Soil compaction is one of the most harmful elements affecting soil structure, limiting plant growth and agricultural productivity. It is crucial to assess the degree of soil penetration resistance to discover solutions to the harmful consequences of compaction. In order to obtain the appropriate value, using soil cone penetration requires time and labor-intensive measurements. Currently, satellite technologies, electronic measurement control systems, and computer software help to measure soil penetration resistance quickly and easily within the precision agriculture applications approach. The quantitative relationships between soil properties and the factors affecting their diversity contribute to digital soil mapping. Digital soil maps use machine learning algorithms to determine the above relationship. Algorithms include multiple linear regression (MLR), k-nearest neighbors (KNN), support vector regression (SVR), cubist, random forest (RF), and artificial neural networks (ANN). Machine learning made it possible to predict soil penetration resistance from huge sets of environmental data obtained from onboard sensors on satellites and other sources to produce digital soil maps based on classification and slope, but whose output must be verified if they are to be trusted. This review presents soil penetration resistance measurement systems, new technological developments in measurement systems, and the contribution of precision agriculture techniques and machine learning algorithms to soil penetration resistance measurement and prediction.
Crime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or livin
... Show MoreThis study has been undertaken to investigate the mineralogical properties and morphological features of sand fraction in some soils of Baghdad / Iraq.The morphological features of sand fractions were studied by Polarized optical microscope. Results have shown that the grains of these minerals from samples of sands have different colors, those from the surface horizons have dark brownish spots, due to staining by organic matter, and have a yellowish– to yellowish brown spots due to accumulation of Iron oxides.Results of light minerals indicated that quartz is dominant due to effect of parent material of these soils. Two types of opaque minerals (black and brown) are found, whereas t
This study has contributed to identify convenience of the land Usifiya of Mahmudiya district baghdad province for the cultivation of sensitive and salt resisting crops and growing pasture .The nine pedons (tracks) of the study have spread over three transects to cover the whole area the north, middle and south .
Depending on Visual Space tupe (TM) for 2007 which is super classified, samples are distributed on all classes of land cover
It is detected the presence of nine series soils namely
MM5- MW96- DM 115 for 1st transect
MF12- DM46 - DM96 for 2nd transect
DM56- DF56 - MW5 for 3rd transect
Soils are classified to the level of sub great group according to (soil Survey Staff) to :
*Typic Torri Fluvents , Typic Haplos
In the present work, radon gas concentrations in different surface soil samples in Baghdad governorate were measured using RAD-7 detector. The results have been shown that, the Radon gas concentrations ranged between (41.67±1.78Bq/m3), to (185.67±4.22Bq/m3), a map showing the distribution of the concentration of radon in selected areas was defined to identify areas with high pollution level. The reason for the high concentration of radon is that these surface soil samples are taken from agricultural areas. It is also known that fertilizers contain uranium levels as well as areas bombed in wars in the country. It is worth noting that all radon concentrations in Baghdad governorate are below the recommended minimum of 200-300Bq/m3) (Inte
... Show MoreSoftware-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
... Show MoreIn this study the simple pullout concrete cylinder specimen reinforced by a single steel bar was analyzed for bond-slip behavior. Three-dimension nonlinear finite element model using ANSYS program was employed to study the behavior of bond between concrete and plain steel reinforcement. The ANSYS model includes eight-noded isoperimetric brick element (SOLID65) to model the concrete cylinder while the steel reinforcing bar was modeled as a truss member (LINK8). Interface element (CONTAC52) was used in this analysis to model the bond between concrete and steel bar. Material nonlinearity due to cracking and/or crushing of concrete, and yielding of the steel reinforcing bar were taken into consideration during the analysis. The accuracy of this
... Show MoreThis study aims to model the flank wear prediction equation in metal cutting, depending on the workpiece material properties and almost cutting conditions. A new method of energy transferred solution between the cutting tool and workpiece was introduced through the flow stress of chip formation by using the Johnson-Cook model. To investigate this model, an orthogonal cutting test coupled with finite element analysis was carried out to solve this model and finding a wear coefficient of cutting 6061-T6 aluminum and the given carbide tool.
Electrical Discharge Machining (EDM) is a non-traditional cutting technique for metals removing which is relied upon the basic fact that negligible tool force is produced during the machining process. Also, electrical discharge machining is used in manufacturing very hard materials that are electrically conductive. Regarding the electrical discharge machining procedure, the most significant factor of the cutting parameter is the surface roughness (Ra). Conventional try and error method is time consuming as well as high cost. The purpose of the present research is to develop a mathematical model using response graph modeling (RGM). The impact of various parameters such as (current, pulsation on time and pulsation off time) are studied on
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