Conference Agenda

Tailings dam stability is a critical aspect of mining safety, as structural failures can cause severe environmental and socioeconomic impacts. This study compares the Bishop and Janbu methods for assessing the stability of four tailings dams in the province of Caravelí, Arequipa (Peru), using SLIDE software. The objective is to determine which of these methods provides more precise and reliable safety factors (FS) under different geotechnical and environmental conditions. To achieve this, site-specific data were collected, the dams were modeled, and both methods were applied under static and pseudo-static loading scenarios. The results reveal significant differences in the sensitivity of the calculated FS values. The Bishop method, which considers moment equilibrium, tends to be more conservative, yielding higher FS values. In contrast, the Janbu method, based on force equilibrium, is more flexible and better accounts for variations in soil properties. The choice of method should be based on site conditions and project requirements, considering soil saturation, seismic loads, and material heterogeneity. This comparative analysis enhances the design and management of tailings dams, optimizing structural safety and ensuring the sustainability of mining operations in Caraveli.

The main objective of the following study is to implement the Power BI Business Intelligence tool in order to improve the decision-making processes of the logistics area in a real estate company and thus carry out an adequate data analysis and make much more strategic decisions for the business. The methodology for this work was a quasi-experimental design, of an applied type, with a quantitative approach with a population of 15 users. The expected results are to demonstrate the usefulness of the tool so that correct decision-making can be made.

Keywords-- Power BI, Decision making, analysis, Visualization, dashboards.

This article provides a detailed exploration of the structure and operation of an advanced system that utilizes artificial intelligence, specifically convolutional neural networks, with the aim of enhancing the early detection of skin cancer, with a particular focus on melanoma. It delves deep into how these cutting-edge technologies are being employed to revolutionize the diagnostic process of this potentially life threatening disease. The article sheds light on the positive impact that artificial intelligence can have on diagnostic accuracy, ultimately potentially leading to a significant improvement in survival rates for melanoma patients.

The tracking and control of picosatellites in ground stations remains a crucial topic within the rapidly advancing aerospace field. This research details the development of software based on Orbital Mechanics, Euler Rotation, and numerical methods for calculating the position of picosatellites. The system simulates the real-time trajectory of artificial satellites, presenting their position in geographic and Cartesian coordinates within a Software Development Interface (IDE). The results obtained were compared with the Satellite Tool Kit (STK) to evaluate the accuracy of the software. The values of the Keplerian Orbital Elements showed a maximum percentage error of 0.148607% and a minimum of 0.00001%, validating the accuracy of the implemented model. During development, issues related to true anomaly and eccentricity were identified and corrected, optimizing the accuracy of orbital position calculations.

The results demonstrate the feasibility of the software for satellite tracking applications, facilitating the integration of autonomous systems in ground stations. This software provides a reliable solution for real-time satellite position tracking, and the methodology can be applied to improve the performance of ground station systems for picosatellite operations. The successful comparison with STK highlights the model’s precision, showcasing its potential for future use in real-world satellite tracking applications.

Nowadays, for companies to be able to position themselves in an expectant way in the market, they must have computer systems that facilitate the business management for all the transactions they perform in their different processes, so that they can have the information available at all times and thus be able to make timely decisions regarding the business. The purpose of this work is to develop and implement a web application for the business management of a company dedicated to the maintenance and repair of equipment. The work focuses on 02 processes of Business Management: Cost analysis, which allows them to have at hand and in summary form, billing data for each service, most frequent customers, expenses incurred, profitability and dates of execution of the service, among other information available, and, on the other hand, the process of Marketing Strategies, which allows them to propose strategies to further build loyalty to frequent customers, design new ones to attract other customers, and perform a greater number of services, increasing sales by 22.83%.

This systematic review examines the use of Big Data management tools in enterprise information systems for decision-making, with the aim of analyzing how these tools mitigate risks in critical decision-making processes. Using the Scopus database and applying the PICO and PRISMA methodologies, 34 relevant articles were selected based on inclusion and exclusion criteria. The findings highlight the feasibility of data management tools such as SQL Server, Power BI, and Apache Hadoop as critical to improving performance in information systems, optimizing data analysis, and reducing operational costs, thereby improving decision-making in organizational systems. The review underlines the importance of integrating these tools to address complex data analysis and decision-making queries in Big Data environments. Key results reveal that these tools have a significant impact on operational efficiency, data processing, and strategic planning, making them indispensable elements for modern businesses. The study concludes that the effective use of Big Data tools not only optimizes business processes, but also supports the sustainable growth of organizations by enabling data-driven decision-making.

Keywords: Big Data, Apache Hadoop, Power BI, SQL Server, decision making, enterprise information systems.