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Effective SMOTE boost with deep learning for IDC identification in whole-slide images
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Breast cancer is highlighted in recent research as one of the most prevalent types of cancer. Timely identification is essential for enhancing patient results and decreasing fatality rates. Utilizing computer-assisted detection and diagnosis early on may greatly improve the chances of recovery by accurately predicting outcomes and developing suitable treatment plans. Grading breast cancer properly, especially evaluating nuclear atypia, is difficult owing to faults and inconsistencies in slide preparation and the intricate nature of tissue patterns. This work explores the capability of deep learning to extract characteristics from histopathology photos of breast cancer. The research introduces a new method called SMOTE-based Convolutional Neural Network (CNN) technology to detect areas impacted by Invasive Ductal Carcinoma (IDC) in whole slide pictures. The trials used a dataset of 162 individuals with IDC, split into training (113 photos) and testing (49 images) groups. Every model was subjected to individual testing. The SMO_CNN model we developed demonstrated exceptional testing and training accuracies of 98.95% and 99.20% respectively, surpassing CNN, VGG19, and ResNet50 models. The results highlight the effectiveness of the created model in properly detecting IDC-affected tissue areas, showing great promise for improving breast cancer diagnosis and treatment planning. We surpassing other models as such, CNN, VGG19, ResNet50.

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Publication Date
Fri May 16 2025
Journal Name
Asean Journal Of Science And Engineering
Enhancing Predictive Maintenance in Energy Systems Using a Hybrid Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) Framework for Rotating Machinery
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This study proposes a hybrid predictive maintenance framework that integrates the Kolmogorov-Arnold Network (KAN) with Short-Time Fourier Transform (STFT) for intelligent fault diagnosis in industrial rotating machinery. The method is designed to address challenges posed by non-linear and non-stationary vibration signals under varying operational conditions. Experimental validation using the FALEX multispecimen test bench demonstrated a high classification accuracy of 97.5%, outperforming traditional models such as SVM, Random Forest, and XGBoost. The approach maintained robust performance across dynamic load scenarios and noisy environments, with precision and recall exceeding 95%. Key contributions include a hardware-accelerated K

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Publication Date
Tue Jan 02 2018
Journal Name
Journal Of Educational And Psychological Researches
The Effect of Using Brainstorming Technique on the Essay Writing and Self- regulation Learning of the Iraqi Secondary Students
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         This study investigated the effect of using brainstorming as a teaching technique on the students’ performance in writing different kinds of essays and self regulation among the secondary students. The total population of this study, consisted of (51) female students of the 5th Secondary grade in Al –kawarzmi School in Erbil during the academic year 2015-2016. The chosen sample consisted of 40 female students, has been divided into two groups. Each one consists of (20) students to represent the experimental group and the control one. Brainstorming technique is used to teach the experimental group, and the conventional method is used to teach the control group. The study inst

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Publication Date
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Development of an Optimized Botnet Detection Framework based on Filters of Features and Machine Learning Classifiers using CICIDS2017 Dataset
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Abstract<p>Botnet is a malicious activity that tries to disrupt traffic of service in a server or network and causes great harm to the network. In modern years, Botnets became one of the threads that constantly evolving. IDS (intrusion detection system) is one type of solutions used to detect anomalies of networks and played an increasing role in the computer security and information systems. It follows different events in computer to decide to occur an intrusion or not, and it used to build a strategic decision for security purposes. The current paper <italic>suggests</italic> a hybrid detection Botnet model using machine learning approach, performed and analyzed to detect Botnet atta</p> ... Show More
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Publication Date
Thu Apr 30 2020
Journal Name
Journal Of Economics And Administrative Sciences
The Role of E-Learning in enhancing Total Quality Management in Educational Institutions: an exploratory study of the opinions of a sample of the staff of the Directorate of Education in the province of Nineveh
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Purpose: The research aims to determine the relationship between E-Learning and Total Quality Management (TQM) in Educational institutions in Nineveh Governorates.

Methodology / Design: The researchers distributed (30) questionnaires to employees (teachers and administrators) of Nineveh Governorate education who represent the community of the research sample, as they were analyzed using the SPSS V.20

The importance of research: The importance of the research in the fact that it focuses on one of the educational methods represented in integrating the traditional method and relying on modern technologies using computers and the Internet in the field of education to improve the reali

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Publication Date
Wed Sep 03 2014
Journal Name
Iraqi Journal Of Science
Antineutrophil cytoplasmic antibodies in patients with tuberculosis
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Tuberculosis is caused by Mycobacterium tuberculosis; it is considered as one of the most common, infectious diseases and major causes of morbidity and mortality worldwide. A prospective study was conducted to obtain more clarification about the impact of causative agent and its treatment to enhance autoantibodies production such as ANCA and BPI which used as diagnostic markers for several diseases, and to provide further insight into the classical risk factors (age and sex).Seventy patients with tuberculosis involved in this study, 35 of them were untreated and 35 with treatment administration these patients were attending to directorate of general health national reference laboratory in Baghdad during the period between November/ 2012 and

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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Hyperprolactenemia in Women with Systemic Lupus Erythematusus
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Recent accumulated evidences suggest that prolactin is an important immunomodulator and may have a role in the pathogenesis of systemic lupus erythematosus (SLE). The aim of this study was to assess the frequency of hyperprolactinemia in women with SLE and to evaluate its correlation with disease flares. Serum prolactin levels were measured in 62 women with SLE and 50 age- and sex-matched healthy controls. In patients and control groups prolactin levels were determined by immunoradiometric assay (IRMA). The prolactin level was found to be higher than normal rang in (40.3%) of SLE patients in active stage versus only (8.06%) of the same SLE patients but in the inactive stage and in (4%) of control group, the elevation was ranging between mi

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Publication Date
Mon Jan 28 2019
Journal Name
Journal Of The College Of Education For Women
Transportation movement with containers in Iraqi harbors
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The use of containers in transportation leads to the reduction in time and effort of the process of loading and unloading of goods as well as protecting the goods from damage and breakage and to reduce the financial costs.
. This development has led also to make changes in the sizes and capacity of ships, therefore changes in the ports must be taken place where they must be provided with an appropriate depth for such vessels, that means the increase in the depth of ports and the establishment of wide storage yards and to provide appropriate mechanisms for handling process.
In this study, the researcher has dealt with this type of transport business in Iraqi ports, namely:
1- Khur Al-Zubair port.
2- Um Qaser port.
In order

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Publication Date
Fri Aug 30 2024
Journal Name
Iraqi Journal Of Science
The Dissipation of the Kinetic Energy for 2D Bounded Flow by Using Moment-Based Boundary Conditions with Burnett Order Stress for LBM
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     In this article, the lattice Boltzmann method with two relaxation time  (TRT)  for the  D2Q9 model is used to investigate numerical results for 2D flow. The problem is performed to show the dissipation of the kinetic energy rate and its relationship with the enstrophy growth for 2D dipole wall collision. The investigation is carried out for normal collision and oblique incidents at an angle of . We prove the accuracy of moment -based boundary conditions with slip and Navier-Maxwell slip conditions to simulate this flow. These conditions are under the effect of Burnett-order stress conditions that are consistent with the discrete Boltzmann equation. Stable results are found by using this kind of boundary condition where d

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Publication Date
Fri Jun 28 2019
Journal Name
Journal Of The College Of Education For Women
The Effectiveness of an Educational Program For Early Intervention depending on Illustrative Pictures to Acquire some concepts For Children with Hearing impairment
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“Child of today is a man of the future" this slogan is one of the most popular logos of international organizations and institutions that dealing with human beings needs in general and children needs in particular, whether these needs are educational, health, social, or economic. Children require special care and extra legal protection, since the child-raising is not the Child’s own issue, but it's the issue of the society in which he/she would integrate.

As the education and language skillsacquisition primarily associated with hearing, because human being receives most of the skills and knowledge through the hearing; that imitate sounds and learn how to speak isacquired only by hearing, so therefore the hearing - impairedchi

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