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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
Wed Jan 01 2020
Journal Name
Modern Sport
Special exercises according to the Dynafoot data and its effect on the force index and the performance of the front straight air flip skill on the ground movements mat device
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Publication Date
Sun Aug 28 2016
Journal Name
World Journal Of Pharmacy And Pharmaceutical Sciences
AN INSIGHT ON THE IDENTIFICATION OF CANCER STEM CELLS USING NOVEL IMMUNOLOGICAL AND MOLECULAR STRATEGIES
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Cancer stem cells (CSCs) are defined as a population of cells present in tumours, which can undergo self-renewal and differentiation. Identification and isolation of these CSCs using putative surface markers have been a priority of research in cancer. With this background we selected pancreatic normal and tumor cells for this study and passaged them into animal tissue culture medium. Further staining was done using alkaline phosphatase and heamatoxilin staining. Blue to purple colored zones in undifferentiated pluripotent stem cells and clear coloration in the chromatin material indicated pancreatic cells. Further studies on the cell surface marker CD 44 were done using ELISA. For this, the protein was extracted from cultivated normal and t

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Publication Date
Fri Jan 01 2016
Journal Name
Middle-east Journal Of Scientific Research
Question Classification Using Different Approach: A Whole Review
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Publication Date
Sat Dec 01 2018
Journal Name
Al-nahrain Journal Of Science
Image Classification Using Bag of Visual Words (BoVW)
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In this paper two main stages for image classification has been presented. Training stage consists of collecting images of interest, and apply BOVW on these images (features extraction and description using SIFT, and vocabulary generation), while testing stage classifies a new unlabeled image using nearest neighbor classification method for features descriptor. Supervised bag of visual words gives good result that are present clearly in the experimental part where unlabeled images are classified although small number of images are used in the training process.

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Publication Date
Sat Feb 01 2025
Journal Name
Algorithms
Three-Dimensional Object Recognition Using Orthogonal Polynomials: An Embedded Kernel Approach
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Computer vision seeks to mimic the human visual system and plays an essential role in artificial intelligence. It is based on different signal reprocessing techniques; therefore, developing efficient techniques becomes essential to achieving fast and reliable processing. Various signal preprocessing operations have been used for computer vision, including smoothing techniques, signal analyzing, resizing, sharpening, and enhancement, to reduce reluctant falsifications, segmentation, and image feature improvement. For example, to reduce the noise in a disturbed signal, smoothing kernels can be effectively used. This is achievedby convolving the distributed signal with smoothing kernels. In addition, orthogonal moments (OMs) are a cruc

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Publication Date
Tue Dec 01 2009
Journal Name
Iraqi Journal Of Physics
Two-dimensional Crystallization of Silica nanospheres using Coplanar DC Electric field
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Abstract:Two-dimensional crystal has been achieved and controlled with the aid of DC electric field applied between two electrodes at 5 millimeters separating distance between them. Sol-gel method has been used to prepared nanosilica particle which used in this work as well as TiO2 nanopaowder. The assembly of the silica particles is due to the interaction between the electrical force, the particles dipole, and the interaction between the particles themselves. When a DC voltage is applied, the particles accumulated and crystallized on the surface between the electrodes. The Light diffraction demonstrates that the hexagonal crystal is always oriented with one axis along the direction of the field. The particles disassemble when the field is

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Publication Date
Sun Nov 19 2023
Journal Name
Aip Conference Proceedings
Designing a database for a three dimensional model using geomatics techniques
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Publication Date
Wed Dec 30 2009
Journal Name
Iraqi Journal Of Physics
Two-dimensional Crystallization of Silica nanospheres using Coplanar DC Electric field
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Two-dimensional crystal has been achieved and controlled
with the aid of DC electric field applied between two electrodes at 5
millimeters separating distance between them. Sol-gel method has
been used to prepared nanosilica particle which used in this work as
well as TiO2 nanopaowder. The assembly of the silica particles is
due to the interaction between the electrical force, the particles
dipole, and the interaction between the particles themselves. When a
DC voltage is applied, the particles accumulated and crystallized on
the surface between the electrodes. The Light diffraction
demonstrates that the hexagonal crystal is always oriented with one
axis along the direction of the field. The particles disass

... Show More
View Publication Preview PDF
Publication Date
Sat Feb 01 2025
Journal Name
Algorithms
Three-Dimensional Object Recognition Using Orthogonal Polynomials: An Embedded Kernel Approach
...Show More Authors

Computer vision seeks to mimic the human visual system and plays an essential role in artificial intelligence. It is based on different signal reprocessing techniques; therefore, developing efficient techniques becomes essential to achieving fast and reliable processing. Various signal preprocessing operations have been used for computer vision, including smoothing techniques, signal analyzing, resizing, sharpening, and enhancement, to reduce reluctant falsifications, segmentation, and image feature improvement. For example, to reduce the noise in a disturbed signal, smoothing kernels can be effectively used. This is achievedby convolving the distributed signal with smoothing kernels. In addition, orthogonal moments (OMs) are a cruc

... Show More
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Crossref (5)
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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
3-D OBJECT RECOGNITION USING MULTI-WAVELET AND NEURAL NETWORK
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This search has introduced the techniques of multi-wavelet transform and neural network for recognition 3-D object from 2-D image using patches. The proposed techniques were tested on database of different patches features and the high energy subband of discrete multi-wavelet transform DMWT (gp) of the patches. The test set has two groups, group (1) which contains images, their (gp) patches and patches features of the same images as a part of that in the data set beside other images, (gp) patches and features, and group (2) which contains the (gp) patches and patches features the same as a part of that in the database but after modification such as rotation, scaling and translation. Recognition by back propagation (BP) neural network as

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