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

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
Fri Jan 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
BotDetectorFW: an optimized botnet detection framework based on five features-distance measures supported by comparisons of four machine learning classifiers using CICIDS2017 dataset
...Show More Authors

<p><span>A Botnet is one of many attacks that can execute malicious tasks and develop continuously. Therefore, current research introduces a comparison framework, called BotDetectorFW, with classification and complexity improvements for the detection of Botnet attack using CICIDS2017 dataset. It is a free online dataset consist of several attacks with high-dimensions features. The process of feature selection is a significant step to obtain the least features by eliminating irrelated features and consequently reduces the detection time. This process implemented inside BotDetectorFW using two steps; data clustering and five distance measure formulas (cosine, dice, driver &amp; kroeber, overlap, and pearson correlation

... Show More
View Publication
Scopus (7)
Crossref (2)
Scopus Crossref
Publication Date
Mon Apr 07 2025
Journal Name
Al-nahrain Journal For Engineering Sciences
Navigating the Challenges and Opportunities of Tiny Deep Learning and Tiny Machine Learning in Lung Cancer Identification
...Show More Authors

Lung cancer is the most common dangerous disease that, if treated late, can lead to death. It is more likely to be treated if successfully discovered at an early stage before it worsens. Distinguishing the size, shape, and location of lymphatic nodes can identify the spread of the disease around these nodes. Thus, identifying lung cancer at the early stage is remarkably helpful for doctors. Lung cancer can be diagnosed successfully by expert doctors; however, their limited experience may lead to misdiagnosis and cause medical issues in patients. In the line of computer-assisted systems, many methods and strategies can be used to predict the cancer malignancy level that plays a significant role to provide precise abnormality detectio

... Show More
View Publication
Scopus Crossref
Publication Date
Mon Apr 26 2021
Journal Name
Journal Of Electrical Engineering &amp; Technology
ANFIS Based Reinforcement Learning Strategy for Control A Nonlinear Coupled Tanks System
...Show More Authors

View Publication
Scopus (11)
Crossref (8)
Scopus Clarivate Crossref
Publication Date
Tue Mar 01 2022
Journal Name
Asian Journal Of Applied Sciences
Comparison between Expert Systems, Machine Learning, and Big Data: An Overview
...Show More Authors

Today, the science of artificial intelligence has become one of the most important sciences in creating intelligent computer programs that simulate the human mind. The goal of artificial intelligence in the medical field is to assist doctors and health care workers in diagnosing diseases and clinical treatment, reducing the rate of medical error, and saving lives of citizens. The main and widely used technologies are expert systems, machine learning and big data. In the article, a brief overview of the three mentioned techniques will be provided to make it easier for readers to understand these techniques and their importance.

View Publication
Crossref (2)
Crossref
Publication Date
Sat Aug 10 2024
Journal Name
Cureus
Machine Learning and Vision: Advancing the Frontiers of Diabetic Cataract Management
...Show More Authors

View Publication
Clarivate Crossref
Publication Date
Wed Mar 16 2022
Journal Name
International Journal Of Recent Contributions From Engineering, Science & It
Smart Learning based on Moodle E-learning Platform and Digital Skills for University Students
...Show More Authors

Publication Date
Sun Jun 02 2013
Journal Name
Baghdad Science Journal
Comparison of Maximum Likelihood and some Bayes Estimators for Maxwell Distribution based on Non-informative Priors
...Show More Authors

In this paper, Bayes estimators of the parameter of Maxwell distribution have been derived along with maximum likelihood estimator. The non-informative priors; Jeffreys and the extension of Jeffreys prior information has been considered under two different loss functions, the squared error loss function and the modified squared error loss function for comparison purpose. A simulation study has been developed in order to gain an insight into the performance on small, moderate and large samples. The performance of these estimators has been explored numerically under different conditions. The efficiency for the estimators was compared according to the mean square error MSE. The results of comparison by MSE show that the efficiency of Bayes est

... Show More
View Publication Preview PDF
Crossref (1)
Crossref
Publication Date
Sun Jun 02 2013
Journal Name
Baghdad Science Journal
Comparison of Maximum Likelihood and some Bayes Estimators for Maxwell Distribution based on Non-informative Priors
...Show More Authors

In this paper, Bayes estimators of the parameter of Maxwell distribution have been derived along with maximum likelihood estimator. The non-informative priors; Jeffreys and the extension of Jeffreys prior information has been considered under two different loss functions, the squared error loss function and the modified squared error loss function for comparison purpose. A simulation study has been developed in order to gain an insight into the performance on small, moderate and large samples. The performance of these estimators has been explored numerically under different conditions. The efficiency for the estimators was compared according to the mean square error MSE. The results of comparison by MSE show that the efficiency of B

... Show More
Preview PDF
Crossref (1)
Crossref
Publication Date
Mon Mar 01 2021
Journal Name
Iop Conference Series: Materials Science And Engineering
Speech Enhancement Algorithm Based on a Hybrid Estimator
...Show More Authors
Abstract<p>Speech is the essential way to interact between humans or between human and machine. However, it is always contaminated with different types of environment noise. Therefore, speech enhancement algorithms (SEA) have appeared as a significant approach in speech processing filed to suppress background noise and return back the original speech signal. In this paper, a new efficient two-stage SEA with low distortion is proposed based on minimum mean square error sense. The estimation of clean signal is performed by taking the advantages of Laplacian speech and noise modeling based on orthogonal transform (Discrete Krawtchouk-Tchebichef transform) coefficients distribution. The Discrete Kra</p> ... Show More
View Publication
Crossref (11)
Crossref
Publication Date
Wed Sep 01 2021
Journal Name
Baghdad Science Journal
Optimum Median Filter Based on Crow Optimization Algorithm
...Show More Authors

          A novel median filter based on crow optimization algorithms (OMF) is suggested to reduce the random salt and pepper noise and improve the quality of the RGB-colored and gray images. The fundamental idea of the approach is that first, the crow optimization algorithm detects noise pixels, and that replacing them with an optimum median value depending on a criterion of maximization fitness function. Finally, the standard measure peak signal-to-noise ratio (PSNR), Structural Similarity, absolute square error and mean square error have been used to test the performance of suggested filters (original and improved median filter) used to removed noise from images. It achieves the simulation based on MATLAB R2019b and the resul

... Show More
View Publication Preview PDF
Scopus (8)
Crossref (4)
Scopus Clarivate Crossref