Sumaya Hamad
University of Anbar

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Single line to ground fault detection and location in medium voltage distribution system network based on neural network Ahmed K. Abbas; Sumaya Hamad; Nuha A. Hamad
Indonesian Journal of Electrical Engineering and Computer Science Vol 23, No 2: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v23.i2.pp621-632

Abstract

The aim of this project was to detect and locate the single ground failure lines that occurs in medium voltage (MV) networks on the transmission lines (TL). Compared with anther faults, single line-to-ground (SLG) is the most frequent. The neural network (NN) algorithm was advanced in order to discover and locate SLG faults. The network is simulated through simulated numerous defects at various locations, as well as changing earth resistance from (or 100 Ω) to TL to gather all of the data. In the electromagnetic transients’ program (EMTP) program software, the existing fault have been measured. In addition, the waves were evaluated by utilize MATLAP's fastfourier-transform to calculate the waves of top three of them, On the MV network are fifty hundred faults are simulated all data in the neural network at MATLAB were trained and examined to improve the NN algorithm according to this data. Comparing all the simulated location faults that have been applied with those all locations detected in the NN algorithm, the overall error between them has been found to be very low and not to exceed 0.7. The Simulink circuit was created from this algorithm and checked in order to predict each failure could occur in the future in the MV network.
Content based video retrieval using discrete cosine transform Sumaya Hamad; Ahmeed Suliman Farhan; Doaa Yaseen Khudhur
Indonesian Journal of Electrical Engineering and Computer Science Vol 21, No 2: February 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v21.i2.pp839-845

Abstract

A content based video retrieval (CBVR)framework is built in this paper.  One of the essential features of video retrieval process and CBVR is a color value. The discrete cosine transform (DCT) is used to extract a query video features to compare with the video features stored in our database. Average result of 0.6475 was obtained by using the DCT after implementing it to the database we created and collected, and on all categories. This technique was applied on our database of video, Check 100 database videos, 5 videos in each category.
Analysis the digital images by using morphology operators Hadeel Amjed Saeed; Sumaya Hamad; Azmi Tawfik Hussain
Indonesian Journal of Electrical Engineering and Computer Science Vol 24, No 3: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v24.i3.pp1654-1662

Abstract

In this paper, we deal with morphology images that try to improve the use of images. On the one hand, the process is used to obtain the histogram of the image then converted it into a non-color image (gray scale). The next step is to perform the erosion, dilation, open and close operations on the images, how these methods have important effects, and how can be used on a variable number of images, and found the differences between them. These operations were applied on four different images, check images, four basic operations (dilation, erosion, open and close) for each image were performed. Then, retrieving process to the original state of the image (the colored copy) was applied. The results found that retrieving the original images is difficult, and there is the occurrence of some noises on the image when it was retrieved. Finally, conclusions of the work are presented.