Universities are among spaces where it's important to ensure thermal comfort in indoor spaces, improving the occupants' well-being and productivity. The problem of the research was to study appropriate glazing systems for the spaces of the University of Baghdad because glazing systems are one of the most important elements of the indoor environments, and it has a major impact on the thermal performance of buildings. Glass is one of the most seasoned materials that are most utilized in the design. Since it is a diaphanous material, it allows sunlight to enter the building, increasing the space's temperature, cooling loads, and energy consumption in summer. The research followed the experimental method by studying and

We are, today, facing a torrent of information, ideas, images and videos due to advances of communication technology and electronic publishing. In addition to the proliferation of social networking sites that allow individuals to use them and participate in their channels without any restrictions limiting their freedom in publishing. Due to these sites many terms have emerged like alternative media which use internet and its various techniques to serve its objectives notably the freedom of expression without restrictions. This research studies the phenomenon of interactive media i.e. alternative media through Facebook along with the freedom that makes it spreading in the society and the relation of individual freedom with social diversit

The method of predicting the electricity load of a home using deep learning techniques is called intelligent home load prediction based on deep convolutional neural networks. This method uses convolutional neural networks to analyze data from various sources such as weather, time of day, and other factors to accurately predict the electricity load of a home. The purpose of this method is to help optimize energy usage and reduce energy costs. The article proposes a deep learning-based approach for nonpermanent residential electrical ener-gy load forecasting that employs temporal convolutional networks (TCN) to model historic load collection with timeseries traits and to study notably dynamic patterns of variants amongst attribute par

Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

There are different types of corruptions such as administrative, political, economic and financial corruption. The corruption forms also varied such as bribery, nepotism and extortion. All types and forms of corruption play significant role in the all economic variables generally and on investments in particular, and the corruption used to be an intermediate means in reducing the rate of economic growth.  The corruption contributes in reducing the domestic investments via pay bribery by investors to officials’ persons for supplemental contracts and tenders which finally leads to reduction in the investment efficiency. The corruption also contributes in rise of operational costs for the investment projects.  In additio

ABSTRACT this paper extends the literature on the elements and effect of financial literacy by investigating the elements of financial literacy and the impact of financial literacy on financial inclusion and savings. This research confirms the results of researches of other economies but exposes some dissimilarities as well. The principal factors of financial literacy are discovered to be government efficiency, educational level, income, economic performance and infrastructure. Both education levels and financial literacy are found to be meaningfully and positively linked to financial inclusion and savings in G20 economies

Background: The rapid evolution of Artificial Intelligence (AI) has significantly influenced Education, demonstrating substantial potential to transform traditional teaching and learning methods. AI reshapes teacher-student interactions and the relationship with knowledge. Objective: To analyze the potential benefits, ethical challenges, and limitations of AI in Education based on recent scientific literature, emphasizing the balance between technology and human interaction. Methods: A documentary research approach with a descriptive focus was employed, following the PRISMA protocol for systematic reviews. The search strategy involved analyzing evidence from 18 scientific articles published within the last six years. Results:AI o