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Non-linear support vector machine classification models using kernel tricks with applications
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The support vector machine, also known as SVM, is a type of supervised learning model that can be used for classification or regression depending on the datasets. SVM is used to classify data points by determining the best hyperplane between two or more groups. Working with enormous datasets, on the other hand, might result in a variety of issues, including inefficient accuracy and time-consuming. SVM was updated in this research by applying some non-linear kernel transformations, which are: linear, polynomial, radial basis, and multi-layer kernels. The non-linear SVM classification model was illustrated and summarized in an algorithm using kernel tricks. The proposed method was examined using three simulation datasets with different sample sizes (50, 100, 200). A comparison between non-linear SVM and two standard classification methods was illustrated using various compared features. Our study has shown that the non-linear SVM method gives better results by checking: sensitivity, specificity, accuracy, and time-consuming. © 2024 Author(s).

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
A Tile with Nested Chain Abacus
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This study had succeeded in producing a new graphical representation of James abacus called nested chain abacus. Nested chain abacus provides a unique mathematical expression to encode each tile (image) using a partition theory where each form or shape of tile will be associated with exactly one partition.Furthermore, an algorithm of nested chain abacus movement will be constructed, which can be applied in tiling theory.

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Publication Date
Mon Jan 01 2024
Journal Name
Jordanian Journal Of Computers And Information Technology
ARABIC SOFT SPELLING CORRECTION WITH T5
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Spelling correction is considered a challenging task for resource-scarce languages. The Arabic language is one of these resource-scarce languages, which suffers from the absence of a large spelling correction dataset, thus datasets injected with artificial errors are used to overcome this problem. In this paper, we trained the Text-to-Text Transfer Transformer (T5) model using artificial errors to correct Arabic soft spelling mistakes. Our T5 model can correct 97.8% of the artificial errors that were injected into the test set. Additionally, our T5 model achieves a character error rate (CER) of 0.77% on a set that contains real soft spelling mistakes. We achieved these results using a 4-layer T5 model trained with a 90% error inject

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Publication Date
Wed Jan 01 2020
Journal Name
Revista Latinoamericana De Hipertensión
Autonomic symptoms in patients with migraine
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Publication Date
Wed Feb 01 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

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Publication Date
Sat Oct 01 2022
Journal Name
The Egyptian Journal Of Hospital Medicine
Neudesin Levels in Patients with Thyroidism
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Background: Neudesin is a peptide secreted in brain and adipose tissues that has neural and metabolic functions. Its role as regulator of energy expenditure leads to assumption that its level may be regulated depending on thyroid gland pathology. Objective: This study aimed to investigate serum neudesin levels in patients with thyroidism and to evaluate1 any possible relationship between plasma neudesin levels and thyroid hormone levels. Methods: The study included 100 women with newly diagnosed thyroidisim were subdivided into two groups: hyperthyroidism group (50 female patients with age ranged from 18 to 60 years) and hypothyroidism group (50 female patients with age ranged from 18 to 75 years). A control group (30 healthy females with a

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Publication Date
Tue Feb 28 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Bitcoin Prediction with a hybrid model
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. In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction a

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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
A Comparative Study on the Double Prior for Reliability Kumaraswamy Distribution with Numerical Solution
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This work, deals with Kumaraswamy distribution. Kumaraswamy (1976, 1978) showed well known probability distribution functions such as the normal, beta and log-normal but in (1980) Kumaraswamy developed a more general probability density function for double bounded random processes, which is known as Kumaraswamy’s distribution. Classical maximum likelihood and Bayes methods estimator are used to estimate the unknown shape parameter (b). Reliability function are obtained using symmetric loss functions by using three types of informative priors two single priors and one double prior. In addition, a comparison is made for the performance of these estimators with respect to the numerical solution which are found using expansion method. The

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Publication Date
Wed Mar 29 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Possible Augmentive Effect of Antioxidant Vitamin C in Patients with Essential Hypertension Treated with Amlodipin or Enalapril
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Hypertension is identified as one of the most significant risk factors for cardiovascular diseases (CVDs). There is growing evidence showing that oxidative stress plays a major role in hypertension. Increased production of reactive oxygen species and decrease bioavailability of antioxidant have been demonstrated in experimental and human hypertension. The present study was directed to determine the beneficial effect of the antioxidant vitamin C in patients with essential hypertension treated with the calcium channel blocker (amlodipine) or with the angiotensin converting enzyme inhibitor (enalapril). Ninety six patients (50 females and 46 males) with essential hyp

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Publication Date
Fri Dec 15 2017
Journal Name
Journal Of Baghdad College Of Dentistry
Effectiveness of Intra articular Injection of Platelet-Rich Plasma in Patients with Anterior Disc Displacement with Reduction
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Background: Anterior disc displacement with reduction (ADDWR) is the most common form of the internal derangement (ID) of temporomandibular joint (TMJ). It is a painful progressive dysfunction and clinically characterized by reciprocal clicking due to shift in the disc anteriorly in relation to the condyle and fossa during mandible elevation. Minimally invasive therapy such as intra-articular injection of platelet-rich plasma (PRP) has been used. PRP is a natural autologous product with a high platelet concentration obtained by centrifugation process to enhance tissue healing through several growth factors (GFs), which are released after endogenous activation. The aim of this study is to assess this technique which is increasingly used toda

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Publication Date
Sun Mar 02 2014
Journal Name
Baghdad Science Journal
Study ABO/Rh system with Endothelial Inflammatory Factors in Iraqi Arab Female with Diabetes Mellitus Type II
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Diabetes mellitus type II is a disorder of metabolism and complex diseases affected by genetic environmental factors and associated with inflammation. The symptoms of type II diabetes develop gradually, which are associated with increased blood concentration of marker of the endothelial inflammatory factors. The expression of adhesion molecules, including E-selectin, intracellular adhesion molecule-1(ICAM-1) and vascular cell adhesion molecule-1 (VCAM-1) on the surface of vascular endothelial cells to help leukocyte stick to other surrounding tissues. Many researchers have made attempts to determine the significance of particular ABO phenotype for the susceptibility to diseases. Many reports show a strong association with the ABO blood grou

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