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.
A total of 200 samples (180 fecal materials and 20 organ samples) were collected from (5 different poultry farms, 10 local poultry shops, 5 houses poultry, 5 Eggs stores shops and 5hand slaughters centers) in Ibb city, Yemen, 2014. According to morphological, cultural, as well as biochemical characterization and serological tests, 59(29.5%) isolates were identified as Salmonella spp. and all Salmonella isolates were categorized by serotype, which comprised of, 37(62.71%) Salmonella Typhimurium serovar, 21(35.59%). Salmonella Enteritidis serovar and 1(1.69%) Salmonella Heidlberg serovar. Antibiotic sensitivity test was done for bacterial isolates and the results showed there were clear differences in antibiotic resistant. Antimicrobial
... Show MoreHealthcare professionals routinely use audio signals, generated by the human body, to help diagnose disease or assess its progression. With new technologies, it is now possible to collect human-generated sounds, such as coughing. Audio-based machine learning technologies can be adopted for automatic analysis of collected data. Valuable and rich information can be obtained from the cough signal and extracting effective characteristics from a finite duration time interval that changes as a function of time. This article presents a proposed approach to the detection and diagnosis of COVID-19 through the processing of cough collected from patients suffering from the most common symptoms of this pandemic. The proposed method is based on adopt
... Show MoreThe experiment was conducted in Al- Mahaweel Research Station in Babel Governorate, Ministry of Agriculture during autumn season 2016-2017 to determine the role of irrigation management processes and micronutrient fertilization in growth and productivity of two varieties of wheat IPA 99 and Al-Rasheed 22 in clay loam soil classified as Typic Torriflovent. The experiment included four irrigation treatments and six fertilization treatments. The experiment was designed under randomized complete block design (RCBD) with three replications. Wheat grain IPA 99 and Al-Rasheed 22 varieties were planted in 23/11/2016 and harvested in 13/5/2017. The amount and periods of irrigation depended on sensors reading of volumetric water content was measured
... Show MoreThe experiment was conducted to study the effect of leaves extract of Salvia sclarea , Rosmarinus officinalis and Thymus vulgaris with 10% and 30% concentration on germination of seeds and growth of seedlings . The effect of these extracts on infection percentage of seeds decay and surface growth of Rhizoctonia solani . The results showed that the three extracts effected significantly to reduced percentage of seeds germination, acceleration of germination , promoter indicator , infection percentage of seeds decay and surface growth of R. solani especially in 30% concentration .
Nano TiO2 thin films on glass substrates were prepared at a constant temperature of (373 K) and base vacuum (10-3 mbar), by pulsed laser deposition (PLD) using Nd:YAG laser at 1064 nm wavelength. The effects of different laser energies between (700-1000)mJ on the properties of TiO2 films was investigated. TiO2 thin films were characterized by X-ray diffraction (XRD) measurements have shown that the polycrystalline TiO2 prepared at laser energy 1000 mJ. Preparation also includes optical transmittance and absorption measurements as well as measuring the uniformity of the surface of these films. Optimum parameters have been identified for the growth of high-quality TiO2 films
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