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Artificial Neural Network Models to Predict the Cost and Time of Wastewater Projects
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Infrastructure, especially wastewater projects, plays an important role in the life of residential communities. Due to the increasing population growth, there is also a significant increase in residential and commercial facilities. This research aims to develop two models for predicting the cost and time of wastewater projects according to independent variables affecting them. These variables have been determined through a questionnaire distributed to 20 projects under construction in Al-Kut City/ Wasit Governorate/Iraq. The researcher used artificial neural network technology to develop the models. The results showed that the coefficient of correlation R between actual and predicted values were 99.4% and 99 %, MAPE was (26.24%), and (5.5%), and AA was (74%), and (94.5%), for cost and time model, respectively. The researcher concluded that the ANN model has a strong correlation and high accuracy, indicating that these models are characterized by high efficiency and good performance in predicting cost and time.

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Publication Date
Mon Apr 15 2019
Journal Name
Proceedings Of The International Conference On Information And Communication Technology
Re-evaluation of the stable improved LEACH routing protocol for wireless sensor network
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Publication Date
Mon Jan 01 2024
Journal Name
Lecture Notes In Networks And Systems
Implementing a Smart Low-Cost System for Diagnosing Bacteria in Women
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Publication Date
Wed Feb 21 2024
Journal Name
Al-rafidain Journal Of Medical Sciences ( Issn 2789-3219 )
Perceptions of Senior Pharmacy Students Towards the Impact of Artificial Intelligence on University Education and Scientific Writing: A Qualitative Study
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Background: The roles of AI in the academic community continue to grow, especially in the enhancement of learning outcomes and the improvement of writing quality and efficiency. Objectives: To explore in depth the experience of senior pharmacy students in using artificial intelligence for academic purposes. Methods: This qualitative study included face-to-face individual interviews with senior pharmacy students from March to May 2023 using a pre-planned interview guide of open-ended questions. All interviews were audio-recorded. Thematic analysis was used to analyze the data. Results: The results were obtained from 15 in-depth face-to-face interviews with senior pharmacy students (5th and 4th years). Eight participants were male, and seven

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Publication Date
Mon Sep 23 2019
Journal Name
Baghdad Science Journal
A Semi-Supervised Machine Learning Approach Using K-Means Algorithm to Prevent Burst Header Packet Flooding Attack in Optical Burst Switching Network
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Optical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm

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Publication Date
Tue Jun 24 2025
Journal Name
Food And Bioprocess Technology
Classification of Apple Slices Treated by Atmospheric Plasma Jet for Post-harvest Processes Using Image Processing and Convolutional Neural Networks
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Abstract<p>Apple slice grading is useful in post-harvest operations for sorting, grading, packaging, labeling, processing, storage, transportation, and meeting market demand and consumer preferences. Proper grading of apple slices can help ensure the quality, safety, and marketability of the final products, contributing to the post-harvest operations of the overall success of the apple industry. The article aims to create a convolutional neural network (CNN) model to classify images of apple slices after immersing them in atmospheric plasma at two different pressures (1 and 5 atm) and two different immersion times (3 and again 6 min) once and in filtered water based on the hardness of the slices usin</p> ... Show More
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Publication Date
Sun Dec 02 2012
Journal Name
Baghdad Science Journal
Stability of Back Propagation Training Algorithm for Neural Networks
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In this paper, we derive and prove the stability bounds of the momentum coefficient µ and the learning rate ? of the back propagation updating rule in Artificial Neural Networks .The theoretical upper bound of learning rate ? is derived and its practical approximation is obtained

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
the role of time management in facilitate the work requirements for employees of the administrative department at the ministry of higher education and scientific research
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The aim of the present study is to provide the adequate knowledge about the role of time management in facilitate the work requirements for employees of the administrative department at the Ministry of Higher Education and Scientific Research. The research depend on studying four important dimensions which are (time planning, time organization, time direction and time observation). In addition to study other five dimensions which are (new procedures, clear procedures, short procedures, the available information and the simplicity of the methods

used).Questionnaire sheets consist of (38 questions) distributed to (170) employees and (146)  sheets only were considered in the study. SPSS program was used

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Publication Date
Wed Jan 01 2020
Journal Name
2nd International Conference On Materials Engineering &amp; Science (iconmeas 2019)
Modeling of adsorption isotherms of oil content through the electrocoagulation treatment of real oily wastewater
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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Weighted Least Squares Estimation of the Effect of Wastewater Pollution of Tigris River / Wasit Governorate
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Abstract

The analysis of Least Squares: LS is often unsuccessful in the case of outliers ​​in the studied phenomena. OLS will lose their properties and then lose the property of Beast Linear Unbiased Estimator (BLUE), because of the Outliers have a bad effect on the phenomenon. To address this problem, new statistical methods have been developed so that they are not easily affected by outliers. These methods are characterized by robustness or (resistance). The Least Trimmed Squares: LTS method was therefore a good alternative to achieving more feasible results and optimization. However, it is possible to assume weights that take into consideration the location of the outliers ​​in the data and det

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Publication Date
Wed Nov 14 2018
Journal Name
Iraqi National Journal Of Nursing Specialties
The Effect of Different Concentrations of Gilvest with Water on the Setting Time of Phosphate-bonded investment
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Objective: To identify of the effect of the different concentrations of the special liquid (for mixing the investment, Gilvest)
and mixed with water/powder ratio on setting time of phosphate–bonded investment.
Method and materials: The present study is (60) specimens made from phosphate bonded investment divided into (4)
groups (control and experimental groups), (15) specimens for each group. The Gillmore needle device is used to setting
time of phosphate bonded investment mixed with different concentration of Gilvest and water.
Results: Showed that there is a high significant difference (P<0.01) between each groups in the ANOVA test and a
significant difference (P<0.05) between the group (A) and control group i

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