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High-accuracy models for iris recognition with merging features
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Due to advancements in computer science and technology, impersonation has become more common. Today, biometrics technology is widely used in various aspects of people's lives. Iris recognition, known for its high accuracy and speed, is a significant and challenging field of study. As a result, iris recognition technology and biometric systems are utilized for security in numerous applications, including human-computer interaction and surveillance systems. It is crucial to develop advanced models to combat impersonation crimes. This study proposes sophisticated artificial intelligence models with high accuracy and speed to eliminate these crimes. The models use linear discriminant analysis (LDA) for feature extraction and mutual information (MI), along with analysis of variance (ANOVA) for feature selection. Two iris classification systems were developed: one using LDA as an input for the OneR machine learning algorithm and another innovative hybrid model based on a One Dimensional Convolutional Neural Network (HM-1DCNN). The MMU database was employed, achieving a performance measure of 94.387% accuracy for the OneR model. Additionally, the HM-1DCNN model achieved 99.9% accuracy by integrating LDA with MI and ANOVA. Comparisons with previous studies show that the HM-1DCNN model performs exceptionally well, with at least 1.69% higher accuracy and lower processing time.

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Publication Date
Fri Dec 31 2021
Journal Name
Iraqi Journal Of Laser
Parametric Optimization for Fatigue Life of 6061-T6 Aluminum Thin Sheets Processed with High-Speed Laser Shock Peening
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Abstract: Aluminum alloys grade 6061-T6 are characterized by their excellent properties and processing characteristics which make them ideal for varieties of industrial applications under cyclic loading, aluminum alloys show less fatigue life than steel alloys of similar strength. In the current study, a nanosecond fiber laser of maximum pulse energy up to 9.9 mJ was used to apply laser shock peening process (LSP) on aluminum thin sheets to introduce residual stresses in order to enhance fatigue life under cyclic loading Box-Behnken design (BBD) based on the design of experiments (DOE) was employed in this study for experimental design data analysis, model building and optimization The effect of working parameters spot size (ω), scannin

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Publication Date
Wed Mar 18 2020
Journal Name
Baghdad Science Journal
A Hybrid Method of Linguistic and Statistical Features for Arabic Sentiment Analysis
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          Sentiment analysis refers to the task of identifying polarity of positive and negative for particular text that yield an opinion. Arabic language has been expanded dramatically in the last decade especially with the emergence of social websites (e.g. Twitter, Facebook, etc.). Several studies addressed sentiment analysis for Arabic language using various techniques. The most efficient techniques according to the literature were the machine learning due to their capabilities to build a training model. Yet, there is still issues facing the Arabic sentiment analysis using machine learning techniques. Such issues are related to employing robust features that have the ability to discrimina

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Publication Date
Sat Jan 23 2021
Journal Name
Neural Computing And Applications
Multi-objectives TLBO hybrid method to select the related risk features with rheumatism disease
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Publication Date
Thu Aug 01 2019
Journal Name
International Journal Of Machine Learning And Computing
Emotion Recognition System Based on Hybrid Techniques
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Emotion recognition has important applications in human-computer interaction. Various sources such as facial expressions and speech have been considered for interpreting human emotions. The aim of this paper is to develop an emotion recognition system from facial expressions and speech using a hybrid of machine-learning algorithms in order to enhance the overall performance of human computer communication. For facial emotion recognition, a deep convolutional neural network is used for feature extraction and classification, whereas for speech emotion recognition, the zero-crossing rate, mean, standard deviation and mel frequency cepstral coefficient features are extracted. The extracted features are then fed to a random forest classifier. In

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Publication Date
Sun Mar 26 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Potentiometric Transducers for the Selective Recognition of Risperidone Based on Molecularly Imprinted Polymer
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          Graphite Coated Electrodes (GCE) based on molecularly imprinted polymers were fabricated for the selective potentiometric determination of Risperidone (Ris). The molecularly imprinted (MIP) and nonimprinted (NIP) polymers were synthesized by bulk polymerization using (Ris.) as a template, acrylic acid (AA) and acrylamide (AAm) as monomers, ethylene glycol dimethacrylate (EGDMA) as a cross-linker and benzoyl peroxide (BPO) as an initiator. The imprinted membranes and the non-imprinted membranes were prepared using dioctyl phthalate (DOP) and Dibutylphthalate (DBP) as plasticizers in PVC matrix. The membranes were coated on graphite electrodes. The MIP electrodes using

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Publication Date
Wed Jan 01 2020
Journal Name
Journal Of Southwest Jiaotong University
A Recognition System for Subjects' Signature Using the Spatial Distribution of Signature Body
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This investigation proposed an identification system of offline signature by utilizing rotation compensation depending on the features that were saved in the database. The proposed system contains five principle stages, they are: (1) data acquisition, (2) signature data file loading, (3) signature preprocessing, (4) feature extraction, and (5) feature matching. The feature extraction includes determination of the center point coordinates, and the angle for rotation compensation (θ), implementation of rotation compensation, determination of discriminating features and statistical condition. During this work seven essential collections of features are utilized to acquire the characteristics: (i) density (D), (ii) average (A), (iii) s

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Publication Date
Sat Aug 02 2025
Journal Name
Engineering, Technology & Applied Science Research
A New Method for Face-Based Recognition Using a Fuzzy Face Deep Model
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Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security

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Publication Date
Sun Dec 01 2024
Journal Name
Chilean Journal Of Statistics
A method of multi-dimensional variable selection for additive partial linear models.
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In high-dimensional semiparametric regression, balancing accuracy and interpretability often requires combining dimension reduction with variable selection. This study intro- duces two novel methods for dimension reduction in additive partial linear models: (i) minimum average variance estimation (MAVE) combined with the adaptive least abso- lute shrinkage and selection operator (MAVE-ALASSO) and (ii) MAVE with smoothly clipped absolute deviation (MAVE-SCAD). These methods leverage the flexibility of MAVE for sufficient dimension reduction while incorporating adaptive penalties to en- sure sparse and interpretable models. The performance of both methods is evaluated through simulations using the mean squared error and variable selection cri

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Publication Date
Tue Jan 09 2024
Journal Name
Wasit Journal Of Sports Sciences
A Comparative Analytical Study of Some Biomechanical Variables and Their Relationship to The Accuracy of The Performance of The Shooting Skill of Jumping High in The Weak and Strong Foot the Players for Youth Handball
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The research aims to identify the most important variables affecting shooting from jumping high and compare them for the two foot the weak and strong, where the researchers adopted the descriptive method, and the sample was chosen by the intentional method, which consists of (4) players from the Iraqi Sports Army Club, where these variables were studied and their impact on The accuracy of aiming at the two men, and the researchers concluded that most of the players have more accuracy in aiming at the strong leg than at the weak leg, which leads to the loss of many real opportunities during the match because of the players changing the situation or wasting the available opportunity when the position of correction is an opportunity for the w

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Publication Date
Thu Feb 01 2024
Journal Name
Baghdad Science Journal
A New Green Approach of CFIA Technique for Direct Assay with a High Throughput of Sulfamethoxazole Drugs Using Condensation Reaction with NQS Agent
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A new design of manifold flow injection (FI) coupling with a merging zone technique was studied for sulfamethoxazole determination spectrophotometrically. The semiautomated FI method has many advantages such as being fast, simple, highly accurate, economical with high throughput . The suggested method based on the production of the orange- colored compound of SMZ with (NQS)1,2-Naphthoquinone-4-Sulphonic acid Sodium salt in alkaline media NaOH at λmax 496nm.The linearity range of sulfamethoxazole was  3-100  μg. mL-1, with (LOD) was 0.593 μg. mL-1 and the RSD% is about 1.25 and the recovery is 100.73%. All various physical and chemical parameters that have an effect on the stability and development of

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