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Mental health has been identified by the World Health Organization (WHO) as a matter of concern internationally. In Colombia, specifically, the importance of mental health care, including the phenomenon of suicide, has been highlighted. In this regard, policymakers have sought alternatives to address or mitigate this issue. In this context, research becomes relevant regarding the development of tools that facilitate decision-making for governmental authorities, for example, through the formulation of forecasting models that enable the identification of trends and patterns of behaviour of suicide attempts. The objective of this study is to formulate and select a regional forecasting model for suicide attempts by means of predictive analytics techniques. This paper contributes to fill the gap in the case of suicide attempts in the city of Medellín, Colombia. The fitting, validation and comparison of three different time series models, under minimum forecast error criteria is presented. The compared models include parametric, Holt-Winters and Box-Jenkins approximations; For the analysed data, the parametric model with cubic, seasonal and ARMA(0.5) components is the one with the lowest forecast error. This model manages to capture the trends of the phenomenon, with a low level of error for the projection for nearby trends, but it does not manage to respond to sudden changes in structure such as those that occurred in the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

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5G networks promise to revolutionize telecommunications by offering significantly faster, more reliable and efficient connectivity compared to their predecessors. However, the inherent complexity of these networks also presents new challenges in terms of performance management and optimization. This paper explores how Machine Learning (ML) can be used to analyze and improve the performance of 5G networks, addressing issues such as congestion, latency, and efficient resource allocation. Practical examples of implementing ML models in Python are presented, using libraries such as Scikit-learn and TensorFlow to predict and optimize network performance. [ABSTRACT FROM AUTHOR]

Successful implementation of Big Data-based business intelligence (BI) solutions is crucial for companies seeking to improve their decision making and gain competitive advantage. This article details the fundamental strategies for effective implementation. First, the objectives and scope of the project must be clearly defined, setting SMART goals and delineating affected areas. Proper technology selection is crucial, evaluating Big Data tools such as Hadoop and Spark, and BI platforms that offer advanced capabilities. Data integration requires consolidating information from various sources, ensuring its quality, and using data warehouses to manage large volumes. Designing effective analytical models includes implementing predictive models, descriptive analytics, and visualizing data through clear dashboards. Staff training and change management are essential to ensure acceptance and efficient use of new tools. Finally, continuous monitoring and evaluation are necessary to measure system performance and make adjustments. By following these strategies, organizations can maximize the value of their data and improve their business performance. [ABSTRACT FROM AUTHOR]

This article presents a theoretical reflection on surveillance as a guarantor of social order. It states that the new surveillance assembly that started with the launch of the Internet tends towards absolute control of life through direct and violent coercion, or entertainment and fun. It deals with three significant surveillance devices, namely, panoptic as a meeting point between the disciplinary society we no longer are and the surveillance society we are becoming; synoptic or the monitoring and surveillance of private, intimate and emotional life; and predictive analytics or the preference for finding correlations among millions of available everyday data that intends, if not to explain the cause of phenomena, to look for new forms of coercion. The reasons why the operation of these devices makes contemporary society a surveillance society are also explored. In expounding the characteristics of each of these devices, the article aims to reveal the role of surveillance in regulating social life. Finally, it reflects on the loss of freedom that brings about the trust and security gained as a result of voluntary or sometimes thoughtless submission to new, subtle and apparently innocent modes of control such as joining social media, subscribing to electronic services, or using any of the most popular search engines. [ABSTRACT FROM AUTHOR]

A tour is provided of the features, possibilities, scientific, technical and technologies that are collected under the interdisciplinary umbrella of big data and web analytics from the point of view of its application in practice. A reflection is offered about the challenges, risks and problems that the tools and data cannot resolve on their own, as well as the contexts in which these data processing techniques are useful for decision making. [ABSTRACT FROM AUTHOR]