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.
This century is witnessing changes in various fields,which have become a challenge to the enterprises in the contemporary business environment, the most important of which is the importance of measurement and disclosure of the role of knowledge capital in the transition to the knowledge economy, which is no longer the land and labor and physical capital resources the basic. Knowledge-based capital has emerged that provides the enterprise with an area of excellence and enhances its position to achieve competitive advantage. The research tackled the concept, objectives, components and importance of knowledge capital, which is fundamental in knowledge management, creating value added and enhancing competitiveness, as well as an
... Show MoreThe Jeribe reservoir in the Jambour Oil Field is a complex and heterogeneous carbonate reservoir characterized by a wide range of permeability variations. Due to limited availability of core plugs in most wells, it becomes crucial to establish correlations between cored wells and apply them to uncored wells for predicting permeability. In recent years, the Flow Zone Indicator (FZI) approach has gained significant applicability for predicting hydraulic flow units (HFUs) and identifying rock types within the reservoir units.
This paper aims to develop a permeability model based on the principles of the Flow Zone Indicator. Analysis of core permeability versus core porosity plot and Reservoir Quality Index (RQI) - Normalized por
... Show MorePetroleum is one of the most important substances consumed by man at present times, a major energy source in this century, petroleum oils can cause environmental pollution during various stages of production, transportation, refining and use, petroleum hydrocarbons pollutions ranging from soil, ground water to marine environment, become an inevitable problem in the modern life, current study focused on bioremediation process of hydrocarbons contaminants that remaining in the bottom of gas cylinders and discharged to the soil. Twenty-four bacterial isolates were isolated from contaminated soils all of them gram negative bacteria, bacterial isolates screening to investigate the ability of biodegradation of hydrocarbons, these isolates inocula
... Show MoreThe present study has been carried out to estimate heavy metals mobility, bioconcentration and transfer from polluted soil to roots tissues and from roots tissues to aerial parts using bioconcentration factor and translocation factor. Soil samples and the biomass of the eight vegetable species have been collected during summer season, 2019 from four different sites in Wadi Al-Arg, Taif Governorate, KSA. In general, heavy metals content of soil samples in site III and IV have recorded elevated values compared with those of site I and II. The soil from site IV has shown the highest concentration of Mn, Ni, Cr, Pb, Cu, and Cd amounted 31.63, 14.05, 13.56, 22.79, 31.02 and 2.98 mg/kg dry soil respectively, while the soil from site III has sh
... Show MoreIn this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo
... Show MoreThe aim of this paper is to measure the characteristics properties of 3 m radio telescope that installed inside Baghdad University campus. The measurements of this study cover some of the fundamental parameters at 1.42 GHz. These parameters concentrated principally on, the system noise temperature, signal to noise ratio and sensitivity, half power beam width, aperture efficiency, and effective area. These parameters are estimated via different radio sources observation like Cas-A, full moon, sky background, and solar drift scan observations. From the results of these observations, these parameters are found to be approximately 64 K, 1.2, 0.9 Jansky, 3.7°, 0.54, and 3.8 m2 respectively. The parameters values have vital affect to quantitativ
... Show MoreAs tight gas reservoirs (TGRs) become more significant to the future of the gas industry, investigation into the best methods for the evaluation of field performance is critical. While hydraulic fractured well in TRGs are proven to be most viable options for economic recovery of gas, the interpretation of pressure transient or well test data from hydraulic fractured well in TGRs for the accurate estimation of important reservoirs and fracture properties (e.g. fracture length, fracture conductivity, skin and reservoir permeability) is rather very complex and difficult because of the existence of multiple flow profiles/regimes. The flow regimes are complex in TGRs due to the large hydraulic fractures n