Abstract: Load forecasting has become in recent years one of the major areas of research in electrical engineering. Most traditional forecasting models and artificial intelligence neural network techniques have been tried out in this task. Artificial neural networks (ANN) have lately received much attention, and a great number of papers have reported successful experiments and practical tests. This article presents the development of an ANN-based short-term load forecasting model with improved generalization technique for the Regional Power Control Center of Saudi Electricity Company, Western Operation Area (SEC-WOA). The proposed ANN is trained with weather-related data and historical electric load-related data using the data from the calendar years 2001, 2002, 2003, and 2004 for training. The model tested for one week at five different seasons, typically, winter, spring, summer, Ramadan and fall seasons, and the mean absolute average error for one hour-ahead load forecasting found 1.12%.
Abstract: The thermal, epithermal and fast fluxes were
calculated for three irradiation channels at Egypt Second Research
Reactor (ETRR-2) using CITVAP code. The validity of the
calculations was verified by experimental measurements. There are
some deviations between measurements and calculations. This is due
to approximations in the calculation models used, homogenization of
regions, condensation of energy groups and uncertainty in nuclear
data used. Neutron flux data for the three irradiation channels are
now available. This would enable predicting the irradiation
conditions needed for future radioisotope production.
Abstract: An experiment was conducted using two aeration
methods (water-into-air and air-into-water) and followed by filtration
processes using manganese greensand material. The properties of
groundwater such as pH, dissolved oxygen, turbidity and heavy metal
concentration (iron and manganese) will be assessed. The objectives
of this study are i) to determine the effective aeration method and ii)
to assess the effectiveness of manganese greensand as filter media in
removing iron and manganese concentration in groundwater. Results
showed that final pH for all samples after treatment are in range from
7.40 and 8.40. Both aeration methods increased the dissolved oxygen
content. Final turbidity for groundwater samples are between 3 NTU
to 29 NTU. Only three out of eight samples achieved iron
concentration of 0.3mg/L and less and all samples reach manganese
concentration of 0.1mg/L and less. Air-into-water aeration method
gives higher percentage of iron and manganese removal compare to
water-into-air method.
Abstract: This paper presents application artificial intelligent (AI) techniques, namely artificial neural network (ANN), adaptive neuro fuzzy interface system (ANFIS), to estimate the real power transfer between generators and loads. Since these AI techniques adopt supervised learning, it first uses modified nodal equation method (MNE) to determine real power contribution from each generator to loads. Then the results of MNE method and load flow information are utilized to estimate the power transfer using AI techniques. The 25-bus equivalent system of south Malaysia is utilized as a test system to illustrate the effectiveness of both AI methods compared to that of the MNE method. The mean squared error of the estimate of ANN and ANFIS power transfer allocation methods are 1.19E-05 and 2.97E-05, respectively. Furthermore, when compared to MNE method, ANN and ANFIS methods computes generator contribution to loads within 20.99 and 39.37msec respectively whereas the MNE method took 360msec for the calculation of same real power transfer allocation.
Abstract: The complexity of teaching English in higher
institutions by non-native speakers within a second/foreign language
setting has created continuous discussions and research about
teaching approaches and teaching practises, professional identities
and challenges. In addition, there is a growing awareness that
teaching English within discipline-specific contexts adds up to the
existing complexity. This awareness leads to reassessments,
discussions and suggestions on course design and content and
teaching approaches and techniques. In meeting expectations
teaching at a university specified in a particular discipline such as
engineering, English language educators are not only required to
teach students to be able to communicate in English effectively but
also to teach soft skills such as problem solving skills. This paper is
part of a research conducted to investigate how English language
educators negotiate with the complexities of teaching problem
solving skills through English language teaching at a technical
university. This paper reports the way an English language educator
identified himself and the way he approached his teaching in this
institutional context.