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Fast Fractal Technique using Modified Moment Features on Domain Blocks
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In this research, a new technique is suggested to reduce the long time required by the encoding process by using modified moment features on domain blocks. The modified moment features were used in accelerating the matching step of the Iterated Function System (IFS). The main disadvantage facing the fractal image compression (FIC) method is the over-long encoding time needed for checking all domain blocks and choosing the least error to get the best matched domain for each block of ranges. In this paper, we develop a method that can reduce the encoding time of FIC by reducing the size of the domain pool based on the moment features of domain blocks, followed by a comparison with threshold (the selected  threshold based on experience is 0.0001). The experiment was conducted on three images with size of 512x512 pixel, resolution of 8 bits/pixel, and different block size (4x4, 8x8 and, 16x16 pixels). The resulted encoding time (ET) values achieved by the proposed method were 41.53, 39.06, and  38.16 sec, respectively, for boat , butterfly, and house images of block size 4x4 pixel.  These values were compared with those obtained by the traditional algorithm for the same images with the same block size, which were 1073.85, 1102.66, and 1084.92 sec, respectively. The results imply that the proposed algorithm could remarkably reduce the ET of the images in comparison with the traditional algorithm.

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Publication Date
Tue Jul 11 2017
Journal Name
The 39th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc'17)
Higuchi fractal dimension of the electroencephalogram as a biomarker for early detection of Alzheimer's disease
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It is widely accepted that early diagnosis of Alzheimer's disease (AD) makes it possible for patients to gain access to appropriate health care services and would facilitate the development of new therapies. AD starts many years before its clinical manifestations and a biomarker that provides a measure of changes in the brain in this period would be useful for early diagnosis of AD. Given the rapid increase in the number of older people suffering from AD, there is a need for an accurate, low-cost and easy to use biomarkers that could be used to detect AD in its early stages. Potentially, the electroencephalogram (EEG) can play a vital role in this but at present, no reliable EEG biomarker exists for early diagnosis of AD. The gradual s

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Publication Date
Sun Sep 03 2017
Journal Name
Baghdad Science Journal
Scale-Invariant Feature Transform Algorithm with Fast Approximate Nearest Neighbor
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There is a great deal of systems dealing with image processing that are being used and developed on a daily basis. Those systems need the deployment of some basic operations such as detecting the Regions of Interest and matching those regions, in addition to the description of their properties. Those operations play a significant role in decision making which is necessary for the next operations depending on the assigned task. In order to accomplish those tasks, various algorithms have been introduced throughout years. One of the most popular algorithms is the Scale Invariant Feature Transform (SIFT). The efficiency of this algorithm is its performance in the process of detection and property description, and that is due to the fact that

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Publication Date
Sun Jan 01 2023
Journal Name
Brazilian Dental Science
Effect of adhesive primer application on shear bond strength of self-adhesive cement to tooth structure and two different CAD/CAM milled blocks
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Publication Date
Sun Dec 01 2019
Journal Name
Baghdad Science Journal
Comparison of Some Suggested Estimators Based on Differencing Technique in the Partial Linear Model Using Simulation
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In this paper new methods were presented based on technique of differences which is the difference- based modified jackknifed generalized ridge regression estimator(DMJGR) and difference-based generalized  jackknifed ridge regression estimator(DGJR), in estimating the parameters of linear part of the partially linear model. As for the nonlinear part represented by the nonparametric function, it was estimated using Nadaraya Watson smoother. The partially linear model was compared using these proposed methods with other estimators based on differencing technique through the MSE comparison criterion in simulation study.

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Publication Date
Thu Jul 01 2021
Journal Name
Iraqi Journal Of Science
Irregular urban Expansion and Its Effects on Air Temperature over Baghdad City using Remote Sensing Technique
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Heat island is known as the increases in air temperature through large and industrial cities compared to surrounding rural areas. In this study, remote sensing technology is used to monitor and track thermal variations within the city center of Baghdad through Landsat satellite images and for the period from 2000 to 2015. Several processors and treatments were applied on these images using GIS 10.6 and ERDAS 2014, such as image correction and extraction, supervised classification, and selection of training samples. Urban areas detection was resulted from the supervised classification linked to the temperature readings of the surface taken from the thermal bands of satellite images. The results showed that the surface temperature of the c

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Publication Date
Wed Jul 17 2024
Journal Name
Journal Of Optics
Influence of concentration on optical and structural properties of zinc sulfide films using spray pyrolysis technique
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Publication Date
Sun Jan 01 2023
Journal Name
Advances In The Theory Of Nonlinear Analysis And Its Application
The Influence of the Magnetic Domain on The Peristaltic Motion of The Non-Newtonian Fluid in A Curved Tube
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Publication Date
Sun Nov 01 2020
Journal Name
Iop Conference Series
Modified PRESENT Encryption algorithm based on new 5D Chaotic system
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Cryptography is a major concern in communication systems. IoE technology is a new trend of smart systems based on various constrained devices. Lightweight cryptographic algorithms are mainly solved the most security concern of constrained devices and IoE systems. On the other hand, most lightweight algorithms are suffering from the trade-off between complexity and performance. Moreover, the strength of the cryptosystems, including the speed of the algorithm and the complexity of the system against the cryptanalysis. A chaotic system is based on nonlinear dynamic equations that are sensitive to initial conditions and produce high randomness which is a good choice for cryptosystems. In this work, we proposed a new five-dimensional of a chaoti

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Publication Date
Fri Nov 05 2021
Journal Name
Journal Of Architectural Environment & Structural Engineering Research
Strength & Conduct of Reinforced Concrete Corner Joint under Negative Moment Effect
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The aim of our study is to reveal the effect of steel reinforcement details,tensile steel reinforcement ratio, compressed reinforcing steel ratio,reinforcing steel size, corner joint shape on the strength of reinforcedconcrete Fc' and delve into it for the most accurate details and concreteconnections about the behavior and resistance of the corner joint ofreinforced concrete, Depending on the available studies and sources inaddition to our study, we concluded that each of these effects had a clearrole in the behavior and resistance of the corner joint of reinforced concreteunder the influence of the negative moment and yield stress. A studyof the types of faults that can be reinforced angle joints obtains detailsand conditions of c

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Publication Date
Sun Apr 30 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Fast Training Algorithms for Feed Forward Neural Networks
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 The aim of this paper, is to discuss several high performance training algorithms fall into two main categories. The first category uses heuristic techniques, which were developed from an analysis of the performance of the standard gradient descent algorithm. The second category of fast algorithms uses standard numerical optimization techniques such as: quasi-Newton . Other aim is to solve the drawbacks related with these training algorithms and propose an efficient training algorithm for FFNN

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