FG Mohammed, HM Al-Dabbas, Science International, 2018 - Cited by 2

Corona Virus Disease-2019 (COVID-19) is a novel virus belongs to the corona virus's family. It spreads very quickly and causes many deaths around the world. The early diagnosis of the disease can help in providing the proper therapy and saving the humans' life. However, it founded that the diagnosis of chest radiography can give an indicator of coronavirus. Thus, a Corner-based Weber Local Descriptor (CWLD) for COVID-19 diagnostics based on chest X-Ray image analysis is presented in this article. The histogram of Weber differential excitation and gradient orientation of the local regions surrounding points of interest are proposed to represent the patterns of the chest X-Ray image. Support Vector Machine (SVM) and Deep Belief Network (DBN)

A system was used to detect injuries in plant leaves by combining machine learning and the principles of image processing. A small agricultural robot was implemented for fine spraying by identifying infected leaves using image processing technology with four different forward speeds (35, 46, 63 and 80 cm/s). The results revealed that increasing the speed of the agricultural robot led to a decrease in the mount of supplements spraying and a detection percentage of infected plants. They also revealed a decrease in the percentage of supplements spraying by 46.89, 52.94, 63.07 and 76% with different forward speeds compared to the traditional method.

A band rationing method is applied to calculate the salinity index (SI) and Normalized Multi-Band Drought Index (NMDI) as pre-processing to take Agriculture decision in these areas is presented. To separate the land from other features that exist in the scene, the classical classification method (Maximum likelihood classification) is used by classified the study area to multi classes (Healthy vegetation (HV), Grasslands (GL), Water (W), Urban (U), Bare Soil (BS)). A Landsat 8 satellite image of an area in the south of Iraq are used, where the land cover is classified according to indicator ranges for each (SI) and (NMDI).

Gray-Scale Image Brightness/Contrast Enhancement with Multi-Model
Histogram linear Contrast Stretching (MMHLCS) method

An environmentally friendly technique was used to prepare titanium dioxide@ silver (core shell) (TiO₂@Ag NPs) using chard leaf extract, a natural stabilizer and reductant. A nanocomposite (NCs) of TiO₂@Ag supported by halloysite nanotubes (HNTs), TiO2@Ag/HNT NCs, was prepared under microwave irradiation. The microwave technique is used to accelerate the reaction and enhance the homogeneity of nanoparticle distribution. Spectroscopic and structural analyses were performed on the resulting nanocomposite. X-ray diffraction (XRD) revealed a clear crystalline structure with grain sizes ranging from 7 to 15 nm, with an average of ~11 nm, the transmission electron microscope (TEM) revealed that the size of nanoparticles in the TiO₂@Ag/HNT N