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Deep Spoof Face Detection Techniques in React Native
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The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimizing deep learning models to operate efficiently on mobile devices, (2) ensuring real-time inference without compromising accuracy, (3) maintaining user privacy when processing sensitive facial data, and (4) addressing the variability in mobile phone cameras, input resolution, and platform limitations across Android and iOS. Furthermore, the increasing sophistication of identity spoofing attacks—such as 3D masks and AI-generated faces—demands more sophisticated, robust, and multimodal detection technologies. The research findings provide a clear roadmap toward practical solutions. By evaluating the latest deep learning architectures, datasets, and anti-spoofing metrics, the study proposes a comprehensive React Native deployment path using TensorFlow Lite and TensorFlow.js to ensure cross-platform compatibility. The proposed system offers a unified classification of identity spoofing attacks and defense mechanisms, along with a structured evaluation framework that compares on-device processing with server-side detection. The results demonstrate that optimized models can achieve high accuracy, low false accept/rejection rates, and sub-second processing speeds on mobile devices. Ultimately, the study provides practical design guidelines for building robust, privacy-preserving, efficient, and real-world consumer-grade fake face detection systems.

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Publication Date
Fri May 01 2026
Journal Name
Microchemical Journal
Modification of screen-printed carbon electrode through nanocomposite ZIF-67/MoO3 in Deep eutectic solvent water mixtures to enhance fentanyl sensitivity
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Publication Date
Sat Jan 31 2026
Journal Name
International Journal Of Intelligent Engineering And Systems
Low-complexity Deep Learning for Joint Channel-type Identification and SNR Estimation in MIMO-OFDM Using CNN–BRNN with LUT Labels
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Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T

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Publication Date
Fri Dec 30 2011
Journal Name
Al-kindy College Medical Journal
The Role of the Use of Low Molecular Weight Heparin in the Prevention of Deep Venous Thrombosis after Total Knee Arthroplasty
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Background A prospective clinical study was
performed to compare the efficacy of the use of lowmolecular-
weight heparin group (enoxparin group)
with control group in the prevention of deep-vein
thrombosis after total knee arthroplasty.
Aim of the study: to assess the prevalence of DVT
after total knee arthroplasty and evaluate the
importance of the use of low molecular weight
heparin in the prevention of this DVT.
Methods Thirty-three patients undergoing total
knee arthroplasty were randomly divided into two
groups. One group consisted of 12 patients who
received no prophylaxis with an anticoagulant (the
control group), other group consisted of 21 patients
who received the low-molecular-weight h

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Publication Date
Sun Oct 19 2025
Journal Name
Lecture Notes In Networks And Systems
Artificial Intelligence Techniques in the Geographical Analysis of Under-Five Child Mortality in the Central Euphrates Provinces for the Year 2022
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Abstract This research adopted a novel mixed-method approach combining quantitative analysis and geospatial statistics with artificial intelligence (AI) techniques to evaluate U5MR in the Middle Euphrates provinces of Iraq in 2022. We investigated spatial patterns, socioeconomic determinants and health system factors related to child mortality, Using data from the Iraqi Ministry of Health in 2022. We uncovered significant disparities across the regions, where the highest death rate in Al Diwaniyah province was 33.1 per 1000 and dropped to 16.6 per 1000 live births in al-Muthanna province. An exhaustive statistical analysis brought to the fore the main factors that accounted for such a variation, that is to say population density in rural a

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Publication Date
Mon Oct 01 2012
Journal Name
International Journal Of Recent Scientific Research
DETECTION OF LTH, FSH AND LH HORMONE LEVEL IN PREGNANT WOMEN INFECTED WITH TOXOPLASMA GONDII
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Infection with the protozoan parasite Toxoplasma gondii is widely prevalent in humans and animals. Infection with Toxoplasma may associate with miscarriage in many pregnant women due to infection. In this study, the level of lutetropic hormone (LTH), folliclestimulating hormone (FSH) and luteinizing hormone (LH) was measured in pregnant women suffering from toxoplasmosis using mini-VIDAS®technique. Results showed that pregnant women have high concentration of both LTH and FSH hormone(10.80 ± 6.53) ng/ml and (9.51 ± 2.40) μIU/ml respectively, while the concentration of LH hormone was lower than normal(4.49 ± 0.56) μIU/ml. Such finding is to suggest that infection with T. gondii is interfering with these hormones in pregnant women.

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Publication Date
Sat Oct 03 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Validity of Hounsfield Units from computed tomographic images of mandibular bone in detection of osteoporosis
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Background: The figure for the clinical application of computed tomography have been increased significantly in oral and maxillofacial field that supply the dentists with sufficient data enables them to play a main role in screening osteoporosis, therefore Hounsfield units of mandibular computed tomography view used as a main indicator to predict general skeleton osteoporosis and fracture risk factor. Material and Methods: Thirty subjects (7 males &23 females) with a mean age of (60.1) years underwent computed tomographic scanning for different diagnostic assessment in head and neck region. The mandibular bone quality of them were determined through Hounsfield units of CT scan images and were correlated with the bone mineral density v

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Publication Date
Fri Jan 01 2021
Journal Name
Biochemical Cellular Archive
detection of anti-helicobacter pylori cag a antibody in sera of patients with eye diseases
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The study conducted to investigate the association between Helicobacter pylori infection and eye diseases (Glaucoma, Cataract, CSR and Uveitis). One hundred and four patients with multiple eye disorders (10-80) years were observed from 10/9/2020 to 18/11/2020 and compared to thirty-one healthy people (19 female and 12 male). Each participant was tested for H. pylori CagAAbs and TNF-α using an enzyme-linked immunosorbent assay (ELISA). The results have shown that there was a non-significant difference (p≥0.05) in the concentration of CagAantibodies in sera of patients with eye diseases except in the case of CSR (central serous chorioretinopathy), which was a significant difference (P≤0.05) compared to the control group. Also, the result

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Publication Date
Thu Jun 29 2023
Journal Name
Journal Of University Of Babylon For Pure And Applied Sciences
Genetic Detection of IMP-1 Gene and its Relationship with Biofilm Formation in Klebsiella pneumonia
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Background: Klebsiella pneumoniae were considered as normal flora of skin, and intestine. It can cause damage to human lungs; the danger of this bacterium is related to exposure to the hospital surroundings. materials and methods: the detection of Klebsiella pneumoniae on morphological and biochemical tests and then assured with VITEK 2 system. Resistance to antibiotics was determined by Kirby-Baeur method. And genotyping of IMP-1 in isolates was done by PCR technique, then biofilm formation was identified by Micro titer plate method. Results: The present study included a collecting of 50 specimens from different clinical specimens, (blood 40%, urine 30%, sputum 20%, wound infection 10%); 10 isolates were identified as K

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Publication Date
Thu Apr 18 2019
Journal Name
Al-kindy College Medical Journal
Basal cell markers:34BE12 and p63, improving detection of basal cells in atypical prostatic lesions
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Background: The diagnosis of prostatic pathology may be of challenging , as some  difficult and suspected, atypical  cases may lack basal cell layer by routine H&E sections . Antibodies against 34BE12(HMW-CK) and p63 aid the diagnosis of such cases , to distinguish benign from  malignant prostatic lesions.

Objective: to identify basal cells in atypical prostatic lesions ,and distinguish benign from malignant prostatic lesions.

Type of the study:  A retro-spective  study.

Methods:  115cases of  paraffin embedded prostatic tissue blocks ,diagnosed as : 76 cases were benign prostatic hy

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Crossref
Publication Date
Sat Jan 01 2022
Journal Name
Iranian Journal Of Earth Sciences
Resistivity surveys application for detection of shallow caves in a case example from Western Iraq
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