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 eye

The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

The fiscal position of governments in rentier economies depends heavily on oil revenues. The relationship between oil prices and the budget surplus or deficit is often nonlinear and characterized by complex temporal dependencies, which may limit the predictive capability of conventional econometric models. Accordingly, this study aims to forecast the Iraqi budget surplus and deficit and compare the predictive performance of the ARDL, NARDL, LSTM, 1D-CNN, and hybrid 1D-CNN-LSTM models using oil prices as the primary predictive variable. The hybrid model integrates the feature-extraction capability of One-Dimensional Convolutional Neural Networks (1D-CNN) with the ability of Long Short-Term Memory (LSTM) networks to capture long-term

Abstract

          The following research is marked by "social intelligence and its role in demonstration the potential abilities for individuals." The discussion dealt with the concepts of contemporary is very important because of their significant role in influencing the work of the Organization, as adopted link between the concepts of social intelligence and the potential role of the first to show the second .The research hypotheses tested in three health institutions in the city of Mosul, the research community is represented (Al-Salam Hospital and General Hospital and the son of ether), while the sample were the leaders of these institutio

In this work, radius of shock wave of plasma plume (R) and speed of plasma (U) have been calculated theoretically using Matlab program.

The research aims to Applied Study in the nature of the impact of information asymmetry for brokerage firms in the common stock trading, The research included the theoretical concepts associated with each of the brokerage firms ,information asymmetry and common stock trading, It used the financial methods on the practical side of the information asymmetry for brokerage firms based in the sector as well as trading volume and spread for common stock , The community of the research included the Iraq Stock Exchange,the sample of research the companies listed which have been trading on its stock for the period August 2015 until December 2015 as well as brokerage firms

amounting to 47 brokerage firm. The resea

Abstract Background: Dne of the key component of nasal tipplasty is effecter control of naral tip projection. Several cartilage grafts have been decreased for this purpose each had its own advantage and disadvantage. Aim: To evaluate using of double teostrut graft for controlling of tip projection. Patients and Methods: A total number of 170 patients were subjected to primary and secondary rhino plaster between January 2020 to January 2023. Those patients had double Teostrut banner graft for support of their nasal tip and maintaining tip projection after operation. Results: The follow period was ranging between 6-12 months. The shape of the nose was evaluating by patents vernal analogues scale. The average score for patients satisfaction wa