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Texture Classification Using Spline, Wavelet Decomposition and Fractal Dimension
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Publication Date
Fri Jul 30 2021
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
EEG Motor-Imagery BCI System Based on Maximum Overlap Discrete Wavelet Transform (MODWT) and Machine learning algorithm
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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 communi

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Publication Date
Tue Jun 30 2015
Journal Name
International Journal Of Computer Techniques
Multifractal-Based Features for Medical Images Classification
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This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
An overview of machine learning classification techniques
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Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

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Publication Date
Tue Dec 15 2020
Journal Name
Al-academy
The aesthetic Dimension of Lighting in the Academic Theatrical Show: اسيل ليث احمد-ثامر شوكت عبد الستار
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     The theatrical show depends in its formation on the technical system and the   elements that it has for the theatrical show, and among these techniques is the lighting, where every director looked for a style and method of implementing them and giving aesthetic functions and characteristics that give the theatrical show an aesthetic and interpretive dimension, and that is through   multiple expressions and connotations of the lighting in giving the show a functional and aesthetic character. Therefore, light has been shed on the lighting and its action in the theatrical show, due to its significant role in the modern theatrical shows. The current research, thus, has been divided into four chapt

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Publication Date
Fri Jun 01 2018
Journal Name
Journal Of The College Of Languages (jcl)
The Political Dimension in the Poems of Uri Tzvi Greenberg הממד הפוליטי בשיריו של אורי-צבי גרינברג
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    אורי-צבי גרינברג, אחד המשוררים היהודים הבולטים במאה ה-20, ולפי מבקרים רבים, היה גרינברג מהמשוררים החלוצים בתקופה שמלאה בחדשנות ובתנודת האירועים הפוליטיים והביטחוניים, באירופה ובמזרח התיכון. גרינברג יליד גליציה ב-1894, גדל במשפחה חסידית, הוא הגר פלסטינה ב-1923, ומשנה ההיא גרינברג נצל את עצמו לעבודה הספרותית והפוליטית ביחד. הוא תרם להקמתם של כתבי-עת והעתונים וכתב יצירות ספרותיות רבות, רובן היו שירים בעלי

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Publication Date
Fri Oct 02 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Computed tomographic measurement of maxillary sinus volume and dimension in correlation to the age and gender (comparative study among individuals with dentate and edentulous maxilla)
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Background : Although development and progress in various diagnostic methods, but still identification of remnants of skeletal and decomposing parts of human is one of the most difficult skills in forensic medicine . Gender and age estimation is also considering an important problem in the identification of unknown skull. The aims of study: To estimate volume and dimension of maxillary sinus in individuals with dentate and edentulous maxillae using CT scan, and to correlate the maxillary sinus volume in relation to gender and age. Materials and Methods : This study included 120 patients ranged from (40-69 years), divided into two groups, dentate group with fully dentate maxilla and edentulous group with complete edentulous maxilla, and e

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Discrete wavelet based estimator for the Hurst parameter of multivariate fractional Brownian motion
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Abstract<p>In this paper, wavelets were used to study the multivariate fractional Brownian motion through the deviations of the random process to find an efficient estimation of Hurst exponent. The results of simulations experiments were shown that the performance of the proposed estimator was efficient. The estimation process was made by taking advantage of the detail coefficients stationarity from the wavelet transform, as the variance of this coefficient showed the power-low behavior. We use two wavelet filters (Haar and db5) to manage minimizing the mean square error of the model.</p>
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Publication Date
Thu Dec 01 2022
Journal Name
Iraqi Journal Of Physics
Study the Effect of Dielectric Barrier Discharge (DBD) Plasma on the Decomposition of Volatile Organic Compounds
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Recently, research has focused on non-thermal plasma (NTP) technologies as a way to remove volatile organic compounds from the air stream, due to its distinctive qualities, which include a quick reaction at room temperature. In this work, the properties of the plasma generated by the dielectric barrier discharge (DBD) system and by a glass insulator were studied. Plasma was generated at different voltages (3, 4, 6, 7, 8 kV ) with a fixed distance between the electrodes of 5 mm, and a constant argon gas flow rate of (2.5) I/min. DBD plasma emission spectra were recorded for each voltage. The Boltzmann plot method was used to calculate the electron temperature in the plasma ( ), and the Stark expansion method was used to calculate the elec

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Publication Date
Sun Dec 31 2023
Journal Name
Iraqi Journal Of Information And Communication Technology
EEG Signal Classification Based on Orthogonal Polynomials, Sparse Filter and SVM Classifier
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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

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Publication Date
Tue Feb 03 2026
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
XGBOOST AND COST-SENSITIVE CART FOR IMBALANCED MULTICLASS DIABETES CLASSIFICATION IN IRAQ
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Diabetes imposes a substantial public health burden; according to the International Diabetes Federation, there were about 3.4 million diabetes related deaths worldwide in 2024, and in Iraq, the Federation reports that one in nine adults lives with diabetes in 2024, with 14,683 adult deaths attributable to diabetes and a total diabetes related health expenditure of 2,078 million United States dollars. The dataset analyzed in this study contains 1,000 records collected in 2020 from two Iraqi teaching hospitals and includes multiple clinical and laboratory measurements with three outcome classes, namely Non diabetic, Pre diabetic, and Diabetic, with a low prevalence of the Pre diabetic class and an imbalanced overall class distribution; the da

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