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Intelligent System for Parasitized Malaria Infection Detection Using Local Descriptors
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Malaria is a curative disease, with therapeutics available for patients, such as drugs that can prevent future malaria infections in countries vulnerable to malaria. Though, there is no effective malaria vaccine until now, although it is an interesting research area in medicine. Local descriptors of blood smear image are exploited in this paper to solve parasitized malaria infection detection problem. Swarm intelligence is used to separate the red blood cells from the background of the blood slide image in adaptive manner. After that, the effective corner points are detected and localized using Harris corner detection method. Two types of local descriptors are generated from the local regions of the effective corners which are Gabor based features and color based features. The extracted features are finally fed to Deep Belief Network (DBN) for classification purpose. Different tests were performed and different combinations of feature types are attempted. The achieved results showed that when using combined vectors of local descriptors, the system gives the desired accuracy which is 100%. The achieved result demonstrates the effectiveness of using local descriptors in solving malaria infection detection problem.

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Publication Date
Mon Jun 01 2020
Journal Name
Journal Of Planner And Development
An Analytical Study for Urban Gentrification on Local Urban Centers
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The urban Gentrification  is an inclusive global phenomenon to restructure the cities on the overall levels, the research to propose a specific study about the concept of urban Gentrification in the cities and showcasing its, specifications, and results, and how to deal with the variables that occur on cities through improvements as part of urban renewal projects, then the general axis of the research is shrinked, choosing the urban centers as the most important areas that deal with the urban Gentrification process due to its direct connection with indivisuals and social changes, and to process the specific axis of the research theses and studies will be showcased that discuss the topic in different research directions, and emerged

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Publication Date
Tue Mar 30 2021
Journal Name
Baghdad Science Journal
Local Dependence for Bivariate Weibull Distributions Created by Archimedean Copula
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In multivariate survival analysis, estimating the multivariate distribution functions and then measuring the association between survival times are of great interest. Copula functions, such as Archimedean Copulas, are commonly used to estimate the unknown bivariate distributions based on known marginal functions. In this paper the feasibility of using the idea of local dependence to identify the most efficient copula model, which is used to construct a bivariate Weibull distribution for bivariate Survival times, among some Archimedean copulas is explored. Furthermore, to evaluate the efficiency of the proposed procedure, a simulation study is implemented. It is shown that this approach is useful for practical situations and applicable fo

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Publication Date
Tue Dec 05 2023
Journal Name
Baghdad Science Journal
A Novel System for Confidential Medical Data Storage Using Chaskey Encryption and Blockchain Technology
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Secure storage of confidential medical information is critical to healthcare organizations seeking to protect patient's privacy and comply with regulatory requirements. This paper presents a new scheme for secure storage of medical data using Chaskey cryptography and blockchain technology. The system uses Chaskey encryption to ensure integrity and confidentiality of medical data, blockchain technology to provide a scalable and decentralized storage solution. The system also uses Bflow segmentation and vertical segmentation technologies to enhance scalability and manage the stored data. In addition, the system uses smart contracts to enforce access control policies and other security measures. The description of the system detailing and p

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Publication Date
Sun Jul 20 2025
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Using a 3D Chaotic Dynamic System as a Random Key Generator for Image Steganography
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In today's digital era, the importance of securing information has reached critical levels. Steganography is one of the methods used for this purpose by hiding sensitive data within other files. This study introduces an approach utilizing a chaotic dynamic system as a random key generator, governing both the selection of hiding locations within an image and the amount of data concealed in each location. The security of the steganography approach is considerably improved by using this random procedure. A 3D dynamic system with nine parameters influencing its behavior was carefully chosen. For each parameter, suitable interval values were determined to guarantee the system's chaotic behavior. Analysis of chaotic performance is given using the

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Publication Date
Mon Jan 28 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The role of local tax revenues in financing local development: Case Study of Tebessa State for the Period[2010-2014[
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Local communities are in need of self-resources so that they can perform their multiple functions which serve the objectives of the local development, and tax revenues are considered as important sources of their funding. However, despite the efforts of the state to reform the fiscal system and to improve the management in the local administration, tax collection can increase when the state adopts a more effective policy to combat tax evasion and tax fraud. Accordingly, this research aims to shed light on the role of local tax revenues in the local development. A set of conclusions are drawn; the most important one is that Algeria, in order to achieve local development, has taken a set of reforms, which are still valid until now. The mos

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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
COVID-19 Diagnosis System using SimpNet Deep Model
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After the outbreak of COVID-19, immediately it converted from epidemic to pandemic. Radiologic images of CT and X-ray have been widely used to detect COVID-19 disease through observing infrahilar opacity in the lungs. Deep learning has gained popularity in diagnosing many health diseases including COVID-19 and its rapid spreading necessitates the adoption of deep learning in identifying COVID-19 cases. In this study, a deep learning model, based on some principles has been proposed for automatic detection of COVID-19 from X-ray images. The SimpNet architecture has been adopted in our study and trained with X-ray images. The model was evaluated on both binary (COVID-19 and No-findings) classification and multi-class (COVID-19, No-findings

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Publication Date
Sat Apr 02 2022
Journal Name
The International Conference On Science In Engineering And Technology (icosiet) 2020 (virtually)
The Possible Application of Intelligent Systems in Traditional Courtyard House.
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Publication Date
Mon Feb 01 2021
Journal Name
International Journal Of Electrical And Computer Engineering (ijece)
Differential evolution detection models for SMS spam
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With the growth of mobile phones, short message service (SMS) became an essential text communication service. However, the low cost and ease use of SMS led to an increase in SMS Spam. In this paper, the characteristics of SMS spam has studied and a set of features has introduced to get rid of SMS spam. In addition, the problem of SMS spam detection was addressed as a clustering analysis that requires a metaheuristic algorithm to find the clustering structures. Three differential evolution variants viz DE/rand/1, jDE/rand/1, jDE/best/1, are adopted for solving the SMS spam problem. Experimental results illustrate that the jDE/best/1 produces best results over other variants in terms of accuracy, false-positive rate and false-negative

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Publication Date
Sun Mar 01 2020
Journal Name
Iraqi Journal Of Physics
Blood Vessels Detection of Diabetic Retinopathy from Retinal Fundus Image using Image Processing Techniques
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Early detection of eye diseases can forestall visual deficiency and vision loss. There are several types of human eye diseases, for example, diabetic retinopathy, glaucoma, arteriosclerosis, and hypertension. Diabetic retinopathy (DR) which is brought about by diabetes causes the retinal vessels harmed and blood leakage in the retina. Retinal blood vessels have a huge job in the detection and treatment of different retinal diseases. Thus, retinal vasculature extraction is significant to help experts for the finding and treatment of systematic diseases. Accordingly, early detection and consequent treatment are fundamental for influenced patients to protect their vision. The aim of this paper is to detect blood vessels from

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Publication Date
Tue Aug 31 2021
Journal Name
Al-kindy College Medical Journal
Assessment of the Effects of SARS-Cov-2 Infection on Multiple Organs Using Laboratory Indices
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Background: Severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2) is still a severe threaft for human health currently, and the researches about it is a focus topic worldwide.

Aim of the study: In this study, we will collect some laboratory results of the patients with coronavirus disease (COVID-19) to assess the function of liver, heart, kidney and even pancreas. 

Subjects and Methods: Laboratory results of the patients with COVID-19 are collected. The biochemical indices are classified and used to assess the according function of liver, heart, kidney; meantime, and blood glucose is also observed and taken as an index to roughly evaluate pancreas.

Results: There were some in

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