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Recurrent Stroke Prediction using Machine Learning Algorithms with Clinical Public Datasets: An Empirical Performance Evaluation
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Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning algorithms implementation in the recurrent stroke prediction models. This research aims to investigate and compare the performance of machine learning algorithms using recurrent stroke clinical public datasets. In this study, Artificial Neural Network (ANN), Support Vector Machine (SVM) and Bayesian Rule List (BRL) are used and compared their performance in the domain of recurrent stroke prediction model. The result of the empirical experiments shows that ANN scores the highest accuracy at 80.00%, follows by BRL with 75.91% and SVM with 60.45%.

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Publication Date
Sat Dec 01 2018
Journal Name
Al-khwarizmi Engineering Journal
Biodegradation of Diesel Contaminated Soil Using Single Bacterial Strains and a Mixed Bacterial Consortium
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This study was conducted to assess the hydrocarbon degradation abilities of Sphingomonas paucimobilis, Pentoae species, Staphylococcus aureus, and Enterobacter cloacae, which isolated from diesel contaminated soil samples. Single strains and mixed bacterial consortia have been investigated their ability to degrade 1.0 % (v/v) of diesel oil in Bushnell- Haas medium as sole.carbon.and.energy.source. At temperature 30C, the individual.bacterial.isolates exhibited low growth and low degradation.than did the.mixed. bacterial.culture. After 28 days.of incubation the.combination.of four isolates degraded.an upper limit.of diesel  88.4%. This was. continued.by 85.1% by S. paucimobilis, 84 % by Pentoae sp., 79% by S.aureus, and

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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Distinguishing Shapes of Breast Cancer Masses in Ultrasound Images by Using Logistic Regression Model
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The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of

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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Biosynthesis, Characterization, Adsorption and Antimicrobial studies of Manganese oxide Nanoparticles Using Punica Granatum Extract
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Manganese sulfate and Punica granatum plant extract were used to create MnO2 nanoparticles, which were then characterized using techniques like Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, atomic force microscopy, X-ray diffraction, transmission electron microscopy, scanning electron microscopy, and energy-dispersive X-ray spectroscopy. The crystal's size was calculated to be 30.94nm by employing the Debye Scherrer equation in X-ray diffraction. MnO2 NPs were shown to be effective in adsorbing M(II) = Co, Ni, and Cu ions, proving that all three metal ions may be removed from water in one go. Ni(II) has a higher adsorption rate throughout the board. Co, Ni, and Cu ion removal efficiencie

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Publication Date
Mon Oct 19 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
The effect of using the interactive video accompanying the static training in learning some basic skills of a model school in squash
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Lately great interests have emerged to find educational alternatives to teach and improve motor skills according to modern educational methods that take into account individual differences and speed in learning for the learner through individual learning that the learner adopts by teaching himself by passing through various educational situations to acquire skills and information in the way he is The learner is the focus of the educational process and among these alternatives the interactive video, the researchers noted through the educational training units at the Model Squash School of the Central Union, and that most of the methods and methods used in learning basic skills take a lot of time in the educational program and do not involve

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Publication Date
Thu Nov 03 2022
Journal Name
Sensors
A Novel Application of Deep Learning (Convolutional Neural Network) for Traumatic Spinal Cord Injury Classification Using Automatically Learned Features of EMG Signal
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In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Enhancement of corrosion protection of metal carbon steel C45 and stainless steel 316 by using inhibitor (Schiff base) in sea water
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This research has presented a solution to the problem faced by alloys: the corrosion problem, by reducing corrosion and enhancing protection by using an inhibitor (Schiff base). The inhibitor (Schiff base) was synthesized by reacting of the substrates materials (4-dimethylaminobenzaldehyde and 4-aminoantipyrine). It was diagnosed by infrared technology IR, where the IR spectrum and through the visible beams proved that the Schiff base was well formed and with high purity. The corrosion behavior of carbon steel and stainless steel in a saline medium (artificial seawater 3.5%NaCl) before and after using the inhibitor at four temperatures: 20, 30, 40, and 50 C° was studied by using three electrodes potentiostat. The corrosion behavior was

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Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
The Effect of Using Information and Communication Technology to Improving the Quality of Blended Learning Elements’, a Survey Study at the Technical College of Management /Baghdad
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 The research has been based on two main variables (information and communication technology) and the quality of blended education (physical and electronic), aiming to reveal the relationship between four dimensions (physical devices, software, databases, communication networks) and the elements of education represented by (the teacher, the student, the teaching process, curriculum).  The methodology and post-analysis-based research were conducted at the Technical College of Management / Baghdad through polling the opinions of a random sample that included (80) teachers out of (86) and the number of students (276) representing a random sample from all departments of the college (for the morning study) out of (3500) stud

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Publication Date
Thu Sep 30 2021
Journal Name
Journal Of Economics And Administrative Sciences
Human Resource Management and its Impact on the Level of Job Performance: An Analytical Research in the Iraqi Ministry of Interior
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        The current research aims to highlight the role of human resource management with its practices (human resource planning, selection and placement, training and development, performance evaluation, compensation, and incentives) in raising the level of individuals' performance and its dimensions (task performance, contextual performance, unproductive work behavior, and adaptive performance) by explaining the research problem, which can be limited to the low level of performance of individuals, where the researchers use the descriptive analytical approach and the SPSS program in the practical aspect of the research community represented by the general manager and his assistant

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Publication Date
Wed Mar 01 2017
Journal Name
Superlattices And Microstructures
Enhanced photoelectrochemical performance of ZnO nanorod arrays decorated with CdS shell and Ag2S quantum dots
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Publication Date
Fri Jun 27 2025
Journal Name
Mechanics Of Time-dependent Materials
Characterization and mechanical performance of stone mastic asphalt mixtures modified with SBS and PE polymers
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This study investigates the characterization and mechanical performance of Stone Mastic Asphalt (SMA) mixtures modified with two types of polymers: styrene–butadiene–styrene (SBS) and high-molecular-weight polyethylene (PE). Neat asphalt cement PG 64-16 was modified using a higher content of SBS and PE at concentrations of 6%, 7%, and 8% by weight of asphalt through the dry blending method to produce Highly Modified Asphalts (HiMA). The physical and rheological properties of the modified binders were evaluated using penetration, softening point, rotational viscosity, and dynamic shear rheometer (DSR) tests. Also, their phase compatibility and morphological changes were evaluated using the storage stability testing and scanning electron

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