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Mobile Position Estimation based on Three Angles of Arrival using an Interpolative Neural Network
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In this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperforms the two other methods in its estimations for different noise conditions.

Publication Date
Thu Feb 07 2019
Journal Name
Iraqi Journal Of Laser
Laser Enhanced Photocatalyic Degradation of Methylene blue using Nanostructured ZnO Catalyst based on Interfacial Charge Transfer
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In this research, annealed nanostructured ZnO catalyst water putrefaction system was built using sun light and different wavelength lasers as stimulating light sources to enhance photocatalytic degradation activity of methylene blue (MB) dye as a model based on interfacial charges transfer. The structural, crystallite size, morphological, particle size, optical properties and degradation ability of annealed nanostructured ZnO were characterized by X-Ray Diffraction (XRD), Atomic Force Microscopy (AFM) and UV-VIS Spectrometer, respectively. XRD results demonstrated a pure crystalline hexagonal wurtzite with crystalline size equal to 23 nm. From AFM results, the average particle size was 79.25nm. All MB samples and MB with annealed nanostr

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Publication Date
Tue Sep 01 2015
Journal Name
Journal Of Engineering
Cost of Optimum Design of Trunk Mains Network Using Geographical Information System and Support Programs
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Sewer network is one of the important utilities in modern cities which discharge the sewage from all facilities. The increase of population numbers consequently leads to the increase in water consumption; hence waste water generation. Sewer networks work is very expensive and need to be designed accurately. Thus construction effective sewer network system with minimum cost is very necessary to handle waste water generation.

 In this study trunk mains networks design was applied which connect the pump stations together by underground pipes for too long distances. They usually have large diameters with varying depths which consequently need excavations and gathering from pump stations and transport the sewage

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Publication Date
Mon Jun 30 2008
Journal Name
Iraqi Journal Of Science
On the Greedy Ridge Function Neural Networks for Approximation Multidimensional Functions
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The aim of this paper is to approximate multidimensional functions f∈C(R^s) by developing a new type of Feedforward neural networks (FFNS) which we called it Greedy ridge function neural networks (GRGFNNS). Also, we introduce a modification to the greedy algorithm which is used to train the greedy ridge function neural networks. An error bound are introduced in Sobolov space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result in [1]).

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Publication Date
Thu Jul 01 2021
Journal Name
Journal Of Physics: Conference Series
Estimation of the reliability function of the Rayleigh distribution using some robust and kernel methods
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Abstract<p>The research presents the reliability. It is defined as the probability of accomplishing any part of the system within a specified time and under the same circumstances. On the theoretical side, the reliability, the reliability function, and the cumulative function of failure are studied within the one-parameter Raleigh distribution. This research aims to discover many factors that are missed the reliability evaluation which causes constant interruptions of the machines in addition to the problems of data. The problem of the research is that there are many methods for estimating the reliability function but no one has suitable qualifications for most of these methods in the data such </p> ... Show More
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Publication Date
Fri Jun 02 2023
Journal Name
المجلة السياسية والدولية
Taiwan's Position in US-China Relations Under President Joseph Biden
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The international standing has an impact on the strategic importance of the country in its relations with other regional and international countries. The strategic position of Taiwan has an impact on the US-Chinese relations, as it is one of the most important issues that raise dispute between the two countries. The while the Chinese consider Taiwan is an ancient legacy of their republic, and an integral part of it, the Americans consider it as an area linking the U.S. to the Asia-Pacific region, through which it intends to help its allies (Japan and South Korea). Moreover, Taiwan has huge economic importance as it is one of the largest manufacturers of electronic chips and semiconductors. This fact represents one of the most important issu

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Publication Date
Mon Dec 28 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
Predicting the Sporting Achievement in the Pole Vault for Men Using Artificial Neural Networks
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The physical sports sector in Iraq suffers from the problem of achieving sports achievements in individual and team games in various Asian and international competitions, for many reasons, including the lack of exploitation of modern, accurate and flexible technologies and means, especially in the field of information technology, especially the technology of artificial neural networks. The main goal of this study is to build an intelligent mathematical model to predict sport achievement in pole vaulting for men, the methodology of the research included the use of five variables as inputs to the neural network, which are Avarage of Speed (m/sec in Before distance 05 meters latest and Distance 05 meters latest, The maximum speed achieved in t

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Publication Date
Wed May 03 2023
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
Enhancing smart home energy efficiency through accurate load prediction using deep convolutional neural networks
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The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

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Publication Date
Sun Aug 28 2016
Journal Name
World Journal Of Pharmacy And Pharmaceutical Sciences
AN INSIGHT ON THE IDENTIFICATION OF CANCER STEM CELLS USING NOVEL IMMUNOLOGICAL AND MOLECULAR STRATEGIES
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Cancer stem cells (CSCs) are defined as a population of cells present in tumours, which can undergo self-renewal and differentiation. Identification and isolation of these CSCs using putative surface markers have been a priority of research in cancer. With this background we selected pancreatic normal and tumor cells for this study and passaged them into animal tissue culture medium. Further staining was done using alkaline phosphatase and heamatoxilin staining. Blue to purple colored zones in undifferentiated pluripotent stem cells and clear coloration in the chromatin material indicated pancreatic cells. Further studies on the cell surface marker CD 44 were done using ELISA. For this, the protein was extracted from cultivated normal and t

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Exploring the Factors Affecting the Elemental Cost Estimation with Relationship Analysis Using AHP
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Cost estimation is considered one of the important tasks in the construction projects management. The precise estimation of the construction cost affect on the success and quality of a construction project. Elemental estimation is considered a very important stage to the project team because it represents one of the key project elements. It helps in formulating the basis to strategies and execution plans for construction and engineering.  Elemental estimation, which in the early stage, estimates the construction costs depending on  . minimum details of the project so that it gives an indication for the initial design stage of a project. This paper studies the factors that affect the elemental cost estimation as well as the rela

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Performance Analysis on Multiple Device Connections of Small Office Home Office Network
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Malaysia has been supported by one of the high-speed fiber internet connections called TM UniFi. TM UniFi is very familiar to be used as a medium to apply Small Office Home Office (SOHO) concept due to the COVID-19 pandemic. Most of the communication vendors offer varieties of network services to fulfill customers' needs and satisfaction during the pandemic. Quality of Services is queried by most users by the fact of increased on users from time to time. Therefore, it is crucial to know the network performance contrary to the number of devices connected to the TM UniFi network. The main objective of this research is to analyze TM UniFi performance with the impact of multiple device connections or users' services. The study was conducted

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