Accurate calculation of transient overvoltages and dielectric stresses from fast-front excitations is required to obtain an optimal dielectric design of power components subjected to these conditions, which are commonly due to switching and lightning, as well as utilization of power-electronic devices. Toroidal transformers are generally used at the low voltage level. However, recent investigations and developments have explored their use at the medium voltage level. This paper analyzes the model-based improvement of the insulation design of medium voltage toroidal transformers. Lumped and distributed parameter models are used and compared to predict the transient response and dielectric stress along the transformer winding. The parameters of the toroidal transformer are computed using the finite element method considering a three-dimensional geometry. Different strategies for insulation design are proposed by means of optimal insulation thickness and electrostatic shield to reduce transient overvoltage and dielectric stress. The results show that the proposed optimal insulation design based on particle swarm optimization with electrostatic shield can substantially reduce the dielectric stress and dielectric distances. Comparison between simulations and experimental results demonstrates that the frequency domain modeling approach results in accurate calculation of transient overvoltages produced by fast front excitation and can be used effectively for insulation design.
In this paper we generalize some of the results due to Bell and Mason on a near-ring N admitting a derivation D , and we will show that the body of evidence on prime near-rings with derivations have the behavior of the ring. Our purpose in this work is to explore further this ring like behavior. Also, we show that under appropriate additional hypothesis a near-ring must be a commutative ring.
Background: Laparoscopic surgery for
appendicitis is now a well established and
advanced method of performing general surgical
procedures.
Objectives: To compare the outcome of
laparoscopic and open appendectomies in terms
of operative time, analgesic requirement,
postoperative complications, hospital stay, return
to normal activity and condition of scar.
Methods: This prospective study was carried
out from 1stMay 2008-1st January 2010, involving
110 patients (45 male and 65 female) with
features suggestive of acute appendicitis were
divided into 45 patients laparoscopic
appendectomy (LA) group and 65 patients open
appendectomy (OA) group, after taking informed
consent. LA was done with the
The continuous growth in technology and technological devices has led to the development of machines to help ease various human-related activities. For instance, irrespective of the importance of information on the Steam platform, buyers or players still get little information related to the application. This is not encouraging despite the importance of information in this current globalization era. Therefore, it is necessary to develop an attractive and interactive application that allows users to ask questions and get answers, such as a chatbot, which can be implemented on Discord social media. Artificial Intelligence is a technique that allows machines to think and be able to make their own decisions. This research showed that the dis
... Show MoreThe current research was aimed at the following:
1. Measurement of Personality Type Observer of the University students.
2. Identify the differences in Personality Type Observer among the University students according to variable of Sex (male / female). And according to variable of Specialization (scientific / literary)
3. Measurement of Withdrawal of the University students.
4. Identify the differences in Withdrawal among the University students according to variable of Sex (male / female). And according to variable of Specialization (scientific / literary).
5. Identify the relationship between Personality Type Observer and Withdrawal.
To achieve this aims of the research, the researchers set up the instrument is scale
Document clustering is the process of organizing a particular electronic corpus of documents into subgroups of similar text features. Formerly, a number of conventional algorithms had been applied to perform document clustering. There are current endeavors to enhance clustering performance by employing evolutionary algorithms. Thus, such endeavors became an emerging topic gaining more attention in recent years. The aim of this paper is to present an up-to-date and self-contained review fully devoted to document clustering via evolutionary algorithms. It firstly provides a comprehensive inspection to the document clustering model revealing its various components with its related concepts. Then it shows and analyzes the principle research wor
... Show MoreBackground: Polycystic ovary syndrome (PCOS) is
the most common form of chronic anovulation
associated with androgen excess; it occurs in about 5
– 10% 0f reproductive age women. Metabolic
syndrome is characterized by insulin resistance,
hypertension, obesity, abnormalities of blood clotting
and dyslipidemia.
Adult women with PCOS have an increased
prevalence of the metabolic syndrome(MBS).
Objectives: To detect the prevalence of metabolic
syndrome in women with proved PCOS, attending the
Specialized Center for Endocrinology and Diabetes, in
Baghdad.
Materials and methods : A total number of 40
women with proved PCOS were included in this study
which was conducted in the Specialized Center f
The proliferation of many editing programs based on artificial intelligence techniques has contributed to the emergence of deepfake technology. Deepfakes are committed to fabricating and falsifying facts by making a person do actions or say words that he never did or said. So that developing an algorithm for deepfakes detection is very important to discriminate real from fake media. Convolutional neural networks (CNNs) are among the most complex classifiers, but choosing the nature of the data fed to these networks is extremely important. For this reason, we capture fine texture details of input data frames using 16 Gabor filters indifferent directions and then feed them to a binary CNN classifier instead of using the red-green-blue
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