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Lung cancer classification using data mining and supervised learning algorithms on multi-dimensional data set
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These With recent developments in machine learning, data mining and computer vision, there is great potential for improvements in early detection of lung cancer using scans and data available. This paper details the methods and techniques used in our project, where the objective is to develop algorithms to determine whether a patient has or is likely to develop lung cancer using dataset images using data mining and machine learning for the classification and examination. We explore approaches to address the problem. Cancer is the most important cause of death globally. The disease diagnosis is a major process to treat the patients who are affected by cancer disease. The diagnosis process is more difficult comparatively known about the cancer disease detection. Developing a proposed data mining model is useful to diagnose the cancer disease once the cancer detection is accomplished using data mining for the examination and classification of machine learning supervised algorithms.

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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
3D scenes semantic segmentation using deep learning based Survey
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Abstract<p>Semantic segmentation realization and understanding is a stringent task not just for computer vision but also in the researches of the sciences of earth, semantic segmentation decompose compound architectures in one elements, the most mutual object in a civil outside or inside senses must classified then reinforced with information meaning of all object, it’s a method for labeling and clustering point cloud automatically. Three dimensions natural scenes classification need a point cloud dataset to representation data format as input, many challenge appeared with working of 3d data like: little number, resolution and accurate of three Dimensional dataset . Deep learning now is the po</p> ... Show More
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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Computers, Communications, Control And Systems Engineering
A Framework for Predicting Airfare Prices Using Machine Learning
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre

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Publication Date
Fri Sep 30 2022
Journal Name
Iraqi Journal Of Computer, Communication, Control And System Engineering
A Framework for Predicting Airfare Prices Using Machine Learning
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci

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Publication Date
Mon Mar 02 2026
Journal Name
International Journal Of Inventions In Engineering &amp; Science Technology
A Review: Campus Violence Detection Using Deep Learning Models
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This paper offers a systemic review of the deep learning methods to detect violence on campus, which is a critical issue in intelligent surveillance to improve the student safety and prompt cut off of violent accidents. The review reviews studies published 2018-2025, concentrating on model structure to detect fights, bullying, vandalism, and aggressive behavior on problematic campuses due to occlusion and light variations and complicated human interactions. The research design includes a comparative study of different deep learning networks, such as CNNs, RNNs, 3D CNNs, attention-based networks, transformers, graph neural networks, neuro-fuzzy, and multimodal systems and federated learning methods. The paper also assesses benchmark

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Publication Date
Mon Jan 09 2023
Journal Name
2023 15th International Conference On Developments In Esystems Engineering (dese)
Deep Learning-Based Speech Enhancement Algorithm Using Charlier Transform
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Publication Date
Mon Jan 01 2024
Journal Name
Computers, Materials &amp; Continua
Credit Card Fraud Detection Using Improved Deep Learning Models
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Publication Date
Sat Jul 12 2025
Journal Name
Indian Journal Of Cardiovascular Disease In Women
Pilot phase of Iraqi Registry of Cardiovascular Diseases in Women: Assessing the Feasibility of Large Data Registry in Absence of Funding
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Objectives:

Despite that cardiovascular disease (CVD) is the main cause of death in women worldwide and that the existent evidence that women with CVD differs from men with the same diseases from many views including pathophysiological to therapeutic. Yet, there is an unmet need for registries focused on sex differences in CVD, as the first step toward patient-centered trials, guidelines, and protocols. To the best of our knowledge, there has been no prior registry focusing exclusively on CVD in women with sex-focused research questions and methodology thus far.

Materials and Methods:

The Iraqi Registry of Cardiovas

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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
The History of Multi Parties and its Effect on Political System in India
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The History of Multi Parties and its Effect on Political System in India

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Publication Date
Wed Sep 26 2018
Journal Name
Communications In Computer And Information Science
A New RGB Image Encryption Based on DNA Encoding and Multi-chaotic Maps
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Publication Date
Fri May 29 2026
Journal Name
Construction Materials
Synergistic Effects of Multi-Walled Carbon Nanotubes and SBS on Asphalt Binder Performance
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The performance and durability of asphalt pavements are strongly influenced by the rheological properties of asphalt binders, particularly under severe climatic and traffic conditions. This study investigates the synergistic effects of incorporating multi-walled carbon nanotubes (CNTs) at dosages ranging from 0.25% to 1% into AC 40-50 asphalt binders modified with 4% Styrene–Butadiene–Styrene (SBS). A comprehensive experimental program involving physical, rheological, and chemical characterization tests was conducted, including penetration, softening point, viscosity, storage stability, a Dynamic Shear Rheometer (DSR), Multiple Stress Creep Recovery (MSCR), Linear Amplitude Sweep (LAS), Fourier Transform Infrared Spectroscopy (F

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