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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 Sep 21 2022
Journal Name
Journal Of Planner And Development
Evaluating the Potentials of Individual Lending Instructions (in Housing Fund Law) to Support Housing Finance Policies in Iraq.
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Iraqi economy has grown rapidly. Iraqi citizen, therefore, should be very much involved with the comprehensive development after his long patience. Such development should begin with him and his family to get the housing commodity, which is indeed not a cheap one.                                                          

  In this regard, the Iraqi legislator drew attention to the necessity of issuing housing finan

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
The Effect Of Optimizers On The Generalizability Additive Neural Attention For Customer Support Twitter Dataset In Chatbot Application
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When optimizing the performance of neural network-based chatbots, determining the optimizer is one of the most important aspects. Optimizers primarily control the adjustment of model parameters such as weight and bias to minimize a loss function during training. Adaptive optimizers such as ADAM have become a standard choice and are widely used for their invariant parameter updates' magnitudes concerning gradient scale variations, but often pose generalization problems. Alternatively, Stochastic Gradient Descent (SGD) with Momentum and the extension of ADAM, the ADAMW, offers several advantages. This study aims to compare and examine the effects of these optimizers on the chatbot CST dataset. The effectiveness of each optimizer is evaluat

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Publication Date
Fri Jan 26 2024
Journal Name
Journal Of Information Systems Engineering And Management
Application of Material Flow Cost Accounting Technology to Support Green Productivity and Its Reflection in Achieving Sustainable Development
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As material flow cost accounting technology focuses on the most efficient use of resources like energy and materials while minimizing negative environmental effects, the research aims to show how this technology can be applied to promote green productivity and its reflection in attaining sustainable development. In addition to studying sustainability, which helps to reduce environmental impacts and increase green productivity, the research aims to demonstrate the knowledge bases for accounting for the costs of material flow and green productivity. It also studies the technology of accounting for the costs of material flow in achieving sustainable development and the role of green productivity in achieving sustainable development. According

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Publication Date
Mon Jun 19 2023
Journal Name
Journal Of Engineering
Effect of Design Parameters and Support Conditions on Natural Frequency of Pipe Excited by a Turbulent Internal Flow
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In this study, the effect of design parameters such as pipe diameter, pipe wall thickness, pipe material and the effect of fluid velocity on the natural frequency of fluid-structure interaction in straight pipe conveying fully developed turbulent flow were investigate numerically,analytically and experimentally. Also the effect of support conditions, simply-simply and clamped-clamped was investigated. Experimentally, pipe vibrations were characterized by accelerometer mounted on the pipe wall. The natural frequencies of vibration were analyzed by using Fast Fourier Transformer (FFT). Five test sections of two different pipe diameters of 76.2
mm and 50.8 mm with two pipe thicknesses of 3.7 mm and 2.4 mm and two pipe materials,stainles

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
The Impact Of Means Of Support On The Intention Entrepreneurial Field Research On A Sample Of Algerian Students
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     The aim of this paper to study the effect of the implicit factors on the entrepreneurial spirit of the students of the Algerian university. Our structural model was proposed based on the model (Shapiro et Sokol, 1982) and the model (Ajzen, 1991). We tested it on a sample of 163 university students at the University of Algiers 3. The model consists of a set of variables (the intention of contracting as a dependent variable, structural and social educational support as independent variables). The results showed that educational and social support factors affect the entrepreneurial spirit of students more than structural support. The Applied Impacts are the enhancing of knowledge capacities of university stu

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Publication Date
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
Social support and their relationship to the quality of life of students of the College Education for Women
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The study is aimed at social support to the students of the College of Education for women (The research sample) and measuring the quality of life at students of the College of Education for women (The research sample) And to identify the relationship between social support and quality of life of students of the College Education for Women and research sample consisted of 200 students The adoption of the resolution as a tool for data collection and the most important results of the search results that the students of the College Education for Women have social support. In other words, parents and friends are supporting the students. The students have the quality of life any positive meaning to life and that when a person has a quality of

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Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Renewable Materials
Boosting Structural and Dielectric Properties of Polyvinyl Alcohol/Starch/Carboxymethyl Cellulose Films with Iron-Doped Carbon Quantum Dots for Advanced Applications
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Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review
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Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

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Publication Date
Wed Jan 01 2025
Journal Name
Lecture Notes In Networks And Systems
Comparison Between the Performance of Human Translators and AI-Supported Applications
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This study aims to conduct an exhaustive comparison between the performance of human translators and artificial intelligence-powered machine translation systems, specifically examining the top three systems: Spider-AI, Metacate, and DeepL. A variety of texts from distinct categories were evaluated to gain a profound understanding of the qualitative differences, as well as the strengths and weaknesses, between human and machine translations. The results demonstrated that human translation significantly outperforms machine translation, with larger gaps in literary texts and texts characterized by high linguistic complexity. However, the performance of machine translation systems, particularly DeepL, has improved and in some contexts

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Publication Date
Sat Jun 26 2021
Journal Name
2021 Ieee International Conference On Automatic Control & Intelligent Systems (i2cacis)
Vulnerability Assessment on Ethereum Based Smart Contract Applications
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