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The effect of using different fibres on the impact-resistance of slurry infiltrated fibrous concrete (SIFCON)
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Abstract<p>Slurry infiltrated fibrous concrete (SIFCON) is a modern type of fibre reinforced concrete (FRC). It has unique properties; SIFCON is superior in compressive strength, flexural strength, tensile strength, impact resistance, energy absorption and ductility. Because of this superiority in these characteristics, SIFCON was qualified for applications of special structures, which require resisting sudden dynamic loads such as explosions and earthquakes. The main aim of this investigation is to determine the effect of fibre type on the apparent density of SIFCON and on performance under impact load. In this investigation, hook-end steel fibre and polyolefin fibre were used. Purely once and hybrid in different portions again. After reviewing previous research, including [1, 2, 3] references three trail mixes were tested with a volume fraction of fibres (4, 6 and 8)%, and after testing them, a volume fraction of 6% was chosen. We chose the volume fraction of 6% and made the type of fibre the variable for comparison in this research. In hybrid fibres this fraction was divided once 2/3 steel fibres with 1/3 polyolefin fibres and vice versa. The specimens of the Impact resistance test were made with two specimens for each series, which are panels with dimensions of 50×50×5 cm. Three cubes were made for each series in the SIFCON apparent density test. Test results prove SIFCON produced from 2/3 polyolefin and 1/3 steel fibres achieved a good density reduction that contributes to reducing the self-weight of the structural element, which is a major aim in this investigation, reducing cost and maintaining high impact resistance.</p>
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Publication Date
Mon Jun 22 2020
Journal Name
Baghdad Science Journal
Using Evolving Algorithms to Cryptanalysis Nonlinear Cryptosystems
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            In this paper, new method have been investigated using evolving algorithms (EA's) to cryptanalysis one of the nonlinear stream cipher cryptosystems which depends on the Linear Feedback Shift Register (LFSR) unit by using cipher text-only attack. Genetic Algorithm (GA) and Ant Colony Optimization (ACO) which are used for attacking one of the nonlinear cryptosystems called "shrinking generator" using different lengths of cipher text and different lengths of combined LFSRs. GA and ACO proved their good performance in finding the initial values of the combined LFSRs. This work can be considered as a warning for a stream cipher designer to avoid the weak points, which may be f

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Publication Date
Tue Oct 27 2020
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
AUTOMATIC ARABIC KEYWORD EXTRACTION USING LOGISTIC REGRESSION
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Publication Date
Sun Sep 24 2023
Journal Name
Journal Of Al-qadisiyah For Computer Science And Mathematics
Human Recognition Using Ear Features: A Review
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Over the past few years, ear biometrics has attracted a lot of attention. It is a trusted biometric for the identification and recognition of humans due to its consistent shape and rich texture variation. The ear presents an attractive solution since it is visible, ear images are easily captured, and the ear structure remains relatively stable over time.  In this paper, a comprehensive review of prior research was conducted to establish the efficacy of utilizing ear features for individual identification through the employment of both manually-crafted features and deep-learning approaches. The objective of this model is to present the accuracy rate of person identification systems based on either manually-crafted features such as D

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Publication Date
Sun Mar 06 2011
Journal Name
Baghdad Science Journal
Numeral Recognition Using Statistical Methods Comparison Study
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The area of character recognition has received a considerable attention by researchers all over the world during the last three decades. However, this research explores best sets of feature extraction techniques and studies the accuracy of well-known classifiers for Arabic numeral using the Statistical styles in two methods and making comparison study between them. First method Linear Discriminant function that is yield results with accuracy as high as 90% of original grouped cases correctly classified. In the second method, we proposed algorithm, The results show the efficiency of the proposed algorithms, where it is found to achieve recognition accuracy of 92.9% and 91.4%. This is providing efficiency more than the first method.

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Publication Date
Thu Jul 01 2021
Journal Name
International Journal Of Nonlinear Analysis And Application
Forecasting enhancement using a hodrick-prescott filter
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: Sound forecasts are essential elements of planning, especially for dealing with seasonality, sudden changes in demand levels, strikes, large fluctuations in the economy, and price-cutting manoeuvres for competition. Forecasting can help decision maker to manage these problems by identifying which technologies are appropriate for their needs. The proposal forecasting model is utilized to extract the trend and cyclical component individually through developing the Hodrick–Prescott filter technique. Then, the fit models of these two real components are estimated to predict the future behaviour of electricity peak load. Accordingly, the optimal model obtained to fit the periodic component is estimated using spectrum analysis and Fourier mod

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Scopus
Publication Date
Sat Jul 28 2018
Journal Name
Journal Of Engineering
Enhanced Oil Recovery using Smart Water Injection
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Smart water flooding (low salinity water flooding) was mainly invested in a sandstone reservoir. The main reasons for using low salinity water flooding are; to improve oil recovery and to give a support for the reservoir pressure.

In this study, two core plugs of sandstone were used with different permeability from south of Iraq to explain the effect of water injection with different ions concentration on the oil recovery. Water types that have been used are formation water, seawater, modified low salinity water, and deionized water.

The effects of water salinity, the flow rate of water injected, and the permeability of core plugs have been studied in order to summarize the best conditions of low salinity

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Publication Date
Thu Jan 01 2015
Journal Name
International Journal Of Computer Science And Mobile Computing
Image Compression using Hierarchal Linear Polynomial Coding
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Publication Date
Sat Jan 01 2022
Journal Name
Turkish Journal Of Physiotherapy And Rehabilitation
classification coco dataset using machine learning algorithms
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In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho

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Publication Date
Tue Aug 01 2017
Journal Name
International Journal Of Advanced Research In Computer And Communication Engineering
Information hiding by using Developed M8PAM Technique
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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
Software Security using Aspect-Oriented Software Development
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Aspect-Oriented Software Development (AOSD) is a technology that helps achieving
better Separation of Concern (SOC) by providing mechanisms to identify all relevant points
in a program at which aspectual adaptations need to take place. This paper introduces a
banking application using of AOSD with security concern in information hiding.

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