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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 use of Gray Level Co-occurrence Matrix (GLCM) features and DBN classifier provides 98.26% accuracy with the two specific classes were tested. Improvements/Applications: AD is a neurological condition affecting the brain and causing dementia that may affect the mind and memory. The disease indirectly impacts more than 15 million relatives, companions and guardians. The results of the present research are expected to help the specialist in decision making process.

Publication Date
Wed Dec 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
The efficiency of Using Attribute and Performance- Based Activity Methods to Raise the Level of Control Deviation A field study in Jaber Bin Hayyan Factory
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Cost is the essence of any production process for it is one of the requirements for the continuity of activities so as to increase the profitability of the economic unit and to support the competitive situation in the market. Therefore, there should be an overall control to reduce the cost without compromising the product quality; to achieve this, the management should have detailed credible and reliable information about the cost to be measured, collected, understood and to analyze the causes for the spread of deviations and obstacles the management faces, and to search for the factors that trigger the emergence of these deviations and obstacles

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Publication Date
Fri Jan 01 2021
Journal Name
Ieee Access
Real Time <i>in Situ</i> Remote Monitoring for Cladding Modified SMF Integrating Nanocomposite Based Ammonia Sensors Deploying EDFA
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Publication Date
Fri Aug 02 2024
Journal Name
Farmacia
SOLUPLUS AND SOLUTOL HS-15 OLMESARTAN MEDOXOMIL NANOMICELLE BASED ORAL FAST DISSOLVING FILM: IN VITRO AND IN VIVO CHARACTERIZATION
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Olmesartan medoxomil (OM) has low bioavailability and limited solubility. To enhance bioavailability, fast dissolving films (FDF) with mixed micelles of soluplus (SPL) and solutol HS15 (STL H15) were developed using solvent casting. The optimised formula, FM2, used polyvinyl alcohol (PVA) and showed high entrapment efficiency, rapid disintegration, and significant improvement in OM bioavailability compared to the market tablet (Olmetec®). FM2 also demonstrated stability and potential for enhanced drug delivery.

Publication Date
Sun Apr 30 2023
Journal Name
Al-kindy College Medical Journal
Comparison between Reference Infliximab (Remicade) and its Biosimilar (Remsima) in Patients with Ankylosing Spondylitis: A Field-based Pharmacoeconomic Study
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Background: Ankylosing spondylitis is a chronic inflammatory disease that mostly involves the spine and sacroiliac joints. It is associated with a decreased quality of life. Biological medicines such as infliximab and its biosimilar are the mainstay treatments for active ankylosing spondylitis.

Objective: The study objective was to conduct a pharmacoeconomic study comparing the cost-effectiveness of the reference infliximab with its biosimilar in ankylosing spondylitis patients visiting public hospitals.

Subjects and Method: This is a two-center pharmacoeconomic study performed at two large teaching governmental hospitals in Baghdad, Iraq, which s

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Publication Date
Mon Jun 30 2025
Journal Name
Acta Logistica
A business continuity-based framework for risk management in smart supply chains: a fuzzy multi-criteria decision-making approach
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The aim of this study is to develop a novel framework for managing risks in smart supply chains by enhancing business continuity and resilience against potential disruptions. This research addresses the growing uncertainty in supply chain environments, driven by both natural phenomena-such as pandemics and earthquakes—and human-induced events, including wars, political upheavals, and societal transformations. Recognizing that traditional risk management approaches are insufficient in such dynamic contexts, the study proposes an adaptive framework that integrates proactive and remedial measures for effective risk mitigation. A fuzzy risk matrix is employed to assess and analyze uncertainties, facilitating the identification of disr

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Publication Date
Thu Aug 01 2019
Journal Name
Nanomedicine: Nanotechnology, Biology And Medicine
Listeria innocua Dps as a nanoplatform for bioluminescence based photodynamic therapy utilizing Gaussia princeps luciferase and zinc protoporphyrin IX
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Publication Date
Wed Oct 30 2024
Journal Name
Internet Technology Letters
Using <scp>5G</scp> Standards for Smart Healthcare Applications and Designing an Artificial Intelligence‐Based Industry 4.0 Communication System
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ABSTRACT<p>The introduction of Industry 4.0, to improve Internet of Things (IoT) standards, has sparked the creation of 5G, or highly sophisticated wireless networks. There are several barriers standing in the way of 5G green communication systems satisfying the expectations for faster networks, more user capacity, lower resource consumption, and cost‐effectiveness. 5G standards implementation would speed up data transmission and increase the reliability of connected devices for Industry 4.0 applications. The demand for intelligent healthcare systems has increased globally as a result of the introduction of the novel COVID‐19. Designing 5G communication systems presents research problems such as optimizing </p> ... Show More
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Publication Date
Fri Mar 31 2023
Journal Name
Oncology And Radiotherapy
The Effect of Green Low Laser (LLL) on the white blood cells on platelet on people on brain and prostate cancer
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The effect of Low-Level Laser (LLL) provided by green semiconductor laser with an emission wavelength of 532 nm on of human blood of people with brain and prostate cancer has been investigated. The effect of LLL on white blood cell (WBC), NEUT, LYMPH and MONO have been considered. Platelet count (PLT) has also been considered in this work. 2 ml of blood sample were irradiating by a green laser of the dose of 4.8 J/cm2. The results suggest a potential effect of LLL on WBC, PLT, NEUT, LYMPH, and MONO of people with brain and prostate cancer Key words: white blood cell , platelet , low-level laser therapy

Publication Date
Thu Jan 04 2024
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The impact of performance based costing technology in measuring the cost of consulting services : (an applied study in the Office of Scientific and Consulting Services - University of Technology
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             This research aims to apply the Performance Focused Activity Based Costing System in the offices of scientific and advisory services at the University of Technology for the purpose of measuring the cost of services provided by these offices in order to reduce costs. To test the hypothesis of the research, the research was applied in the consulting offices of the University of Technology through the financial statements for the year ending 12/31/2017 of the Scientific and Consulting Services Office of the University of Technology, because the data of these years were issued and audited by the Federal Office of Financial Supervision.

A number of

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Economics And Administrative Sciences
Comparison of the method of partial least squares and the algorithm of singular values decomposion to estimate the parameters of the logistic regression model in the case of the problem of linear multiplicity by using the simulation
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The logistic regression model is an important statistical model showing the relationship between the binary variable and the explanatory variables.                                                        The large number of explanations that are usually used to illustrate the response led to the emergence of the problem of linear multiplicity between the explanatory variables that make estimating the parameters of the model not accurate.    

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