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GNSS Baseline Configuration Based on First Order Design
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The quality of Global Navigation Satellite Systems (GNSS) networks are considerably influenced by the configuration of the observed baselines. Where, this study aims to find an optimal configuration for GNSS baselines in terms of the number and distribution  of baselines to improve the quality criteria of the GNSS networks. First order design problem (FOD) was applied in this research to optimize GNSS network baselines configuration, and based on sequential adjustment method to solve its objective functions.

FOD for optimum precision (FOD-p) was the proposed model which based on the design criteria of A-optimality and E-optimality. These design criteria were selected as objective functions of precision, which lead to a homogenous and anisotropic network, respectively  using Matlab programming language (V. 2012a). Al Ghammas Township, Al-Qadisiya city, which consists of twenty-five stations was taken as a study area in this research.

The results showed that there are 300 potential baselines for the GNSS network of the study area, which were reduced during the optimum configuration to about 70% of the total potential baselines by applying FOD-p, and there is high level of improvement in the objective functions of precision which  reached to about 90% .

 

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Publication Date
Fri Jul 19 2024
Journal Name
An International Journal Of Optimization And Control: Theories & Applications (ijocta)
Design optimal neural network based on new LM training algorithm for solving 3D - PDEs
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In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

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Publication Date
Sun Jun 12 2011
Journal Name
Baghdad Science Journal
An algorithm for binary codebook design based on the average bitmap replacement error (ABPRE)
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In this paper, an algorithm for binary codebook design has been used in vector quantization technique, which is used to improve the acceptability of the absolute moment block truncation coding (AMBTC) method. Vector quantization (VQ) method is used to compress the bitmap (the output proposed from the first method (AMBTC)). In this paper, the binary codebook can be engender for many images depending on randomly chosen to the code vectors from a set of binary images vectors, and this codebook is then used to compress all bitmaps of these images. The chosen of the bitmap of image in order to compress it by using this codebook based on the criterion of the average bitmap replacement error (ABPRE). This paper is suitable to reduce bit rates

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Publication Date
Tue Oct 01 2019
Journal Name
Journal Of Engineering
Evaluation of the Performance of Online GPS/GNSS Data Processing Services for Monitoring the Land Deformations and Movements
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In recent years, the Global Navigation Satellite Services (GNSS) technology has been frequently employed for monitoring the Earth crust deformation and movement. Such applications necessitate high positional accuracy that can be achieved through processing GPS/GNSS data with scientific software such as BERENSE, GAMIT, and GIPSY-OSIS. Nevertheless, these scientific softwares are sophisticated and have not been published as free open source software. Therefore, this study has been conducted to evaluate an alternative solution, GNSS online processing services, which may obtain this privilege freely. In this study, eight years of GNSS raw data for TEHN station, which located in Iran, have been downloaded from UNAVCO website

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Publication Date
Thu May 31 2018
On the Use of 6th-Order Tunable Complementary Metal-Oxide-Semiconductor Varactor based Filter in Ultra-Wideband Low Noise Amplifier
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Background:

The plethora of the emerged radio frequency applications makes the frequency spectrum crowded by many applications and hence the ability to detect specific application’s frequency without distortion is a difficult task to achieve.

Objective:

The goal is to achieve a method to mitigate the highest interferer power in the frequency spectrum in order to eliminate the distortion.

Method:

This paper presents the application of the proposed tunable 6th-order notch filter on Ultra-Wideband (UWB) Complementary Metal-Oxide-Semiconductor (CMOS) Low Noise

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Publication Date
Mon Jun 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Use of lower squares and restricted boxes In the estimation of the first-order self-regression parameter AR (1) (simulation study)
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Use of lower squares and restricted boxes
In the estimation of the first-order self-regression parameter
AR (1) (simulation study)

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Publication Date
Fri Jun 18 2021
Journal Name
International Journal Of Emerging Technologies In Learning (ijet)
The Effectiveness of Educational Pillars Based on Vygotsky's Theory in Achievement and Information Processing Among First Intermediate Class Students
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The aim of the research is to identify the effectiveness of the educational pillars strategy based on Vygotsky's theory in mathematical achievement and information processing of first-grade intermediate students. In pursuit of the research objectives, the experimental method was used, and the quasi-experimental design was used for two equivalent groups, one control group taught traditionally and the other experi-mental taught according to the educational pillars strategy. The research sample consisted of (66) female students from the first intermediate grade, who were inten-tionally chosen after ensuring their equivalence, taking into account several factors, most notably chronological age and their level of mathematics, and they we

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Publication Date
Tue Feb 28 2023
Journal Name
International Journal Of Intelligent Engineering And Systems
Design and Implementation of EEG-Based Smart Structure
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Publication Date
Tue Sep 01 2020
Journal Name
Microprocessors And Microsystems
Design considerations for a microprocessor-based Doppler radar
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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Computational Design And Engineering
CFD analysis of phase-change material-based heat storage with dimple-shaped fins: evaluation of fin configuration and distribution pattern
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Abstract<p>Phase-change materials (PCMs) have a remarkable potential for use as efficient energy storage means. However, their poor response rates during energy storage and retrieval modes require the use of heat transfer enhancers to combat these limitations. This research marks the first attempt to explore the potential of dimple-shaped fins for the enhancement of PCM thermal response in a shell-and-tube casing. Fin arrays with different dimensions and diverse distribution patterns were designed and studied to assess the effect of modifying the fin geometric parameters and distribution patterns in various spatial zones of the physical domain. The results indicate that increasing the number of </p> ... Show More
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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
A New Model Design for Combating COVID -19 Pandemic Based on SVM and CNN Approaches
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       In the current worldwide health crisis produced by coronavirus disease (COVID-19), researchers and medical specialists began looking for new ways to tackle the epidemic. According to recent studies, Machine Learning (ML) has been effectively deployed in the health sector. Medical imaging sources (radiography and computed tomography) have aided in the development of artificial intelligence(AI) strategies to tackle the coronavirus outbreak. As a result, a classical machine learning approach for coronavirus detection from      Computerized Tomography (CT) images was developed. In this study, the convolutional neural network (CNN) model for feature extraction and support vector machine (SVM) for the classification of axial

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