Soil pH is one of the main factors to consider before undertaking any agricultural operation. Methods for measuring soil pH vary, but all traditional methods require time, effort, and expertise. This study aimed to determine, predict, and map the spatial distribution of soil pH based on data taken from 50 sites using the Kriging geostatistical tool in ArcGIS as a first step. In the second step, the Support Vector Machines (SVM) machine learning algorithm was used to predict the soil pH based on the CIE-L*a*b values taken from the optical fiber sensor. The standard deviation of the soil pH values was 0.42, which indicates a more reliable measurement and the data distribution is normal. The Kriging method gave a prediction accuracy of 65% while the SVM algorithm gave an accuracy of 80%. The root mean square error (RMSE) was 0.36, 0.16 and the mean absolute error (MAE) was 0.37, 0.13, respectively, for the two methods. These two methods allow the prediction of soil pH and thus the assessment of soils, allowing for easier and more efficient management decisions and sustaining productivity.
Globally, buildings use about 40% of energy. Many elements, such as the physical properties of the structure, the efficiency of the cooling and heating systems, the activity of the occupants, and the building’s sustainability, affect the energy consumption of a building. It is really difficult to predict how much energy a building will need. To improve the building’s sustainability and create sustainable energy sources to reduce carbon dioxide emissions from fossil fuel combustion, estimating the building's energy use is necessary. This paper explains the energy consumed in the lecture building of the Al-Khwarizmi College of Engineering, University of Baghdad (UOB), Baghdad, Iraq. The weather data and the building construction informati
... Show MoreElevated C-Reactive Protein (CRP) level in serum is a risk factor for type 2 diabetes ,this relationship is likely to be the cause it means elevated CRP leads to T2D in future . Our objective was to examine CRP in male Type 2 Diabetes(T2D) patients in different age ,we studied 120 male subjects divided to two groups according to their age. First group A age (31 - 40) year old ,60 person )30 control & 30 T2D patients(,3 person for each same age: second group B age (41 – 50) years old ,60 person )30 control & 30 T2D patients(,3 person for each same age. We examined blood sugar ,cholesterol and CRP in each group. and we toke the mean of samples in the same age in each data in all the 4 groups. Our data shows that CRP
... Show MoreHypertension is a cardiovascular problem with high rates of epidemiology and risks of morbidity and mortality in the global area. Nitric oxide (NO) is one of the reactive oxygen species (ROS) that produced from L-arginine by nitric oxide synthase (NOS) enzyme. NO involves in various vital processes in human health, one of which is the modulation of vasoconstriction and relaxation of the vascular system. We have aimed to investigate the link between NO and NOS with hypertension in women. The relationship between NO and NOS, as well as the usefulness of them as indicators of hypertension risks were subjects of study in this article. The results have revealed that hypertensive women had significant (P<0.05) lower levels of NO (15.07±3.41 IU/m
... Show MoreImage recognition is one of the most important applications of information processing, in this paper; a comparison between 3-level techniques based image recognition has been achieved, using discrete wavelet (DWT) and stationary wavelet transforms (SWT), stationary-stationary-stationary (sss), stationary-stationary-wavelet (ssw), stationary-wavelet-stationary (sws), stationary-wavelet-wavelet (sww), wavelet-stationary- stationary (wss), wavelet-stationary-wavelet (wsw), wavelet-wavelet-stationary (wws) and wavelet-wavelet-wavelet (www). A comparison between these techniques has been implemented. according to the peak signal to noise ratio (PSNR), root mean square error (RMSE), compression ratio (CR) and the coding noise e (n) of each third
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