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
Mon Jun 01 2015
Journal Name
Journal Of Engineering
Construction of Graduation Certificate Issuing System Based on Digital Signature Technique
...Show More Authors

With the development of computer architecture and its technologies in recent years, applications like e-commerce, e-government, e-governance and e-finance are widely used, and they act as active research areas. In addition, in order to increase the quality and quantity of the ordinary everyday transactions, it is desired to migrate from the paper-based environment to a digital-based computerized environment. Such migration increases efficiency, saves time, eliminates paperwork, increases safety and reduces the cost in an organization. Digital signatures are playing an essential role in many electronic and automatic based systems and facilitate this migration. The digital signatures are used to provide many services and s

... Show More
View Publication Preview PDF
Publication Date
Sun Jan 01 2023
Journal Name
International Journal Of Humanities And Social Sciences/ Rimak
AN EMPIRICAL ANALYSIS OF EDUCATIONAL RESEARCH BASED ON CRITICAL DISCOURSE ANALYSIS
...Show More Authors

APDBN Rashid, International Journal of Humanities and Social Sciences/ RIMAK, 2023

View Publication
Publication Date
Sat Jan 01 2011
Journal Name
Journal Of College Of Education
Recognition the Arabic Characters Based on the Characteristics of Arabic Language
...Show More Authors

Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Science
Blue Organic-Inorganic Light Emitting Diode Based on Electroluminescence CdS Nanoparticle
...Show More Authors

     A hybrid cadmium sulfide nanoparticles (CdSNPs) electroluminescence (EL) device was fabricated by Phase – Segregated Method and characterized. It was fabricated as layers of (ITO/poly-TPD:CdS ) and (ITO/poly-TPD:CdS /Alq3). Poly-TPD is an excellent Hole Transport Layer (HTL), CdSNPs is an emitting layer and Alq3 as electron transport layer (ETL). The EL of Organic-Inorganic Light Emitting Diode (OILED) was studied at room temperature at 26V. This was achieved according to band-to-band transition in CdSNPs. From the I-V curve behavior, the addition of Alq3 layer decreased the transfer of electrons by about 250 times. The I-V behavior for (poly-TPD/CdS) is exponential with a maximum current of 4500 µA. While, the current i

... Show More
Preview PDF
Scopus (4)
Crossref (3)
Scopus Crossref
Publication Date
Sat May 24 2025
Journal Name
Iraqi Journal For Computer Science And Mathematics
Intrusion Detection System for IoT Based on Modified Random Forest Algorithm
...Show More Authors

An intrusion detection system (IDS) is key to having a comprehensive cybersecurity solution against any attack, and artificial intelligence techniques have been combined with all the features of the IoT to improve security. In response to this, in this research, an IDS technique driven by a modified random forest algorithm has been formulated to improve the system for IoT. To this end, the target is made as one-hot encoding, bootstrapping with less redundancy, adding a hybrid features selection method into the random forest algorithm, and modifying the ranking stage in the random forest algorithm. Furthermore, three datasets have been used in this research, IoTID20, UNSW-NB15, and IoT-23. The results are compared with the three datasets men

... Show More
View Publication Preview PDF
Scopus (1)
Crossref (1)
Scopus Crossref
Publication Date
Mon Jul 15 2019
Journal Name
Iet Microwaves, Antennas & Propagation
Hilbert metamaterial printed antenna based on organic substrates for energy harvesting
...Show More Authors

Abstract In this study, an investigation is conducted to realise the possibility of organic materials use in radio frequency (RF) electronics for RF-energy harvesting. Iraqi palm tree remnants mixed with nickel oxide nanoparticles hosted in polyethylene, INP substrates, is proposed for this study. Moreover, a metamaterial (MTM) antenna is printed on the created INP substrate of 0.8 mm thickness using silver nanoparticles conductive ink. The fabricated antenna performances are instigated numerically than validated experimentally in terms of S11 spectra and radiation patterns. It is found that the proposed antenna shows an ultra-wide band matching bandwidth to cover the frequencies from 2.4 to 10 GHz with bore-sight gain variation from 2.2 to

... Show More
View Publication
Scopus (54)
Crossref (33)
Scopus Clarivate Crossref
Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Facial Emotion Images Recognition Based On Binarized Genetic Algorithm-Random Forest
...Show More Authors

Most recognition system of human facial emotions are assessed solely on accuracy, even if other performance criteria are also thought to be important in the evaluation process such as sensitivity, precision, F-measure, and G-mean. Moreover, the most common problem that must be resolved in face emotion recognition systems is the feature extraction methods, which is comparable to traditional manual feature extraction methods. This traditional method is not able to extract features efficiently. In other words, there are redundant amount of features which are considered not significant, which affect the classification performance. In this work, a new system to recognize human facial emotions from images is proposed. The HOG (Histograms of Or

... Show More
View Publication Preview PDF
Scopus (12)
Crossref (11)
Scopus Crossref
Publication Date
Wed Aug 31 2022
Journal Name
International Journal Of Intelligent Engineering And Systems
Performance Evaluation Based on Multi-UAV in Airborne Computer Network System
...Show More Authors

View Publication
Scopus (4)
Crossref (1)
Scopus Crossref
Publication Date
Wed Mar 13 2024
Journal Name
Journal Of Robotics
Hierarchical Stabilization and Tracking Control of a Flexible-Joint Bipedal Robot Based on Anti-Windup and Adaptive Approximation Control
...Show More Authors

Bipedal robotic mechanisms are unstable due to the unilateral contact passive joint between the sole and the ground. Hierarchical control layers are crucial for creating walking patterns, stabilizing locomotion, and ensuring correct angular trajectories for bipedal joints due to the system’s various degrees of freedom. This work provides a hierarchical control scheme for a bipedal robot that focuses on balance (stabilization) and low-level tracking control while considering flexible joints. The stabilization control method uses the Newton–Euler formulation to establish a mathematical relationship between the zero-moment point (ZMP) and the center of mass (COM), resulting in highly nonlinear and coupled dynamic equations. Adaptiv

... Show More
View Publication
Scopus (3)
Scopus Clarivate Crossref
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
...Show More Authors

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

... Show More
View Publication Preview PDF
Scopus (1)
Scopus Crossref