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Bayesian Regularized Neural Network Model Development for Predicting Daily Rainfall from Sea Level Pressure Data: Investigation on Solving Complex Hydrology Problem
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Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bayesian regularized neural networks (BRNNs), Bayesian additive regression trees (BART), extreme gradient boosting (xgBoost), and hybrid neural fuzzy inference system (HNFIS) were used considering the complex relationship of rainfall with sea level pressure. Principle components of SLP domain correlated with daily rainfall were used as predictors. The results revealed that the efficacy of AI models is predicting daily rainfall one day before. The relative performance of the models revealed the higher performance of BRNN with normalized root mean square error (NRMSE) of 0.678 compared with HNFIS (NRMSE = 0.708), BART (NRMSE = 0.784), xgBoost (NRMSE = 0.803), and ELM (NRMSE = 0.915). Visual inspection of predicted rainfall during model validation using density-scatter plot and other novel ways of visual comparison revealed the ability of BRNN to predict daily rainfall one day before reliably.

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Publication Date
Fri Feb 28 2025
Journal Name
International Journal Of Intelligent Engineering And Systems
MCNet: Mask Cell of Multi Class Deep Network for Blood Cells Detection and Classification
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Physicians are likely to expend significant labor and time while manually calculating blood smears. Automatic computer-based methods for classifying acute lymphoblastic leukemia have trouble correctly lighting stained white blood cell microscopy images and accurately separating cells that touch or overlap. Additionally, incorporating machine learning techniques into medical services is very hard because doctors can deal with rough guesses as long as the results aren't too bad, but they can't use these calculations for actual medical care. Enabling a A deep network having knowledge of the accuracy of its own predictions is a fascinating and crucial issue. Most instances segmentation frameworks weigh the mask quality during the instance

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Publication Date
Wed Jan 01 2020
Journal Name
International Conference Of Numerical Analysis And Applied Mathematics Icnaam 2019
Functionalized multi-walled carbon nanotubes network sensor for NO2 gas detection at room temperature
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Publication Date
Thu Nov 02 2023
Journal Name
Journal Of Engineering
Prediction Unconfined Compressive Strength for Different Lithology Using Various Wireline Type and Core Data for Southern Iraqi Field
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Unconfined Compressive Strength is considered the most important parameter of rock strength properties affecting the rock failure criteria.  Various research have developed rock strength for specific lithology to estimate high-accuracy value without a core.  Previous analyses did not account for the formation's numerous lithologies and interbedded layers. The main aim of the present study is to select the suitable correlation to predict the UCS for hole depth of formation without separating the lithology. Furthermore, the second aim is to detect an adequate input parameter among set wireline to determine the UCS by using data of three wells along ten formations (Tanuma, Khasib, Mishrif, Rumaila, Ahmady, Maudud, Nahr Um

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Publication Date
Wed Dec 13 2017
Journal Name
Al-khwarizmi Engineering Journal
Performance Comparison of Different Advanced Control Schemes for Glucose Level Control under Disturbing Meal
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Abstract

In this work, diabetic glucose concentration level control under disturbing meal has been controlled using two set of advanced controllers. The first set is sliding mode controllers (classical and integral) and the second set is represented by optimal LQR controllers (classical and Min-, ax). Due to their characteristic features of disturbance rejection, both integral sliding mode controller and LQR Minmax controller are dedicated here for comparison. The Bergman minimal mathematical model was used to represent the dynamic behavior of a diabetic patient’s blood glucose concentration to the insulin injection. Simulations based on Matlab/Simulink, were performed to verify the performance of each controll

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Publication Date
Mon Feb 04 2019
Journal Name
Journal Of The College Of Education For Women
Most preference colours for Iraqi Femal clothes in university level and theire psychology efect
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Colour is part of human environ ment and is present almost every
where in cluding clothes.
Clours have positive and negative effects on the person's psychology.
Thus we can ask the following question: what are the clours preffered
by the Iraqi females in the university level and what is the lightness and purity
of these colours and their effect on their psychology?
In this research we included 563 Baghdad university female student for
the year 2005-2006.
The question are included anumber of qnestions that gave answers to
the research main objectives.

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Publication Date
Mon Mar 12 2018
Journal Name
Arabian Journal For Science And Engineering
Estimate Level of Radon Concentration for Drinking Water in Some Regions of Baghdad City
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Publication Date
Sun Dec 06 2009
Journal Name
Baghdad Science Journal
Effect of salinity on survival, development and growth of Artemia sp.
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This study aimed to determine the possibility of culturing genus Artemia in under laboratory conditions for locally culturing and producing. Different salinity concentrations were used, ranging from 5-40g/l . the results showed that the concentration 30g/l is the best for hatching. This concentration recorded hatching efficiency of 68800 nauplii/g cysts and hatching percentage of 45.86%, while the concentration 5g/l recorded less hatching efficiency and hatching percentage of 20266 nauplii/g and 13.5% respectively . Investigating the effect of salinity on individuals survival and growth using saline concentrations ranging from 30to 100g/l, revealed that the best percentage was 75.00% in the first week with 70g/l, whilst the best rates of

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Publication Date
Sat Feb 01 2020
Journal Name
Alexandria Engineering Journal
Impact of development on Baghdad’s urban microclimate and human thermal comfort
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Publication Date
Sat Jan 05 2019
Journal Name
Iraqi Journal Of Physics
The Influence of RF power, pressure and substrate temperature on optical properties of RF Sputtered vanadium pentoxide thin films
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The V2O5 films were deposited on glass substrates which produce using "radio frequency (RF)"power supply and Argon gas technique. The optical properties were investigated by, UV spectroscopy at "radio frequency" (RF) power ranging from 75 - 150 Watt and gas pressure, (0.03, 0.05 and 0.007 Torr), and substrate temperature (359, 373,473 and 573) K. The UV-Visible analysis shows that the average transmittance of all films in the range 40-65 %. When the thickness has been increased the transhumance was decreased from (65-40) %. The values of energy band gap were lowered from (3.02-2.9 eV) with the increase of thickness the films in relation to an increase in power, The energy gap decreased (2.8 - 2.7) eV with an increase in the pressure and

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Publication Date
Wed Jan 01 2020
Journal Name
Spe Asia Pacific Oil & Gas Conference And Exhibition
Effect of nanoparticles on the interfacial tension of CO2-oil system at high pressure and temperature: An experimental approach
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In the recent decade, injection of nanoparticles (NPs) into underground formation as liquid nanodispersions has been suggested as a smart alternative for conventional methods in tertiary oil recovery projects from mature oil reservoirs. Such reservoirs, however, are strong candidates for carbon geo-sequestration (CGS) projects, and the presence of nanoparticles (NPs) after nanofluid-flooding can add more complexity to carbon geo-storage projects. Despite studies investigating CO2 injection and nanofluid-flooding for EOR projects, no information was reported about the potential synergistic effects of CO2 and NPs on enhanced oil recovery (EOR) and CGS concerning the interfacial tension (γ) of CO2-oil system. This study thus extensively inves

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