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Calculating Surface Roughness for a Large Scale SEM Images by Mean of Image Processing
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Publication Date
Sun Apr 03 2011
Journal Name
Journal Of Educational And Psychological Researches
Constructing The Psychological Tranquility Scale of the University of Baghdad Students
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Constructing The Psychological Tranquility Scale of the University of Baghdad Students
The research aimed to :
- Constructing the Psychological Tranquility Scale of the University of Baghdad Students.
- Appointing the psychological content standard for the accepting Answer of student about the scale.
The research Sample was (414) boy and girl from Baghdad University Students for the Studying year (2008-2009), So the Scale of the Psychological Tranquility Scale was bilt on them in good psychometric properties from truth Factor analyzing which was its super saturation was reached to (50) item from its items a value more than the super sutution norm (0,30) for kaizer, also the firm value was Relaibility for the scale by the way

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Publication Date
Sat Jul 28 2018
Journal Name
Journal Of Engineering
Effectiveness of Meso-Scale Approach in Modeling of Plain Concrete Beam
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The main aim of this research paper is investigating the effectiveness and validity of Meso-Scale Approach (MSA) as a modern technique for the modeling of plain concrete beams. Simply supported plain concrete beam was subjected to two-point loading to detect the response in flexural. Experimentally, a concrete mix was designed and prepared to produce three similar standard concrete prisms for flexural testing. The coarse aggregate used in this mix was crushed aggregate. Numerical Finite Element Analysis (FEA) was conducted on the same concrete beam using the meso-scale modeling. The numerical model was constructed to be a bi-phasic material consisting of cement mortar and coarse aggregate. The interface between the two c

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Publication Date
Wed Jul 17 2019
Journal Name
Aip Conference Proceedings
The interpolation effect on the spare sinogram for 3D image reconstruction
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The effect of using three different interpolation methods (nearest neighbour, linear and non-linear) on a 3D sinogram to restore the missing data due to using angular difference greater than 1° (considered as optimum 3D sinogram) is presented. Two reconstruction methods are adopted in this study, the back-projection method and Fourier slice theorem method, from the results the second reconstruction proven to be a promising reconstruction with the linear interpolation method when the angular difference is less than 20°.

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Publication Date
Wed Dec 13 2023
Journal Name
2023 3rd International Conference On Intelligent Cybernetics Technology & Applications (icicyta)
GPT-4 versus Bard and Bing: LLMs for Fake Image Detection
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The recent emergence of sophisticated Large Language Models (LLMs) such as GPT-4, Bard, and Bing has revolutionized the domain of scientific inquiry, particularly in the realm of large pre-trained vision-language models. This pivotal transformation is driving new frontiers in various fields, including image processing and digital media verification. In the heart of this evolution, our research focuses on the rapidly growing area of image authenticity verification, a field gaining immense relevance in the digital era. The study is specifically geared towards addressing the emerging challenge of distinguishing between authentic images and deep fakes – a task that has become critically important in a world increasingly reliant on digital med

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
Indoor/Outdoor Deep Learning Based Image Classification for Object Recognition Applications
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With the rapid development of smart devices, people's lives have become easier, especially for visually disabled or special-needs people. The new achievements in the fields of machine learning and deep learning let people identify and recognise the surrounding environment. In this study, the efficiency and high performance of deep learning architecture are used to build an image classification system in both indoor and outdoor environments. The proposed methodology starts with collecting two datasets (indoor and outdoor) from different separate datasets. In the second step, the collected dataset is split into training, validation, and test sets. The pre-trained GoogleNet and MobileNet-V2 models are trained using the indoor and outdoor se

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Publication Date
Sat Oct 30 2021
Journal Name
Iraqi Journal Of Science
Small Binary Codebook Design for Image Compression Depending on Rotating Blocks
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     The searching process using a binary codebook of combined Block Truncation Coding (BTC) method and Vector Quantization (VQ), i.e. a full codebook search for each input image vector to find the best matched code word in the codebook, requires a long time.   Therefore, in this paper, after designing a small binary codebook, we adopted a new method by rotating each binary code word in this codebook into 900 to 2700 step 900 directions. Then, we systematized each code word depending on its angle  to involve four types of binary code books (i.e. Pour when , Flat when  , Vertical when, or Zigzag). The proposed scheme was used for decreasing the time of the coding procedure, with very small distortion per block, by designing s

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Publication Date
Mon Dec 05 2022
Journal Name
Baghdad Science Journal
MSRD-Unet: Multiscale Residual Dilated U-Net for Medical Image Segmentation
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Semantic segmentation is an exciting research topic in medical image analysis because it aims to detect objects in medical images. In recent years, approaches based on deep learning have shown a more reliable performance than traditional approaches in medical image segmentation. The U-Net network is one of the most successful end-to-end convolutional neural networks (CNNs) presented for medical image segmentation. This paper proposes a multiscale Residual Dilated convolution neural network (MSRD-UNet) based on U-Net. MSRD-UNet replaced the traditional convolution block with a novel deeper block that fuses multi-layer features using dilated and residual convolution. In addition, the squeeze and execution attention mechanism (SE) and the s

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Publication Date
Tue Aug 01 2023
Journal Name
Proceedings Of International Structural Engineering And Construction
COLORED ROOFS: A SOLUTION TO MITIGATION UHI AND REDUCING URBAN SURFACE HEATING
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The city is a built-up urban space and multifunctional structures that ensure safety, health and the best shelter for humans. All its built structures had various urban roofs influenced by different climate circumstances. That creates peculiarities and changes within the urban local climate and an increase in the impact of urban heat islands (UHI) with wastage of energy. The research question is less information dealing with the renovation of existing urban roofs using color as a strategy to mitigate the impact of UHI. In order to achieve local urban sustainability; the research focused on solutions using different materials and treatments to reduce urban surface heating emissions. The results showed that the new and old technologies, produ

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Publication Date
Thu Apr 24 2025
Journal Name
Pertanika Journal Of Science And Technology
Enhancing Leachate Treatment with Electrocoagulation: A Computational Approach Using Response Surface Methodology
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Malaysia's growing population and industrialisation have increased solid waste accumulation in landfills, leading to a rise in leachate production. Leachate, a highly contaminated liquid from landfills, poses environmental risks and affects water quality. Conventional leachate treatments are costly and time-consuming due to the need for additional chemicals. Therefore, the Electrocoagulation process could be used as an alternative method. Electrocoagulation is an electrochemical method of treating water by eliminating impurities by applying an electric current. In the present study, the optimisation of contaminant removal was investigated using Response Surface Methodology. Three parameters were considered for optimisation: the curr

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Publication Date
Sun Jan 01 2023
Journal Name
Aip Conference Proceedings
The efficiency of cluster analysis to analyzing medical image of Covid-19 patient by using K-means algorithm
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