the prediction to one single specific degree course. Hence, we intend to provide the institution with one single tool capable of including the heterogeneity of the universe of students as well as educational dynamics. A different approach to feature selection is proposed, which enables to completely exclude categories of predictive variables, making the model useful for scenarios in which not all categories of data considered are collected. The introduced model can be used at a central level by the decision-makers who are entitled to design actions to mitigate academic failure. © 2019, Springer Nature Switzerland AG.
2019
Autores
Pereira, M; Bessa, RJ; Gouveia, C;
Publicação
2019 IEEE MILAN POWERTECH
Abstract
While the transmission system benefits from a high observability, the distribution system has a relatively low level of observability. This problem is already being addressed with the deployment of smart meters, in an effort to make the smart grid concept a reality. Nevertheless, as observability increases, so too does the volume of data, which makes the development of advanced software tools a very important subject. In this paper, the application of image analysis techniques to a low voltage grid is explored, by converting voltage data into an image format, using a cognitive network to evaluate and cluster grid operating modes. The proposed method is applied to a 33-bus low voltage grid to evaluate voltage profiles at each bus and the associated technical limits (voltage limits alarms).
2019
Autores
CARVALHO, A; MORAIS, EP; CUNHA, CR;
Publicação
IBIMA Business Review
Abstract
2019
Autores
Jackson K.; Chapman S.; Conod U.; Correia C.; Sivo G.;
Publicação
AO4ELT 2019 - Proceedings 6th Adaptive Optics for Extremely Large Telescopes
Abstract
The Gemini Infrared Multi-Object Spectrograph (GIRMOS) instrument proposes to carry out Multi-Object Adaptive Optics (MOAO) correction on the residual of the Gemini Mutlti-Conjugate AO System (GeMS)corrected wavefronts in either Ground Layer (GLAO) or Multi-Conjugate (MCAO) mode. This work has been undertaken to determine the extent to which the ensquared energy delivered to a GIRMOS IFU can be improved over typical GeMS operation by adding MOAO correction. One of the key advantages of using the MOAO-fed IFUs is the improvement in performance toward the edge of the field, making the full 2’ field of GeMS more available for simultaneous observing. Using the Object Oriented Matlab Adaptive Optics (OOMAO) library1 to simulate the full system under a wide range of configurations and error conditions, we have established the baseline error budget and used the simulation to enable ongoing investigation into the particular control schemes and system errors that arise from using GeMS LGS and NGS WFSs to divide atmospheric correction between up to 3 DMs at different altitude conjugations and optimization directions.
2019
Autores
Pinto, T; Santos, G; Vale, Z;
Publicação
AAMAS '19: PROCEEDINGS OF THE 18TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS
Abstract
Power and energy systems lack decision-support systems that enable studying big problems as a whole. The interoperability between multi-agent systems that address specific parts of the global problem is essential. Ontologies ease interoperability between heterogeneous systems providing semantic meaning to the information exchanged between the various parties. This paper presents the practical application of a society of multi agent systems, which uses ontologies to enable the interoperability between different types of agent-based simulators, directed to the simulation and operation of electricity markets, smart grids and residential energy management. Real data-based demonstration shows the proposed approach advantages in enabling comprehensive, autonomous and intelligent power system simulation studies.
2019
Autores
Queiroz, S; Vilela, J; Monteiro, E;
Publicação
2019 WIRELESS DAYS (WD)
Abstract
Index Modulation (IM) is a technique that activate k out of n subcarriers of an OFDM symbol to transmit p(1) = right perpendicularlog(2) (n k)left perpendicular bits in symbol's indexes. Since both the symbol's spectrum width and transmission air-time duration remain the same, OFDM-IM outperforms OFDM's Spectral Efficiency (SE) for larger values of (n k). However, OFDM-IM requires an extra step called Index Selector (IxS) which takes T-alpha time units to map a given p(1)-bit input to its corresponding pattern of active subcarriers. This extra overhead virtually enlarges the symbol duration, which is not captured by the classic SE definition. To fulfill this gap, in this work we present the Spectro-Computational Efficiency (SCE) metric. SCE parameterizes either the absolute runtime of T-alpha on a reference hardware or its computational complexity T-alpha(n; k) as function of n and k. Based on SCE, we present theoretical case studies to identify the asymptotic bounds for T-alpha(n, k) across different choices of k. if T-alpha(n, n=2) is at most linear on n the resulting overhead is asymptotically negligible and IxS can handle an arbitrarily large OFDM symbol. Otherwise, OFDM-IM's SCE tends to zero regardless of the hardware processor speed. Also, we situate the inflection-point values for OFDM-IM's SCE between (6 3) and (14 7) in some practical case studies.
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