Preferred Language
Articles
/
qxawGIcBVTCNdQwCMTaR
Prediction of Sediment Accumulation Model for Trunk Sewer Using Multiple Linear Regression and Neural Network Techniques
...Show More Authors

Sewer sediment deposition is an important aspect as it relates to several operational and environmental problems. It concerns municipalities as it affects the sewer system and contributes to sewer failure which has a catastrophic effect if happened in trunks or interceptors. Sewer rehabilitation is a costly process and complex in terms of choosing the method of rehabilitation and individual sewers to be rehabilitated.  For such a complex process, inspection techniques assist in the decision-making process; though, it may add to the total expenditure of the project as it requires special tools and trained personnel. For developing countries, Inspection could prohibit the rehabilitation proceeds. In this study, the researchers proposed an alternative method for sewer sediment accumulation calculation using predictive models harnessing multiple linear regression model (MLRM) and artificial neural network (ANN). AL-Thawra trunk sewer in Baghdad city is selected as a case study area; data from a survey done on this trunk is used in the modeling process. Results showed that MLRM is acceptable, with an adjusted coefficient of determination (adj. R2) in order of 89.55%. ANN model found to be practical with R2 of 82.3% and fit the data better throughout its range. Sensitivity analysis showed that the flow is the most influential parameter on the depth of sediment deposition.

Scopus Clarivate Crossref
View Publication
Publication Date
Wed Dec 01 2021
Journal Name
Baghdad Science Journal
Advanced Intelligent Data Hiding Using Video Stego and Convolutional Neural Networks
...Show More Authors

Steganography is a technique of concealing secret data within other quotidian files of the same or different types. Hiding data has been essential to digital information security. This work aims to design a stego method that can effectively hide a message inside the images of the video file.  In this work, a video steganography model has been proposed through training a model to hiding video (or images) within another video using convolutional neural networks (CNN). By using a CNN in this approach, two main goals can be achieved for any steganographic methods which are, increasing security (hardness to observed and broken by used steganalysis program), this was achieved in this work as the weights and architecture are randomized. Thus,

... Show More
View Publication Preview PDF
Scopus (10)
Crossref (1)
Scopus Clarivate Crossref
Publication Date
Tue Apr 04 2023
Journal Name
Journal Of Techniques
Comparison Between the Kernel Functions Used in Estimating the Fuzzy Regression Discontinuous Model
...Show More Authors

Some experiments need to know the extent of their usefulness to continue providing them or not. This is done through the fuzzy regression discontinuous model, where the Epanechnikov Kernel and Triangular Kernel were used to estimate the model by generating data from the Monte Carlo experiment and comparing the results obtained. It was found that the. Epanechnikov Kernel has a least mean squared error.

View Publication Preview PDF
Crossref (1)
Scopus Crossref
Publication Date
Sun Jul 31 2022
Journal Name
Journal Of Computational Innovation And Analytics (jcia)
PERFORMANCE MEASURE OF MULTIPLE-CHANNEL QUEUEING SYSTEMS WITH IMPRECISE DATA USING GRADED MEAN INTEGRATION FOR TRAPEZOIDAL AND HEXAGONAL FUZZY NUMBERS
...Show More Authors

In this paper, a procedure to establish the different performance measures in terms of crisp value is proposed for two classes of arrivals and multiple channel queueing models, where both arrival and service rate are fuzzy numbers. The main idea is to convert the arrival rates and service rates under fuzzy queues into crisp queues by using graded mean integration approach, which can be represented as median rule number. Hence, we apply the crisp values obtained to establish the performance measure of conventional multiple queueing models. This procedure has shown its effectiveness when incorporated with many types of membership functions in solving queuing problems. Two numerical illustrations are presented to determine the validity of the

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Engineering Science And Technology (jestec)
Water Quality Assessment And Total Dissolved Solids Prediction For Tigris River In Baghdad City Using Mathematical Models
...Show More Authors

Total dissolved solids are at the top of the parameters list of water quality that requires investigations for planning and management, especially for irrigation and drinking purposes. If the quality of water is sufficiently predictable, then appropriate management is possible. In the current study, Multiple Linear Regression (MLR) and Artificial Neural Network (ANN) models were used as indicators of water quality and for the prediction of Total Dissolved Solids (TDS) along the Tigris River, in Baghdad city. To build these models five water parameters were selected from the intakes of four water treatment plants on the Tigris River, for the period between 2013 and 2017. The selected water parameters were Total Dissolved Solids (TDS

... Show More
Publication Date
Sun Jan 05 2025
Journal Name
Science Journal Of University Of Zakho
DETECTION AND RECOGNITION OF IRAQI LICENSE PLATES USING CONVOLUTIONAL NEURAL NETWORKS
...Show More Authors

Due to the large population of motorway users in the country of Iraq, various approaches have been adopted to manage queues such as implementation of traffic lights, avoidance of illegal parking, amongst others. However, defaulters are recorded daily, hence the need to develop a mean of identifying these defaulters and bring them to book. This article discusses the development of an approach of recognizing Iraqi licence plates such that defaulters of queue management systems are identified. Multiple agencies worldwide have quickly and widely adopted the recognition of a vehicle license plate technology to expand their ability in investigative and security matters. License plate helps detect the vehicle's information automatically ra

... Show More
View Publication Preview PDF
Crossref
Publication Date
Sun Sep 04 2011
Journal Name
Baghdad Science Journal
The Prediction of the Electromagnetic Properties and the ?(E2/M1) of 110-116Cd-Isotopes in IBM Model
...Show More Authors

The Nuclear structure of 110-116Cd isotopes was studied theoretically in the framework of the interacting boson model of IBM-l and IBM-2. The properties of the lowest mixed symmetry states such as the 1+, 2+ and 3+ levels produced by the IBM-2 model in the vibrational-limit U(5) of Cd - isotopes are studied in details. This analysis shows that the character of mixed symmetry of 2+ is shared between and states in 110-114Cd – isotopes, the large shar goes to s, while in isotope, the state is declared as a mixed symmetry state without sharing. This identification is confirmed by the percentage of F-spin contribution. The electromagnetic properties of E2 and Ml operators were investigated and the results were analyzed. Various

... Show More
View Publication Preview PDF
Crossref
Publication Date
Wed Feb 15 2023
Journal Name
Full Text Book Of Minar Congress 7
EVALUATING THE CHANGE DETECTION OF(NDVI) FOR BABYLON CITY USING REMOTE SENSING AND GIS TECHNIQUES (2015-2020)
...Show More Authors

The normalized difference vegetation index (NDVI) is an effective graphical indicator that can be used to analyze remote sensing measurements using a space platform, in order to investigate the trend of the live green vegetation in the observed target. In this research, the change detection of vegetation in Babylon city was done by tracing the NDVI factor for temporal Landsat satellite images. These images were used and utilized in two different terms: in March 19th in 2015 and March 5th in 2020. The Arc-GIS program ver. 10.7 was adopted to analyze the collected data. The final results indicate a spatial variation in the (NDVI), where it increases from (1666.91 𝑘𝑚2) in 2015 to (1697.01 𝑘𝑚2)) in 2020 between the t

... Show More
View Publication
Crossref
Publication Date
Sat Jan 01 2011
Journal Name
Iraqi Journal Of Physics
Measurement of Background Radioactivity in Baghdad's Main Water Supply Stations: Sediment Samples
...Show More Authors

Sediment samples were collected from main water processing and supply plants in Baghdad, and tested for radioactivity from both natural and artificial sources. These stations are: East Dijla (Tigris), Al-Kadisia, Al-Karama, Al-Rasheed, Al-Sader, Al-Wathba, and Al-Wihda supply stations. Qualitative measurements were made, and the results showed that most sediments exhibited natural radioactive level and sometimes less than the international regular standards. Specially, K-40 and Ra-226 results were much less than the standards for radioactive concentrations. Ac-228 concentration was found rather than Th-232 (in Al-Sader and Al-Wihda samples) but with low concentrations of about 10-15 Bg/kg and detection confidence ~45% , and Ce-141 and Be

... Show More
View Publication Preview PDF
Publication Date
Tue Jan 01 2019
Journal Name
Science International
USING CRYPTOANALYSIS POLICIES AND TECHNIQUES TO CREATE STRONG PASSWORD
...Show More Authors

Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
Mining categorical Covid-19 data using chi-square and logistic regression algorithms
...Show More Authors

View Publication Preview PDF
Scopus (2)
Crossref (1)
Scopus Crossref