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Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a CT lung cancer dataset consisting of 1000 images and four different classes. The data augmentation process is applied to prevent overfitting, increase the size of the data, and enhance the training process. Score-level fusion and ensemble learning are also used to get the best performance and solve the low accuracy problem. All models were evaluated using accuracy, precision, recall, and the F1-score. Results: Experiments show the high performance of the ensemble model with 99.44% accuracy, which is better than all of the current state-of-the art methodologies. Conclusion: The current study's findings demonstrate the high accuracy and robustness of the proposed ensemble transfer deep learning using various transfer learning models

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Publication Date
Fri Feb 21 2025
Journal Name
Applied System Innovation
Utilizing Soft Computing Techniques to Estimate the Axial Permanent Deformation of Asphalt Concrete
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Rutting is a crucial concern impacting asphalt concrete pavements’ stability and long-term performance, negatively affecting vehicle drivers’ comfort and safety. This research aims to evaluate the permanent deformation of pavement under different traffic and environmental conditions using an Artificial Neural Network (ANN) prediction model. The model was built based on the outcomes of an experimental uniaxial repeated loading test of 306 cylindrical specimens. Twelve independent variables representing the materials’ properties, mix design parameters, loading settings, and environmental conditions were implemented in the model, resulting in a total of 3214 data points. The network accomplished high prediction accuracy with an R

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Publication Date
Sun Jan 08 2023
Journal Name
Journal Of Planner And Development
Measuring the extent to which Application the criteria Transfer stations (regularity) for the municipalities of Karrada and Shula
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The process of transporting waste from urban areas to sanitary landfill sites requires large amounts of money due to the length and distance. To address this problem, temporary transfer stations were established by the Municipality of Baghdad to reduce the cost of transportation, and for the purpose of preserving the environment in a sustainable manner, standards were set for the establishment of these stations. The two stations of Al-Karrada Municipality and Al-Shula Municipality were chosen as a case study to measure the extent of adopting and applying the standards for establishing substations locally, regionally and internationally, and the most important results were reached Which is that the transforming (regular) stations of the t

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Publication Date
Fri Mar 29 2024
Journal Name
Iraqi Journal Of Science
Evaluating the Performance and Behavior of CNN, LSTM, and GRU for Classification and Prediction Tasks
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     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod

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Publication Date
Sat Jul 01 2023
Journal Name
Iop Conference Series: Earth And Environmental Science
Monitoring the land surface temperature for Al-Ahdab oil field in 2022 using R.S and GIS techniques
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Abstract<p>The skin temperature of the earth’s surface is referred to as the Land Surface Temperature (LST). the availability of long-term and high-quality temperature records is important for various uses that affect people’s lives and livelihoods. Much valid information was provided to this research from remote sensing technology by using Landsat 8 (L8) imagery to estimate LST for Al-Ahdab oil field in Wasit city in Iraq. The aim of this research is to analyze LST variations based on Landsat 8 data for 2022 (January, April, July, and October). ArcMap 10.8 was used to estimate LST results. The results values ranged from (about 10 C in January to about 46 C in July). The results show that LS</p> ... Show More
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Publication Date
Tue Dec 11 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
Burden of Mothers’ Care for Children with Colostomy at Baghdad Medical City Teaching Hospital
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Objective(s): To assess the burden of mothers` care for child with colostomy and find out relationships between child and mother socio-demographic data with mothers` burden. Methodology: a descriptive study was conducted from 1 August 2013 to 1 September 2014. The sample consisted of 100 children and their mothers at Baghdad Teaching hospital in Baghdad city. A questionnaire was prepared based on the previous literature review, meeting mothers of children with colostomy, and the Zarit Burden Interview scale. Data has collected through the application of questionnaire and interview techniques. Results: T

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Publication Date
Fri Jan 20 2023
Journal Name
Journal Of Electronic Materials
Influence of Dry and Wet Etching on AlInSb Contact Resistivity, Transfer Length, and Sheet Resistance Using Circular Transmission Model
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Publication Date
Thu Aug 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
Analyzing current and future direction of non-oil primary balance: Case Study of Iraq Using Exponential Smoothing model
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In recent years, non-oil primary balance indicator has been given considerable financial important in rentier state. It highly depends on this indicator to afford a clear and proper picture of public finance situation in term of appropriate and sustainability in these countries, due to it excludes the effect of oil- rental from compound of financial accounts which provide sufficient information to economic policy makers of how economy is able to create potential added value and then changes by eliminating one sided shades of economy. In Iraq, since, 2004, the deficit in value of this indicator has increased, due to almost complete dependence on the revenues of the oil to finance the budget and the obvious decline of the non-oil s

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Publication Date
Thu Jun 20 2019
Journal Name
Baghdad Science Journal
Social Worked-Examples Technique to Enhance Student Engagement in Program Visualization
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Learning programming is among the top challenges in computer science education. A part of that, program visualization (PV) is used as a tool to overcome the high failure and drop-out rates in an introductory programming course. Nevertheless, there are rising concerns about the effectiveness of the existing PV tools following the mixed results derived from various studies. Student engagement is also considered a vital factor in building a successful PV, while it is also an important part of the learning process in general. Several techniques have been introduced to enhance PV engagement; however, student engagement with PV is still challenging. This paper employed three theories—constructivism, social constructivism and cognitive load t

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Publication Date
Tue Aug 03 2021
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The role of coordination and joint cooperation in raising the quality of auditing in accordance with the INTOSAI standard(9150 (: Applied research in the General Company for Marketing Medicines and Medical Appliances - Kimadia
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The process of coordination and joint cooperation between SAIs and internal auditors in the public sector is considered one of the very important matters in performing efficient audits and are of high quality, especially if this coordination and cooperation is implemented in accordance with international standards, as it leads to avoiding duplication in auditing work. And the distribution of work in a distribution that achieves the objectives of auditing in general and is of general benefit to the economic unit.

The research problem lies in the weakness of the relationship between internal auditing and external auditing as a result of not applying INTOSAI Standard (9150) coordination and joint cooperation

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Publication Date
Tue Dec 20 2016
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Development Accounting Rule disclosure by accounting policies in the light of Islamic and electronic banking Activities (Proposal pattern): Proposal pattern
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the bank sect for any country  is very important  because  its represent a major  nerve   to feed a verity economic and finance activities .development any state measure by development  banking  sets and its represent  important  factor to investors attract . and because  important  of this subject ,teen accounting rule is a specialized for it .its related by  Disclosures in the Financial Statements Of Banks and The Similar Institutions, its accredit  by auditing and accounting standard  consul in republic of Iraq.in date 10/28/1998.                      &

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