Video corrections of undergraduate teaching lab reports

Comunicació presentada a INTED2019, 13th International Technology, Education and Development Conference. (March 11-13, 2019, Valencia, Spain).Here it is presented a new methodology based on using video recordings for the evaluation and marking of lab reports in the undergraduate teaching labs. Students are typically requested these reports at each lab session. The reports are partly (or fully) used for the determination of the students mark related to the teaching labs. These reports do not always have the quality expected, since undergraduate students frequently experience different difficulties. Video recordings of the marking process of the reports, with the inclusion of a detailed identification and explanation of the mistakes found, have been performed for the Materials Technology subject in the 4th course of the Industrial Technology Engineering degree. These video recordings, unlike the typically adopted corrections using text comments, were more warmly welcomed by the students, increased the comprehension of the mistakes they performed, and helped them to learn how to prepare higher quality reports. In addition, most of the students considered that these video corrections should be generally implemented in all the teaching labs. Finally, it was also found that marking through this method saves a significant amount of marking time to the lecture

Combined hydro-wind generation bids in a pool-based electricity market

Present regulatory trends are promoting the irect participation of wind energy in electricity markets. The final result of these markets sets the production scheduling for the operation time, including a power commitment from the wind generators. However, wind resources are uncertain, and the final power delivered usually differs from the initial power committed. This imbalance produces an overcost in the system, which must be paid by those who produce it, e.g., wind generators among others. As a result, wind farm revenue decreases, but it could increase by allowing wind farms to submit their bids to the markets together with a hydro generating unit, which may easily modify its production according to the expected imbalance. This paper presents a stochastic optimization technique that maximizes the joint profit of hydro and wind generators in a pool-based electricity market, taking into account the uncertainty of wind power prediction.En prens

Aerodynamic Optimization of High-Speed Trains Nose using a Genetic Algorithm and Artificial Neural Network

An aerodynamic optimization of the train aerodynamic characteristics in term of front wind action sensitivity is carried out in this paper. In particular, a genetic algorithm (GA) is used to perform a shape optimization study of a high-speed train nose. The nose is parametrically defined via Bézier Curves, including a wider range of geometries in the design space as possible optimal solutions. Using a GA, the main disadvantage to deal with is the large number of evaluations need before finding such optimal. Here it is proposed the use of metamodels to replace Navier-Stokes solver. Among all the posibilities, Rsponse Surface Models and Artificial Neural Networks (ANN) are considered. Best results of prediction and generalization are obtained with ANN and those are applied in GA code. The paper shows the feasibility of using GA in combination with ANN for this problem, and solutions achieved are included

A Framework for Evaluating Land Use and Land Cover Classification Using Convolutional Neural Networks

Analyzing land use and land cover (LULC) using remote sensing (RS) imagery is essential for many environmental and social applications. The increase in availability of RS data has led to the development of new techniques for digital pattern classification. Very recently, deep learning (DL) models have emerged as a powerful solution to approach many machine learning (ML) problems. In particular, convolutional neural networks (CNNs) are currently the state of the art for many image classification tasks. While there exist several promising proposals on the application of CNNs to LULC classification, the validation framework proposed for the comparison of different methods could be improved with the use of a standard validation procedure for ML based on cross-validation and its subsequent statistical analysis. In this paper, we propose a general CNN, with a fixed architecture and parametrization, to achieve high accuracy on LULC classification over RS data from different sources such as radar and hyperspectral. We also present a methodology to perform a rigorous experimental comparison between our proposed DL method and other ML algorithms such as support vector machines, random forests, and k-nearest-neighbors. The analysis carried out demonstrates that the CNN outperforms the rest of techniques, achieving a high level of performance for all the datasets studied, regardless of their different characteristics.Ministerio de Economía y Competitividad TIN2014-55894-C2-1-RMinisterio de Economía y Competitividad TIN2017-88209-C2-2-

Applications of impedance spectroscopy in thermoelectricity

t is widely used in a lot of different fields (solar cells, fuel cells, corrosion, supercapacitors, batteries, etc.). • Powerful and very reliable equipment are available in the market. • It allows the separation of the physical processes occurring in a device

The Monetary Transmission Mechanism in Chile: A Medium-Sized Macroeconometric Model

This paper proposes and estimates a macroeconomic model of the Chilean economy. The model is designed as a short- and medium-term inflation-forecasting tool, which precisely identifies the transmission mechanism followed by monetary policy in Chile. The model specifies short-run dynamics as well as long-run equilibrium conditions. Cointegration and error correction techniques are used to estimate the relevant parameters, while some relations are calibrated. The model includes the main components of aggregate demand and external accounts, a supply-side block that relies on a standard production function, a specification for asset prices, and a wage/markup/price and labor market block. The short- and long run interdependence among each of these factors is taken into account to yield a forward-looking macroeconomic dynamic equilibrium. The key steadystate relative prices, such as the long-run real interest rate, the real exchange rate, and the sovereign risk premium, are endogenously determined. The model is used to explore and quantify the effects of monetary policy on inflation and how monetary policy is transmitted to inflation. The results obtained here are compared to the results of other simpler but less informative models, such as VAR and a smaller scale macroeconomic model, based on Phillips curves. The paper analyzes the response of some key macroeconomic variables to a number of permanent shocks.

La Colmena, una publicación humanística y transformadora

La colmena ha cumplido veinte años de vida, en los que ha mantenido una incuestionable calidad editorial y se ha afirmado como una prueba fehaciente del compromiso de la Universidad Autónoma del Estado de México con la difusión de la cultura. En cada uno de los ochenta números de esta publicación trimestral es posible constatar la vitalidad cultural de nuestra institución, al igual que su vocación humanística y su orientación universal