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Artificial Intelligence Techniques to Identify Individuals through Palm Image Recognition
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Artificial intelligence (AI) is entering many fields of life nowadays. One of these fields is biometric authentication. Palm print recognition is considered a fundamental aspect of biometric identification systems due to the inherent stability, reliability, and uniqueness of palm print features, coupled with their non-invasive nature. In this paper, we develop an approach to identify individuals from palm print image recognition using Orange software in which a hybrid of AI methods: Deep Learning (DL) and traditional Machine Learning (ML) methods are used to enhance the overall performance metrics. The system comprises of three stages: pre-processing, feature extraction, and feature classification or matching. The SqueezeNet deep learning model was utilized to resize images and feature extraction. Finally, different ML classifiers have been tested for recognition based on the extracted features. The effectiveness of each classifier was assessed using various performance metrics. The results show that the proposed system works well, and all the methods achieved good results; however, the best results obtained were for the Support Vector Machine (SVM) with a linear kernel.

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Publication Date
Mon Nov 01 2021
Journal Name
Energy Reports
Global solar radiation prediction over North Dakota using air temperature: Development of novel hybrid intelligence model
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Publication Date
Sat Mar 01 2025
Journal Name
Water, Air, & Soil Pollution
Adsorptive Performance of High Surface Area Date Palm Bunch Activated Carbon Towards Methyl Violet and Fuchsin Basic Dyes Removal: Thermochemical Activation And Statistical Optimization
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Herein, date palm (Phoenix dactylifera) bunch (DPB) waste was transformed into activated carbon (DPAC) adsorbent by using microwaveinduced ZnCl2 activation for 15 min at a power of 600 W. Several analytical methods were used to explain the physicochemical parameters of DPBAC including XRD, pHpzc, BET, SEM–EDX, and FTIR. Afterwards, the adsorptive performance of DPBAC was thoroughly investigated for the removal of two structurally different organic dyes namely methyl violet (MV) and fuchsin basic (FB). The key adsorption parameters, including the dose of DPBAC (A: 0.02–0.06 g), the solution pH (B: 4–10), and the contact time (C: 2–20 min) were statistically optimized using the Box-Behnken design with response surface methodology (RSM

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Publication Date
Wed Mar 05 2025
Journal Name
Water, Air, & Soil Pollution
Adsorptive Performance of High Surface Area Date Palm Bunch Activated Carbon Towards Methyl Violet and Fuchsin Basic Dyes Removal: Thermochemical Activation And Statistical Optimization
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Publication Date
Tue Jun 12 2018
Journal Name
المجلة العراقية لبحوث السوق وحماية المستهلك
BIOLOGICAL ASPECTS AND PREDATORY EFFICIENY OF PREDATOR Chilocorus bipustulatus (L.) COLEOPTERA :COCCINELLIDAE ON DATE PALM SCALE Parlatoria blanchardi (T.) DIASPIDIDAE: HOMOPTERA UNDER LABORATORY CONDITIONS.
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Laboratory studies were conducted at the biological control unit, college of Agriculture, University of Baghdad to evaluate some biological aspects of the predator Chilocorus bipustulatus (Coleoptera: Coccinellidae), which is considered one of the most important predators on many insect pests, especially the scale insect, Parlatoria blanchardi, (Homoptera: Diaspididae) on date palms. The results showed that biological parameters of the predator were varied according to different degree of temperature. Egg incubation period was significantly different and reached to 7.5 and 5.44 day at 25 and 30°C respectively, Fertility was the same 100% at both temperature degrees. Larval growth periods were 17.41 and 16.12 day as well as the mortality du

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Publication Date
Thu May 03 2001
Journal Name
Master's Thesis
The image of the United States of America in the Iraqi press
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Publication Date
Sun Jun 30 2024
Journal Name
Iraqi Journal Of Science
Gray-Scale Image Compression Method Based on a Pixel-Based Adaptive Technique
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     Today in the digital realm, where images constitute the massive resource of the social media base but unfortunately suffer from two issues of size and transmission, compression is the ideal solution. Pixel base techniques are one of the modern spatially optimized modeling techniques of deterministic and probabilistic bases that imply mean, index, and residual. This paper introduces adaptive pixel-based coding techniques for the probabilistic part of a lossy scheme by incorporating the MMSA of the C321 base along with the utilization of the deterministic part losslessly. The tested results achieved higher size reduction performance compared to the traditional pixel-based techniques and the standard JPEG by about 40% and 50%,

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Publication Date
Tue Dec 07 2021
Journal Name
2021 14th International Conference On Developments In Esystems Engineering (dese)
Content Based Image Retrieval Based on Feature Fusion and Support Vector Machine
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Publication Date
Sun Sep 05 2010
Journal Name
Baghdad Science Journal
Effect of Partial Coherence illuminated bar on evaluation technique of diffraction image
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In this work, we are obviously interested in a general solution for the calculation of the image of a single bar in partially coherent illumination. The solution is based on the theory of Hopkins for the formation of images in optical instruments in which it was shown that for all practical cases, the illumination of the object may be considered as due to a self – luminous source placed at the exit pupil of the condenser , and the diffraction integral describing the intensity distribution in the image of a single bar – as an object with half – width (U0 = 8 ) and circular aperture geometry is viewed , which by suitable choice of the coherence parameters (S=0.25,1.0.4.0) can be fitted to the observed distribution in various types of mi

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Publication Date
Sun Oct 05 2025
Journal Name
Mesopotamian Journal Of Computer Science
DGEN: A Dynamic Generative Encryption Network for Adaptive and Secure Image Processing
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Cyber-attacks keep growing. Because of that, we need stronger ways to protect pictures. This paper talks about DGEN, a Dynamic Generative Encryption Network. It mixes Generative Adversarial Networks with a key system that can change with context. The method may potentially mean it can adjust itself when new threats appear, instead of a fixed lock like AES. It tries to block brute‑force, statistical tricks, or quantum attacks. The design adds randomness, uses learning, and makes keys that depend on each image. That should give very good security, some flexibility, and keep compute cost low. Tests still ran on several public image sets. Results show DGEN beats AES, chaos tricks, and other GAN ideas. Entropy reached 7.99 bits per pix

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Publication Date
Sat Jun 01 2024
Journal Name
Journal Of Engineering
Copy Move Image Forgery Detection using Multi-Level Local Binary Pattern Algorithm
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Digital image manipulation has become increasingly prevalent due to the widespread availability of sophisticated image editing tools. In copy-move forgery, a portion of an image is copied and pasted into another area within the same image. The proposed methodology begins with extracting the image's Local Binary Pattern (LBP) algorithm features. Two main statistical functions, Stander Deviation (STD) and Angler Second Moment (ASM), are computed for each LBP feature, capturing additional statistical information about the local textures. Next, a multi-level LBP feature selection is applied to select the most relevant features. This process involves performing LBP computation at multiple scales or levels, capturing textures at different

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