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Design and Implementation of a Contactless Smart House Network System
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The Internet of Things (IoT) technology is every object around us and it is used to connect these objects to the Internet to verify Machine to Machine (M2M) communication. The smart house system is the most important application of IoT technology; it is increase the quality of life and decrease the efforts. There were many problems that faced the existing smart house networking systems, including the high cost of implementation and upgrading, high power consumption, and supported limited features. Therefore, this paper presents the design and implementation of smart house network system (SHNS) using Raspberry Pi and Arduino platforms as network infrastructure with ZigBee technology as wireless communication. SHNS consists of two main parts: the main station part and the wireless house nodes part. The local wireless communication between the house nodes and the main station is done through ZigBee technology with low power and low data rate. The mode of operation of these house nodes can be configured dynamically by the end user and determined multicast or broadcast operation according to the user requirements. The implementation and upgrading of SHNS are costless, flexible and required less power comparing with other reviewed systems.

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Publication Date
Mon Mar 08 2021
Journal Name
Baghdad Science Journal
Diagnostically study of the Digestive system Helminthes
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A total of 247 specimens of the Mallard were collected from Baghdad city and kut City and 154 specimens the collection was started from October1999

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Publication Date
Fri Mar 01 2013
Journal Name
International Journal Of Recent Research And Review
Electrical Discharges Characterization of Planar Sputtering System
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Abstract: A home-made dc sputtering is characterized by cathode potential of 250-2500 V and sputtering gas pressures of (3.5×10-2 – 1.5) mbar. This paper studies in experiment the breakdown of argon, nitrogen, and oxygen in a uniform dc electric field at different discharge gaps and cathode potentials. Paschen curves for Argon, Nitrogen, and oxygen are obtained by measuring the breakdown voltage of gas within a stainless steel vacuum chamber with two planar, stainless steel electrodes. The Paschen curves in Ar, N2, and O2 gases show that the breakdown voltage between two electrodes is a function of pd (The product of the pressure inside the chamber and distance between the electrodes). Current-voltage characteristics visualization of the

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Publication Date
Mon Jan 13 2025
Journal Name
Journal Of The Iraqi University
The legal system of Administrative BOT Contracts
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Publication Date
Mon Jul 25 2016
Journal Name
Earthquakes And Structures
Vibration response of saturated sand - foundation system
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In this study, the response and behavior of machine foundations resting on dry and saturated sand was investigated experimentally. A physical model was manufactured to simulate steady state harmonic load applied on a footing resting on sandy soil at different operating frequencies. Total of (84) physical models were performed. The parameters that were taken into consideration include loading frequency, size of footing and different soil conditions. The footing parameters are related to the size of the rectangular footing and depth of embedment. Two sizes of rectangular steel model footing were used. The footings were tested by changing all parameters at the surface and at 50 mm depth below model surface. Meanwhile, the investigated paramete

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Publication Date
Thu Aug 01 2024
Journal Name
Al-kindy College Medical Journal
Automation of the Healthcare System in Iraq
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In the last few years, following the relative stability of the political, economic, and security environments, Iraq has embarked on a transformation towards an ambitious program of automation across various sectors. However, this automation program faces numerous challenges, including significant investments in technology and training, addressing social impacts, and combating widespread illiteracy

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Publication Date
Sat Jun 30 2018
Journal Name
Proceedings Of The International Conference On Intelligent Science And Technology
The nature of intelligent system in buildings
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Publication Date
Tue May 01 2018
Journal Name
Journal Of Engineering
Prediction of Municipal Solid Waste Generation Models Using Artificial Neural Network in Baghdad city, Iraq
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The importance of Baghdad city as the capital of Iraq and the center of the attention of delegations because of its long history is essential to preserve its environment. This is achieved through the integrated management of municipal solid waste since this is only possible by knowing the quantities produced by the population on a daily basis. This study focused to predicate the amount of municipal solid waste generated in Karkh and Rusafa separately, in addition to the quantity produced in Baghdad, using IBM SPSS 23 software. Results that showed the average generation rates of domestic solid waste in Rusafa side was higher than that of Al-Karkh side because Rusafa side has higher population density than Al-Karkh side. T

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Publication Date
Mon May 01 2023
Journal Name
Ain Shams Engineering Journal
Neural network modeling of rutting performance for sustainable asphalt mixtures modified by industrial waste alumina
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Publication Date
Wed May 25 2022
Journal Name
Iraqi Journal Of Science
Using Persistence Barcode to Show the Impact of Data Complexity on the Neural Network Architecture
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    It is so much noticeable that initialization of architectural parameters has a great impact on whole learnability stream so that knowing  mathematical properties of dataset results in providing neural network architecture a better expressivity and capacity. In this paper, five random samples of the Volve field dataset were taken. Then a training set was specified and the persistent homology of the dataset was calculated to show impact of data complexity on selection of multilayer perceptron regressor (MLPR) architecture. By using the proposed method that provides a well-rounded strategy to compute data complexity. Our method is a compound algorithm composed of the t-SNE method, alpha-complexity algorithm, and a persistence barcod

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Publication Date
Thu May 10 2018
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
An Improvement of MRI Brain Images Classification Using Dragonfly Algorithm as Trainer of Artificial Neural Network
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  Computer software is frequently used for medical decision support systems in different areas. Magnetic Resonance Images (MRI) are widely used images for brain classification issue. This paper presents an improved method for brain classification of MRI images. The proposed method contains three phases, which are, feature extraction, dimensionality reduction, and an improved classification technique. In the first phase, the features of MRI images are obtained by discrete wavelet transform (DWT). In the second phase, the features of MRI images have been reduced, using principal component analysis (PCA). In the last (third) stage, an improved classifier is developed. In the proposed classifier, Dragonfly algorithm is used instead

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