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Offline Signature Verification Based on Neural Network
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The investigation of signature validation is crucial to the field of personal authenticity. The biometrics-based system has been developed to support some information security features.Aperson’s signature, an essential biometric trait of a human being, can be used to verify their identification. In this study, a mechanism for automatically verifying signatures has been suggested. The offline properties of handwritten signatures are highlighted in this study which aims to verify the authenticity of handwritten signatures whether they are real or forged using computer-based machine learning techniques. The main goal of developing such systems is to verify people through the validity of their signatures. In this research, images of a group of signatures, numbering 70 images, were used. Image preprocessing steps were performed on them, and their features were extracted using the median filter. After that, the eigenvector and eigenvalue were calculated using the PCA algorithm. Then the backpropagation neural network algorithm was applied for training and testing where the performance reached 6.7995e−07 for 82 epochs and the accuracy was 99.98%.

Publication Date
Mon Jul 01 2024
Journal Name
Journal Of Food Process Engineering
Artificial intelligence‐based modeling of novel non‐thermal milk pasteurization to achieve desirable color and predict quality parameters during storage
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Abstract<sec><label></label><p>This study proposed using color components as artificial intelligence (AI) input to predict milk moisture and fat contents. In this sense, an adaptive neuro‐fuzzy inference system (ANFIS) was applied to milk processed by moderate electrical field‐based non‐thermal (NP) and conventional pasteurization (CP). The differences between predicted and experimental data were not significant (<italic>p</italic> > 0.05) for lightness (<italic>L</italic>*), redness‐greenness (<italic>a</italic>*), yellowness‐blueness (<italic>b</italic>*), total color differences (∆<italic>E</italic>), hue angle (<italic>h</italic></p></sec> ... Show More
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Publication Date
Thu Oct 01 2015
Journal Name
International Journal Of Modern Trends In Engineering And Research (ijmter)
Effect of changing hidden neurons and activation function on Back Propagation (BP) Speed
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The Back-Propagation (BP) is the best known and widely used learning algorithm in training multiple neural network. A vast variety of improvements to BP algorithm have been proposed since ninety’s. in this paper, the effects of changing the number of hidden neurons and activation equation are investigated. According to the simulation results, the convergence speed have been improved and become much faster by the previous two modifications on the BP algorithm.

Publication Date
Wed Jun 26 2019
Journal Name
Journal Of Mechanics Of Continua And Mathematical Sciences
VSM Based Models and Integration of Exact and Fuzzy Similarity For Improving Detection of External Textual Plagiarism admin June 29, 2019
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Publication Date
Sat Nov 30 2024
Journal Name
Asia Pacific Journal Of Molecular Biology And Biotechnology
Random amplified polymorphic DNA-based polymerase chain reaction is an effective tool to examine the genotoxic effects of some food colors
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A large number of natural or synthetic dyes have been removed from both national and international lists of permitted food colors because of their mutagenic or carcinogenic activity. Therefore, this study aimed to use the Random Amplified Polymorphic DNA-Based Polymerase Chain Reaction (RAPD-PCR) assay as a feasible method to evaluate the ability of some food colors as genotoxin-induced DNA damage and mutations. Lactiplantibacillus plantarum was used as a bioindicator to determine the genotoxic effects by RAPD-PCR using M13 primer after treatment with some synthetic dyes currently used as food color additives, including Sunset Yellow, Carmoisine, and Tartrazine. Besides qualitative analysis, the bioinformatic GelJ software was used for clus

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Publication Date
Tue Sep 30 2025
Journal Name
Gsc Advanced Research And Reviews
A comprehensive review of metal-organic framework based biosensors for detection of reactive oxygen species and hydrogen peroxide in biomedical applications
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Metal-organic frameworks (MOFs) have emerged as revolutionary materials for developing advanced biosensors, especially for detecting reactive oxygen species (ROS) and hydrogen peroxide (H₂O₂) in biomedical applications. This comprehensive review explores the current state-of-the-art in MOF-based biosensors, covering fundamental principles, design strategies, performance features, and clinical uses. MOFs offer unique benefits, including exceptional porosity (up to 10,400 m²/g), tunable structures, biocompatibility, and natural enzyme-mimicking properties, making them ideal platforms for sensitive and selective detection of ROS and H₂O₂. Recent advances have shown significant improvements in detection capabilities, with limit

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Publication Date
Sun Aug 28 2022
Journal Name
Geodesy And Cartography
OBJECT-BASED APPROACHES FOR LAND USE-LAND COVER CLASSIFICATION USING HIGH RESOLUTION QUICK BIRD SATELLITE IMAGERY (A CASE STUDY: KERBELA, IRAQ)
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Land Use / Land Cover (LULC) classification is considered one of the basic tasks that decision makers and map makers rely on to evaluate the infrastructure, using different types of satellite data, despite the large spectral difference or overlap in the spectra in the same land cover in addition to the problem of aberration and the degree of inclination of the images that may be negatively affect rating performance. The main objective of this study is to develop a working method for classifying the land cover using high-resolution satellite images using object based method. Maximum likelihood pixel based supervised as well as object approaches were examined on QuickBird satellite image in Karbala, Iraq. This study illustrated that

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Publication Date
Tue Mar 21 2023
Journal Name
Biomedical And Pharmacology Journal
Development and Validation of HPLC Method For the Detection of Fusidic Acid Loaded in Non-ionic and Cationic Nanoemulsion-Based Gels
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Fusidic acid (FA) is a well-known pharmaceutical antibiotic used to treat dermal infections. This experiment aimed for developing a standardized HPLC protocol to determine the accurate concentration of fusidic acid in both non-ionic and cationic nano-emulsion based gels. For this purpose, a simple, precise, accurate approach was developed. A column with reversed-phase C18 (250 mm x 4.6 mm ID x 5 m) was utilized for the separation process. The main constituents of the HPLC mobile phase were composed of water: acetonitrile (1: 4); adjusted at pH 3.3. The flow rate was 1.0 mL/minute. The optimized wavelength was selected at 235 nm. This approach achieved strong linearity for alcoholic solutions of FA when loaded at a serial concentrati

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Publication Date
Thu Dec 01 2022
Journal Name
Baghdad Science Journal
Determination of Nickel and Cobalt in Cosmetic Products Marketed in Iraq Using Spectrophotometric and Microfluidic Paper-based Analytical Device (µPADs) Platform
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Two quantitative, environment-friendly and easily monitored assays for Ni (II) and Co (III) ions analysis in different lipstick samples collected from 500-Iraqi dinars stores located in Baghdad were introduced. The study was based on the reaction of nickel (II) ions with dimethylglyoxime (DMG) reagent and the reaction of cobalt (III) ions with 1-nitroso-2-naphthol (NN) reagent to produce colored products. The color change was measured by spectrophotometric method at 565 nm and 430 nm for Ni and Co, respectively, with linear calibration graphs in the concentration range 0.25-100 mg L-1 (Ni) and 0.5-100 mg L-1 (Co) and LOD and LOQ of 0.11 mg L-1 and 0.36 mg L-1 (Ni), and 0.15 mg L-1 an

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Publication Date
Wed Feb 27 2013
Journal Name
Asean Journal For Science And Engineering In Materials
ASTM F75 Alloys: A Systematic Review of Microstructural Characteristics and Manufacturing Advances from Conventional to Laser-Based Techniques with Bibliometric Analysis
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This study provides a systematic and bibliometric review of ASTM F75 cobalt–chromium alloys, focusing on microstructure and the shift from conventional to laser-based manufacturing. Using combined analytical methods, it evaluates microstructure, mechanical properties, corrosion behavior, and biocompatibility. Results show that laser-based techniques such as LPBF and DMLS produce finer grain sizes (1–10 µm vs. 50–200 µm), leading to improved hardness (20–40%) and tensile strength (15–30%). Despite challenges like residual stress and process optimization, these methods show strong potential for high-performance and sustainable applications.

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Publication Date
Sat Feb 01 2025
Journal Name
Pharmaceutical Nanotechnology
Preparation, <i>In-vitro, Ex-vivo</i>, and Pharmacokinetic Study of Lasmiditan as Intranasal Nanoemulsion-based <i>In Situ</i> Gel
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Background:

Lasmiditan (LAS) is a recently developed antimigraine drug and was approved in October, 2019 for the treatment of acute migraines; however, it suffers from low oral bioavailability, which is around 40%.

Objective:

This study aimed to improve the LAS bioavailability via formulation as nanoemulsionbased in situ gel (NEIG) given intranasally and then compare the traditional aqueous-LASsuspension (AQS) with the two successful intranasal prepared formulations (NEIG 2 and NEIG 5) in order to determine its relative bioavailability (F-relative) via using rabbits.

Method:
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