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Human Face Recognition Using Wavelet Network
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            This paper presents a study of wavelet self-organizing maps (WSOM) for face recognition. The WSOM is a feed forward network that estimates optimized wavelet based for the discrete wavelet transform (DWT) on the basis of the distribution of the input data, where wavelet basis transforms are used as activation function.

 

 

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
Biosynthesis, Characterization, Adsorption and Antimicrobial studies of Vanadium Oxide Nanoparticles Using Punica Granatum Extract
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This study includes using green or biosynthesis-friendly technology, which is effective in terms of low cost and low time and energy to prepare V2O5NPs nanoparticles from vanadium sulfate VSO4.H2O using aqueous extract of Punica Granatum at a concentration of 0.1M and with a basic medium PH= 8-12. The V2O5NPs nanoparticles were diagnosed using several techniques, such as FT-IR, UV-visible with energy gap Eg = 3.734eV, and the X-Ray diffraction XRD was calculated using the Debye Scherrer equation. It was discovered to be 34.39nm, Scanning Electron Microscope (SEM), Transmission Electron Microscopy TEM. The size, structure, and composition of synthetic V2O5

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Publication Date
Fri Mar 31 2017
Journal Name
Al-khwarizmi Engineering Journal
Big-data Management using Map Reduce on Cloud: Case study, EEG Images' Data
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Database is characterized as an arrangement of data that is sorted out and disseminated in a way that allows the client to get to the data being put away in a simple and more helpful way. However, in the era of big-data the traditional methods of data analytics may not be able to manage and process the large amount of data. In order to develop an efficient way of handling big-data, this work studies the use of Map-Reduce technique to handle big-data distributed on the cloud. This approach was evaluated using Hadoop server and applied on EEG Big-data as a case study. The proposed approach showed clear enhancement for managing and processing the EEG Big-data with average of 50% reduction on response time. The obtained results provide EEG r

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Publication Date
Sun Mar 01 2020
Journal Name
Baghdad Science Journal
Mobile-based Telemedicine Application using SVD and F-XoR Watermarking for Medical Images
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A medical- service platform is a mobile application through which patients are provided with doctor’s diagnoses based on information gleaned from medical images. The content of these diagnostic results must not be illegitimately altered during transmission and must be returned to the correct patient. In this paper, we present a solution to these problems using blind, reversible, and fragile watermarking based on authentication of the host image. In our proposed algorithm, the binary version of the Bose_Chaudhuri_Hocquengham (BCH) code for patient medical report (PMR) and binary patient medical image (PMI) after fuzzy exclusive or (F-XoR) are used to produce the patient's unique mark using secret sharing schema (SSS). The patient’s un

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Publication Date
Sun Dec 01 2013
Journal Name
Journal Of Economics And Administrative Sciences
Evoluation of service system in the general eduction Baghdad hospital using Q GERT
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That the essential contribution of this research is a description of how complex systems analysis service of the properties of the queue in Baghdad Teaching Hospital using a technique network is techniques method (Q - GERT) an acronym of the words:

Queuing theory _ Graphical Evaluation and Review Technique

Any method of assessment and review chart where you will be see the movement flow of patients within the system and after using this portal will be represented system in the form of planned network probabilistic analysis and knowledge of statistical distributions appropriate for times of arrival and departure were using the program ready (Win QSB) and simulatio

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Publication Date
Sun Dec 30 2012
Journal Name
Al-kindy College Medical Journal
Initial Recognition and Prophecy of Diabetic Nephropathy in Type I Diabetes in a Sample of Iraqi Patients
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Back ground: Diabetic nephropathy is rapidly becoming the leading cause of end-stage renal disease (ESRD). The onset and course of DN can be ameliorated to a very significant degree if intervention institutes at a point very early in the course of the development of this complication.
Objective: The aim of this study was to characterize risk factors associated with nephropathy in type I diabetes and construct a module for early prediction of diabetic nephropathy (DN) by analyzing their risk factors.
Methods: Case control design of 400 patients with type I diabetes mellitus (IDDM), aged 19-45 years. The cases were 200 diabetic patients with overt protein urea while the controls were 200 diabetic patients with no protein urea or micr

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Publication Date
Tue Jan 01 2019
Journal Name
Ieee Access
Intelligent EMG Pattern Recognition Control Method for Upper-Limb Multifunctional Prostheses: Advances, Current Challenges, and Future Prospects
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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Future of Mathematical Modelling: A Review of COVID-19 Infected Cases Using S-I-R Model
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The spread of novel coronavirus disease (COVID-19) has resulted in chaos around the globe. The infected cases are still increasing, with many countries still showing a trend of growing daily cases. To forecast the trend of active cases, a mathematical model, namely the SIR model was used, to visualize the spread of COVID-19. For this article, the forecast of the spread of the virus in Malaysia has been made, assuming that all Malaysian will eventually be susceptible. With no vaccine and antiviral drug currently developed, the visualization of how the peak of infection (namely flattening the curve) can be reduced to minimize the effect of COVID-19 disease. For Malaysians, let’s ensure to follow the rules and obey the SOP to lower the

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Planner And Development
Mapping Paddy Rice Fields Using Landsat and Sentinel Radar Images in Urban Areas for Agriculture Planning
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     This research develops a new method based on spectral indices and random forest classifier to detect paddy rice areas and then assess their distributions regarding to urban areas. The classification will be conducted on Landsat OLI images and Landsat OLI/Sentinel 1 SAR data. Consequently, developing a new spectral index by analyzing the relative importance of Landsat bands will be calculated by the random forest. The new spectral index has improved depending on the most three important bands, then two additional indices including the normalized difference vegetation index (NDVI), and standardized difference built-up index (NDBI) have been used to extract paddy rice fields from the data. Several experiments being

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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
Sun Aug 10 2025
Journal Name
Journal Of Medicinal Plants And By-products
Harnessing Medicinal Plants and Their By-products to Combat Fungal Pathogens in the Face of Climate Change: Implications for Global Food Security
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This study investigates the impacts of climate change (CC) on the emergence and proliferation of fungal pathogens, with a particular focus on global food security and the potential of medicinal plants and their by-products as sustainable mitigation strategies. Through a systematic literature review of articles published up to 2024, we analyze how CC exacerbates the spread and severity of fungal diseases in crops, leading to significant agricultural losses and threats to food availability. The findings highlight that, alongside conventional approaches such as genetic resistance and precision farming, bioactive compounds derived from medicinal plants and their by-products offer promising, eco-friendly alternatives for the management of fungal

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