Ground-based active optical sensors (GBAOS) have been successfully used in agriculture to predict crop yield potential (YP) early in the season and to improvise N rates for optimal crop yield. However, the models were found weak or inconsistent due to environmental variation especially rainfall. The objectives of the study were to evaluate if GBAOS could predict YP across multiple locations, soil types, cultivation systems, and rainfall differences. This study was carried from 2011 to 2013 on corn (Zea mays L.) in North Dakota, and in 2017 in potatoes in Maine. Six N rates were used on 50 sites in North Dakota and 12 N rates on two sites, one dryland and one irrigated, in Maine. Two active GBAOS used for this study were GreenSeeker and Holland Scientific Crop Circle Sensor ACS 470 (HSCCACS-470) and 430 (HSCCACS-430). Rainfall data, with or without including crop height, improved the YP models in term of reliability and consistency. The polynomial model was relatively better compared to the exponential model. A significant difference in the relationship between sensor reading multiplied by rainfall data and crop yield was observed in terms of soil type, clay and medium textured, and cultivation system, conventional and no-till, respectively, in the North Dakota corn study. The two potato sites in Maine, irrigated and dryland, performed differently in terms of total yield and rainfall data helped to improve sensor YP models. In conclusion, this study strongly advocates the use of rainfall data while using sensor-based N calculator algorithms.
In this work, we have investigated optical properties of the thermally evaporation PbS/CdS thin films. The optical constant such as (refractive index n, dielectric constant εi,r and Extinction coefficient κ) of the deposition films were obtained from the analysis of the experimental recorded transmittance spectral data. The optical band gap of PbS/CdS films is calculate from (αhυ)1/2 vs. photon energy curve.
NiO0.99Cu0.01 films have been deposited using thermal evaporation
technique on glass substrates under vacuum 10-5mbar. The thickness
of the films was 220nm. The as -deposited films were annealed to
different annealing temperatures (373, 423, and 473) K under
vacuum 10-3mbar for 1 h. The structural properties of the films were
examined using X-ray diffraction (XRD). The results show that no
clear diffraction peaks in the range 2θ= (20-50)o for the as deposited
films. On the other hand, by annealing the films to 423K in vacuum
for 1 h, a weak reflection peak attributable to cubic NiO was
detected. On heating the films at 473K for 1 h, this peak was
observed to be stronger. The most intense peak is at 2θ = 37
Chlorine doped SnS have been prepared utilizing chemical spray pyrolysis. The effects of chlorine concentration on the optical constants were studied. It was seen that the transmittance decreased with doping, while reflectance, refractive index, extinction coefficient, real and imaginary parts of dielectric constant were increased as the doping percentage increased. The results show also that the skin depth decrease as the chlorine percentage increased which could be assure that it is transmittance related.
In this research, a sensor for chemical solutions was designed and formed using optical fiber-based on a surface Plasmon resonance technology. A single-mode optical fiber with three different diameters (25, 45 and 65) µm was used, respectively. The second layer of the low refractive fiber was replaced by gold, which was electrically deposited at 40 µm thickness. For each of the three types of optical fiber, different saline concentrations (different index of refraction) were used to evaluate the performance of the refractive index sensor (chemical sensor) by measuring its sensitivity and resolutions. The highest values we could get for these two parameters were 240mm/RIU, and 6*10-5 RIU respectively, when the diameter of a
... Show MoreThis research aims to clarify the importance of an accounting information system that uses artificial intelligence to detect earnings manipulation. The research problem stems from the widespread manipulation of earning in economic entities, especially at the local level, exacerbated by the high financial and administrative corruption rates in Iraq due to fraudulent accounting practices. Since earning manipulation involves intentional fraudulent acts, it is necessary to implement preventive measures to detect and deter such practices. The main hypothesis of the research assumes that an accounting information system based on artificial intelligence cannot effectively detect the manipulation of profits in Iraqi economic entities. The researche
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