Preferred Language
Articles
/
bsj-9029
An Observation and Analysis the role of Convolutional Neural Network towards Lung Cancer Prediction
...Show More Authors

Lung cancer is one of the most serious and prevalent diseases, causing many deaths each year. Though CT scan images are mostly used in the diagnosis of cancer, the assessment of scans is an error-prone and time-consuming task. Machine learning and AI-based models can identify and classify types of lung cancer quite accurately, which helps in the early-stage detection of lung cancer that can increase the survival rate. In this paper, Convolutional Neural Network is used to classify Adenocarcinoma, squamous cell carcinoma and normal case CT scan images from the Chest CT Scan Images Dataset using different combinations of hidden layers and parameters in CNN models. The proposed model was trained on 1000 CT Scan Images of cancerous and non-cancerous cells to find the best combination of parameters in CNN to predict lung cancer accurately.  The proposed system recorded the highest accuracy of 92.79%. In addition to that, the paper addresses 192 observations made using the CNN model. 

Scopus Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Mon Jun 17 2019
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
A Study of Positive and Negative Parity States in 114Te nucleus by the Interacting Boson Model .IBM by Neural Network(Back propagation multi-layer neural network) .
...Show More Authors

Positive and negative parity states for 114Te have been studied applying the vibration al limit U(5) of Interacting boson model (IBM- 1 ) . The present results have shown their good agreement with experimental data in addition to the determination of the spin/parity of new energy levels are not assigned experimentally as the levels 0+2 and 5+1 and the levels 3"1 and 5-1 . Then back propagation multiLayer neural network used for positive and negative parity states for 114Te and shown their membership to the Vibration limit U(5) the network implemented by MATLAB system.

View Publication Preview PDF
Publication Date
Wed Dec 05 2018
Journal Name
Italian Journal Of Gynaecology & Obstetrics
Prediction of Fetal Lung Maturity by Ultrasonic Thalamic Echogenicity and Ossification Centers of Fetal Femur and Tibia
...Show More Authors

Publication Date
Thu May 05 2016
Journal Name
Global Journal Of Engineering Science And Researches
EVALUATE THE RATE OF CONTAMINATION SOILS BY COPPER USING NEURAL NETWORK TECHNIQUE
...Show More Authors

The aim of this paper is to design suitable neural network (ANN) as an alternative accurate tool to evaluate concentration of Copper in contaminated soils. First, sixteen (4x4) soil samples were harvested from a phytoremediated contaminated site located in Baghdad city in Iraq. Second, a series of measurements were performed on the soil samples. Third, design an ANN and its performance was evaluated using a test data set and then applied to estimate the concentration of Copper. The performance of the ANN technique was compared with the traditional laboratory inspecting using the training and test data sets. The results of this study show that the ANN technique trained on experimental measurements can be successfully applied to the rapid est

... Show More
View Publication Preview PDF
Publication Date
Thu Sep 01 2011
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The Role of higher Education Institutes in restricting Administrative and Financial Corruption: An Analytic Reading
...Show More Authors

Corruption, in all its categories and forms, is regarded as the nowadays virus which has greatly spread in most institutes and society, a matter that cause a great waste of resources.

      According to the reports of international transparency Institute, Iraq is regarded as one of the greatest countries in corruption.

      Regardless of the reasons and forms of corruption, the retreat in work – values and ethics are the main reasons behind that.

      Being the main source of providing qualified staff "educators" for the working market, the high education institutes face great challenges in standing against corruption inside and outside

... Show More
View Publication Preview PDF
Publication Date
Sat Dec 30 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
The Finite Element Neural Network And Its Applications To Forward And Inverse Problems
...Show More Authors

In this paper, first we   refom1Ulated   the finite   element  model

(FEM)   into   a   neural   network   structure   using   a   simple   two   - dimensional problem. The structure of this neural network is described

, followed  by its   application   to   solving  the forward    and  inverse problems. This model is then extended to the general case and the advantages and  di sadvantages  of  this  approach  are  descri bed  along with an analysis  of  the sensi tivity   of

... Show More
View Publication Preview PDF
Publication Date
Sat Sep 30 2017
Journal Name
Al-khwarizmi Engineering Journal
Travel Time Prediction Models and Reliability Indices for Palestine Urban Road in Baghdad City
...Show More Authors

Abstract

     Travel Time estimation and reliability measurement is an important issues for improving operation efficiency and safety of traffic roads networks. The aim of this research is the estimation of total travel time and distribution analysis for three selected links in Palestine Arterial Street in Baghdad city. Buffer time index results in worse reliability conditions. Link (2) from Bab Al Mutham intersection to Al-Sakara intersection produced a buffer index of about 36%  and 26 % for Link (1) Al-Mawall intersection to Bab Al- Mutham intersection and finally for link (3) which presented a 24% buffer index. These illustrated that the reliability get worst for link

... Show More
View Publication Preview PDF
Crossref (11)
Crossref
Publication Date
Mon May 22 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
The Effect of Number of Training Samples for Artificial Neural Network
...Show More Authors

 In this paper we study the effect of the number of training samples for  Artificial neural networks ( ANN ) which is necessary for training process of feed forward neural network  .Also we design 5 Ann's and train 41 Ann's which illustrate how good the training samples that represent the actual function for Ann's.

View Publication Preview PDF
Publication Date
Thu Feb 29 2024
Journal Name
International Journal Of Design & Nature And Ecodynamics
Artificial Neural Network Assessment of Groundwater Quality for Agricultural Use in Babylon City: An Evaluation of Salinity and Ionic Composition
...Show More Authors

View Publication Preview PDF
Scopus Crossref
Publication Date
Sun Jun 01 2008
Journal Name
2008 Ieee International Joint Conference On Neural Networks (ieee World Congress On Computational Intelligence)
Linear block code decoder using neural network
...Show More Authors

View Publication
Scopus (12)
Crossref (7)
Scopus Clarivate Crossref
Publication Date
Sun Jun 11 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Artificial Neural Network for TIFF Image Compression
...Show More Authors

The main aim of image compression is to reduce the its size to be able for transforming and storage, therefore many methods appeared to compress the image, one of these methods is "Multilayer Perceptron ". Multilayer Perceptron (MLP) method which is artificial neural network based on the Back-Propagation algorithm for compressing the image. In case this algorithm depends upon the number of neurons in the hidden layer only the above mentioned will not be quite enough to reach the desired results, then we have to take into consideration the standards which the compression process depend on to get the best results. We have trained a group of TIFF images with the size of (256*256)  in our research, compressed them by using MLP for each

... Show More
View Publication Preview PDF
Crossref