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Lossy Image Compression Using Hybrid Deep Learning Autoencoder Based On kmean Clusteri
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Image compression plays an important role in reducing the size and storage of data while increasing the speed of its transmission through the Internet significantly. Image compression is an important research topic for several decades and recently, with the great successes achieved by deep learning in many areas of image processing, especially image compression, and its use is increasing Gradually in the field of image compression. The deep learning neural network has also achieved great success in the field of processing and compressing various images of different sizes. In this paper, we present a structure for image compression based on the use of a Convolutional AutoEncoder (CAE) for deep learning, inspired by the diversity of human eyes' observation of the different colors and features of images. We propose a multi-layer hybrid system for deep learning using the unsupervised CAE architecture and using the color clustering of the K-mean algorithm to compress images and determine their size and color intensity. The system is implemented using Kodak and Challenge on Learned Image Compression (CLIC) dataset for deep learning. Experimental results show that our proposed method is superior to the traditional compression methods of the autoencoder, and the proposed work has better performance in terms of performance speed and quality measures Peak Signal To Noise Ratio (PSNR) and Structural Similarity Index (SSIM) where the results achieved better performance and high efficiency With high compression bit rates and low Mean Squared Error (MSE) rate the results recorded the highest compression ratios that ranged between (0.7117 to 0.8707) for the Kodak dataset and (0.7191 to 0.9930) for CLIC dataset. The system achieved high accuracy and quality in comparison to the error coefficient, which was recorded (0.0126 to reach 0.0003) below, and this system is onsidered the most quality and accurate compared to the methods of deep learning compared to the deep learning methods of the autoencoder

Publication Date
Fri Jul 12 2024
Journal Name
Aaps Pharmscitech
Nanosuspension-Based Repaglinide Fast-Dissolving Buccal Film for Dissolution Enhancement
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Drug solubility and dissolution remain a significant challenge in pharmaceutical formulations. This study aimed to formulate and evaluate repanglinide (RPG) nanosuspension-based buccal fast-dissolving films (BDFs) for dissolution enhancement. RPG nanosuspension was prepared by the antisolvent-precipitation method using multiple hydrophilic polymers, including soluplus®, polyvinyl alcohol, polyvinyl pyrrolidine, poloxamers, and hydroxyl propyl methyl cellulose. The nanosuspension was then directly loaded into BDFs using the solvent casting technique. Twelve formulas were prepared with a particle size range of 81.6-1389 nm and PDI 0.002-1 for the different polymers. Nanosuspensions prepared with soluplus showed a favored mean particle size o

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Scopus (11)
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Publication Date
Sun Oct 01 2023
Journal Name
Baghdad Science Journal
Using VGG Models with Intermediate Layer Feature Maps for Static Hand Gesture Recognition
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A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

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Scopus (14)
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Publication Date
Wed Mar 16 2022
Journal Name
Journal Of Educational And Psychological Researches
The Degree to Which Princess Rahma University College Students Possess E-Learning Skills Related to Moodle from their Point of View, in Light of the Corona Crisis
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This study aims to identify the degree of students of Princess Rahma University College owning e-learning skills related to MOODLE as they perceived in the of light Corona crisis. The researchers' questionnaire consisted of (37) items, distributed in three areas of e-learning skills related to the MOODLE on (147) students were chosen randomly. The results of the study showed that the degree of students 'possession of e-learning skills related to the MOODLE was significant. The results also revealed that there were statistically significant differences in the degree of students' possession of electronic learning skills related to the MOODLE due to sex in favor of females. Finally, there were no statistically significant differences in the

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Publication Date
Wed Apr 01 2009
Journal Name
International Journal Of Applied Environmental Sciences
An expert System for Predicting the Effects of Noise Pollution on Grass Trimming Task Using Fuzzy Modeling
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Grass trimming operation is widely done in Malaysia for the purpose of maintaining highways. Large number of operators engaged in this work encounters high level of noise generated by back pack type grass trimmer used for this purpose. High level of noise exposure gives different kinds of ill effect on human operators. Exact nature of deteriorated work performance is not known. For predicting the work efficiency deterioration, fuzzy tool has been used in present research. It has been established that a fuzzy computing system will help in identification and analysis of fuzzy models fuzzy system offers a convenient way of representing the relationships between the inputs and outputs of a system in the form of IF-THEN rules. The paper presents

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Publication Date
Sat Oct 17 2026
Journal Name
Journal Mustansiriyah Of Sports Science
The Effect of Ocular Reflex Exercises Using a Proposed Device on Eyes - Hands Coordination for Junior Boxers
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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
Continuous On-Line Tar Measurements for Gasification Process Monitoring using Fluorescence Excitation-Emission Matrices at Elevated Temperature
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Biomass has been extensively investigated, because of its presence as clean energy source. Tars and particulates formation problems are still the major challenges in development especially in the implementation of gasification technologies into nowadays energy supply systems. Laser Induced Fluorescence spectroscopy (LIF) method is incorporated for determining aromatic and Polycyclic Aromatic Hydrocarbons (PAH) produced at high temperature gasification technology. The effect of tars deposition when the gases are cooled has been highly reduced by introducing a new concept of measurement cell. The samples of PAH components have been prepared with the standard constrictions of measured PAHs by using gas chromatograph (GC). OPO laser with tun

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Publication Date
Fri Jan 01 2021
Journal Name
Iraqi Journal Of Agricultural Sciences
Effect of cultural media and nutrient solution on quality and production of cucumber by using hydroponic system.
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Publication Date
Fri Jul 25 2025
Journal Name
Modern Sport
The Effect of Training Exercises Using an Innovative Device on Developing Skill Performance Among Female Foil Fencers
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Publication Date
Sun May 31 2020
Journal Name
International Journal Of Psychosocial Rehabilitation
The effect of rehabilitating exercises by using a therapeutic medium on some motor abilities of hemiplegia patients
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Cerebral palsy "is one of the diseases that afflict children, and it is a term given to the condition of a child who is exposed to a normal brain injury by accident due to its inability to grow or damage to the cells of the areas responsible for movement and knowledge of strength and balance during the stage of normal development." (116: 1999: 10) Cerebral palsy causes disruption in movement and posture due to damage to brain cells in areas that control and coordinate muscle tone, reflexes, strength, and movement. The degree and location of brain damage varies greatly between people with paralysis, as well as the severity of disability and symptoms, as they fall into severe to very simple, and cerebral palsy is one of the diseases that caus

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Publication Date
Sat Aug 04 2012
Journal Name
University Of Thi-qar Journal
Prediction of Ultimate Soil Bearing Capacity for Shallow Strip Foundation on Sandy Soils by Using (ANN) Techniqu
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Bearing capacity of soil is an important factor in designing shallow foundations. It is directly related to foundation dimensions and consequently its performance. The calculations for obtaining the bearing capacity of a soil needs many varying parameters, for example soil type, depth of foundation, unit weight of soil, etc. which makes these calculation very variable–parameter dependent. This paper presents the results of comparison between the theoretical equation stated by Terzaghi and the Artificial Neural Networks (ANN) technique to estimate the ultimate bearing capacity of the strip shallow footing on sandy soils. The results show a very good agreement between the theoretical solution and the ANN technique. Results revealed that us

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