Preferred Language
Articles
/
jih-3467
Enhanced Support Vector Machine Methods Using Stochastic Gradient Descent and Its Application to Heart Disease Dataset
...Show More Authors

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.

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Tue Oct 01 2013
Journal Name
Sensors And Actuators A: Physical
Enhanced energy harvesting using multiple piezoelectric elements: Theory and experiments
...Show More Authors

View Publication
Scopus (61)
Crossref (53)
Scopus Clarivate Crossref
Publication Date
Sat Dec 31 2022
Journal Name
Journal Of Economics And Administrative Sciences
Using Some Estimation Methods for Mixed-Random Panel Data Regression Models with Serially Correlated Errors with Application
...Show More Authors

This research includes the study of dual data models with mixed random parameters, which contain two types of parameters, the first is random and the other is fixed. For the random parameter, it is obtained as a result of differences in the marginal tendencies of the cross sections, and for the fixed parameter, it is obtained as a result of differences in fixed limits, and random errors for each section. Accidental bearing the characteristic of heterogeneity of variance in addition to the presence of serial correlation of the first degree, and the main objective in this research is the use of efficient methods commensurate with the paired data in the case of small samples, and to achieve this goal, the feasible general least squa

... Show More
View Publication Preview PDF
Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Detecting Textual Propaganda Using Machine Learning Techniques
...Show More Authors

Social Networking has dominated the whole world by providing a platform of information dissemination. Usually people share information without knowing its truthfulness. Nowadays Social Networks are used for gaining influence in many fields like in elections, advertisements etc. It is not surprising that social media has become a weapon for manipulating sentiments by spreading disinformation.  Propaganda is one of the systematic and deliberate attempts used for influencing people for the political, religious gains. In this research paper, efforts were made to classify Propagandist text from Non-Propagandist text using supervised machine learning algorithms. Data was collected from the news sources from July 2018-August 2018. After annota

... Show More
View Publication Preview PDF
Scopus (18)
Crossref (11)
Scopus Clarivate Crossref
Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Economics And Administrative Sciences
Using Statistical Methods to Increase the Contrast Level in Digital Images
...Show More Authors

This research deals with the use of a number of statistical methods, such as the kernel method, watershed, histogram, and cubic spline, to improve the contrast of digital images. The results obtained according to the RSME and NCC standards have proven that the spline method is the most accurate in the results compared to other statistical methods.

 

View Publication Preview PDF
Crossref
Publication Date
Mon May 01 2023
Journal Name
Journal Of Economics And Administrative Sciences (jeas)
Using Statistical Methods to Increase the Contrast Level in Digital Images
...Show More Authors

This research deals with the use of a number of statistical methods, such as the kernel method, watershed, histogram and cubic spline, to improve the contrast of digital images. The results obtained according to the RSME and NCC standards have proven that the spline method is the most accurate in the results compared to other statistical methods

Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
Using jack knife to estimation logistic regression model for Breast cancer disease
...Show More Authors

 

It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values  (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sun Feb 28 2021
Journal Name
Journal Of Economics And Administrative Sciences
Using jack knife to estimation logistic regression model for Breast cancer disease
...Show More Authors

 

It is considered as one of the statistical methods used to describe and estimate the relationship between randomness (Y) and explanatory variables (X). The second is the homogeneity of the variance, in which the dependent variable is a binary response takes two values  (One when a specific event occurred and zero when that event did not happen) such as (injured and uninjured, married and unmarried) and that a large number of explanatory variables led to the emergence of the problem of linear multiplicity that makes the estimates inaccurate, and the method of greatest possibility and the method of declination of the letter was used in estimating A double-response logistic regression model by adopting the Jackna

... Show More
View Publication Preview PDF
Crossref
Publication Date
Tue Sep 01 2009
Journal Name
Al-khwarizmi Engineering Journal
Low Cost Heart Rate Monitor Using Led-Led Sensor
...Show More Authors

A high sensitivity, low power and low cost sensor has been developed for photoplethysmography (PPG) measurement. The PPG principle was applied to follow the dilatation and contraction of skin blood vessels during the cardiac cycle. A standard light emitting diodes (LEDs) has been used as a light emitter and detector, and in order to reduce the space, cost and power, the classical analogue-to-digital converters (ADCs) replaced by the pulse-based signal conversion techniques. A general purpose microcontroller has been used for the implementation of measurement protocol. The proposed approach leads to better spectral sensitivity, increased resolution, reduction in cost, dimensions and power consumption. The basic sensing configuration prese

... Show More
View Publication Preview PDF
Publication Date
Sun Jan 01 2023
Journal Name
Heart Transplantation
Cardioimmunology and Heart Transplantation
...Show More Authors

View Publication
Scopus Crossref
Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Scheduling Critical Activities of Stochastic Projects Management
...Show More Authors

In this paper, we consider the problem of stochastic project network when some or all activities are interrupted. An approach has been built to schedule the critical activities, by constructing some expressions based on the project lateness costs due to the interruption activities. Two simple example are presented to validate our approach.

Key words: Project Management, Project scheduling, Stochastic activity duration, Stochastic PERT.    

Introduction

   Recently, Projects planning and optimal timing, under uncertainty are extremely critical for many organizations, see [19]. Having an effective mathematical model wi

... Show More
View Publication Preview PDF
Crossref