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
The study aims to investigate the effect of the Six Thinking Hats Strategy on the achievement of essay writing skills among third-year students in Arabic Language and Literature who are Persian speakers enrolled in the course of Essay Writing (III) at Shiraz University for the academic year 2019-2020. The sample of the study consisted of (15) male and female students who were taught according to the pre-posttest, using the quasi-experimental approach. After applying the statistical analysis on the scores of the post-test, the results showed that there are statistically significant differences in the average of students' achievement in the skills of essay writing in terms of using the Six Thinking Hats Strategy. The results also proved th
... Show MoreTo evaluate the Interaction of Mn(II), Fe(II), Co(II), Ni(II),Cu(II), Zn(II) And Cd(II) Mixed- Ligand Complexes of cephalexin mono hydrate (antibiotics) And Furan-2-Carboxylic Acid To The Different DNA Sources. All the metal complexes were observed to cleave the DNA. A difference in the bands of complexes .The cleavage efficiency of the complexes compared with that of the control is due to their efficient DNA-binding ability and the other factors like solubility and bond length between the metal and ligand may also increase the DNA-binding ability. The ligands (Cephalexin mono hydrate (antibiotics) and Furan-2- Carboxylic acid and there newly synthesized metal complexes shows good antimicrobial activities and Binding DNA , thus, can be used
... Show MoreThis paper is a review of the genus Sitta in Iraq, Five species of this genus are recognized
Sitta kurdistanica, S. neumayr, S. europaea, S.dresseri and S. tephronota. Geographical
distribution and systematic nots were given for separation and identification, also some notes
on nest building and nest sites of S. tephronota supporting by figures are presented.
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The research aims to reveal the impact of media policy in Iraqi media outlets on the level of objectivity in these outlets. A study from the communicators’ point of view where the researcher used a survey method on the communicators in media outlets to reveal the extent of media policies knowledge as well as the pressures exerted by this policy on communicators in media outlets. It also reveals the extent of their commitment to objectivity, neutrality in dealing with information and the way used to transfer it.
The research sample included (179) respondents from communicators in a range of Media outlets such as (Press, Radio, and Television), The researcher was careful with the diversity of the sample, and
Deep learning techniques are applied in many different industries for a variety of purposes. Deep learning-based item detection from aerial or terrestrial photographs has become a significant research area in recent years. The goal of object detection in computer vision is to anticipate the presence of one or more objects, along with their classes and bounding boxes. The YOLO (You Only Look Once) modern object detector can detect things in real-time with accuracy and speed. A neural network from the YOLO family of computer vision models makes one-time predictions about the locations of bounding rectangles and classification probabilities for an image. In layman's terms, it is a technique for instantly identifying and recognizing
... Show MoreText Clustering consists of grouping objects of similar categories. The initial centroids influence operation of the system with the potential to become trapped in local optima. The second issue pertains to the impact of a huge number of features on the determination of optimal initial centroids. The problem of dimensionality may be reduced by feature selection. Therefore, Wind Driven Optimization (WDO) was employed as Feature Selection to reduce the unimportant words from the text. In addition, the current study has integrated a novel clustering optimization technique called the WDO (Wasp Swarm Optimization) to effectively determine the most suitable initial centroids. The result showed the new meta-heuristic which is WDO was employed as t
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The research seeks to identify the proposed scenarios to predict and ward off monetary credit risks that the bank is exposed to in the future, using the banking stress tests model, and showing their impact on capital adequacy and profitability ratio,To achieve this purpose, Sumer Commercial Bank was taken as a case study, and mathematical equations were used to extract the results. Low percentage of profits and returns, strictness in the process of granting credit and financing operations in order to reduce credit risks.
Abstract
This study aims to find the relationships between social capital (social network, social trust, shared goals) and knowledge sharing (knowledge Donating, knowledge collecting) as independent variables and their impact on improving the quality of educational services (academic staffs quality, Quality of teaching methods and study curriculums). This research is an important, because it attempts to identify the relationship between social capital and the knowledge sharing and their effect on improving the quality of educational service for universities. The study problem was determined in several questions related to the nature of the correlation relationship - the impact between the different independent variables (
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