The Universidad Azteca (also known as Universidad Azteca de Chalco) is a private university in Chalco, Mexico in a community in Mexico State in the greater Mexico City area. Universidad Azteca is a private university with recognition of the Official Validity of Studies awarded by the Federal Secretary of Education (RVOE), accredited by the Federal Ministry of Education of the Republic and recognized by the Federal Government to provide higher education and award graduate and postgraduate university degrees. According to the Mexican Higher Education Laws, Universidad Azteca is authorized to offer study programs and award degrees with RVOE and offer autonomous programs and award academic degrees of the university. The study areas with RVOE (accreditation) are Administration Informatics; Architecture; Business Administration; Education Sciences; International Commerce; Law; Pedagogics; Psychology; Public Accounting. The University awards undergraduate Bachelor, graduate Master, postgraduate Master and Doctoral degrees in international programs in accordance with the Bologna Process and issues a Diploma Supplement. Universidad Azteca International Network System is the university extension, collaborating with other universities globally and branch campus facilities in Austria, Switzerland, United Arab Emirates, India.
In the hybrid cloud environment cost, scalability, and performance are major obstacles for the quick expansion of data-intensive applications. Standard techniques of workload scheduling generally fail in dynamically optimizing resource demands and complex hybrid infrastructure, leading to low efficiency and substandard costs. Cost reduction while preserving or enhancing the performance of data-intensive applications in hybrid clouds is investigated in this paper. Scheduled SC can reduce needless data movement, comprehend workload in both public and private cloud resources, and minimize dynamic infrastructure to satisfy a range of application needs by utilizing future-stating analysis, real-time resource monitoring, and MLoperated adaptive decision-making. The analysis finds a number of machine learning techniques that allow for accurate, automated charge placements, resulting in a notable reduction in computation. These methods include learning reinforcement and multi-object optimization. A comprehensive grasp of the benefits and drawbacks of applying ML-based scheduling in complex cloud ecosystems is provided by research integration, which also addresses operational concepts like safety, complexity, and ongoing model maintenance. These findings show how intelligent automation can assist companies in the Big Data era in finding a balance between cost-effectiveness and technical agility.
The integration of Artificial Intelligence (AI) into supply chain systems has emerged as a transformative force in advancing sustainability objectives, reducing environmental impact, and promoting more responsible resource use across global logistics networks. As supply chains grow more complex—spanning continents, involving a diverse network of suppliers, and responding to increasingly dynamic consumer demands—traditional management approaches struggle to maintain efficiency and sustainability simultaneously. AI addresses these limitations through its capacity for intelligent data processing, real-time decision-making, and predictive analytics, enabling organizations to transition towards greener, more transparent, and more ethical supply chain practices. One of the most notable contributions of AI to supply chain sustainability lies in its role in optimizing resource consumption. AI-driven tools facilitate inventory optimization, ensuring the right quantity of goods is produced, transported, and stocked, thus minimizing waste associated with overproduction and excess storage.
The global transition to renewable energy presents both challenges and opportunities. This study uses data storytelling and Tableau’s visualization tools to explore energy trends from 2000 to 2019. Animated charts reveal rising renewable capacity and carbon emissions; notably, Brazil maintained low emissions despite economic growth. Geospatial analysis highlights China’s high emissions alongside rapid GDP growth, underscoring the vital need to balance development with sustainability (Mete, 2023). Furthermore, orbit charts expose regional gaps: Africa lags in wind and bioenergy, Asia leads in hydropower, and Europe excels in solar. These interconnected insights are crucial for policymakers to craft targeted strategies. Transforming complex data into visual stories supports informed decisions and drives innovative solutions toward a sustainable global energy future
This doctoral thesis explores the effectiveness of immigration policy solutions in the United States, focusing on the interplay between political interests, economic market manipulation, and legal rulings. Employing a qualitative narrative literature review, the study examines these factors role in shaping immigration policies and their impact of social, legal, and economic equity. Through an interdisciplinary approach, it aims to offer insights into developing more equitable and effective immigration policies.
The transformative influence of information and communication technology (ICT) on the landscape of higher education in Mexico has significantly altered operational processes and labor conditions across nearly all economic sectors, its influence on higher education remained relatively constrained until the year 2019. Our analysis investigates this phenomenon through three distinct frameworks. From an educational standpoint, we scrutinize the methodologies by which universities implement ICT in pedagogical practices and learning environments. Prior to 2020, the adoption of these technologies by both students and educators was minimal. Employing organizational theory, we investigate the alterations in institutional frameworks and regulatory landscapes that occur in response to external pressures. We adopt a perspective grounded in academic capitalism to explore the role of higher education institutions as entities of knowledge production, as well as the implications of ICT integration for transitioning the mode of production from a pre-capitalist to a capitalist framework.
