Preferred Language
Articles
/
GhdIU44BVTCNdQwCfEIj
EEG Signal Classification Based on Orthogonal Polynomials, Sparse Filter and SVM Classifier
...Show More Authors

This work implements an Electroencephalogram (EEG) signal classifier. The implemented method uses Orthogonal Polynomials (OP) to convert the EEG signal samples to moments. A Sparse Filter (SF) reduces the number of converted moments to increase the classification accuracy. A Support Vector Machine (SVM) is used to classify the reduced moments between two classes. The proposed method’s performance is tested and compared with two methods by using two datasets. The datasets are divided into 80% for training and 20% for testing, with 5 -fold used for cross-validation. The results show that this method overcomes the accuracy of other methods. The proposed method’s best accuracy is 95.6% and 99.5%, respectively. Finally, from the results, it is obvious that the number of moments selected by the SP should exceed 30% of the overall EEG samples for accuracy to be over 90%.

Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Fri Jan 01 2010
Journal Name
Journal Of Collage Of Education
FILTER BASES AND ω-PERFECT FUNCTIONS
...Show More Authors

In this paper introduce some generalizations of some definitions which are, closure converge to a point, closure directed toward a set, almost ω-converges to a set, almost condensation point, a set ωH-closed relative, ω-continuous functions, weakly ω-continuous functions, ω-compact functions, ω-rigid a set, almost ω-closed functions and ω-perfect functions with several results concerning them.

Preview PDF
Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Indoor/Outdoor Deep Learning Based Image Classification for Object Recognition Applications
...Show More Authors

With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

... Show More
View Publication Preview PDF
Scopus (5)
Scopus Crossref
Publication Date
Sat Jan 10 2015
Journal Name
British Journal Of Mathematics & Computer Science
The Use of Gradient Based Features for Woven Fabric Images Classification
...Show More Authors

View Publication
Crossref
Publication Date
Wed Apr 01 2015
Journal Name
2015 Annual Ieee Systems Conference (syscon) Proceedings
Automatic generation of fuzzy classification rules using granulation-based adaptive clustering
...Show More Authors

View Publication
Scopus (4)
Crossref (4)
Scopus Crossref
Publication Date
Wed May 17 2023
Journal Name
International Journal Of Computational Intelligence Systems
Prediction of ROP Zones Using Deep Learning Algorithms and Voting Classifier Technique
...Show More Authors
Abstract<p>Retinopathy of prematurity (ROP) can cause blindness in premature neonates. It is diagnosed when new blood vessels form abnormally in the retina. However, people at high risk of ROP might benefit significantly from early detection and treatment. Therefore, early diagnosis of ROP is vital in averting visual impairment. However, due to a lack of medical experience in detecting this condition, many people refuse treatment; this is especially troublesome given the rising cases of ROP. To deal with this problem, we trained three transfer learning models (VGG-19, ResNet-50, and EfficientNetB5) and a convolutional neural network (CNN) to identify the zones of ROP in preterm newborns. The dataset to train th</p> ... Show More
View Publication
Scopus (10)
Crossref (13)
Scopus Clarivate Crossref
Publication Date
Fri Jan 01 2021
Journal Name
Computers, Materials &amp; Continua
Fused and Modified Evolutionary Optimization of Multiple Intelligent Systems Using ANN, SVM approaches
...Show More Authors

View Publication
Scopus (6)
Crossref (6)
Scopus Clarivate Crossref
Publication Date
Thu Dec 01 2022
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
A survey on bio-signal analysis for human-robot interaction
...Show More Authors

<span lang="EN-US">The use of bio-signals analysis in human-robot interaction is rapidly increasing. There is an urgent demand for it in various applications, including health care, rehabilitation, research, technology, and manufacturing. Despite several state-of-the-art bio-signals analyses in human-robot interaction (HRI) research, it is unclear which one is the best. In this paper, the following topics will be discussed: robotic systems should be given priority in the rehabilitation and aid of amputees and disabled people; second, domains of feature extraction approaches now in use, which are divided into three main sections (time, frequency, and time-frequency). The various domains will be discussed, then a discussion of e

... Show More
View Publication Preview PDF
Scopus (5)
Crossref (4)
Scopus Crossref
Publication Date
Sun Jan 01 2017
Journal Name
Ieee Access
On Computational Aspects of Tchebichef Polynomials for Higher Polynomial Order
...Show More Authors

View Publication
Scopus (53)
Crossref (54)
Scopus Clarivate Crossref
Publication Date
Fri Mar 15 2024
Journal Name
Journal Of Baghdad College Of Dentistry
A clinicopathological analysis of 151 odontogenic tumors based on new WHO classification 2022: A retrospective cross-sectional study
...Show More Authors

Background: Odontogenic tumors are a diverse group of lesions with a variety of clinical behavior and histopathologic subtypes, from hamartomatous and benign to malignant. The study aimed to examine the clinical and pathological features of odontogenic tumors in Baghdad over the last 11 years (2011–2021). Materials and Methods: The present retrospective study analyzed all formalin-fixed, paraffin-embedded tissue blocks of patients diagnosed with an odontogenic tumor that were retrieved from archives at a teaching hospital/College of Dentistry in Baghdad University, Iraq, between 2011 and 2021. The diagnosis of each case was confirmed by examining the hematoxylin and eosin stained sections by two expert pathologists. Data from pati

... Show More
Scopus (2)
Crossref (3)
Scopus Crossref
Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Big-data Management using Map Reduce on Cloud: Case study, EEG Images' Data
...Show More Authors

Database is characterized as an arrangement of data that is sorted out and disseminated in a way that allows the client to get to the data being put away in a simple and more helpful way. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work studies the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on EEG Big-data as a case study. The proposed approach showed clear enhancement for managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG r

... Show More
View Publication Preview PDF
Crossref