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Externally Bonded CFRP for Flexural Strengthening of RC Beams with Different Levels of Soffit Curvature
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This paper reports a comprehensive study on the behavior of concavely curved soffit reinforced concrete (RC) beams strengthened in flexure with carbon fiber-reinforced polymer (CFRP) composites under static loading. The main objective of this paper is to explore the effect of surface concavity on the bond performance of externally bonded wet layup CFRP sheets and laminates. An experimental program consisting of flexural strengthening of 24 RC beams with concavely curved soffits was carried out. All specimens were simply supported RC beams tested under three-point bending. Of the 24 beams, 6 beams were flat soffit RC beams, and the remainder were fabricated with concavely curved soffits with a degree of curvature that is ranging from 5 mm/m to 20 mm/m. All tested specimens were 2,700-mm long and had a constant cross section at midspan of 140-mm wide × 260-mm deep. The experiments showed that all strengthened beams failed by intermediate crack-induced (IC) debonding of the CFRP. The experimental results were then used, together with those for other specimens in the literature to set recommendations for strengthening concavely curved RC beams.

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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Modeling sequential preparation with rheumatoid tonsils in Nineveh for the period 2004-2009
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Abstract
             In this research will be treated with a healthy phenomenon has a significant impact on different age groups in the community, but a phenomenon tonsillitis where they will be first Tawfiq model slope self moving averages seasonal ARMA Seasonal through systematic Xbox Cengnzla counter with rheumatoid tonsils in the city of Mosul, and for the period 2004-2009 with prediction of these numbers coming twelve months, has found that the specimen is the best representation of the data model is the phenomenon SARMA (1,1) * (2,1) 12  from the other side and explanatory variables using a maximum temperature and minimum temperature, sol

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Publication Date
Wed Dec 23 2020
Journal Name
2020 International Conference On Advanced Science And Engineering (icoase)
A Comparative Study Using LZW with Wavelet or DCT for Compressing Color Images
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As a result of the significance of image compression in reducing the volume of data, the requirement for this compression permanently necessary; therefore, will be transferred more quickly using the communication channels and kept in less space in memory. In this study, an efficient compression system is suggested; it depends on using transform coding (Discrete Cosine Transform or bi-orthogonal (tap-9/7) wavelet transform) and LZW compression technique. The suggested scheme was applied to color and gray models then the transform coding is applied to decompose each color and gray sub-band individually. The quantization process is performed followed by LZW coding to compress the images. The suggested system was applied on a set of seven stand

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Publication Date
Sun Nov 01 2020
Journal Name
2020 2nd Annual International Conference On Information And Sciences (aicis)
An Enhanced Multi-Objective Evolutionary Algorithm with Decomposition for Signed Community Detection Problem
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Publication Date
Wed Nov 02 2022
Journal Name
Turkish Journal Of Computer And Mathematics Education (turcomat)
Mpeg-Dash System via HTTP2 Protocol with HEVC Encoder for Video Streaming Services
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MPEG-DASH is an adaptive bitrate streaming technology that divides video content into small HTTP-objects file segments with different bitrates. With live UHD video streaming latency is the most important problem. In this paper, creating a low-delay streaming system using HTTP 2.0. Based on the network condition the proposed system adaptively determine the bitrate of segments. The video is coded using a layered H.265/HEVC compression standard, then is tested to investigate the relationship between video quality and bitrate for various HEVC parameters and video motion at each layer/resolution. The system architecture includes encoder/decoder configurations and how to embedded the adaptive video streaming. The encoder includes compression besi

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Publication Date
Tue Jul 01 2014
Journal Name
Int. J. Eng. Ra
Pressure Gradient Influence on MHD Flow for Generalized Burgers’ Fluid with Slip Condition
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This paper presents a research for magnetohydrodynamic (MHD) flow of an incompressible generalized Burgers’ fluid including by an accelerating plate and flowing under the action of pressure gradient. Where the no – slip assumption between the wall and the fluid is no longer valid. The fractional calculus approach is introduced to establish the constitutive relationship of the generalized Burgers’ fluid. By using the discrete Laplace transform of the sequential fractional derivatives, a closed form solutions for the velocity and shear stress are obtained in terms of Fox H- function for the following two problems: (i) flow due to a constant pressure gradient, and (ii) flow due to due to a sinusoidal pressure gradient. The solutions for

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Publication Date
Sun Jan 01 2017
Journal Name
Iec2017 Proceedings Book
Improving TF-IDF with Singular Value Decomposition (SVD) for Feature Extraction on Twitter
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Publication Date
Mon Dec 21 2020
Journal Name
2020 Emerging Technology In Computing, Communication And Electronics (etcce)
An Integrated Grey Wolf Optimizer with Nelder-Mead Method for Workflow Scheduling Problem
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Publication Date
Sun Feb 03 2019
Journal Name
Journal Of The College Of Education For Women
Emotional deprivation and its relation with the behavioral and nervous problems for adolescents
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Publication Date
Fri Sep 01 2023
Journal Name
The Medical Journal Of Malaysia
Serum interleukin-40: an innovative diagnostic biomarker for patients with systemic lupus erythematosus
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Scopus
Publication Date
Wed Oct 09 2024
Journal Name
Engineering, Technology & Applied Science Research
Improving Pre-trained CNN-LSTM Models for Image Captioning with Hyper-Parameter Optimization
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

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