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 comparison to the actual observational results. ANN simulation gives a clear insight into three crescent moon visibility regions: invisible (I), probably visible (P), and certainly visible (V). The proposed ANN is suitable for building lunar calendars, so it was used to build a four-year calendar on the horizon of Baghdad. The built calendar was compared with the official Hijri calendar in Iraq.
This study includes a detailed morphological description of Cosmina baghdadensis sp. nov.
from Iraq.
Many characters are used in identification especially chaetotaxy and male genetalia.
Locality, host plant, and data of collection were given.
Solanum americanum is a new annual shrubby plant seen recently in fields and gardens of Baghdad city. A new species is described and illustrated, inhabit wet or semi dry places and have consequently a mesophytic habit. A detailed morphological study of the stems, leaves, Inflorescence, flower, male and female reproductive organs and fruits has been done, revealed several interesting taxonomic characteristics, which have not previously been studied in Iraq. Also, anatomical studies reveals constant taxonomical characteristics such as the presence of anthocayanine in outer row of epidermis, distinct chlorenchyma in whole cortex, the wide pith of stems, and presence of distinct mesophyll that differentiated into palisade layer and spongy laye
... Show MoreTrialeurodes irakensis sp. n. is describe and illustrated from Iraq. T.vaporariorurn (westwood)
is reported and for the first time for the Iraqi fauna. A ke to species of Trialeurodes found in
Iraq is presented.
This research includes a detaile description of new species Rhyncomya irakensis sp. nov.
from Iraq.
Localities distribution, host plants and data of collection were recorded.
Mobile ad hoc network security is a new area for research that it has been faced many difficulties to implement. These difficulties are due to the absence of central authentication server, the dynamically movement of the nodes (mobility), limited capacity of the wireless medium and the various types of vulnerability attacks. All these factor combine to make mobile ad hoc a great challenge to the researcher. Mobile ad hoc has been used in different applications networks range from military operations and emergency disaster relief to community networking and interaction among meeting attendees or students during a lecture. In these and other ad hoc networking applications, security in the routing protocol is necessary to protect against malic
... Show MoreThis paper experimentally investigates the heating process of a hot water supply using a neural network implementation of a self-tuning PID controller on a microcontroller system. The Particle Swarm Optimization (PSO) algorithm employed in system tuning proved very effective, as it is simple and fast optimization algorithm. The PSO method for the PID parameters is executed on the Matlab platform in order to put these parameters in the real-time digital PID controller, which was experimented with in a pilot study on a microcontroller platform. Instead of the traditional phase angle power control (PAPC) method, the Cycle by Cycle Power Control (CBCPC) method is implemented because it yields better power factor and eliminates harmonics
... Show MoreAlzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of
... Show MoreA new concrete rheometer is introduced including its innovation, actual design, working rules,
calibration, and reliability. A modified design of Tattersall two-point device is created. Some of
components are purchased from local and foreign markets, while other components and the
manufacturing process are locally fabricated. The matching viscosity method of determining the mixer
viscometer constants is demonstrated and followed to relate torque and rotational speed to yield stress
and viscosity (Bingham parameters). The calibration procedures and its calculation are explained.
Water is used as a Newtonian fluid, while; cement paste (cement + water) with w/c ratio equal to
(0.442) is used as a non-Newtonian fluid. Th
Abstract: Data mining is become very important at the present time, especially with the increase in the area of information it's became huge, so it was necessary to use data mining to contain them and using them, one of the data mining techniques are association rules here using the Pattern Growth method kind enhancer for the apriori. The pattern growth method depends on fp-tree structure, this paper presents modify of fp-tree algorithm called HFMFFP-Growth by divided dataset and for each part take most frequent item in fp-tree so final nodes for conditional tree less than the original fp-tree. And less memory space and time.