The accurate extracting, studying, and analyzing of drainage basin morphometric aspects is important for the accurate determination of environmental factors that formed them, such as climate, tectonic activity, region lithology, and land covering vegetation.

This work was divided into three stages; the 1^st stage was delineation of the Al-Abiadh basin borders using a new approach that depends on three-dimensional modeling of the studied region and a drainage network pattern extraction using (Shuttle Radar Topographic Mission) data, the 2^nd was the classification of the Al-Abiadh basin streams according to their shape and widenings, and the 3^rd was ex

The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow

In this work, solid random gain media were fabricated from laser dye solutions containing nanoparticles as scattering centers. Two different rhodamine dyes (123 and 6G) were used to host the highly-pure titanium dioxide nanoparticles to form the random gain media. The spectroscopic characteristics (mainly fluorescence) of these media were determined and studied. These random gain media showed laser emission in the visible region of electromagnetic spectrum. Fluorescence characteristics can be controlled to few nanometers by adjusting the characteristics of the host and nanoparticles as well as the preparation conditions of the samples. Emission of narrow linewidth (3nm) and high intensity in the visible region (533-537nm) was obtained.

A study were conducted to examinate the effect of organic and aqueous (Hot, Cold) Extracts from leaves of Duranta repens on the growth and activities of the following types of Bacteria:- Staphylococcus aureus,Streptococcus pyogens ,Escherichia coli,Klebsilla pneumonia, in addition to the yeast Candida albicans and the fungi Aspergullis niger ,Aspergulls flavus.The result showed that gram Positive Bacteria is more sensitive to the extracts than gram negative bacteria with Minimum inhibitory concentration (MIC) value (50,25,50,100)% and Minimum Bactericidal Concentration (MBC) value (100,50,200,100)% for all types Bacteria respectively . The most active extract against A.niger ,A,flavus was cold and hot aqueous extract from the leaves with d

Various Hall Effects have been successfully observed in samples of n-type indium antimonide with values for conductivity, energy gap, Hall mobility and Hall coefficient all agreeing with theory. A particular interest in developing a method for obtaining accurate values of carrier concentrations in semiconductor samples has been fulfilled with an experimental result of (1.6×1016 cm-3 ±10.7%) giving a percentage difference of (6.7%) to a quoted value of (1.5×1016cm-3) at (77K) using an (80mW C.W. CO2) laser beam at (10.6μm) to illuminate a similar sample of n-type indium antimonide, an "Optical" Hall effect has been observed. Although some doubt has been raised as to the validity of effect i.e. "thermal" rather than "Optical", values o

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Support vector machines (SVMs) are supervised learning models that analyze data for classification or regression. For classification, SVM is widely used by selecting an optimal hyperplane that separates two classes. SVM has very good accuracy and extremally robust comparing with some other classification methods such as logistics linear regression, random forest, k-nearest neighbor and naïve model. However, working with large datasets can cause many problems such as time-consuming and inefficient results. In this paper, the SVM has been modified by using a stochastic Gradient descent process. The modified method, stochastic gradient descent SVM (SGD-SVM), checked by using two simulation datasets. Since the classification of different ca

 

The problem of independent motion control of mobile robot (МR) in conditions when unforeseen changes of conditions of interaction of wheels with a surface are considered. An example of such changes can be sudden entrance МR a slippery surface. The deployment of an autonomous unmanned ground vehicle for field applications provides the means by which the risk to personnel can be minimized and operational capabilities improved. In rough terrain, it is critical for mobile robots to maintain good wheel traction. Wheel slip could cause the rover to lose control and become trapped. This paper describes the application of fuzzy control to a feedback system within slippery environment. The study is conducted on an example of М