Three Seismic Attributes are used to enhance or delineate geologic feature that cannot be detected within seismic resolution limit. These are Instantaneous Amplitude, Instantaneous Phase and Instantaneous Frequency Attributes. These are applied along two defined picked surface horizons within 3D seismic data for an area in southern Iraq. Two geologic features are deduced, the first represents complex channel system at the top of Saadi Formation and the second represents submarine fan within Mishrif Formation. The semblances of these ancient geological features are dramatically enhanced by using flattening technique.
Uranium concentration and the annual committed effective dose in some selected medicinal plants commonly used in Iraq have been determined using fission tracks technique etch in twelve medical plants samples using CR-39 track detector. The results show that the uranium concentration ranged from 0.044±0.021 ppm in Thyme sample to 0.2±0.03 ppm in Black Pepper and Cardamom samples with an average value of 0.14 ±0.0 4ppm. The average annual effective dose due to ingestion of uranium radionuclide was 13.77x10 -5 mSv/y, which is below the world average annual committed effective dose of 0.3 mSv/y for ingestion of natural radionuclides.
The diseases presence in various species of fruits are the crucial parameter of economic composition and degradation of the cultivation industry around the world. The proposed pear fruit disease identification neural network (PFDINN) frame-work to identify three types of pear diseases was presented in this work. The major phases of the presented frame-work were as the following: (1) the infected area in the pear fruit was detected by using the algorithm of K-means clustering. (2) hybrid statistical features were computed over the segmented pear image and combined to form one descriptor. (3) Feed forward neural network (FFNN), which depends on three learning algorithms of back propagation (BP) training, namely Sca
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