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bsj-4283
A Modified Support Vector Machine Classifiers Using Stochastic Gradient Descent with Application to Leukemia Cancer Type Dataset
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Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different cancer types is important for cancer diagnosis and drug discovery, SGD-SVM is applied for classifying the most common leukemia cancer type dataset. The results that are gotten using SGD-SVM are much accurate than other results of many studies that used the same leukemia datasets.

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Publication Date
Thu Jun 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
Customers emotional blackmail and reduce it the new product- study of the opinions of a sample of customers who deal with peak economy for household items in najaf al Ashraf
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The challenges facing today's multi-customer and this is due to the multiplicity of products and speed in launching new products so search came to reveal the  reveal the of the new product classification standards through a relationship (good products, low interest products, useful products and products desired) and the customer emotionally blackmail through deportation (fear, obligation and guilt). dentified the problem of the research in several questions focused on the nature of the relationship between the variables of research, and for that outline supposedly to search it expresses the head of one hypothesis and branched out of which four hypotheses subset, but in order to ensure the validity of the ass

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Publication Date
Sun Jan 22 2023
Journal Name
Mesopotamian Journal Of Big Data
Parallel Machine Learning Algorithms
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 To expedite the learning process, a group of algorithms known as parallel machine learning algorithmscan be executed simultaneously on several computers or processors. As data grows in both size andcomplexity, and as businesses seek efficient ways to mine that data for insights, algorithms like thesewill become increasingly crucial. Data parallelism, model parallelism, and hybrid techniques are justsome of the methods described in this article for speeding up machine learning algorithms. We alsocover the benefits and threats associated with parallel machine learning, such as data splitting,communication, and scalability. We compare how well various methods perform on a variety ofmachine learning tasks and datasets, and we talk abo

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
COVID-19 Diagnosis Using Spectral and Statistical Analysis of Cough Recordings Based on the Combination of SVD and DWT
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Healthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt

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Publication Date
Tue Nov 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Using Public and Private Cloud Computing in developing the Evaluation System of annual employees' performance at Iraqi Universities: A comparative study
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Abstract

Business organizations are using the technological innovations like cloud computing (CC) as a developmental platform in order to improve the performance of their information systems. In that context, our paper discusses know-how in employing the public and private CC to serve as platforms to develop the evaluation system of annual employees' performance (ESAEP) at Iraqi universities. Therefore, we ask the paper question which is Is it possible to adopt the innovative solutions of ICTs (Like: public and private CC) for finding the developmental vision about management information systems at business organizations?”. In addition, the paper aim

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Anemia and The Level of IL-6 in Children Infected with Entamoeba histolytica and Giardia lamblia
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The relation between anemia and inflammatory immune response has lately had much attention. This research was conducted from October 2018 until April 2019, including  (110) children below 12 years from both gender in some Hospitals, Primary Health care centers, Public Primary Schools and Kindergarten in Baghdad, Iraq. The objective of this study is to determine the possible correlation between iron deficiency anemia and inflammatory immune response  among children infected with Entamoeba  histolytica or Giardia  lamblia. Blood samples were taken from all groups to measure  hemoglobin level, serum iron, total iron binding capacity (TIBC), mean corpuscular volume (MCV), and mean corpuscular  hemoglobin concentration

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Publication Date
Thu Jun 20 2019
Journal Name
Baghdad Science Journal
An Optimised Method for Fetching and Transforming Survey Data based on SQL and R Programming Language
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The development of information systems in recent years has contributed to various methods of gathering information to evaluate IS performance. The most common approach used to collect information is called the survey system. This method, however, suffers one major drawback. The decision makers consume considerable time to transform data from survey sheets to analytical programs. As such, this paper proposes a method called ‘survey algorithm based on R programming language’ or SABR, for data transformation from the survey sheets inside R environments by treating the arrangement of data as a relational format. R and Relational data format provide excellent opportunity to manage and analyse the accumulated data. Moreover, a survey syste

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Publication Date
Wed Dec 27 2017
Journal Name
Al-khwarizmi Engineering Journal
A New Approach for Designing Multi Information Management System Using XML Technology
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XML is being incorporated into the foundation of E-business data applications. This paper addresses the problem of the freeform information that stored in any organization and how XML with using this new approach will make the operation of the search very efficient and time consuming. This paper introduces new solution and methodology that has been developed to capture and manage such unstructured freeform information (multi information) depending on the use of XML schema technologies, neural network idea and object oriented relational database, in order to provide a practical solution for efficiently management multi freeform information system.

    

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Publication Date
Mon Dec 31 2018
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
STUDY THE SYNERGISM EFFECT OF ALCOHOL EXTRACT OF Thymus vulgaris WITH ANTIBIOTICS AGAINST pseudomonas aeruginosa.: STUDY THE SYNERGISM EFFECT OF ALCOHOL EXTRACT OF Thymus vulgaris WITH ANTIBIOTICS AGAINST pseudomonas aeruginosa.
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The current study includes 144 samples were 106 bacterial samples belonging to the clinical sources, 38 bacterial samples belonging to the environmental sources to investigate the presence of bacteria P. aeruginosa. The results of diagnosis clarified that there are 45 bacterial isolates belonging to the bacterium P. aeruginosa The examination of the sensitivity of all bacterial isolates was done for elected 45 isolation towards the 11 antibiotic by spread method on the dishes. The results showed that the resistance ratio toward Cefixim, Cefotaxim, Tetracycline, Amoxicillin, Cloxacillin, Methicillin, Erythromycin and Naldixic acid was 77.7, 73.3, 84.4, 82.2, 80, 77.7, 77.7 and 73.3 respectively, While most isolates were sensitive to all o

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Publication Date
Thu Mar 30 2023
Journal Name
Journal Of Economics And Administrative Sciences
An Artificial Intelligence Algorithm to Optimize the Classification of the Hepatitis Type
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Hepatitis is one of the diseases that has become more developed in recent years in terms of the high number of infections. Hepatitis causes inflammation that destroys liver cells, and it occurs as a result of viruses, bacteria, blood transfusions, and others. There are five types of hepatitis viruses, which are (A, B, C, D, E) according to their severity. The disease varies by type. Accurate and early diagnosis is the best way to prevent disease, as it allows infected people to take preventive steps so that they do not transmit the difference to other people, and diagnosis using artificial intelligence gives an accurate and rapid diagnostic result. Where the analytical method of the data relied on the radial basis network to diagnose the

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Publication Date
Tue Dec 13 2022
Journal Name
Mathematical Modelling Of Engineering Problems
Dynamic Response and Reliability Analysis of Stochastic Multi-Story Frame Structures under Random Excitation
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In earthquake engineering problems, uncertainty exists not only in the seismic excitations but also in the structure's parameters. This study investigates the influence of structural geometry, elastic modulus, mass density, and section dimension uncertainty on the stochastic earthquake response of a multi-story moment resisting frame subjected to random ground motion. The North-south component of the Ali Gharbi earthquake in 2012, Iraq, is selected as ground excitation. Using the power spectral density function (PSD), the two-dimensional finite element model of the moment resisting frame's base motion is modified to account for random ground motion. The probabilistic study of the moment resisting frame structure using stochastic fin

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