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Nicosia, Cyprus

Papadopoulos H.,Frederick University | Papadopoulos H.,Frederick Research Center
Neurocomputing | Year: 2013

Venn Prediction (VP) is a new machine learning framework for producing well-calibrated probabilistic predictions. In particular it provides well-calibrated lower and upper bounds for the conditional probability of an example belonging to each possible class of the problem at hand. This paper proposes five VP methods based on Neural Networks (NNs), which is one of the most widely used machine learning techniques. The proposed methods are evaluated experimentally on four benchmark datasets and the obtained results demonstrate the empirical well-calibratedness of their outputs and their superiority over the outputs of the traditional NN classifier. © 2012 Elsevier B.V.


Papadakis A.P.,Frederick University
Journal of Plasma Physics | Year: 2013

The streamer propagation in point-plane, non-uniform gaps under high applied electric fields, prior to the impact of primary streamer on cathode, is analyzed. The configuration used is an anode hyperboloid with 50-μm radius of curvature, and a flat plate as the cathode. The applied voltage is 130-kV direct current, and an initial electron is assumed to exist close to the anode in ambient air. The geometry used is a two-dimensional axisymmetry with a gap of 5 cm between the anode and the cathode. It is shown that the streamer is formed on the anode tip as expected, and midway toward the cathode, it separates into two streamers, the primary streamer that continues its propagation toward the cathode, and the branched streamer expanding radially toward the outer boundaries. The qualitative behavior of the discharge is analyzed in terms of streamer speeds, radial and axial electric fields, charged particle densities, and conductive currents. A branched streamer plasma structure was observed along the path of the primary plasma structure expanding radially outwards. Copyright © 2012 Cambridge University Press.


Fokaides P.A.,Frederick University | Papadopoulos A.M.,Aristotle University of Thessaloniki
Energy and Buildings | Year: 2014

The establishment of a methodology for the calculation of the cost-optimal insulation thickness of building elements has been a subject of interest for some years. Many studies have been conducted on the ideal insulation thickness and been based on specific assumptions and approaches. The introduction of the Energy Performance of Buildings Directive recast (2010/31/EC) in May 2010, leads to the compulsory implementation of a specific methodology for this purpose by all European Union member states (Article 5, EPBD recast). Therefore, a study on this subject was conducted, to evaluate the results of previous studies and the strengths and weaknesses of the previous methodologies and to determine how the methodologies should be further developed to provide more reliable results. Additionally, a derived model was validated by a parametric study that examined all possible aspects that could potentially affect the end results. The minimum requirements of the insulation thickness for three selected European cities were also compared to the results of the proposed model applied to these cities. The results show that the proposed model provides a better compromise between simplicity and accuracy, leading at the same time to significantly lower U-values and therefore to improved energy efficiency of the buildings. © 2013 Elsevier B.V. All rights reserved.


Charalambous C.,Frederick University | Fleszar K.,American University of Beirut
Computers and Operations Research | Year: 2011

A new heuristic algorithm for solving the two-dimensional bin-packing problem with guillotine cuts (2DBPG) is presented. The heuristic constructs a solution by packing a bin at a time. Central to the adopted solution scheme is the principle of average-area sufficiency proposed by the authors for guiding selection of items to fill a bin. The algorithm is tested on a set of standard benchmark problem instances and compared with existing heuristics producing the best-known results. The results presented attest to the efficacy of the proposed scheme. © 2010 Elsevier Ltd. All rights reserved.


Panaoura A.,Frederick University
Computers in Human Behavior | Year: 2012

The present study investigates the improvement of students' mathematical performance by using a mathematical model through a computerized approach. We had developed an intervention program and 11 years students worked independently on a mathematical model in order to improve their self-representation in mathematics, to self-regulate their performance and consequently to improve their problem solving ability. The emphasis of using the specific model was on dividing the problem solving procedure into stages, the concentration on the students' cognitive processes at each stage and the self-regulation of those cognitive processes in order to overcome cognitive obstacles. The use of the computer offered the opportunity to give students general comments, hints and feedback without the involvement of their teachers. Students had to communicate with a cartoon animation presenting a human being who faced difficulties and cognitive obstacles during problem solving procedure. Three tools were constructed for pre- and post-test (self-representation, mathematical performance and self-regulation). There were administered to 255 students (11 years old), who constituted the experimental and the control group. Results confirmed that providing students with the opportunity to self-reflect on their learning behavior when they encounter obstacles in problem solving is one possible way to enhance students' self-regulation and consequently their mathematical performance. © 2012 Elsevier Ltd. All rights reserved.

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