Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp

Abstract. This study presents experimental and numerical investigation on the effectiveness of electrode geometry on flushing and debris removal in Electrical Discharge Drilling (EDD) process. A new electrode geometry, namely side-cut electrode, was designed and manufactured based on circular electrode geometry. Several drilling operations were performed on stainless steel 304 using rotary tubular electrodes with circular and side-cut geometries. Drilling performance was characterized by Material Removal Rate (MRR), Electrode Wear Rate (EWR), and Tool Wear Ratio (TWR). Dimensional features and surface quality of drilled holes were evaluated based on Overcut (OC), Hole Depth (HD), and Surface Roughness (SR). Three-dimensional

Three scolopacids out of 150 are found infected with Haemoproteus scolopaci Galli-
Valerio 1929 and H. tringae n. sp. A detailed description of the new taxon is presented along
with a comparison of the diagnostic measurements between the two species.

Natural polymers are often non-toxic, biodegradable, biocompatible, and safe. A novel ligand was synthesized as a natural polymer using chitosan and oleander plant extract [(2R,3S,4R,5S)-5-(acetoxyamino)-4-hydroxy-3,6-dimethoxytetrahydro-2H-pyran-2-yl) methyl (16R)-3-(((2S,4S,5R)-4-methoxy-2,5-dimethyltetrahydro-2H-pyran-2-yl)oxy-10,13,16-trimethyl-17-(5-oxo-2,5-dihydrofuran-3-yl) hexadecahydro-14H-cyclopenta [a] phenanthren-14-yl) phthalate] (Chitosan-Ph-Oleander). This ligand and its complexes with several metals (Cr+3, Mn+2, Fe+3, Ni+2, Cu+2, Zn+2) were characterized using FTIR, UV-visible and 1H-NMR spectroscopy, as well as by molar conductivity, magnetic moment, and TGA analysis. The biological activity for the prepared polymer

    This study identified the genus Coelastrella Chodat, 1922 which was isolated from a sediment sample taken from the Tigris river in Baghdad Governorate, Iraq. The alga was isolated and cultured in modified Chu 10 media and the morphological features of the isolated algae were observed in light microscopy (LM); it showed some characteristic features of this genus, such as its ellipsoidal or lemon- shaped cells, a visible pyrenoid and the chloroplast parietal. To ensure correct identification of the isolated alga, a molecular analysis using 18S rRNA gene and DNA sequencing revealed a match with C. terrestris (Reisigl) Hedewald & N. Hanagata 2002. This species is a new record in Iraq

The first aim of this paper was to evaluate the push-out bond strength of the gutta-percha coating of Thermafil and GuttaCore and compare it with that of gutta-percha used to coat an experimental hydroxyapatite/polyethylene (HA/PE) obturator. The second aim was to assess the thickness of gutta-percha around the carriers of GuttaCore and HA/PE obturators using microcomputed tomography (μCT). Ten (size 30) 1 mm thick samples of each group (Thermafil, GuttaCore, and HA/PE) were prepared. An orthodontic wire with a diameter of 0.5 mm was attached to the plunger of an Instron machine in order to allow the push-out testing of the gutta-percha coating. Five samples of (GuttaCore and HA/PE) were scanned using

This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the appl