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Improved Automatic Registration Adjustment of Multi-source Remote Sensing Datasets
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Registration techniques are still considered challenging tasks to remote sensing users, especially after enormous increase in the volume of remotely sensed data being acquired by an ever-growing number of earth observation sensors. This surge in use mandates the development of accurate and robust registration procedures that can handle these data with varying geometric and radiometric properties. This paper aims to develop the traditional registration scenarios to reduce discrepancies between registered datasets in two dimensions (2D) space for remote sensing images. This is achieved by designing a computer program written in Visual Basic language following two main stages: The first stage is a traditional registration process by defining a set of control point pairs using manual selection, then comput the parameters of global affine transformation model to match them and resample the images. The second stage included matching process refinement by determining the shift value in control points (CPs) location depending on radiometric similarity measure. Then shift map technique was adjusted to adjust the process using 2nd order polynomial transformation function. This function has chosen after conducting statistical analyses, comparing between the common transformation functions (similarity, affine, projection and 2nd order polynomial). The results showed that the developed approach reduced the root mean square error (RMSE) of registration process and decreasing the discrepancies between registered datasets with 60%, 57% and 48% respectively for each one of the three tested datasets.

 

 

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Publication Date
Sun Mar 28 2021
Journal Name
Iraqi Journal For Electrical And Electronic Engineering
A Light Weight Multi-Objective Task Offloading Optimization for Vehicular Fog Computing
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Most Internet of Vehicles (IoV) applications are delay-sensitive and require resources for data storage and tasks processing, which is very difficult to afford by vehicles. Such tasks are often offloaded to more powerful entities, like cloud and fog servers. Fog computing is decentralized infrastructure located between data source and cloud, supplies several benefits that make it a non-frivolous extension of the cloud. The high volume data which is generated by vehicles’ sensors and also the limited computation capabilities of vehicles have imposed several challenges on VANETs systems. Therefore, VANETs is integrated with fog computing to form a paradigm namely Vehicular Fog Computing (VFC) which provide low-latency services to mo

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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Access
Dual-Layer Compressive Sensing Scheme Incorporating Adaptive Cross Approximation Algorithm for Solving Monostatic Electromagnetic Scattering Problems
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Publication Date
Fri Sep 30 2022
Journal Name
Energy Science And Engineering
CFD analysis on optimizing the annular fin parameters toward an improved storage response in a triple‐tube containment system
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Publication Date
Mon Jun 04 2018
Journal Name
Baghdad Science Journal
Comparative NO2 Sensing Characteristics of SnO2:WO3 Thin Film Against Bulk and Investigation of Optical Properties of the Thin Film
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A comparative investigation of gas sensing properties of SnO2 doped with WO3 based on thin film and bulk forms was achieved. Thin films were deposited by thermal evaporation technique on glass substrates. Bulk sensors in the shape of pellets were prepared by pressing SnO2:WO3 powder. The polycrystalline nature of the obtained films with tetragonal structure was confirmed by X-ray diffraction. The calculated crystalline size was 52.43 nm. Thickness of the prepared films was found 134 nm. The optical characteristics of the thin films were studied by using UV-VIS Spectrophotometer in the wavelength range 200 nm to 1100 nm, the energy band gap, extinction coefficient and refractive index of the thin film were 2.5 eV , 0.024 and 2.51, respective

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Publication Date
Tue Dec 05 2017
Journal Name
International Journal Of Science And Research (ijsr)
Multi Response Optimization of Submerged Arc Welding Using Taguchi Fuzzy Logic Based on Utility Theory
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Publication Date
Fri Apr 01 2022
Journal Name
Heliyon
Stigma towards health care providers taking care of COVID-19 patients: A multi-country study
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Publication Date
Tue Dec 20 2022
Journal Name
Iraqi Journal Of Biotechnology
Synergistic Effect of Conocarpus erectus Extract and some Antibiotics against Multi-Drug Resistant Pseudomonas aeruginosa
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Over the past few decades, the health benefits are under threat as many commonly used antibiotics have become less and less effective against certain illnesses not only because many of them produce toxic reactions but also due to the emergence of drug-resistant bacteria. The clinical use of a combination of antibiotic therapy for Pseudomonas aeruginosa infections is probably more effective than monotherapy. The present study aims to estimate the antibacterial and antibiofilm activity of Conocarpus erectus leaves extracts against multi-drug resistant P. aeruginosa isolated from different hospitals in Baghdad city. One hundred fifty different clinical specimens were collected from patients from September 2021 to January 2022. All samples were

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Publication Date
Mon Mar 07 2022
Journal Name
Journal Of Educational And Psychological Researches
Mono-Multi Vision and Its Relationship to Psychological Rebellion and Personality Traits of University Students
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The current research seeks to identify mono-multi Vision and its relation to the psychological rebellion and personality traits of university students. To achieve this aim, the researcher has followed all the procedures of the descriptive correlational approach, as it is the closest approach to the objectives of the current research. The researcher has determined his research community for Baghdad University students for the academic year 2019-2020. As for the research sample, it was chosen by the random stratified method with a sample of (500) male and female students. In order to collect data from the research sample, the researcher adopted a mono-multi-dimensional scale

(Othman, 2007), the researcher designed a psychological r

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Publication Date
Sat Apr 30 2022
Journal Name
Eastern-european Journal Of Enterprise Technologies
Improvement of noisy images filtered by bilateral process using a multi-scale context aggregation network
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Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

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Publication Date
Tue Jan 01 2019
Journal Name
Proceedings Of The 5th International Conference On Information Systems Security And Privacy
Identification and Extraction of Digital Forensic Evidence from Multimedia Data Sources using Multi-algorithmic Fusion
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