Soil that has been contaminated by heavy metals is a serious environmental problem. A different approach for forecasting a variety of soil physical parameters is reflected spectroscopy is a low-cost, quick, and repeatable analytical method. The objectives of this paper are to predict heavy metal (Ti, Cr, Sr, Fe, Zn, Cu and Pb) soil contamination in central and southern Iraq using spectroscopy data. An XRF was used to quantify the levels of heavy metals in a total of 53 soil samples from Baghdad and ThiQar, and a spectrogram was used to examine how well spectral data might predict the presence of heavy metals metals. The partial least squares regression PLSR models performed well in predicting the Sr and Cr elements using spectroscopy, with coefficients R2 = 0.73 and RMSE = 63.8 for the determination, and R2 = 0.60 and RMSE = 16.4 for Cr, respectively. This research validates the detection of heavy metal contamination using reflectance spectroscopy. Results of the current study proved that some heavy elements have spectral features become either when their concentrations low or high, such as Cr, Sr, Cu and Zn. The current study opens new possibilities for studying these elements using remote sensing in the future.
Water has a great self-generating capacity that can neutralize the polluting interventions carried out by humans. However, if human activities continue this uncontrolled and unsustainable exploitation of this resource, this regenerating capacity shall fail and it will be jeopardized definitively. Shatt Al-Arab River in South of Iraq. It has an active role in providing water for irrigation, industry, domestic use and a commercial gateway to Iraq. in the last five years Shatt Al-Arab suffered from a rise in pollutants due to the severe decline in sewage networks, irregular networks and pesticide products, as well as the outputs of factories and companies that find their way to water sou
Water has a great self-generating capacity that can neutralize the polluting interventions carried out by humans. However, if human activities continue this uncontrolled and unsustainable exploitation of this resource, this regenerating capacity shall fail and it will be jeopardized definitively. Shatt Al-Arab River in South of Iraq. It has an active role in providing water for irrigation, industry, domestic use and a commercial gateway to Iraq. in the last five years Shatt Al-Arab suffered from a rise in pollutants due to the severe decline in sewage networks, irregular networks and pesticide products, as well as the outputs of factories and companies that find their way to water sources and lead to a widespread collapse of water quality.
... Show MoreThis study focused on spectral clustering (SC) and three-constraint affinity matrix spectral clustering (3CAM-SC) to determine the number of clusters and the membership of the clusters of the COST 2100 channel model (C2CM) multipath dataset simultaneously. Various multipath clustering approaches solve only the number of clusters without taking into consideration the membership of clusters. The problem of giving only the number of clusters is that there is no assurance that the membership of the multipath clusters is accurate even though the number of clusters is correct. SC and 3CAM-SC aimed to solve this problem by determining the membership of the clusters. The cluster and the cluster count were then computed through the cluster-wise J
... Show MoreEach educational system aims at having an effective way of
teaching that leads to an effective learing.This needs preparing good inputs in their standard qualifications and good effective ways in the phae of processes during which reliable and valid methods and technjqucs of teaching are used.
Instructional techniques have gained, lately, an increasing and
great attention of educationists because of their many techniques arc Frcinet's which they can be applied in our cducutional institution (schools, institutes and colleges),after giving a brief profile of Frcint
and his educa tiona! ideas and his innovations in the field of
instructional techniques.<
... Show MoreWaters of some wells at Almuqdadea region Diyala province, east of Iraq have been
compared with wells at Alfalluja region, Alanbar province west of Iraq. Five wells were
selected randomly at each of the two regions to measure several factors represented by
temperature (C), P
H
, Electric Conductivity (EC), Sodium (Na),Calcium (Ca), Magnesium
(Mg),Total Hardness (TH), Carbonate (Co3),Chloride (Cl), Nitrite (NO2), Nitrate (NO3)
Phosphate (PO4) Sulfate (So4), in addition to the heavy metals such as Chromium (Cr),
Cadmium (Cd) Lead (Pb) & Iron (Fe). The mean concentration of the above factors in water
of wells at the above regions had been measured during the period from April to September
(2010).
Green areas are an essential component of city planning, as they serve as an outlet for them to spend their free time, in addition to the environmental role that these green areas play in improving the city’s climate by purifying the air and beautifying the city. The study’s problem is summarized in identifying the appropriateness of the current spatial distribution of green areas in the city of Najaf with the current population densities and the pattern in which green areas are distributed using GIS and knowing the per capita share of those green areas in the city, the research assumes that the inconsistency of spaces between regions Green and residential neighbourhoods need to c
Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Tre
... Show MoreMany academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Deci
... Show MoreThe 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
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