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Compression Index and Compression Ratio Prediction by Artificial Neural Networks
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Information about soil consolidation is essential in geotechnical design. Because of the time and expense involved in performing consolidation tests, equations are required to estimate compression index from soil index properties. Although many empirical equations concerning soil properties have been proposed, such equations may not be appropriate for local situations. The aim of this study is to investigate the consolidation and physical properties of the cohesive soil. Artificial Neural Network (ANN) has been adapted in this investigation to predict the compression index and compression ratio using basic index properties. One hundred and ninety five consolidation results for soils tested at different construction sites in Baghdad city were used. 70% of these results were used to train the prediction ANN models and the rest were equally divided to test and validate the ANN models. The performance of the developed models was examined using the correlation coefficient R. The final models have demonstrated that the ANN has capability for acceptable prediction of compression index and compression ratio. Two equations were proposed to estimate compression index using the connecting weights algorithm, and good agreements with test results were achieved.

 

 

 

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Publication Date
Tue Jan 01 2019
Journal Name
Indian Journal Of Ecology
Effectiveness of oxidation enzymes in the ratio of gluten to wheat bread via different treatments of weeds control
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Publication Date
Sun Mar 31 2024
Journal Name
Iraqi Geological Journal
Permeability Prediction and Facies Distribution for Yamama Reservoir in Faihaa Oil Field: Role of Machine Learning and Cluster Analysis Approach
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Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F

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Publication Date
Wed Jun 15 2022
Journal Name
Journal Of Baghdad College Of Dentistry
Effect of Artificial Aging Test on PEEK CAD/CAM Fabricated Orthodontic Fixed Lingual Retainer
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Background: The purpose of this study was to evaluate the effect of in vitro long-term simulation of oral conditions on the bond strength of PEEK CAD/CAM lingual retainers.

Material and methods: The sample consisted of 12 PEEK CAD/CAM retainers each composed of 2 centrally perforated 3x4mm pads joined by a connector. They were treated by 98% sulfuric acid for 1 minute and then conditioned with Single Bond Universal and bonded to the lingual surface of premolar teeth by 3M Transbond TM System. Half of the retainers were artificially aged using a 30-day water storage and 5000 thermocycling protocol before bond strength testing to compare with the non-aged specimens.

Results: The artificially aged retainers showed a marginally

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Publication Date
Sat Feb 27 2021
Journal Name
Journal Of Engineering
Using Geographic Information Systems (GIS) Program and Water Quality Index (WQI) to Assess and Manage Groundwater Quality in the City of Baghdad
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Groundwater is an essential source because of its high quality and continuous availability characterize this water resource. Therefore, the study of groundwater has required more attention. The present study aims to assess and manage groundwater quality's suitability for various purposes through the Geographical Information System GIS and the Water Quality Index WQI. The study area is located in the city of Baghdad in central Iraq, with an approximate area of ​​900 , data were collected from the relevant official departments representing the locations of 97 wells of groundwater in the study area for the year 2019, as it included physicochemical parameters such as  pH, EC, TDS, Na, K, Mg, Ca, Cl,  , and &nbs

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
Offline Signature Biometric Verification with Length Normalization using Convolution Neural Network
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Offline handwritten signature is a type of behavioral biometric-based on an image. Its problem is the accuracy of the verification because once an individual signs, he/she seldom signs the same signature. This is referred to as intra-user variability. This research aims to improve the recognition accuracy of the offline signature. The proposed method is presented by using both signature length normalization and histogram orientation gradient (HOG) for the reason of accuracy improving. In terms of verification, a deep-learning technique using a convolution neural network (CNN) is exploited for building the reference model for a future prediction. Experiments are conducted by utilizing 4,000 genuine as well as 2,000 skilled forged signatu

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Publication Date
Sun Apr 08 2018
Journal Name
Al-khwarizmi Engineering Journal
Design of Hybrid Neural Fuzzy Controller for Human Robotic Leg System
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 In this paper, the human robotic leg which can be represented mathematically by single input-single output (SISO) nonlinear differential model with one degree of freedom, is analyzed and then a simple hybrid neural fuzzy controller is designed to improve the performance of this human robotic leg model. This controller consists from SISO fuzzy proportional derivative (FPD) controller with nine rules summing with single node neural integral derivative (NID) controller with nonlinear function. The Matlab simulation results for nonlinear robotic leg model with the suggested controller showed that the efficiency of this controller when compared with the results of the leg model that is controlled by PI+2D, PD+NID, and F

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Publication Date
Fri Apr 28 2023
Journal Name
Mathematical Modelling Of Engineering Problems
Design Optimal Neural Network for Solving Unsteady State Confined Aquifer Problem
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Publication Date
Sun Jan 27 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Waste as a resource of economic resources: A case study using environmentalthe index MIP
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Due to increased consumption of resources, especially energy it was necessary to find alternatives characterized by the same quality as well as being of less expensive, and most important of these alternatives are characterized by waste and the fact that humancannot stop consumption. So we  have consideredwaste as an  alternative and cheap economic resources and by using environmental index the MIP (input materials per unit ,unit / service) is based on the grounds that the product is not the end of itselfit is a product to meet the need  of a product or service, awarded a resource input and output within the five basic elements are the raw materials is ecological, Raw materials ecological, water, air and soil erosion for a

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Publication Date
Sun Dec 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Using Time Series Methods To Modify The Seasonal Variations in the Consumer Price Index
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     As is  known that the consumer price index (CPI) is one of the most important  price indices because of its direct effect on the welfare of the individual and his living.

       We have been address the problem of Strongly  seasonal  commodities in calculating  (CPI) and identifying some of the solution.

   We have  used an actual data  for a set of commodities (including strongly seasonal commodities) to calculate the index price by using (Annual Basket With Carry Forward Prices method) . Although this method can be successfully used in the context of seasonal&nbs

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Publication Date
Wed Jun 09 2021
Journal Name
International Journal Of Environmental Science And Technology
Water quality index toward a reliable assessment for water supply uses: a novel approach
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