The differential protection of power transformers appears to be more difficult than any type of protection for any other part or element in a power system. Such difficulties arise from the existence of the magnetizing inrush phenomenon. Therefore, it is necessary to recognize between inrush current and the current arise from internal faults. In this paper, two approaches based on wavelet packet transform (WPT) and S-transform (ST) are applied to recognize different types of currents following in the transformer. In WPT approach, the selection of optimal mother wavelet and the optimal number of resolution is carried out using minimum description length (MDL) criteria before taking the decision for the extraction features from the WPT tree. In ST approach,
the spectral energy index and the standard deviation (STD) are calculated from the S-matrix obtained by discrete S-transform. The two approaches are tested for generating a trip signal and disconnecting the transformer supply experimentally using 1KVA, 220/110V, 50Hz, ∆ / Y threephase transformer. The experimental results show that the trip signal is initiated faster in WPT approach while the transformer is disconnected from the supply after a delay of 10-15msec in the
two approaches due to computer interface and the relay circuit used.
The use of Bayesian approach has the promise of features indicative of regression analysis model classification tree to take advantage of the above information by, and ensemble trees for explanatory variables are all together and at every stage on the other. In addition to obtaining the subsequent information at each node in the construction of these classification tree. Although bayesian estimates is generally accurate, but it seems that the logistic model is still a good competitor in the field of binary responses through its flexibility and mathematical representation. So is the use of three research methods data processing is carried out, namely: logistic model, and model classification regression tree, and bayesian regression tree mode
... Show MoreSupport vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca
... Show MoreThis research basically gives an introduction about the multiple intelligence
theory and its implication into the classroom. It presents a unit plan based upon the
MI theory followed by a report which explains the application of the plan by the
researcher on the first class student of computer department in college of sciences/
University of Al-Mustansiryia and the teacher's and the students' reaction to it.
The research starts with a short introduction about the MI theory is a great
theory that could help students to learn better in a relaxed learning situation. It is
presented by Howard Gardener first when he published his book "Frames of
Minds" in 1983 in which he describes how the brain has multiple intelligen
The proposal of nonlinear models is one of the most important methods in time series analysis, which has a wide potential for predicting various phenomena, including physical, engineering and economic, by studying the characteristics of random disturbances in order to arrive at accurate predictions.
In this, the autoregressive model with exogenous variable was built using a threshold as the first method, using two proposed approaches that were used to determine the best cutting point of [the predictability forward (forecasting) and the predictability in the time series (prediction), through the threshold point indicator]. B-J seasonal models are used as a second method based on the principle of the two proposed approaches in dete
... Show MoreBlogging is about more than just putting thoughts on a web; it's about connecting with and hearing from anyone who read the work. Many web sites now days help to get a free account to quick post thoughts and photos interact with people, and more. The fastest way to understand blogging is to try it out, but in that case securing the blog is important, by including authentication schemes. In this paper we suggest implications of our research for improving the design and usefulness of blogging systems, and also we divided the blogs depending on the subject and need, which are either to be used in public or only used by small group, so we can suggest different steps for securing the blogs.
Let be an infinite dimensional separable complex Hilbert space and let , where is the Banach algebra of all bounded linear operators on . In this paper we prove the following results. If is a operator, then 1. is a hypercyclic operator if and only if D and for every hyperinvariant subspace of . 2. If is a pure, then is a countably hypercyclic operator if and only if and for every hyperinvariant subspace of . 3. has a bounded set with dense orbit if and only if for every hyperinvariant subspace of , .
The combination of wavelet theory and neural networks has lead to the development of wavelet networks. Wavelet networks are feed-forward neural networks using wavelets as activation function. Wavelets networks have been used in classification and identification problems with some success.
In this work we proposed a fuzzy wavenet network (FWN), which learns by common back-propagation algorithm to classify medical images. The library of medical image has been analyzed, first. Second, Two experimental tables’ rules provide an excellent opportunity to test the ability of fuzzy wavenet network due to the high level of information variability often experienced with this type of images.
&n
... Show MoreThe research aims to presenting a number of scenarios for the investment of the marshes. The problem of research problem was that there is no in-depth analysis of the marshes environment. The traditional methods of the environmental analysis are insufficient. The research community is represented by the decision makers in Maysan Governorate. The research led to proposing of three scenarios with statement the requirements for the success of each one. The most important conclusions are that the three proposed scenarios for marshes investment depend on the availability of the required volunteers for each scenario. The higher the availability of the requirements, the more optimistic the scenario becomes. If t
... Show MoreThis study aims to recognize the most common thinking styles and level of the need for cognitive university students , the relation between thinking styles and the need for cognitive, and there are differences according to gender .The sample consists of (250) males and females university students for the academic year (2013-2014), and the researcher uses two scales;" thinking styles scale (Harison &Bramson, 1986), and the need for cognitive scale" (Cacioppo, Petty & Kao , 1996).
The results show that there is difference in the range of the prevalence of the thinking styles among university students , the scientific thinking style is the most common , the students have got the arrange level of the need for cognitive , and there
Prediction of accurate values of residual entropy (SR) is necessary step for the
calculation of the entropy. In this paper, different equations of state were tested for the
available 2791 experimental data points of 20 pure superheated vapor compounds (14
pure nonpolar compounds + 6 pure polar compounds). The Average Absolute
Deviation (AAD) for SR of 2791 experimental data points of the all 20 pure
compounds (nonpolar and polar) when using equations of Lee-Kesler, Peng-
Robinson, Virial truncated to second and to third terms, and Soave-Redlich-Kwong
were 4.0591, 4.5849, 4.9686, 5.0350, and 4.3084 J/mol.K respectively. It was found
from these results that the Lee-Kesler equation was the best (more accurate) one