Preferred Language
Articles
/
dhYrrIwBVTCNdQwCyf7N
EEG Motor-Imagery BCI System Based on Maximum Overlap Discrete Wavelet Transform (MODWT) and Machine learning algorithm

The ability of the human brain to communicate with its environment has become a reality through the use of a Brain-Computer Interface (BCI)-based mechanism. Electroencephalography (EEG) has gained popularity as a non-invasive way of brain connection. Traditionally, the devices were used in clinical settings to detect various brain diseases. However, as technology advances, companies such as Emotiv and NeuroSky are developing low-cost, easily portable EEG-based consumer-grade devices that can be used in various application domains such as gaming, education. This article discusses the parts in which the EEG has been applied and how it has proven beneficial for those with severe motor disorders, rehabilitation, and as a form of communicating with the outside world. This article examines the use of the SVM, k-NN, and decision tree algorithms to classify EEG signals. To minimize the complexity of the data, maximum overlap discrete wavelet transform (MODWT) is used to extract EEG features. The mean inside each window sample is calculated using the Sliding Window Technique. The vector machine (SVM), k-Nearest Neighbor, and optimize decision tree load the feature vectors.

Scopus Crossref
View Publication
Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
Transfer Learning Based Traffic Light Detection and Recognition Using CNN Inception-V3 Model

Due to the lack of vehicle-to-infrastructure (V2I) communication in the existing transportation systems, traffic light detection and recognition is essential for advanced driver assistant systems (ADAS) and road infrastructure surveys. Additionally, autonomous vehicles have the potential to change urban transportation by making it safe, economical, sustainable, congestion-free, and transportable in other ways. Because of their limitations, traditional traffic light detection and recognition algorithms are not able to recognize traffic lights as effectively as deep learning-based techniques, which take a lot of time and effort to develop. The main aim of this research is to propose a traffic light detection and recognition model based on

... Show More
View Publication Preview PDF
Scopus (3)
Crossref (2)
Scopus Crossref
Publication Date
Thu Dec 01 2022
Journal Name
Journal Of Engineering
Deep Learning-Based Segmentation and Classification Techniques for Brain Tumor MRI: A Review

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

... Show More
View Publication Preview PDF
Crossref (5)
Crossref
Publication Date
Sun Apr 29 2018
Journal Name
Iraqi Journal Of Science
Semantic Based Video Retrieval System: Survey

In this review paper a number of studies and researches are surveyed, in order to assist the upcoming researchers, to know about the techniques available in the field of semantic based video retrieval. The video retrieval system is used for finding the users’ desired video among a huge number of available videos on the Internet or database. This paper gives a general discussion on the overall process of the semantic video retrieval phases. In addition to its present a generic review of techniques that has been proposed to solve the semantic gap as the major scientific problem in semantic based video retrieval. The semantic gap is formed because of the difference between the low level features that are extracted from video content and u

... Show More
View Publication Preview PDF
Publication Date
Wed May 24 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
On Comparison between Radial Basis Function and Wavelet Basis Functions Neural Networks

      In this paper we study and design two feed forward neural networks. The first approach uses radial basis function network and second approach uses wavelet basis function network to approximate the mapping from the input to the output space. The trained networks are then used in an conjugate gradient algorithm to estimate the output. These neural networks are then applied to solve differential equation. Results of applying these algorithms to several examples are presented

View Publication Preview PDF
Publication Date
Mon May 01 2017
Journal Name
2017 5th International Conference On Information And Communication Technology (icoic7)
Analysis of the number of ants in ant colony system algorithm

View Publication
Scopus (26)
Crossref (11)
Scopus Crossref
Publication Date
Sat Aug 31 2019
Journal Name
Iraqi Journal Of Physics
The Landsat Imagery Gap Filling using Median Filter Method

The Enhanced Thematic Mapper Plus (ETM+) that loaded onboard the Landsat-7 satellite was launched on 15 April 1999. After 4 years, the image collected by this sensor was greatly impacted by the failure of the system’s Scan Line Corrector (SLC), a radiometry error.The median filter is one of the basic building blocks in many image processing situations. Digital images are often distorted by impulse noise due to errors generated by the noise sensor, errors that occur during the conversion of signals from analog-to-digital, as well as errors generated in communication channels. This error inevitably leads to a change in the intensity of some pixels, while some pixels remain unchanged. To remove impulse noise and improve the quality of the

... Show More
View Publication Preview PDF
Crossref
Publication Date
Thu Aug 29 2024
Journal Name
International Journal Of Sustainable Development And Planning
Exploring the Transformative Effects of GPS and Satellite Imagery on Urban Landscape Perceptions in Baghdad: A Mixed-Methods Analysis

View Publication
Scopus Crossref
Publication Date
Fri Jan 21 2022
Journal Name
Environmental Science And Pollution Research
Development of new computational machine learning models for longitudinal dispersion coefficient determination: case study of natural streams, United States

View Publication
Crossref (17)
Crossref
Publication Date
Sat Nov 02 2019
Journal Name
Advances In Intelligent Systems And Computing
Modified Opposition Based Learning to Improve Harmony Search Variants Exploration

View Publication
Scopus (9)
Crossref (6)
Scopus Clarivate Crossref
Publication Date
Sun Jan 05 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
The Effect of Motor Sense Exercises for Developing Motor and Physiological Abilities of Backstroke and Forward Stroke Service Skill in Badminton

The aim of the research is to prepare motor sense exercises for developing motor and physiological abilities of backstroke and forward stroke service skill in badminton and investigated their effect. The research is adopted the experimental method with two groups design. The sample of the research is 8 players (13-15 years). The sample is divided into two groups of 4 players for each group. Both groups are exposed to pre and post tests, after the experimented were finished, the results are statically analyzed. The results have showed that there are positive developing abilities of motor and physiological of service skill in badminton. Finally, these prepared exercises are recommended for developing players’ abilities in badminton.

View Publication Preview PDF