Preferred Language
Articles
/
gUITNJsBMeyNPGM3Rdjz
Predicting Potential Salinity in River Water for Irrigation Water Purposes Using Integrative Machine Learning Models
...Show More Authors
ABSTRACT<p>Accurate prediction of river water quality parameters is essential for environmental protection and sustainable agricultural resource management. This study presents a novel framework for estimating potential salinity in river water in arid and semi‐arid regions by integrating a kernel extreme learning machine (KELM) with a boosted salp swarm algorithm based on differential evolution (KELM‐BSSADE). A dataset of 336 samples, including bicarbonate, calcium, pH, total dissolved solids and sodium adsorption ratio, was collected from the Idenak station in Iran and was used for the modelling. Results demonstrated that KELM‐BSSADE outperformed models such as deep random vector functional link (dRVFL), general regression neural network (GRNN), multivariate adaptive regression spline (MARS), online sequential extreme learning machine (OSELM) and extreme gradient boosting decision tree (XGBoost) when compared with observed river salinity data. Also, the KELM‐BSSADE model effectively identified optimal inputs through the Boruta‐XGBoost (B‐XGB) feature selection method. Four metaheuristic‐based KELM models were developed, utilizing grey wolf optimizer, whale optimization, slime mould algorithm and equilibrium optimizer, further illustrating the capability of KELM‐BSSADE in estimating potential salinity in river water. By accurately estimating potential salinity, KELM‐BSSADE can assist in optimizing irrigation practices, ensuring that agricultural demands are met while minimizing the risk of salinity‐related crop damage.</p>
Scopus Clarivate Crossref
View Publication
Publication Date
Tue Oct 01 2019
Journal Name
Poultry Science
Effect of using ionized water on some productive and physiological performance of Japanese quails
...Show More Authors

This study was conducted to explore the effects of using ionized water on the productive and physiological performance of Japanese quails (Coturnix japonica). Our study was conducted at a private farm from 20th April, 2016 to 13th July, 2016 (84 d). One hundred 42-day-old Japanese quail chicks were used, divided randomly into 5 groups with 4 replicates. Treatments consisted in a control group (T1 - normal water:), alkaline (T2 - pH 8 and T3 - pH 9), and acidic water (T4 - pH 6 and T5 - pH 5). All birds were fed a balanced diet of energy and protein. The egg production ratio, egg weight, cumulative number of eggs, egg mass, feed conversion ratio, productivity per hen per week, and effects on plasma lipids, uric acid, glucose, calcium, and ph

... Show More
View Publication
Scopus (5)
Crossref (3)
Scopus Clarivate Crossref
Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
Monitoring the Vegetation and Water Content of Al-Hammar Marsh Using Remote Sensing Techniques
...Show More Authors

The object of the presented study was to monitor the changes that had happened in the main features (water, vegetation, and soil) of Al-Hammar Marsh region. To fulfill this goal, different satellite images had been used in different times, MSS 1973, TM 1990, ETM+ 2000, 2002, and MODIS 2009, 2010. A new technique of the unsupervised classification called (Color Extracting Technique) was used to classify the satellite images. MATLAP programming used the technique and separated Al-Hammar Marsh from other water features (rivers, irrigated lands, etc.) when calculated the changes in the water content of the study region. ArcGIS 9.3 (arcMAP, arcToolbox) were used to achieve this work and calculate area of each class.

View Publication Preview PDF
Crossref (2)
Crossref
Publication Date
Tue Jun 27 2023
Journal Name
Journal Of Global Innovations In Agricultural Sciences
The use of remote sensing technology in defining the water depth in the lakes and water bodies: Western Iraq as a case study
...Show More Authors

The study's primary purpose is to explore an appropriate way of monitoring and assessing water depths using the satellite remote sensing technique of the Al Habbaniyah Lake in Iraq. This research studied the experience-conditions (thresholds) of different bands for multi-temporal satellite image data with different satellite image sensors (Landsat 5-TM, and EO1-ALI) for the same region, to recognize regions of water depths. The threshold values are taken that to separate the Al Habbaniyah Lake to the required depths (shallow, deep, and very deep), as a supervised method. A three-dimension feature space plot had used to represent these regions. The relationship of the mean values of the three separated water regions with all TM and A

... Show More
View Publication
Scopus (1)
Scopus Crossref
Publication Date
Fri Mar 30 2007
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Testing of Drinking Water Reservoirs Coating
...Show More Authors

The present study refers to a ready-made three components epoxy based paint made by the Modern Paints Industries Company (Al-Za'farania, Baghdad) subjected to several tests in order to improve its specifications by optimizing the application conditions. The paint components are under the trade names: Resin (D-5547), Hardener (H-1457) and Thinner (P-851). The paint is used for painting drinking water reservoirs from inside.

View Publication Preview PDF
Publication Date
Wed Aug 17 2022
Journal Name
Applied Sciences
Predicting Fruit’s Sweetness Using Artificial Intelligence—Case Study: Orange
...Show More Authors

The manual classification of oranges according to their ripeness or flavor takes a long time; furthermore, the classification of ripeness or sweetness by the intensity of the fruit’s color is not uniform between fruit varieties. Sweetness and color are important factors in evaluating the fruits, the fruit’s color may affect the perception of its sweetness. This article aims to study the possibility of predicting the sweetness of orange fruits based on artificial intelligence technology by studying the relationship between the RGB values of orange fruits and the sweetness of those fruits by using the Orange data mining tool. The experiment has applied machine learning algorithms to an orange fruit image dataset and performed a co

... Show More
View Publication Preview PDF
Scopus (30)
Crossref (24)
Scopus Clarivate Crossref
Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Post COVID-19 Effect on Medical Staff and Doctors' Productivity Analysed by Machine Learning
...Show More Authors

The COVID-19 pandemic has profoundly affected the healthcare sector and the productivity of medical staff and doctors. This study employs machine learning to analyze the post-COVID-19 impact on the productivity of medical staff and doctors across various specialties. A cross-sectional study was conducted on 960 participants from different specialties between June 1, 2022, and April 5, 2023. The study collected demographic data, including age, gender, and socioeconomic status, as well as information on participants' sleeping habits and any COVID-19 complications they experienced. The findings indicate a significant decline in the productivity of medical staff and doctors, with an average reduction of 23% during the post-COVID-19 period. T

... Show More
View Publication Preview PDF
Scopus (8)
Crossref (13)
Scopus Crossref
Publication Date
Tue Jun 04 2019
Journal Name
Jordan Journal Of Biological Sciences
Differential Expression for Genes in Response to Drought and Salinity in Ruta graveolens Plantlets
...Show More Authors

Abiotic stress-induced genes may lead to understand the response of plants and adaptability to salinity and drought stresses. Differential display reverse transcriptase – polymerase chain reaction (DDRT-PCR) was used to investigate the differences in gene expression between drought- and salinity-stressed plantlets of Ruta graveolens. Direct and stepwise exposures to drought- or salt-responsive genes were screened in R. graveolens plantlets using the DDRT technique. Gene expression was investigated both in the control and in the salt or drought-stressed plantlets and differential banding patterns with different molecular sizes were observed using the primers OPA-01 (646,770 and 983 pb), OPA-08 (593 and 988 pb), OPA-11 (674 and 831 pb

... Show More
Preview PDF
Scopus (4)
Scopus
Publication Date
Tue Dec 30 2014
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Coagulation/ Flocculation, Microfiltration and Nanofiltration for Water Treatment of Main Outfall Drain for Injection in Nasiriyah Oil Field
...Show More Authors

 

The present work aims to study the efficiency of coagulation/ flocculation as 1st stage, natural gravity water filter or microfiltration (MF) as 2nd stage and nanofiltration (NF) technology as final stage for treatment of water of main outfall drain (MOD) for injection in Nasiriyah oil field. Effects of operating parameters such as coagulant dosage, speed and time of slow mixing step and settling time in the 1st stage were studied. Also feed turbidity and total suspended solids (TSS) in the 2

... Show More
View Publication Preview PDF
Publication Date
Wed Feb 22 2023
Journal Name
Iraqi Journal Of Science
Extraction Drainage Network for Lesser Zab River Basin from DEM using Model Builder in GIS
...Show More Authors

ArcHydro is a model developed for building hydrologic information systems to synthesize geospatial and temporal water resources data that support hydrologic modeling and analysis. Raster-based digital elevation models (DEMs) play an important role in distributed hydrologic modeling supported by geographic information systems (GIS). Digital Elevation Model (DEM) data have been used to derive hydrological features, which serve as inputs to various models. Currently, elevation data are available from several major sources and at different spatial resolutions. Detailed delineation of drainage networks is the first step for many natural resource management studies. Compared with interpretation from aerial photographs or topographic maps, auto

... Show More
View Publication Preview PDF
Publication Date
Tue Jan 01 2019
Journal Name
Energy Procedia
Calculation of Salinity and Soil Moisture indices in south of Iraq - Using Satellite Image Data
...Show More Authors

A band rationing method is applied to calculate the salinity index (SI) and Normalized Multi-Band Drought Index (NMDI) as pre-processing to take Agriculture decision in these areas is presented. To separate the land from other features that exist in the scene, the classical classification method (Maximum likelihood classification) is used by classified the study area to multi classes (Healthy vegetation (HV), Grasslands (GL), Water (W), Urban (U), Bare Soil (BS)). A Landsat 8 satellite image of an area in the south of Iraq are used, where the land cover is classified according to indicator ranges for each (SI) and (NMDI).

View Publication
Scopus (10)
Crossref (5)
Scopus Clarivate Crossref