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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 Sep 22 2024
Journal Name
Journal Of Petroleum Research And Studies
Optimizing Gas Lift for Improved Oil Recovery in a Middle East Field: A Genetic Algorithm Approach
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This paper presents a study of the application of gas lift (GL) to improve oil production in a Middle East field. The field has been experiencing a rapid decline in production due to a drop in reservoir pressure. GL is a widely used artificial lift technique that can be used to increase oil production by reducing the hydrostatic pressure in the wellbore. The study used a full field model to simulate the effects of GL on production. The model was run under different production scenarios, including different water cut and reservoir pressure values. The results showed that GL can significantly increase oil production under all scenarios. The study also found that most wells in the field will soon be closed due to high water cuts. Howev

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Publication Date
Wed Jun 01 2022
Journal Name
Civil Engineering Journal
Usage of EB-CFRP for Improved Flexural Capacity of Unbonded Post-Tensioned Concrete Members Exposed to Partially Damaged Strands
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The study presents the performance of flexural strengthening of concrete members exposed to partially unbonded prestressing with a particular emphasis on the amount (0, 14.2, and 28.5%) of cut strands-symmetrical and asymmetrical damage. In addition to examining the influence of cut strands on the remaining capacity of post-tensioned unbonded members and the effectiveness of carbon fiber reinforced polymer laminates restoration, The investigated results on rectangular members subjected to a four-point static bending load based on the composition of the laminate affected the stress of the CFRP, the failure mode, and flexural strength and deflection are covered in this study. The experimental results revealed that the usage of CFRP la

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Publication Date
Sun Oct 01 2023
Journal Name
Journal Of Photochemistry And Photobiology A: Chemistry
Facile assembly of CoS/Ag2MoO4 nanohybrids for visible light-promoted Z-type-induced synergistically improved photocatalytic degradation of antibiotics
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Publication Date
Thu Jun 08 2023
Journal Name
Iraqi Journal Of Laser
PDF Sensing and differentiation between normal flora and pathogenic of E.coli Bacteria using 410 nm diode laser
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Abstract: Background: Optical biosensors offer excellent properties and methods for detecting bacteria when compared to traditional analytical techniques.  It allows direct detection of many biological and chemical materials.  Bacteria are found in the human body naturally non-pathogenic and pathologically, as they are found in other living organisms.  One of these bacteria is Escherichia coli (E. coli) which are found in the human body in its natural and pathogenic form. E.coli bacteria cause many diseases, including Stomach, intestines, urinary system infections, and others. The aim of this study: is sensing and differentiation between normal flora and pathogenic E.coli. Material and method:

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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Access
A Direct Solution Scheme for Wide-Angle Electromagnetic Scattering Problems Using Compressive Sensing-Based Method of Moments
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Publication Date
Sat Mar 23 2024
Journal Name
Journal Of Optics
Tapered single-mode no-core optical fiber sensor coated with layer gold for hemoglobin sensing
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The present work focuses on the experimental implementation of one of the fiber optical sensors, the optical glass fiber built on surface Plasmon resonance. A type of optical glass fiber was used in this work, single-mode no-core fiber with pre-tapering diameter: (125.1 μm) and (125.3 μm), respectively. The taper method can be tested by measuring the output power of the optical fiber before and after chemical etching to show the difference in cladding diameter due to the effect of hydrofluoric acid with increasing time for the taper process. The optical glass fiber sensor can be fabricated using the taper method to reduce the cladding diameter of the fibers to (83.12 µm, 64.37 µm, and 52.45 µm) for single-mode fibers using Hydrofluoric

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Publication Date
Mon Jan 01 2024
Journal Name
2nd International Conference For Engineering Sciences And Information Technology (esit 2022): Esit2022 Conference Proceedings
ZnO nanostructures as low concentration NO2 gas sensor and impact the temperature on sensing properties
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Zinc oxide (ZnO) nanostructures were synthesized through the hydrothermal method at various conditions growth times (6,7 and 8 hrs.) and a growth temperature (70, 90, and 100 ºC). The prepared ZnO nanostructure samples were described using scanning electron microscopy (SEM) and X-ray diffractometer to distinguish their surface morphologies and crystal structures. The ZnO samples were confirmed to have the same crystal type, with different densities and dimensions (diameter and length). The obtained ZnO nanostructures were used to manufacture gas sensors for NO2 gas detection. Sensing characteristics for the fabricated sensor to NO2 gas were examined at different operating temperatures (180, 200, 220, and 240) ºC with a low gas concentrati

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Publication Date
Wed May 29 2019
Journal Name
Indian Journal Of Physics
Effect of lasing energy on the structure and optical and gas sensing properties of chromium oxide thin films
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Publication Date
Fri Jun 03 2022
Journal Name
Basra Journal Of Science
Morphological and Electrical properties of Polyvinylpyrrolidone/Multi-walled Carbon Nanotubes Nanocomposite with Graphene
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The solution casting method was used to prepare a polyvinylpyrrolidone (PVP)/Multi-walled carbon nanotubes (MWCNTs) nanocomposite with Graphene (Gr). Field Effect Scanning Electron Microscope (FESEM) and Fourier Transformer Infrared (FTIR) were used to characterize the surface morphology and optical properties of samples. FESEM images revealed a uniform distribution of graphene within the PVP-MWCNT nanocomposite. The FTIR spectra confirmed the nanocomposite information is successful with apperaring the presence of primary distinct peaks belonging to vibration groups that describe the prepared samples.. Furthermore, found that the DC electrical conductivity of the prepared nanocomposites increases with increasing MWCNT concentratio

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Publication Date
Mon Apr 01 2019
Journal Name
2019 International Conference On Automation, Computational And Technology Management (icactm)
Multi-Resolution Hierarchical Structure for Efficient Data Aggregation and Mining of Big Data
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Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

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