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.
This research was designed to investigate the factors affecting the frequency of use of ride-hailing in a fast-growing metropolitan region in Southeast Asia, Kuala Lumpur. An intercept survey was used to conduct this study in three potential locations that were acknowledged by one of the most famous ride-hailing companies in Kuala Lumpur. This study used non-parametric and machine learning techniques to analyze the data, including the Pearson chi-square test and Bayesian Network. From 38 statements (input variables), the Pearson chi-square test identified 14 variables as the most important. These variables were used as predictors in developing a BN model that predicts the probability of weekly usage frequency of ride-hai
... Show MoreBackground: The main purpose of this study is to find if there is any correlation between the level of C-reactive protein (CRP) in gingival crevicular fluid with its serum level in chronic periodontitis patients and to explore the differences between them according to the probing depth. Materials and methods: Forty seven male subjects enrolled in this study. Thirty males with chronic periodontitis considered as study group whom further subdivided according to probing depth into subgroup 1 with pocket depth ≤6mm, subgroup 2 with pocket depth >6mm. The other 17 subjects considered as controls. For all subjects, clinical examination where done for periodontal parameters plaque index (PLI), gingival index (GI), bleeding on probing (BOP),
... Show MoreThe present work deals with the performance of screw piles constructed in gypseous soil of medium relative density; such piles are extensively used in piles foundations supported structures subjected to axial forces. The carrying capacity and settlement of a single screw pile model of several diameters (20, 30, and 40) mm inserted in gypseous soil is investigated in the present study. The gypsum content of soil used in tests was 40%. The bedding soil used in tests was prepared by raining technique with a relative density of 40%. A physical model was manufactured to demonstrate the tests in the laboratory. The model of screw pile has been manufactured of steel with a total length of 50
Soil is a crucial component of environment. Total soil analysis may give information about possible enrichment of the soil with heavy metals. Heavy metals, potentially contaminate soils, may have been dumped on the ground. chromium, nickel and cadmium,
The study area soils suffer from several problems appear as tkhesvat and cracks in the roads and waterlogging which reduces the susceptibility of soil to withstand pressure, this study was conducted on the soil of the Karkh district based on field study that included (6) samples of soil physical analyses contain different ratios of (mud, sand, silt) as percentages (52%, 45%, 3 #) respectively, and liquidity limit rate (39%) Stroke rate plasticity was (20.6%) The rate coefficient of plasticity total (19.2%)0
Collapsible soil has a metastable structure that experiences a large reduction in volume or collapse when wetting. The characteristics of collapsible soil contribute to different problems for infrastructures constructed on its such as cracks and excessive settlement found in buildings, railways channels, bridges, and roads. This paper aims to provide an art review on collapse soil behavior all over the world, type of collapse soil, identification of collapse potential, and factors that affect collapsibility soil. As urban grow in several parts of the world, the collapsible soil will have more get to the water. As a result, there will be an increase in the number of wetting collapse problems, so it's very important to com
... Show MoreBackground: This study evaluated the influence of different fiber formulations incorporation in resin composite on cuspal deflection (CD) of endodontically-treated teeth with mesio-occluso-distal (MOD) cavities. Materials and Methods: Thirty-two freshly extracted maxillary premolar teeth received MOD cavity preparation followed by endodontic treatment using single cone obturation technique, and divided into: Group I: direct composite resin only using a centripetal technique, Group II: direct composite resin with short fiber-reinforced composite (everX Flow), Group III: direct composite resin with leno wave ultra-high molecular weight polyethylene (LWUHMWPE) fibers placed on the cavity floor, and Group IV: direct composite resin with LWUHMWP
... Show MoreTwelve pends were selected and distributed on three verticals transects paths on the Tigers river in Al Rasheed county.Passing through land covers, that classified and covers the whole region. Based on the 8 Landsat of the year 2015. It was oriental classified by using Erdas 10.2 . The pedons were distributed on the area of each varicty of these classes. the series of soil according of the transect series (DW74,MMg,DMu6 , Df96) respectively were represented P1 , P2 , P3 , P4 .
The second transits series(DM97,MM5,DM96,DF115) respectively were represented P5 , P6 , P7 , P8 .The third transits series(DM46,MMg,MF12,MM11) re
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