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jih-3467
Enhanced Support Vector Machine Methods Using Stochastic Gradient Descent and Its Application to Heart Disease Dataset
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Support Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a very high accuracy and is quite robust. ESGD-SVM is used to analyze the heart disease dataset downloaded from Harvard Dataverse. The entire analysis was performed using the program R version 4.3.

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Publication Date
Sat Sep 15 2018
Journal Name
Journal Of Baghdad College Of Dentistry
Prosthetic Status in Relation to Weight Status and Occupation among Parkinson's Disease Patients in Baghdad-Iraq
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Background: The symptoms of Parkinson's disease (PD) can lead to problems in movement and coordination that lead to difficulty in maintaining well oral cleaning which can then negatively affect dental status of those Patients. The aim of present study: To evaluate prosthetic status in relation to weight status and occupation by age and gender among Parkinson's disease Patients in Baghdad-Iraq. Methods: The sample consisted of 104 patients with Parkinson disease attended to the Neurosciences Hospital in Baghdad city / Iraq, aged 60-79 years Prosthetic Status was recorded according to WHO(1997). Weight status was recorded according to Trowbridge 1988 and occupation was recorded according to Erikson and Goldthorpe (1992) and Ganzeboom et al (

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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
Forecasting Cryptocurrency Market Trends with Machine Learning and Deep Learning
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Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The

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Publication Date
Sat Oct 31 2020
Journal Name
Eastern-european Journal Of Enterprise Technologies
Design and development of high-accuracy machine for wire bending
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Publication Date
Fri Jan 01 2016
Journal Name
Mathematical Problems In Engineering
Enhanced Simulated Annealing for Solving Aggregate Production Planning
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Simulated annealing (SA) has been an effective means that can address difficulties related to optimization problems. is now a common discipline for research with several productive applications such as production planning. Due to the fact that aggregate production planning (APP) is one of the most considerable problems in production planning, in this paper, we present multi-objective linear programming model for APP and optimized by . During the course of optimizing for the APP problem, it uncovered that the capability of was inadequate and its performance was substandard, particularly for a sizable controlled problem with many decision variables and plenty of constraints. Since this algorithm works sequentially then the current state wi

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Publication Date
Sat Oct 05 2019
Journal Name
Journal Of Engineering And Applied Sciences
Enhanced Dielectrically Properties of Up-Pistachio Peel Composites
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Publication Date
Sun May 01 2011
Journal Name
2011 Ieee 3rd International Conference On Communication Software And Networks
Towards computer vision feedback for enhanced CNC machining
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Publication Date
Thu Dec 01 2011
Journal Name
2011 Developments In E-systems Engineering
Enhanced Computation Time for Fast Block Matching Algorithm
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Publication Date
Fri Apr 26 2024
Journal Name
Annals Of The Romanian Society For Cell Biology
The response of cauliflower growth and yield to organic and chemical fertilizers application and spraying with salicylic acid
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Publication Date
Sun Jan 20 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Text Classification Based on Weighted Extreme Learning Machine
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The huge amount of documents in the internet led to the rapid need of text classification (TC). TC is used to organize these text documents. In this research paper, a new model is based on Extreme Machine learning (EML) is used. The proposed model consists of many phases including: preprocessing, feature extraction, Multiple Linear Regression (MLR) and ELM. The basic idea of the proposed model is built upon the calculation of feature weights by using MLR. These feature weights with the extracted features introduced as an input to the ELM that produced weighted Extreme Learning Machine (WELM). The results showed   a great competence of the proposed WELM compared to the ELM. 

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Publication Date
Fri Jan 10 2025
Journal Name
Al–bahith Al–a'alami
New Methods and Old Issues: Theoretical and Methodological Approaches to Social Network Sites in the Arab Region
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This paper critically looks at the studies that investigated the Social Network Sites in the Arab region asking whether they made a practical addition to the field of information and communication sciences or not. The study tried to lift the ambiguity of the variety of names, as well as the most important theoretical and methodological approaches used by these studies highlighting its scientific limitations. The research discussed the most important concepts used by these studies such as Interactivity, Citizen Journalism, Public Sphere, and Social Capital and showed the problems of using them because each concept comes out of a specific view to these websites. The importation of these concepts from a cultural and social context to an Ara

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