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The Diagnostic Accuracy of Sonography, With Graded Compression to Image Acute Appendicitis Compared to Histopathologic Results
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Acute appendicitis is the most common surgical abdominal emergency. Its clinical diagnosis remains a challenge to surgeons, so different imaging options were introduced to improve diagnostic accuracy. Among these imaging modality choices, diagnostic medical sonography (DMS) is a simple, easily available, and cost effective clinical tool. The purpose of this study was to assess the accuracy of DMS, in the diagnosis of acute appendicitis compared to the histopathology report, as a gold standard. Between May 2015 and May 2016, 215 patients with suspected appendicitis were examined with DMS. The DMS findings were recorded as positive and negative for acute appendicitis and compared with the histopathological results, as a gold standard. In all, 173 patients were correctly diagnosed as having acute appendicitis by DMS out of 200 cases, with a final histopathologic result. Similarly, DMS revealed 13 normal appendices out of 15 nonappendicitis patients. This demonstrated that DMS has a sensitivity of 86.5%, specificity of 86.6%, positive predictive value of 99.8%, negative predictive value of 32.5%, and overall accuracy of 86.5%. These results suggest that DMS may be an accurate, sensitive, and specific tool for diagnosing acute appendicitis and reducing unnecessary appendectomies. DMS should be considered as a credible imaging modality for diagnosing acute appendicitis.

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Publication Date
Wed Sep 26 2018
Journal Name
Journal Of Research In Ecology
Study of changes using biochemical markers in albino mice after acute exposure to acetamiprid
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The present study aimed to investigate the acetamiprid effects on biochemical aspects in albino mice. Thirty albino mice at the age of 6-8 weeks and average weight 25±5 g were divided into three groups each having ten (10) healthy mice. The first group was orally administrated with distilled water while the second and third groups were orally administrated with 50 mg/mL and 100 mg/mL respectively of acetamprid (0.1 mL) daily for one week. LD50 of acetamiprid was measured and found to be 200 mg/kg. The parameters of evaluations included liver function using Aspartate Aminotransferase (AST), Alanine Aminotransferase (ALT) and Alkaline Phosphatase (ALP). Lipid profile was anal

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Publication Date
Sun Jun 30 2019
Journal Name
International Journal Of Research In Social Sciences And Humanities
CHARACTERISTICS OF THE POWER CHAIN FUNCTION CURVE AND ITS RELATION TO THE ACCURACY OF THE HIGH-JUMP JUMP IN THE HANDBALL
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The skill high-jump scoring is based on mechanical and physical abilities. The most important of all is the strength used by the player from the moment of preparation to the moment of scoring, which led the researchers to study the characteristics of the series of power chain functions of this skill according to (Biosyn System) The players of the national team's back line have a handball to find out the relationship between the properties of the power chain curve and the accuracy of the high jump to the upper and lower target angles. The aim of the research was to identify the values of the Force Series variables for the skill of the high-jump curve of the handball as well as the relationship between the properties of the power chain functi

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Publication Date
Tue Aug 10 2021
Journal Name
Design Engineering
Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eye

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Publication Date
Wed Sep 20 2023
Journal Name
Journal Of Aeronautical Materials
The Effect of A Dry Training Program Using Aids On The Results Of Error Measures And The Effect Size On The Air Pistol Accuracy Of Correction
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The world is keeping pace with evolution in all its fields as a result of scientists' pursuit of continuous scientific and technological development. This evolution included the sports field, which had a large space in the aspect of development and for all disciplines, Therefore, it's reflected today in what we see of records and advanced achievements in sporting events and activities. The development in the field of sports was the result of scientific research (Hussein and Jawad., 2022), where the interest in the training process has become one of the most important pillars of the development of achievement (Neamah and Altay., 2020). The shooting sport has also witnessed a remarkable development due to the diversity and development of its

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Modeling Jar Test Results Using Gene Expression to Determine the Optimal Alum Dose in Drinking Water Treatment Plants
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Coagulation is the most important process in drinking water treatment. Alum coagulant increases the aluminum residuals, which have been linked in many studies to Alzheimer's disease. Therefore, it is very important to use it with the very optimal dose. In this paper, four sets of experiments were done to determine the relationship between raw water characteristics: turbidity, pH, alkalinity, temperature, and optimum doses of alum [   .14 O] to form a mathematical equation that could replace the need for jar test experiments. The experiments were performed under different conditions and under different seasonal circumstances. The optimal dose in every set was determined, and used to build a gene expression model (GEP). The models were co

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Publication Date
Thu Sep 11 2025
Journal Name
Sulaimani Journal For Humanities
Psychological hesitation and its relationship to the accuracy of serving reception skills among Baghdad University volleyball team players
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This study aims to determine the relationship between psychological frequency and the accuracy of receiving a serve in volleyball. The researchers used a descriptive approach, which is best suited to the research problem. The study sample consisted of 12 players from the University of Baghdad volleyball team. Ten players were selected purposively, and two were excluded from the research sample for use in a pilot study, as well as players who participate in volleyball at sports clubs. The sample size represented 83% of the original population. The researchers used the Psychological Frequency Scale developed by Firas Abdul Hussein (1999) for sports-related applications, which consists of 51 positive and negative items. The SPSS version 26 sof

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Publication Date
Tue Dec 15 2020
Journal Name
Journal Of Baghdad College Of Dentistry
Gingival health condition among children of inbreeding parents compared to children of outbreeding parents in Babylon governorate / Iraq
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Background: Consanguineous marriage is a relationship between biologically related individuals. Genetic factors have a role in gene environment interactions that takes the center stage. The evidence of oral disease (gingivitis and periodontitis) may depend on genetic syndromes, inherited diseases, familial studies etc. The present study aims at assessing dental plaque and gingival health condition in children of inbreeding parents compared with children of outbreeding parents among primary schools in Al-Qasem city/ Babylon governorate in Iraq. Materials and methods: this comparative study included three hundred ninety eight (398) students, 6-12 years old, from 4 primary schools; 199 children had their parents of inbreeding marriage with

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Publication Date
Thu Nov 01 2012
Journal Name
Ijcsi International Journal Of Computer Science
Implementing a novel approach an convert audio compression to text coding via hybrid technique
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Compression is the reduction in size of data in order to save space or transmission time. For data transmission, compression can be performed on just the data content or on the entire transmission unit (including header data) depending on a number of factors. In this study, we considered the application of an audio compression method by using text coding where audio compression represented via convert audio file to text file for reducing the time to data transfer by communication channel. Approach: we proposed two coding methods are applied to optimizing the solution by using CFG. Results: we test our application by using 4-bit coding algorithm the results of this method show not satisfy then we proposed a new approach to compress audio fil

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Publication Date
Mon Jan 01 2024
Journal Name
International Journal Of Mathematics And Computer Science
Artificial Intelligence Techniques to Identify Individuals through Palm Image Recognition
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Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

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Scopus (12)
Crossref (4)
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Publication Date
Fri Aug 16 2024
Journal Name
International Journal Of Mathematics And Computer Science
Artificial Intelligence Techniques to Identify Individuals through Palm Image Recognition
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Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep le

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Scopus (12)
Crossref (4)
Scopus Clarivate Crossref