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Image Compression Based on Arithmetic Coding Algorithm
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The past years have seen a rapid development in the area of image compression techniques, mainly due to the need of fast and efficient techniques for storage and transmission of data among individuals. Compression is the process of representing the data in a compact form rather than in its original or incompact form. In this paper, integer implementation of Arithmetic Coding (AC) and Discreet Cosine Transform (DCT) were applied to colored images. The DCT was applied using the YCbCr color model. The transformed image was then quantized with the standard quantization tables for luminance and chrominance. The quantized coefficients were scanned by zigzag scan and the output was encoded using AC. The results showed a decent compression ratio with high image quality.

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Publication Date
Tue Jan 01 2019
Journal Name
Ieee Access
Sensing Performance of Modified Single Mode Optical Fiber Coated With Nanomaterials-Based Ammonia Sensors Operated in the C-Band
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Publication Date
Wed Aug 30 2023
Journal Name
Iraqi Journal Of Science
Efficient Cloud-Based Resource Sharing Through Multi-Tenancy and Load Balancing: An Exploration of Higher Education and Digital Libraries
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      Cloud computing has gained considerable attention in academia and industry in recent years. The cloud facilitates data sharing and enables cost efficiency, thus playing a vital role today as well as for the foreseeable future. In this paper, a brief discussion the application of multi-tenant and load-balancing technologies to cloud-based digital resource sharing suitable for academic and digital libraries is presented. As a new paradigm for digital resource sharing, a proposal of improving the current user service model with private cloud storage for other sectors, including the medical and financial fields is offered. This paper gives a summary of cloud computing and its possible applications, combined with digital data optim

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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
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
Fri May 12 2023
Journal Name
Bulletin Of The Chemical Society Of Ethiopia
SYNTHESIS, CHARACTERIZATION, ANTIMICROBIAL STUDIES, AND MOLECULAR DOCKING STUDIES OF TRANSITION METAL COMPLEXES FORMED FROM A BENZOTHIAZOLE-BASED AZO LIGAND
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The azo ligand obtained from the diazotization reaction of 2-aminobenzothiazole and 4- nitroaniline yielded a novel series of complexes with Co(II), Ni(II), Cu(II), and Zn(II) ions. The complexes were investigated using spectral techniques such as UV-Vis, FT-IR, 1H and 13C NMR spectroscopic analyses, LC-MS and atomic absorption spectrometry, electrical conductivity, and magnetic susceptibility. The molar ratio of the synthesized compounds was determined using the ligand exchange ratio, which revealed the metal-ligand ratios in the isolated complexes were 1:2. The synthesized complexes were tested for antimicrobial activity against S. aureus, E. coli, C. albicans, and C. tropicalis bacterial species. Additionally, their binding affinities we

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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
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
Sat Apr 30 2022
Journal Name
Revue D'intelligence Artificielle
Performance Evaluation of SDN DDoS Attack Detection and Mitigation Based Random Forest and K-Nearest Neighbors Machine Learning Algorithms
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne

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Publication Date
Wed Nov 23 2022
Journal Name
Dental Hypotheses
Remineralization of Dentine Caries Using Moringa Oleifera Based Nano-Silver Fluoride: A Single-Blinded, Randomized, Active-Controlled Clinical Trial
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Publication Date
Wed Aug 30 2023
Journal Name
Baghdad Science Journal
Deep Learning-based Predictive Model of mRNA Vaccine Deterioration: An Analysis of the Stanford COVID-19 mRNA Vaccine Dataset
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The emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA

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