Power System Parameters Forecasting Using Hilbert-Huang Transform and Machine Learning

A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and a feature analysis of initial retrospective data using the Hilbert-Huang transform and machine learning algorithms. The random forests and gradient boosting trees learning techniques were examined. The decision tree techniques were used to rank the importance of variables employed in the forecasting models. The Mean Decrease Gini index is employed as an impurity function. The resulting hybrid forecasting models employ the radial basis function neural network and support vector regression. Apart from introduction and references the paper is organized as follows. The section 2 presents the background and the review of several approaches for short-term forecasting of power system parameters. In the third section a hybrid machine learning-based algorithm using Hilbert-Huang transform is developed for short-term forecasting of power system parameters. Fourth section describes the decision tree learning algorithms used for the issue of variables importance. Finally in section six the experimental results in the following electric power problems are presented: active power flow forecasting, electricity price forecasting and for the wind speed and direction forecasting

What influences student participation in asynchronous online discussions

Asynchronous online discussions are widely used in online and blended learning courses. Participation by adult learners can be encouraged by the contributions of teachers, and when online groups are given well-structured tasks that are assessed. The introduction of such discussions to a pre-existing short course in mentorship for qualified health care professionals offered an opportunity to compare participation by different groups studying concurrently. This was done by counting numbers of student contributions to twenty-four different online groups, regardless of length or content. This showed that the contribution of teachers was not an important factor in influencing student participation, though individual students who contributed prolifically tended to encourage their fellow group members to contribute more. These results may not be generalizable: the course was short, the discussions focused on a well-structured and assessed task, and the learners were mature

Intended or unintended? Issues arising from the implementation of the UK Government’s 2003 Schools Workforce Remodelling Act

The United Kingdom (UK) Government's 2003 Workforce Remodelling Act (DfES, 2003) contained nine key points aimed at supporting teachers and schools to raise educational standards without adding additional workload responsibilities. In September 2005 planning, preparation and assessment (PPA) time was introduced. This allows for all teachers to have 10% of their timetable to plan lessons, prepare resources and assess pupils' work. This raises issues of what 10% of their time, with pupils, teachers relinquish for PPA. One common solution in primary schools seems to have been to employ coaches (particularly football coaches) to teach Physical Education (PE) lessons. The purpose of this study was therefore to identify the knowledge, skill and understanding of a group of community-based football coaches working in PPA time in primary schools and to understand the implications for schools, coaches and coach educators. Results showed that these coaches had very little knowledge of the National Curriculum Physical Education (NCPE) and used a narrow range of teaching methods. Some of their pedagogical decision making had a negative consequence on pupils' learning. Thirteen of the twenty-one coaches studied did not plan in the short, medium or long term. There was evidence of routine action (Dewey, 1933) although there was some evidence of reflection. These findings are discussed in relation to the implications of employing coaches to teach the NCPE in schools and also in relation to what Continuing Professional Development (CPD) coaches need to develop the necessary knowledge, skills and understanding for working in schools. Although there is a clear PE focus to this current study, there are implications for the teaching of other subjects in primary schools in England and for the use of sports coaches within education in other national contexts. Despite differences in government policies and practices in schools, in many countries there are likely to be issues with the status, delivery and resourcing of PE

Linear Time Feature Selection for Regularized Least-Squares

We propose a novel algorithm for greedy forward feature selection for regularized least-squares (RLS) regression and classification, also known as the least-squares support vector machine or ridge regression. The algorithm, which we call greedy RLS, starts from the empty feature set, and on each iteration adds the feature whose addition provides the best leave-one-out cross-validation performance. Our method is considerably faster than the previously proposed ones, since its time complexity is linear in the number of training examples, the number of features in the original data set, and the desired size of the set of selected features. Therefore, as a side effect we obtain a new training algorithm for learning sparse linear RLS predictors which can be used for large scale learning. This speed is possible due to matrix calculus based short-cuts for leave-one-out and feature addition. We experimentally demonstrate the scalability of our algorithm and its ability to find good quality feature sets.Comment: 17 pages, 15 figure

Comparative assessment of young learners' foreign language competence in three Eastern European countries

This paper concerns teacher practices in, and beliefs about, the assessment of young learners' progress in English in three Eastern European countries (Slovenia, Croatia, and the Czech Republic). The central part of the paper focuses on an international project involving empirical research into assessment of young learners' foreign language competence in Slovenia, Croatia and the Czech Republic. With the help of an adapted questionnaire, we collected data from a non-random sample of primary and foreign language teachers who teach foreign languages at the primary level in these countries. The research shows that English as a foreign language is taught mostly by young teachers either primary specialists or foreign language teachers. These teachers most frequently use oral assessment/interviews or self-developed tests. Other more authentic types of assessment, such as language portfolios, are rarely used. The teachers most frequently assess speaking and listening skills, and they use assessment involving vocabulary the most frequently of all. However, there are significant differences in practice among the three countries