Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

The study examines the root causes of delays that the project manager is unable to resolve or how the decision-maker can identify the best opportunities to get over these obstacles by considering the project constraints defined as the project triangle (cost, time, and quality) in post-disaster reconstruction projects to review the real challenges to overcome these obstacles. The methodology relied on the exploratory description and qualitative data examined. 43 valid questionnaires were distributed to qualified experienced engineers. A list of 49 factors causes was collected from previous international and local studies. A Relative Important Index (RII) is adapted to determine the level of importance of each sub-criterion in the fou

Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T

Artificial intelligence techniques are reaching us in several forms, some of which are useful but can be exploited in a way that harms us. One of these forms is called deepfakes. Deepfakes is used to completely modify video (or image) content to display something that was not in it originally. The danger of deepfake technology impact on society through the loss of confidence in everything is published. Therefore, in this paper, we focus on deepfakedetection technology from the view of two concepts which are deep learning and forensic tools. The purpose of this survey is to give the reader a deeper overview of i) the environment of deepfake creation and detection, ii) how deep learning and forensic tools contributed to the detection

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance

China and India are considered both rising countries, and both are among the world's most populous and fastest growing economies. The long-term growth of both China and India has reinforced the importance of their bilateral relationship. The relations between China and India are complex, as relations between them have undergone great changes during the past seven decades, ranging from friendship to hostility. This study proceeds from the hypothesis that the nature and path of Sino-Indian relations after 2013 are affected by several factors and variables, some of which represent opportunities, others represent challenges and obstacles. Several opportunities have contributed to the reformulation of bilateral relations in terms of mutual ga

The aim of the research is to provide an analytical study to promote financial inclusion in Iraq by clarifying the opportunities and challenges of the economic and demographic situation in Iraq, studying the structure of the financial system and introducing non-bank financial institutions operating in Iraq, and using the descriptive approach. Analytical in the study of the phenomenon of research, the research reached a number of conclusions, the most prominent of which were:

• Iraqi society is a young society.
• The majority of the population is 70 percent. They live almost in urban areas.
• The coverage of bank branch networks is concentrated in only four provinces, leaving other provinces outside financial

In this paper, we used four classification methods to classify objects and compareamong these methods, these are K Nearest Neighbor's (KNN), Stochastic Gradient Descentlearning (SGD), Logistic Regression Algorithm(LR), and Multi-Layer Perceptron (MLP). Weused MCOCO dataset for classification and detection the objects, these dataset image wererandomly divided into training and testing datasets at a ratio of 7:3, respectively. In randomlyselect training and testing dataset images, converted the color images to the gray level, thenenhancement these gray images using the histogram equalization method, resize (20 x 20) fordataset image. Principal component analysis (PCA) was used for feature extraction, andfinally apply four classification metho