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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 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%.

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Engineering Science And Technology
THE INFLUENCE OF CHEMICAL COMPOSITION OF ASPHALT CEMENT ON THE PHYSICAL AND RHEOLOGICAL PROPERTIES
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Failure in asphalt mixture and distress in pavement are major issues to roads infrastructure. Selecting an appropriate chemical composition of asphalt cement is a key component in avoiding these issues. This work aimed to investigate the effect of the chemical composition of different polar fractions on the rheological and physical properties of asphalt cement. Four types of asphalt cement with penetration grades of 20/30, 40/50, 60/70 and 85/100 were divided into four fractions. Complex shear modules, rutting resistance and rotational viscosity of the asphalt cement were determined by using a Dynamic Shear Rheometer and a Rotation Viscometer, respectively. The results show that an increase in the asphaltene content and Gastel index resulte

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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Engineering
Effect of Heat Treatments and Carbon Content on the Damping Properties of Structural Steel
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Low- and medium-carbon structural steel components face random vibration and dynamic loads (like earthquakes) in many applications. Thus a modification to improve their mechanical properties, essentially damping properties, is required. The present study focuses on improving and developing these properties, significantly dampening properties, without losing the other mechanical properties. The specimens used in the present study are structural steel ribbed bar ISO 6935 subjected to heating temperatures of (850, 950, and 1050) ˚C, and cooling schemes of annealing, normalizing, sand, and quenching was selected. The damping properties of the specimens were measured experimentally with the area under the curve for the loadi

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Publication Date
Sun Sep 01 2019
Journal Name
Journal Of Physics: Conference Series
Seed weight effect on germination properties and seedling growth of some cultivars of lupine
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A laboratory experiment was carried out and repeated at field of College of Agricultural Engineering Sciences, University of Baghdad in 2017. First factor was three cultivars of lupine 'Giza-1', 'Giza-2' and 'Hamburg'. Second factor was three seed weights (lower weight, medium weight and higher weight) which was following the cultivars factor. Nested design was used. Results showed supremacy of 'Giza-1' cultivar significantly and gave higher germination ratio, radical length, seedling dry weight, seedling vigour index, field emergence ratio, plant height and number of leaves per plant. The treatment ('Giza-1'×higher seed weight) was supremacy significantly and gave higher germination ratio, radical length, plumule length, and seedling vigo

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Publication Date
Mon Feb 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Comparative study of logistic regression and artificial neural networks on predicting breast cancer cytology
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<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

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Publication Date
Sat Jan 01 2022
Journal Name
Materials Today: Proceedings
Evaluating the individual, dual usage of (TGP) and (SF) additives on improving gypsum characteristics
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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Pathological And Immunological Study On Infection With Escherichia Coli In ale BALB/c mice
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Publication Date
Sat Oct 04 2025
Journal Name
Infrastructures
Influence of Coarse Aggregate Geometry and Mineral Composition on the Durability of Asphalt Concrete
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The durability of asphalt concrete is highly dependent on the geometry and mineralogy of coarse aggregates, yet their combined influence on mechanical and moisture resistance properties is still not fully understood. This study evaluates the effects of coarse aggregate geometry, specifically flat and elongated particle ratios and angularity, as well as mineral composition (quartz versus calcite), on asphalt mixture durability. The durability of mixtures was evaluated through Marshall properties as well as moisture susceptibility indicators, including the tensile strength ratio (TSR) and index of retained strength (IRS). Statistical analyses (ANOVA and t-tests) were also conducted to confirm the significance of the observed effects.

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Publication Date
Sun Jan 01 2023
Journal Name
Pakistan Journal Of Botany
Efficiency of plant extracts on Aspergillus growth and aflatoxin B1 production in Zea mays
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The detection of fungi contaminating maize grain and the effect of four plant extracts Azadirachta indica, Eucalyptus globulus Glycyrrhiza glabra and Zingiber officinale on the growth of A. flavus and its ability to produce AflatoxinB1. The results showed that the incidence of Aspergillus spp., was 52.75% of the isolated fungi, of which 29.50% was due to Aspergillus flavus, followed by Penicillium spp., with an incidence of 21.06%, and then Fusarium spp., with a rate of 18.13%. The percentage of toxin-producing A. flavus isolates reached 70.8% out of 24 isolates. The results showed the effect of alcoholic plant extracts at a concentration of 10 mg/ml on the fungal growth activity of A. flavus, the alcoholic extract of neem leaves was superi

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Publication Date
Tue Apr 19 2022
Journal Name
Al Mustansiriyah Journal Of Pharmaceutical Sciences
Effect of pioglitazone treatment on serum chemerin and vaspin levels in polycystic ovary syndrome.
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Abdominal fat synthesizes a variety of adipokines, including vaspin and chemerin, that affect the resistance to insulin. This research was conducted to demonstrate the effect of pioglitazone, one insulin sensitizer used to decrease insulin resistance, on these adipokines in   obese patients with polycystic ovary (PCOS). Twenty-five obese women with PCOS were treated with pioglitazone 15mg/bid for 12 weeks. Modifications in fasting blood glucose (FBG), serum fasting insulin (FSI), chemerin and vaspin serum levels, follicle stimulation hormone (FSH), luteinizing hormone (LH), testosterone (T), and in baseline and post-therapy were assessed. Body mass index decreased without any substantial variance after 12 weeks of piogl

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Publication Date
Fri Jul 08 2022
Journal Name
Innovation Of Businesses, And Digitalization During Covid-19 Pandemic
The Impact of Political Stability and Macroeconomic Variables on Foreign Direct Investment in Turkey
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Foreign direct investment (FDI) is one of the most practical types of foreign investment. FDI contributes to job creation, foreign exchange earnings and national income escalation, improving semi-skill and skilled labor. Based on our knowledge, this paper is the first study attempting to investigate the effect of political stability on the FDI in Turkey using an econometric approach. Achieving this objective, a co-integration analysis was conducted between the FDI and its determinants in the short-run and long-run including “macroeconomic indicators” and “Political Stability (PS)” in Turkey. Using annual data from 1974 to 2017 via Auto-Regressive Distributed Lag (ARDL) model. The results confirm the positive correlation betwe

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