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Nowadays, economic growth is influenced by many domestic and foreign global issues, concerning the decrease of industrial output for the rise in economic inequality and the weakening of the overall condition in the countries. The role of economic growth is based on human capital and investment. Therefore, in this paper, the human capital and economic management system (HC‐EMS) has been proposed to enhance the country's quality based on the capital structure investment. HC explores the role of command and its significance in the production and creation aspects of human capital such that an area can grow creatively. HC‐EMS analysed critical monitoring systems for developing human resources and the high‐tech and creative economic sectors and presented suggestions for change. Besides, there is a need to prove the shortcomings and benefits of human resource development systems and statistical approaches for gathering and analysing information. The impact of financial services and financial transactions may vary; therefore, it is critically important for fostering economic growth. The experimental result suggests that the proposed HC‐EMS achieves the highest growth development ratio than other existing methods. [ABSTRACT FROM AUTHOR]

Open data has been improving both publishing platforms and the consumers-oriented process over the years, providing better openness policies and transparency. Although organizations have tried to open their data, the enrichment of their resources through the Web of Data has been decreasing. Linked data has been suffering from notable difficulties in different stages of its life cycle, becoming over the years less attractive to users. According to that, we decided to explore how the lack of some opening requirements affects the decline of the Web of Data. This paper presents the Web of Data radiography, analyzing the governmental domain as a case study. The results indicate that it is necessary to strengthen the data opening process to improve resource enrichment on the Web and have better datasets. These improvements describe that open data must be public, accessible (in machine-readable formats), described (use of robust, granular metadata), reusable (made available under an open license), complete (published in primary forms), and timely (preserve the value of the data). The implementation of these characteristics would enhance the availability and reuse of datasets. Besides, organizations must understand that opening and enriching their data require a completely new approach, and they have to pay special attention and control to this project, generally by putting money, the commitment by management at all levels, and lots of time. On the contrary, given the magnitude of availability and reuse problems identified in the opening and enrichment data process, it is believed that the Web of Data model would inevitably lose the interest it aroused at the beginning if not addressed immediately by data quality, openness, and enrichment issues. Besides, its use would be restricted to a few particular niches or would even disappear altogether. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) technologies allow building a digital representation of people, objects, or physical phenomena to be available on the Internet. Thus, stakeholders can access this information from remote places or computational systems could analyze this data to find patterns, make decisions, or execute actions. For instance, a doctor could diagnose patients by analyzing the received data from an IoT system even when patients are located in a remote place. This article proposes an IoT system for monitoring electrocardiogram (ECG) signal and processing heart data in order to generate an alert when an arrhythmia is present. This system involves a Polar H10 heart sensor, machine-learning models to classify heart events, and communication technology to share and store patient's information. In the first place, the architecture of the IoT monitoring system and the communication between the components are described by discussing the designing criteria. Second, the experimentation process performs the training and the assessment of three classification algorithms, random forest, convolutional neural network, and k-nearest neighbors. The results show that k-nearest neighbor has the best accuracy percentage classifying the arrhythmias under study (premature ventricular contraction 94%, fusion of ventricular beat 81%, and supraventricular premature beat 82%); also, it is able to discern normal and unclassifiable beats with 93% and 97%, respectively. [ABSTRACT FROM AUTHOR]

The Pacific Alliance is an economic and development initiative where four Latin American nations: Chile, Colombia, Mexico, and Peru, seek the growth in the economics of the four nations. It is in this way that agriculture plays an important role in this union since it is one of the greatest sources of income in each nation. However, the internal conflict that afflicts each country generates stagnation in economic growth, affecting its exports. Forced displacement is one of the main consequences of the internal conflict within the countries that make up the Pacific Alliance. Therefore, a model of Population Dynamics System P (PDP System) is proposed, viewing this phenomenon as a classic predator-prey model, where one 'predator' resources that in this case are the territories, and in this struggle one species predominates over the other. The simulations showed how the populations are being affected and how the analogy between the social conflict described above and the Lokta-Volterra model can be modelled with a topic that has always been considered to be social. Although much more complex scenarios can be simulated by adding other variables, this study is an approach that yields important results that can be considered in other studies [ABSTRACT FROM AUTHOR]

Aim: This paper aims to analyze, prepare, and review the general guidelines and rules that govern the development of key factors influencing the enhancement of emotionally supportive networks and selection models using fuzzy logic theory. The researchers have identified eight important components of the information society (IS), representing the computerized economy's growth to explain a realistic framework for medium-term gauges and proposals. Materials and methods: A discrete-nonstop opportunity paradigm portrays the creation of the general framework, in which the mutual effects of each of the components are spoken to models within the state-space. The software's mechanical quality offers improvement displayed along these lines that may indicate future interest to programing suppliers. The researchers have given supposed to the developments and interests of information technology (IT) professionals in R&D to provide insightful foundations. For example, this study will demonstrate the development of emotionally supportive networks and recommendations of choices for 3D-web-based businesses and their impact on mechanical advancement, examples of use and social behavior. Results: During an IS/IT foreknowledge undertaking completed in Poland in 2019 and sponsored by the Education Research and Development Foundation ERDF, the results were obtained. [ABSTRACT FROM AUTHOR]

The huge amount of data on the Internet and the diverse list of strategies used to try to link this information with relevant searches through Linked Data have generated a revolution in data treatment and its representation. Nevertheless, the conventional search engines like Google are kept as strategies with good reception to do search processes. The following article presents a study of the development and evolution of search engines, more specifically, to analyze the relevance of findings based on the number of results displayed in paging systems with Google as a case study. Finally, it is intended to contribute to indexing criteria in search results, based on an approach to Semantic Web as a stage in the evolution of the Web. [ABSTRACT FROM AUTHOR]

Robotics applications to healthcare have become more prominent in the last few years. Some of the many robotics applications in healthcare include surgical robots, pharmacy robots, robotic telemedicine, robotics-assisted infectious disease management, robotics rehabilitation medicine and many more. The authors propose a grey-level correlation algorithm using neural networks to efficiently solve medical resource management problems. [Extracted from the article]

This article provides a deep analysis of the water quality at the upper basin of the Bogota River (Colombia) between 2008 and 2017. The Water Quality Index has been the indicator employed to determine the ecological status of the river. This index was chosen in order to normalize the analysis, given that it is commonly used by the Institute of Hydrology, Meteorology and Environmental Studies, a government agency of the Ministry of Environment and Sustainable Development of Colombia, to determine the state of surface effluents. The results obtained were organized in a double-entry matrix in order to relate the variables of the sample period and the sampling station. The research revealed an insufficient quality of water, demonstrating that the high stretch of the Bogota River basin has, in general, regular or acceptable water quality, while only five stations showed an acceptable status. Surprisingly, the stations located close to the wastewater treatment plants of the municipalities of Choconta, Suesca, Gachancipa, and Tocancipa, as well as Rio Negro, have a poor water quality, discharging a high load of contaminants into the river. Although great efforts have been made by Colombian authorities to restore the critical state of the majority of their aquatic ecosystems, recent implementation of policies and instruments have not shown significant achievements yet. For this reason, this study aims to present a powerful decision-tool for the monitoring and evaluation of correction measures implemented on this river basin. The data used in this research were provided by the Regional Autonomous Corporation of Cundinamarca. [ABSTRACT FROM AUTHOR]