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 current research aims at: - Identifying the role played by the leadership in empowerment and organizational learning abilities and their reflection on the knowledge capital, and the extent to which these concepts can be applied effectively at Wasit University. The problem of research .... In a series of questions: The most important is that the dimensions leadership empowerment and distance learning organizational capacity correlation relationship and impact and significant statistical significance with the capital knowledge.
To understand the nature of the relationship and the impact between the variables, leadership was adopted by empowerment as the fir
... Show MoreThis study sought to investigate the impacts of big data, artificial intelligence (AI), and business intelligence (BI) on Firms' e-learning and business performance at Jordanian telecommunications industry. After the samples were checked, a total of 269 were collected. All of the information gathered throughout the investigation was analyzed using the PLS software. The results show a network of interconnections can improve both e-learning and corporate effectiveness. This research concluded that the integration of big data, AI, and BI has a positive impact on e-learning infrastructure development and organizational efficiency. The findings indicate that big data has a positive and direct impact on business performance, including Big
... Show MoreThis paper deals with a central issue in the field of human communication and reveals the roaming monitoring of the incitement and hatred speech and violence in media, its language and its methods. In this paper, the researcher seeks to provide a scientific framework for the nature of the discourse of incitement, hatred speech, violence, and the role that media can play in solving conflicts with their different dimensions and in building community peace and preventing the emergence of conflicts among different parties and in different environments. In this paper, the following themes are discussed:
The root of the discourse of hatred and incitement
The nature and dimensions of the discourse of incitement and hatred speech
The n
The theatrical image represents one of the tools of communication with the other to create a communicative language that is produced and transmitted by the actor and his body through the theatrical space to convey the meaning in all its forms and types. The actor is concerned with the composition and construction of these images. My girl, the image is fragmented and multiple and different. Therefore, based on the foregoing, the researcher has divided his research into four chapters, representing the (methodological framework). First, the research problem, which is manifested in the following question (what is the structure of the fragmented image of the actor's performance? The Iraqi playwright), and secondly: the importance of the resea
... Show MoreGoal of research is to investigate the impact of the use of effective learning model in the collection of the fourth grade students/Department of physics in the material educational methods and the development of critical thinking .to teach this goal has been formulated hypothesis cefereeten zero subsidiary of the second hypothesis .To investigate the research hypothesis were selected sample of fourth-grade students of the department of physics at the univers
... Show MoreIt is well known that drilling fluid is a key parameter for optimizing drilling operations, cleaning the hole, and managing the rig hydraulics and margins of surge and swab pressures. Although the experimental works represent valid and reliable results, they are expensive and time consuming. In contrast, continuous and regular determination of the rheological fluid properties can perform its essential functions during good construction. The aim of this study is to develop empirical models to estimate the drilling mud rheological properties of water-based fluids with less need for lab measurements. This study provides two predictive techniques, multiple regression analysis and artificial neural networks, to determine the rheological
... Show MoreThe most significant function in oil exploration is determining the reservoir facies, which are based mostly on the primary features of rocks. Porosity, water saturation, and shale volume as well as sonic log and Bulk density are the types of input data utilized in Interactive Petrophysics software to compute rock facies. These data are used to create 15 clusters and four groups of rock facies. Furthermore, the accurate matching between core and well-log data is established by the neural network technique. In the current study, to evaluate the applicability of the cluster analysis approach, the result of rock facies from 29 wells derived from cluster analysis were utilized to redistribute the petrophysical properties for six units of Mishri
... Show MoreBrainstorming has been a common approach in many industries where the result is not always accurate, especially when procuring automobile spare parts. This approach was replaced with a scientific and optimized method that is highly reliable, hence the decision to optimize the inventory inflation budget based on spare parts and miscellaneous costs of the typical automobile industry. Some factors required to achieve this goal were investigated. Through this investigation, spare parts (consumables and non-consumables) were found to be mostly used in Innoson Vehicle Manufacturing (IVM), Nigeria but incorporated miscellaneous costs to augment the cost of spare parts. The inflation rate was considered first due to the market's
... Show MoreThis paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to
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