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Global NAVIGATION Satellite System Contribution for Observing the Tectonic Plate Movements: Status and Perspectives

The long-term monitoring of land movements represents the most successful application of the Global Navigation Satellite System (GNSS), particularly the Global Positioning System. However, the application of long term monitoring of land movements depends on the availability of homogenous and consistent daily position time series of stations over a period of time. Such time series can be produced very efficiently by using Precise Point Positioning and Double Difference techniques based on particular sophisticated GNSS processing softwares. Nonetheless, these rely on the availability of GNSS products which are precise satellite orbit and clock, and Earth orientation parameters. Unfortunately, several changes and modifications have been made periodically on the policy of producing these products which led to degradation in the consistency of these products over time. For the long term monitoring of land movements, it is essential that any such developments and changes can also be used to produce improved products that go back in time, to enable the homogeneous reprocessing of archived observation data. This paper deals with two main themes. Firstly, it demonstrates the significant and imperative role of the GNSS in geological applications by addressing major global and regional studies of the Earth’s deformation which represent one of the main and essential applications in satellite geodesy. The role of the continues GPS measurements in this application is highlighted and discussed for modeling global and regional plate motions and modeling Glacial Isostatic Adjustment. Secondly, this paper locates the most important obstacles which stand behind the inability to use the GNSS in applications of long-term monitoring of land movements.

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Engineering
An Adaptive Multi-Objective Particle Swarm Optimization Algorithm for Multi-Robot Path Planning

This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In ord

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Accurate Four-Step Hybrid Block Method for Solving Higher-Order Initial Value Problems

This paper focuses on developing a self-starting numerical approach that can be used for direct integration of higher-order initial value problems of Ordinary Differential Equations. The method is derived from power series approximation with the resulting equations discretized at the selected grid and off-grid points. The method is applied in a block-by-block approach as a numerical integrator of higher-order initial value problems. The basic properties of the block method are investigated to authenticate its performance and then implemented with some tested experiments to validate the accuracy and convergence of the method.

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of The Mechanical Behavior Of Materials
Efficiency of CFRP torsional strengthening technique for L-shaped spandrel reinforced concrete beams
Abstract<p>The present study aims to get experimentally a deeper understanding of the efficiency of carbon fiber-reinforced polymer (CFRP) sheets applied to improve the torsional behavior of L-shaped reinforced concrete spandrel beams in which their ledges were loaded in two stages under monotonic loading. An experimental program was conducted on spandrel beams considering different key parameters including the cross-sectional aspect ratio (<italic>i.e.</italic>, web height/web thickness), and the availability of the CFRP strengthening system. The ledge of the spandrel beams was exposed during testing to a very high eccentric load, which was transferred to the web of the spandrel beam </p> ... Show More
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Publication Date
Sun Mar 02 2008
Journal Name
Baghdad Science Journal
Calculations of Signal to Noise Ratio (SNR) for Free Space Optical Communication Systems

In this paper, we calculate and measure the SNR theoretically and experimental for digital full duplex optical communication systems for different ranges in free space, the system consists of transmitter and receiver in each side. The semiconductor laser (pointer) was used as a carrier wave in free space with the specification is 5mW power and 650nm wavelength. The type of optical detector was used a PIN with area 1mm2 and responsively 0.4A/W for this wavelength. The results show a high quality optical communication system for different range from (300-1300)m with different bit rat (60-140)kbit/sec is achieved with best values of the signal to noise ratio (SNR).

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Publication Date
Wed Jan 13 2021
Journal Name
Iraqi Journal Of Science
Bio-charge Elastic Characterization for A Qualitative Perspective of Innovative Bio-Composite Materials

In order to save natural resources, recycling necessarily becomes a top priority for all of us, to save exhaustible resources, produce green energy and preserve the environment.
In this perspective, we are trying to valorize a waste of animal origin, largely neglected by the actors of materials, through an industrial transformation into a biological charge to make new sustainable bio-composite materials.
Using a tensile test bench, we try to mechanically characterize this biomaterial of renewable resources that, unlike eco-composites, has been neglected by the material actors.
Obtained from waste, with a high recycling potential and from renewable resources, the bio-charge to be analyzed will be injected, later in different poly

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Publication Date
Sun Feb 27 2022
Journal Name
Iraqi Journal Of Science
Efficient Hybrid DCT-Wiener Algorithm Based Deep Learning Approach For Semantic Shape Segmentation

    Semantic segmentation is effective in numerous object classification tasks such as autonomous vehicles and scene understanding. With the advent in the deep learning domain, lots of efforts are seen in applying deep learning algorithms for semantic segmentation. Most of the algorithms gain the required accuracy while compromising on their storage and computational requirements. The work showcases the implementation of Convolutional Neural Network (CNN) using Discrete Cosine Transform (DCT), where DCT exhibit exceptional energy compaction properties. The proposed Adaptive Weight Wiener Filter (AWWF) rearranges the DCT coefficients by truncating the high frequency coefficients. AWWF-DCT model reinstate the convolutional l

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Publication Date
Sun Sep 01 2019
Journal Name
Al-khwarizmi Engineering Journal
Electrodepositing of Multi-Layer Ni-Ag Coated by Copper Nanoparticles for Solar Absorber

In this work, the effect of the addition of bright nickel plating and silver carried out by the electroplating method has been studied, on the coating of copper nanoparticles on the copper base metal via the process of thermal evaporation. The improvement of the solar absorber using CuNP in combination with the bright nickel and silver was obtained to be better than copper nanoparticles individually. A bright nickel enhanced the absorbed thermal stability. Also, other optical properties, absorptions, and emissivity slightly decreased from (93% to 87%), while the existence of silver had a slight impact on absorption of about (86.50%). On the other hand, thermal conductivity was evaluated using hot disk analyzer. The results showed a good

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Publication Date
Sat Nov 14 2020
Journal Name
Journal Of Information Systems And Telecommunication (jist)
Optical Power Distributions for 4×4 MIMO Visible Light Communications in Indoor Environment

Visible Light Communication (VLC) has emerged as a powerful technique for wireless communication systems. Providing high data rate and increasing capacity are the major problems in VLC. Recent evidence suggests that Multiple Input Multiple Output (MIMO) technique can offers improved data rates and increased link range. This paper describes the design and implementation of visible light communication system in indoor environment exploring the benefits of MIMO. The specific objective of this research was to implement a 4× 4 Multiple Input (LEDs) Multiple Output (photodetectors)-VLC communication system, where a 16 white power LEDs in four arrays are setting up at transmitter and four RX modules are setting up at receiver side without the nee

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Publication Date
Mon Jan 29 2024
Journal Name
Advances In Systems Analysis, Software Engineering, And High Performance Computing
Evaluating Antivirus Effectiveness Against Malware in Ascending Order for Increasing Blockchain Endpoint Protection

Blockchain represents a new promising technology with a huge economic impact resulting from its uses in various fields such as digital currency and banking; malware represents a serious threat to users, and there are many differences in the effectiveness of antivirus software used to deal with the problem of malware. This chapter has developed a coefficient for measuring the effectiveness of antivirus software. This chapter evaluates the effectiveness of antivirus software by conducting tests on a group of protection programs using a folder containing an amount of data. These programs are applied to combat viruses contained in this folder. The study revealed that the effectiveness of antivirus software is as follows: AVG scored 0%,

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Publication Date
Tue Nov 30 2021
Journal Name
Iraqi Journal Of Science
Inspecting Hybrid Data Mining Approaches in Decision Support Systems for Humanities Texts Criticism

The majority of systems dealing with natural language processing (NLP) and artificial intelligence (AI) can assist in making automated and automatically-supported decisions. However, these systems may face challenges and difficulties or find it confusing to identify the required information (characterization) for eliciting a decision by extracting or summarizing relevant information from large text documents or colossal content.   When obtaining these documents online, for instance from social networking or social media, these sites undergo a remarkable increase in the textual content. The main objective of the present study is to conduct a survey and show the latest developments about the implementation of text-mining techniqu

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