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Multi-objectives TLBO hybrid method to select the related risk features with rheumatism disease
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Publication Date
Tue Aug 14 2018
Journal Name
International Journal Of Engineering & Technology
Hybrid DWT-DCT compression algorithm & a new flipping block with an adaptive RLE method for high medical image compression ratio
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Huge number of medical images are generated and needs for more storage capacity and bandwidth for transferring over the networks. Hybrid DWT-DCT compression algorithm is applied to compress the medical images by exploiting the features of both techniques. Discrete Wavelet Transform (DWT) coding is applied to image YCbCr color model which decompose image bands into four subbands (LL, HL, LH and HH). The LL subband is transformed into low and high frequency components using Discrete Cosine Transform (DCT) to be quantize by scalar quantization that was applied on all image bands, the quantization parameters where reduced by half for the luminance band while it is the same for the chrominance bands to preserve the image quality, the zig

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Publication Date
Wed Apr 01 2020
Journal Name
Medico-legal Update
Knowledge and protective health behaviors concerning risk factors for coronary heart disease among baghdad university students
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Publication Date
Wed Oct 21 2015
Journal Name
Integrated Journal Of Engineering Research And Technology
A HYBRID CUCKOO SEARCH AND BACK-PROPAGATION ALGORITHMS WITH DYNAMIC LEARNING RATE TO SPEED UP THE CONVERGENCE (SUBPL) ALGORITHM
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BP algorithm is the most widely used supervised training algorithms for multi-layered feedforward neural net works. However, BP takes long time to converge and quite sensitive to the initial weights of a network. In this paper, a modified cuckoo search algorithm is used to get the optimal set of initial weights that will be used by BP algorithm. And changing the value of BP learning rate to improve the error convergence. The performance of the proposed hybrid algorithm is compared with the stan dard BP using simple data sets. The simulation result show that the proposed algorithm has improved the BP training in terms of quick convergence of the solution depending on the slope of the error graph.

Publication Date
Thu Jan 20 2022
Journal Name
Webology
Hybrid Intrusion Detection System based on DNA Encoding, Teiresias Algorithm and Clustering Method
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Until recently, researchers have utilized and applied various techniques for intrusion detection system (IDS), including DNA encoding and clustering that are widely used for this purpose. In addition to the other two major techniques for detection are anomaly and misuse detection, where anomaly detection is done based on user behavior, while misuse detection is done based on known attacks signatures. However, both techniques have some drawbacks, such as a high false alarm rate. Therefore, hybrid IDS takes advantage of combining the strength of both techniques to overcome their limitations. In this paper, a hybrid IDS is proposed based on the DNA encoding and clustering method. The proposed DNA encoding is done based on the UNSW-NB15

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Publication Date
Mon Aug 01 2022
Journal Name
Baghdad Science Journal
Accurate Four-Step Hybrid Block Method for Solving Higher-Order Initial Value Problems
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This paper focuses on developing a self-starting numerical approach that can be used for direct integration of higher-order initial value problems of Ordinary Differential Equations. The method is derived from power series approximation with the resulting equations discretized at the selected grid and off-grid points. The method is applied in a block-by-block approach as a numerical integrator of higher-order initial value problems. The basic properties of the block method are investigated to authenticate its performance and then implemented with some tested experiments to validate the accuracy and convergence of the method.

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Advance Science And Technology
MR Images Classification of Alzheimer's Disease Based on Deep Belief Network Method
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Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
Solutions and Recent Challenges Related to Energy in Wireless Body Area Networks with Integrated Technologies: Applications and Perspectives
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          In this paper, we have investigated some of the most recent energy efficient routing protocols for wireless body area networks. This technology has seen advancements in recent times where wireless sensors are injected in the human body to sense and measure body parameters like temperature, heartbeat and glucose level. These tiny wireless sensors gather body data information and send it over a wireless network to the base station. The data measurements are examined by the doctor or   physician and the suitable cure is suggested. The whole communication is done through routing protocols in a network environment. Routing protocol consumes energy while helping non-stop communic

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Publication Date
Tue Feb 28 2017
Journal Name
Journal Of Engineering
Contributory Factors Related to Permanent Deformation of Hot Asphalt Mixtures
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Permanent deformation (Rutting) of asphalt  pavements which appears in many roads in Iraq, have caused a major impact on pavement performance by reducing the useful service life of pavement and creating services hazards for highway users. The main objective of this research is investigating the effect of some contributory factors related to permanent deformation of asphalt concrete mixture. To meet the objectives of this research, available local materials are used including asphalt binder, aggregates, mineral filler and modified asphalt binder. The Superpave mix design system was adopted with varying volumetric compositions. The Superpave Gyratory Compactor was used to compact 24 asphalt concrete cylindrical specimens. To collect t

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Publication Date
Tue Jan 01 2013
Journal Name
The Iraqi Journal Of Agricultural Sciences
GENETIC VARIATION OF SOME OAT TRAITS RELATED TO WATER SALINITY
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Salinity of soil or irrigation water is one of the most important obstacle towards crop production and productivity, especially with the increasing scarcity of fresh water in Iraq and the Arab countries. The impact of salinity will be alleviated with the increasing temperature due to global warming. The objectives of this article was to shed some light on traits more related to salinity stress tolerance in oats, and to identify genetic variation of these traits. A split-plot arrangement experiment with RCBD was applied through 2011-2013 on the farm of Dept. of Field Crops/Coll. of Agric./Univ. of Baghdad. The oats cultivars; Hamel, Pimula and Genzania were set in sub-plots, whereas water quality was set in main-plots. Water quality had two

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Publication Date
Thu Aug 01 1996
Journal Name
Unpublished
Temporomandibular disorders in pretreatment orthodontic patients as related to malocclusion
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Temporomandibular disorders (TMDs) were investigated in 143 pretreatment orthodontic patients (43 males and 102 females) whose age ranged between 10-25 years at the College of Dentistry, University of Baghdad, Iraq. The study was undertaken to elucidate the prevalence and severity of TMDs in malocclusion patients and to defme the relationships between malocclusion and TMDs. The clinical signs and subjective symptoms were recorded according to the principles introduced by Helkimo (1974b). Subjective symptoms were reported by 65.7% of the patients with 22.40/0 described as severe, and the most common symptoms were TMJ sounds and feeling offatigue. Clinical signs were observed in 81.8% of the sample with 22.4 and 6.3% described as moderate and

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