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Evaluation of Ultrasonography in the Diagnosis of Acute Appendicitis with Histopathology as Gold Standard
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Background: Acute appendicitis is the most common surgical abdominal emergency with a life time prevalence of 1 to 7 individuals. Because the clinical diagnosis of acute appendicitis remains a challenge to surgeons, so different aids were introduced like different scoring systems, computer aided programs, ultrasonography, computerized tomography, Magnetic resonance imaging, Gastrointestinal tract contrast studies and laparoscopy to improve the diagnostic accuracy.

Objective: To evaluate ultrasound in the diagnosis of acute appendicitis in those patients clinically diagnosed with histopathology as gold standard.

Methods: A cross sectional study carried in Al-kindy Teaching Hospital through one year duration from 1st of may2015 to1st of May 2016. All included patients were subjected to ultrasonographic examination to assess the vermiform appendix with a graded compression technique. The Ultrasonography findings were recorded as positive and negative for acute appendicitis.

All the appendices removed from the study patients were sent for histopathological study. Statistical analysis done using (SPSS) version 21, Chi-sequare test used for categorical variables and t-test was used to compare between two means. Level of significance (P value) set at ≤ 0.05.

Results: A total of 215 patients with suspected appendicitis, males 112 (52.09%) and females 103(47.9%) were included in present study. The validity results of ultrasound in comparison with histopathology findings were as following; accuracy 86.5%, sensitivity 86.5%, specificity 86.6%, positive predictive value 99.8% and negative predictive value 32.5%.

Conclusion: The ultrasonography has a good accuracy, sensitivity and specificity in diagnosing acute appendicitis.

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Publication Date
Sat Feb 12 2022
Journal Name
Engineering, Technology & Applied Science Research
Prestressing Effects on Full Scale Deep Beams with Large Web Openings¨: An Experimental and Numerical Study
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Most studies on deep beams have been made with reinforced concrete deep beams, only a few studies investigate the response of prestressed deep beams, while, to the best of our knowledge, there is not a study that investigates the response of full scale (T-section) prestressed deep beams with large web openings. An experimental and numerical study was conducted in order to investigate the shear strength of ordinary reinforced and partially prestressed full scale (T-section) deep beams that contain large web openings in order to investigate the prestressing existence effects on the deep beam responses and to better understand the effects of prestressing locations and opening depth to beam depth ratio on the deep beam performance and b

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Publication Date
Wed Nov 27 2024
Journal Name
International Journal Of Integrated Engineering
Noise Modeling and Removal from Electrocardiogram Signals: A Study Using Wavelet Transform with Graphical User Interface
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The electrocardiogram (ECG) is the recording of the electrical potential of the heart versus time. The analysis of ECG signals has been widely used in cardiac pathology to detect heart disease. The ECGs are non-stationary signals which are often contaminated by different types of noises from different sources. In this study, simulated noise models were proposed for the power-line interference (PLI), electromyogram (EMG) noise, base line wander (BW), white Gaussian noise (WGN) and composite noise. For suppressing noises and extracting the efficient morphology of an ECG signal, various processing techniques have been recently proposed. In this paper, wavelet transform (WT) is performed for noisy ECG signals. The graphical user interface (GUI)

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Publication Date
Tue Jun 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
Compare Prediction by Autoregressive Integrated Moving Average Model from first order with Exponential Weighted Moving Average
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The prediction process of time series for some time-related phenomena, in particular, the autoregressive integrated moving average(ARIMA) models is one of the important topics in the theory of time series analysis in the applied statistics. Perhaps its importance lies in the basic stages in analyzing of the structure or modeling and the conditions that must be provided in the stochastic process. This paper deals with two methods of predicting the first was a special case of autoregressive integrated moving average which is ARIMA (0,1,1) if the value of the parameter equal to zero, then it is called Random Walk model, the second was the exponential weighted moving average (EWMA). It was implemented in the data of the monthly traff

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Publication Date
Mon Nov 06 2023
Journal Name
Eneurologicalsci
Dandy-Walker syndrome associated with a giant occipital meningocele: A case report and a literature review
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HTH Ahmed Dheyaa Al-Obaidi,", Ali Tarik Abdulwahid', Mustafa Najah Al-Obaidi", Abeer Mundher Ali', eNeurologicalSci, 2023

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Publication Date
Sun Apr 13 2025
Journal Name
Scientific Reports
Optimized image segmentation using an improved reptile search algorithm with Gbest operator for multi-level thresholding
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Abstract<p>Image segmentation using bi-level thresholds works well for straightforward scenarios; however, dealing with complex images that contain multiple objects or colors presents considerable computational difficulties. Multi-level thresholding is crucial for these situations, but it also introduces a challenging optimization problem. This paper presents an improved Reptile Search Algorithm (RSA) that includes a Gbest operator to enhance its performance. The proposed method determines optimal threshold values for both grayscale and color images, utilizing entropy-based objective functions derived from the Otsu and Kapur techniques. Experiments were carried out on 16 benchmark images, which inclu</p> ... Show More
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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
AlexNet Convolutional Neural Network Architecture with Cosine and Hamming Similarity/Distance Measures for Fingerprint Biometric Matching
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In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare

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Publication Date
Fri Oct 01 2010
Journal Name
2010 Ieee Symposium On Industrial Electronics And Applications (isiea)
Distributed t-way test suite data generation using exhaustive search method with map and reduce framework
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Publication Date
Fri Apr 14 2023
Journal Name
Journal Of Big Data
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
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Abstract<p>Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for</p> ... Show More
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Publication Date
Fri Feb 09 2024
Journal Name
Sustainability
Enhancing Asphalt Performance and Its Long-Term Sustainability with Nano Calcium Carbonate and Nano Hydrated Lime
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Nanomaterials enhance the performance of both asphalt binders and asphalt mixtures. They also improve asphalt durability, which reduces resource consumption and environmental impact in the long term associated with the production and transportation of asphalt materials. Thus, this paper studies the effectiveness of Nano Calcium Carbonate (Nano CaCO3) and Nano Hydrated Lime (NHL) as modifiers and examines their impact on ranges from 0% to 10% through comprehensive laboratory tests. Softening point, penetration, storage stability, viscosity, and mass loss due to short-term aging using the Rolling Thin Film Oven Test (RTFO) were performed on asphalt binders. Results indicated a significant improvement in binder stiffness, particularly

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Publication Date
Sun Mar 28 2021
Journal Name
Journal Of The College Of Education For Women
The Phenomenon of Phonological Follow in Al-Amali Abi Ali Al-Qali’s Book (seq.356 Hijri): A Phonological Study: هند فاضل عباس
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This research discusses the verbal follow phenomenon in Al-Amali Abi Al-Qali’s book (seq.356 Hijri). It aims to limit the examples of this phenomenon in the book, and  examine it phonologically. Accordingly, the researcher adopted the analaytical descriptive approach, taking into account Al-Rawi’s letter when ordering the verbal follow-based examples, and the order they took in the book in question. The purposes behind this phonological study of verbal follow in Al-Amali’s book are to: reach the sounds which Arabs prefer in the process of following, confirm different beautiful and desirable senses, have easy and speedy pronunciation, maintain harmony between adjacent sounds, count the sounds that occur at the beginning of the

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