Rudimentary non-communicating functional uterine horn with unicornuate uterus, originating from anomalous embryological development of one Mullerian duct, is prone to different complications either at the gynecological or obstetrical level such as chronic pelvic pain, hematometra, subfertility and decreased quality of life. This unique case report presents a 14-year-old female with a history of severe chronic pelvic pain. She was diagnosed with Familial Mediterranean Fever (FMF) and had an appendectomy for suspected appendicitis within the symptoms’ interval. Ultrasound showed a right 5*6 cm right complex cystic mass assuming ovarian in place. She underwent a suspected endometrioma cystectomy operation and was diagnosed with left unico

A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

This study was carried out in the laboratories of fish and animal resource center-Agricultural Research Directorate for the period between 1/3-26/5/2015 to study the effect of total and partial substitution of white corn (WC) Sorghum bicolor germinated for different period and additive mixture of probiotic & diet enzymes of yellow corn (YC) Zea mays in common carp Cyprinus carpio L. diets. The fish fed on experimental diets contained two levels of substitution germination WC with three different periods and not germination with 0.5% mixture of probiotic+diet enzymes (50% and 100%) from YC. A 11 experimental diets were formulated, diets 1 and 2 used raw WC without germinate at two substitution levels of 50% and 100% respectively of YC

     Data mining is a data analysis process using software to find certain patterns or rules in a large amount of data, which is expected to provide knowledge to support decisions. However, missing value in data mining often leads to a loss of information. The purpose of this study is to improve the performance of data classification with missing values, ​​precisely and accurately. The test method is carried out using the Car Evaluation dataset from the UCI Machine Learning Repository. RStudio and RapidMiner tools were used for testing the algorithm. This study will result in a data analysis of the tested parameters to measure the performance of the algorithm. Using test variations: performance at C5.0, C4.5, and k-NN at 0% missi

The accumulation of sediment in reservoirs poses a major challenge that impacts the storage capacity, quality of water, and efficiency of hydroelectric power generation systems. Geospatial methods, including Geographic Information Systems (GIS) and Remote Sensing (RS), were used to assess Dukan Reservoir sediment quantities. Satellite and reservoir water level data from 2010 to 2022 were used for sedimentation assessment. The satellite data was used to analyze the water spread area, employing the Normalized Difference Water Index (NDWI) and Modified Normalized Difference Water Index (MNDWI) to enhance the water surface in the satellite imagery of Dukan Reservoir. The cone formula was employed to calculate the live storag

A Geographic Information System (GIS) is a computerized database management system for accumulating, storage, retrieval, analysis, and display spatial data. In general, GIS contains two broad categories of information, geo-referenced spatial data and attribute data. Geo-referenced spatial data define objects that have an orientation and relationship in two or three-dimensional space, while attribute data is qualitative data that can be counted for recording and analysis. The main aim of this research is to reveal the role of GIS technology in the enhancement of bridge maintenance management system components such as the output results, and make it more interpretable through dynamic colour coding and more sophisticated visualization

Sheet piles are necessary with hydraulic structures as seepage cut-off to reduce the seepage. In this research, the computational work methodology was followed by building a numerical model using Geo-Studio program to check the efficiency of using concrete sheet piles as a cut-off or reducer for seepage with time if the sheet piles facing the drawdown technique. Al-Kifil regulator was chosen as a case study, an accurate model was built with a help of observed reading of the measuring devices, which was satisfactory and helped in checking the sheet piles efficiency. Through the study, three scenarios were adopted (with and without) drawdown technique, it was found that at the short time there's no effect of the drawdown technique on