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AlexNet Convolutional Neural Network Architecture with Cosine and Hamming Similarity/Distance Measures for Fingerprint Biometric Matching
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In information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compared to traditional image filtering techniques. This paper aimed to utilize a specific CNN architecture known as AlexNet for the fingerprint-matching task. Using such an architecture, this study has extracted the significant features of the fingerprint image, generated a key based on such a biometric feature of the image, and stored it in a reference database. Then, using Cosine similarity and Hamming Distance measures, the testing fingerprints have been matched with a reference. Using the FVC2002 database, the proposed method showed a False Acceptance Rate (FAR) of 2.09% and a False Rejection Rate (FRR) of 2.81%. Comparing these results against other studies that utilized traditional approaches such as the Fuzzy Vault has demonstrated the efficacy of CNN in terms of fingerprint matching. It is also emphasizing the usefulness of using Cosine similarity and Hamming Distance in terms of matching.

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Publication Date
Sat Jun 01 2024
Journal Name
Results In Engineering
Electrochemical preparation and characterization of a new configuration SnO2 anode and its application for treating petroleum refinery wastewater
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Publication Date
Fri Apr 01 2022
Journal Name
International Journal Of Hydrogen Energy
Assessment of wettability and rock-fluid interfacial tension of caprock: Implications for hydrogen and carbon dioxide geo-storage
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Publication Date
Thu Jan 30 2020
Journal Name
Neuroquantology
HOMO-LUMO Energies and Geometrical Structures Effecton Corrosion Inhibition for Organic Compounds Predict by DFT and PM3 Methods
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A theoretical study on corrosion inhibitors was done by quantum calculations includes semi-empirical PM3 and Density Functional Theory (DFT) methods based on B3LYP/6311++G (2d,2P). Benzimidazole derivative (oxo(4- ((phenylcarbamothioyl) carbamoyl)phenyl) ammonio) oxonium (4NBP) and thiourea derivative 2-((4- bromobenzyl)thio) -1H-benzo[d] imidazole (2SB) were used as corrosion inhibitors and an essential quantum chemical parameters correlated with inhibition efficiency, EHOMO (highest occupied molecular orbital energy) and ELUMO (lowest molecular orbital energy). Other parameters are also studied like energy gap [ΔE (HOMO-LUMO)], electron affinity (EA), hardness (Δ), dipole moment (μ), softness (S), ionization potential (IE), absolut

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Publication Date
Sat Aug 09 2025
Journal Name
Scientific Reports
Machine learning models for predicting morphological traits and optimizing genotype and planting date in roselle (Hibiscus Sabdariffa L.)
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Accurate prediction and optimization of morphological traits in Roselle are essential for enhancing crop productivity and adaptability to diverse environments. In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. The dataset was generated from a field experiment involving ten Roselle genotypes and five planting dates. Both RF and MLP exhibited robust predictive capabilities; however, RF (R² = 0.84) demonstrated superior performance compared to MLP (R² = 0.80), underscoring its efficacy in capturing the nonlinear genoty

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Publication Date
Fri Dec 01 2017
Journal Name
Journal Of Economics And Administrative Sciences
A comparison between Bayesian Method and Full Maximum Likelihood to estimate Poisson regression model hierarchy and its application to the maternal deaths in Baghdad
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Abstract:

 This research aims to compare Bayesian Method and Full Maximum Likelihood to estimate hierarchical Poisson regression model.

The comparison was done by  simulation  using different sample sizes (n = 30, 60, 120) and different Frequencies (r = 1000, 5000) for the experiments as was the adoption of the  Mean Square Error to compare the preference estimation methods and then choose the best way to appreciate model and concluded that hierarchical Poisson regression model that has been appreciated Full Maximum Likelihood Full Maximum Likelihood  with sample size  (n = 30) is the best to represent the maternal mortality data after it has been reliance value param

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Publication Date
Sun Sep 07 2014
Journal Name
Baghdad Science Journal
Organic Content in the Sediments of Tigris and Diyala Rivers, south of Baghdad, and its Relationship with some Environmental factors, Benthic Invertebrates Groups and Values of Diversity Indices
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This study was conducted to detect the relationship between organic content in the sediment of Rivers Tigris and Diyala, at two locations south of Baghdad, with some environmental factors and the benthic invertebrates and values of diversity indices. Monthly samples collected from the area for the period November 2007 to October 2008. Results showed differences in the physical and chemical characteristics of the two sites, Where the annual average in Tigris and Diyala were respectively for: water temperature (19, 20) C°, pH (8, 8), dissolved oxygen (4, 8) mg / l , Biochemical oxygen Demand BOD5 (3,44 ) mg/l, TDS (632,1585) mg / l, TSS (42, 44) mg / l, turbidity (28,74) NTU, and total hardness as CaCO3 (485,823) mg / l ,Sulfat

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Publication Date
Sun Dec 07 2014
Journal Name
Baghdad Science Journal
Synthesis and Spectral Analysis of Mn (II), Cu (II) ,Ni (II) and Cd (II) Complexes with Mixed Ligands containing 1,10-phenanthroline and Schiff base derived of 4-aminoantipyrine
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The complexes of Schiff base of 4-aminoantipyrine and 1,10-phenanthroline with metal ions Mn (II), Cu (II), Ni (II) and Cd (II) were prepared in ethanolic solution, these complexes were characterized by Infrared , electronic spectra, molar conductance, Atomic Absorption ,microanalysis elemental and magnetic moment measurements. From these studies the tetrahedral geometry structure for the prepared complexes were suggested.The prepared ligand of 4-aminoantipyrine was characterized by using Gc-mass spectrometer .

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Publication Date
Wed Jul 08 2009
Journal Name
Diala Journal
Synthesis and Spectral Analysis of VO(II),Cr (III) , Zn(II),Cd(II),Hg(II)and UO2(II) Complexes with Mixed Ligands of Bipyridyl and Novl Schiff Base
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Salicylaldehyde was react with 4-amino-2,3-dimethyl-1-phenyl-3-Pyrazoline-5-on to produce the novel Schiff base ligand 2,3-dimethyl-1-phenyl-4-salicylidene-3-pyrazoline-5-on (HL). A new complexes of VO(II), Cr(Ш), Zn(II), Cd(II), Hg(II) and UO2(II) with mixed ligands of bipyridyl and new shiff base ( 2,3-dimethyl-1-phenyl-4-salicylidene-3-pyrazoline-5-on) (HL) were prepared . All prepared compounds were identified by atomic absorption, FT.IR , UV-Visable spectra and molar conductivity. From the above data, the proposed molecular structure for VO(II) complex is squre pyramidal while (Zn(II), Cd(II), Hg(II)) and ( UO2(II),Cr(III)) complexes are forming tetrahedral and octahedral geometry respectively.

Publication Date
Mon Mar 31 2025
Journal Name
International Journal Of Advanced Technology And Engineering Exploration
Breast cancer survival rate prediction using multimodal deep learning with multigenetic features
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Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Economics And Administrative Sciences
The adoption of ISO 45001: 2018 in the civil aviation establishment test and its accessibility to the standard
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The current research aims to analyze the extent of the adoption of the standards of ISO 45001: 2018 for occupational safety and health management by the General Establishment of Civil Aviation. The research problem was the extent to which the General Establishment of Civil Aviation approved ISO 45001: 2018 for occupational safety and health management. The questionnaire was used as a primary data collection tool, the sample was distributed (50) form, they were selected from the category of employees of the establishment at different levels to represent the research community. Data were analyzed using the statistical package (SPSS), a number of vector statistical methods were used as well as arithmetic mean, standard deviation, an

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