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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
Sun Jan 01 2023
Journal Name
Journal Of Education College Wasit University
تقصي فاعلية التعليم الالكتروني خلال فيروس كورونا المستجد (كوفيد 19) في كلية التربية للبنات/ جامعة بغداد
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      تبنت العديد من المؤسسات الأكاديمية التعلم الإلكتروني منذ سنوات ، وقد أثبت فاعليته في كثير من هذه المؤسسات لاسيما تلك المهتمة بتعلم اللغات الاجنبية. الا انه  مع انتشار جائحة كورونا اصبح التعليم الالكتروني  ضرورة ملحة في الجامعات في جميع أنحاء العالم ، بما في ذلك الجامعات العراقية.  تهدف الدراسة الحالية إلى تقصي أثر هذا الوباء على التعلم الإلكتروني في أحدى الكليات العراقية . يفترض الباحث أن تقبل ال

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Publication Date
Mon Feb 14 2022
Journal Name
Journal Of Educational And Psychological Researches
The Use Of Computerized Curriculum Individually and Cooperatively In the Achievement of Ninth Grade Students in Mathematics
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The study aimed to investigate the effect of using the intructional computer individually or through the cooperative groups on the achievement of the ninth grade students in mathematics compared to the traditional method. The experimental method adapted three groups out of three schools were chosen, two groups of the students where applied the computer method. The comtrol group used the simple random method, and it used the diagnostic test as tool for the study.The result showed that there is a statistically significant difference between the mean scores of the experimental groups and the control group on the post-test for the two experimental groups.

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Publication Date
Sat Jan 01 2022
Journal Name
International Journal Of Research In Social Sciences & Humanities
COLLABORATIVE WRITING AS A MEANS IN DEVELOPING EFL LEARNERS’ WRITING PERFORMANCE
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Collaborative learning is a way that prepares students practically for real-world applications. Working together as teamwork to execute various writing skills is essential in most professions since it increases the level of experience. Thus, the current study aims to identify the role collaborative writing in developing students' level of performance in writing. It is qualitative in nature since the researcher depended on the extant literature in achieving the objective of the study. The researcher touched upon related theories that addressed Collaborative learning, categories, and problems .It concluded that collaborative writing increases the students’ self-confidence, self-esteem, creativity, and motivation through the interact

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Publication Date
Wed Jun 01 2022
Journal Name
Iraqi Journal Of Physics
Statistical Analysis and Forecasting of Rainfall Patterns and Trends in Gombe North-Eastern Nigeria
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Rainfall in Nigeria is highly dynamic and variable on a temporal and spatial scale. This has taken a more pronounced dimension due to climate change. In this study, Standard Precipitation Index (SPI) and Mann-Kendall test statistical tools were employed to analyze rainfall trends and patterns in Gombe metropolis between 1990 and 2020 and the ARIMA model was used for making the forecast for ten (10) years. Daily rainfall data of 31 years obtained from Nigerian Meteorological Agency, (NIMET) was used for the study. The daily rainfall data was subjected to several analyses. Standard precipitation index showed that alternation of wet and dry period conditions had been witnessed in the study area. The result obtained showed that there is an u

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Publication Date
Mon Dec 20 2021
Journal Name
Baghdad Science Journal
Crucial File Selection Strategy (CFSS) for Enhanced Download Response Time in Cloud Replication Environments
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Cloud Computing is a mass platform to serve high volume data from multi-devices and numerous technologies. Cloud tenants have a high demand to access their data faster without any disruptions. Therefore, cloud providers are struggling to ensure every individual data is secured and always accessible. Hence, an appropriate replication strategy capable of selecting essential data is required in cloud replication environments as the solution. This paper proposed a Crucial File Selection Strategy (CFSS) to address poor response time in a cloud replication environment. A cloud simulator called CloudSim is used to conduct the necessary experiments, and results are presented to evidence the enhancement on replication performance. The obtained an

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Publication Date
Sun Sep 22 2024
Journal Name
Journal Of Petroleum Research And Studies
Optimizing Gas Lift for Improved Oil Recovery in a Middle East Field: A Genetic Algorithm Approach
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This paper presents a study of the application of gas lift (GL) to improve oil production in a Middle East field. The field has been experiencing a rapid decline in production due to a drop in reservoir pressure. GL is a widely used artificial lift technique that can be used to increase oil production by reducing the hydrostatic pressure in the wellbore. The study used a full field model to simulate the effects of GL on production. The model was run under different production scenarios, including different water cut and reservoir pressure values. The results showed that GL can significantly increase oil production under all scenarios. The study also found that most wells in the field will soon be closed due to high water cuts. Howev

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Publication Date
Thu Nov 17 2022
Journal Name
Journal Of Discrete Mathematical Sciences And Cryptography
Minimum spanning tree application in Covid-19 network structure analysis in the countries of the Middle East
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Coronavirus disease (Covid-19) has threatened human life, so it has become necessary to study this disease from many aspects. This study aims to identify the nature of the effect of interdependence between these countries and the impact of each other on each other by designating these countries as heads for the proposed graph and measuring the distance between them using the ultrametric spanning tree. In this paper, a network of countries in the Middle East is described using the tools of graph theory.

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Publication Date
Mon Aug 01 2022
Journal Name
Bulletin Of Electrical Engineering And Informatics
Solid waste recycling and management cost optimization algorithm
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Solid waste is a major issue in today's world. Which can be a contributing factor to pollution and the spread of vector-borne diseases. Because of its complicated nonlinear processes, this problem is difficult to model and optimize using traditional methods. In this study, a mathematical model was developed to optimize the cost of solid waste recycling and management. In the optimization phase, the salp swarm algorithm (SSA) is utilized to determine the level of discarded solid waste and reclaimed solid waste. An optimization technique SSA is a new method of finding the ideal solution for a mathematical relationship based on leaders and followers. It takes a lot of random solutions, as well as their outward or inward fluctuations, t

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Publication Date
Fri Dec 09 2022
Journal Name
Molecules
Palm Raceme as a Promising Biomass Precursor for Activated Carbon to Promote Lipase Activity with the Aid of Eutectic Solvents
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This study concerns the role of activated carbon (AC) from palm raceme as a support material for the enhancement of lipase-catalyzed reactions in an aqueous solution, with deep eutectic solvent (DES) as a co-solvent. The effects of carbonization temperature, impregnation ratio, and carbonization time on lipase activity were studied. The activities of Amano lipase from Burkholderia cepacia (AML) and lipase from the porcine pancreas (PPL) were used to investigate the optimum conditions for AC preparation. The results showed that AC has more interaction with PPL and effectively provides greater enzymatic activity compared with AML. The optimum treatment conditions of AC samples that yield the highest enzymatic activity were 0.5 (NaOH (

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Publication Date
Tue Feb 01 2022
Journal Name
Baghdad Science Journal
New White Method of Parameters and Reliability Estimation for Transmuted Power Function Distribution
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        In this paper, an estimate has been made for parameters and the reliability function for Transmuted power function (TPF) distribution through using some estimation methods as proposed new technique for white, percentile, least square, weighted least square and modification moment methods. A simulation was used to generate random data that follow the (TPF) distribution on three experiments (E1 , E2 , E3)  of the real values of the parameters, and with sample size (n=10,25,50 and 100) and iteration samples (N=1000), and taking reliability times (0< t < 0) . Comparisons have been made between the obtained results from the estimators using mean square error (MSE). The results showed the

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