Repositorio Universidad Internacional Iberoamericana
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907 research outputs found
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An improved WiFi sensing based indoor navigation with reconfigurable intelligent surfaces for 6G enabled IoT network and AI explainable use case
No full textThe expanding number of low cost sensors and smart devices drives the internet-of-things (IoT) ecosystem of the future. These sensing devices are connected to the internet for information exchange. The location and positioning of these nodes is very important information required in vast range of location based services like smart homes, smart healthcare, environmental monitoring, personal navigation and smart transportation. This paper presents an intelligent solution for node localization in a 6G enabled IoT network. An indoor communication network scenario is proposed in which reconfigurable intelligent surfaces (RISs) are installed to locate the sensor nodes operating in that network. The performance evaluation of the proposed scheme is carried out with optimum number of reflecting elements and optimum phase shifts. It is observed that optimized RISs with 100 reflecting elements improve the estimated localization error by 7.4% over non-optimum RISs. Also, the minimum gain of 6% in localization error is offered using equal phase shifts over random phase shifts. Further, the effect of channel conditions on the average estimation error in node locations is also elaborated. In the end, the explainable artificial intelligence (XAI) empowered indoor localization is discussed as a use case scenario and the performance comparison of the algorithms is evaluated
Análisis del nivel de conocimiento, las destrezas y las actitudes de los docentes en enfermería en torno al uso de simuladores de alta fidelidad
No full textEn este estudio se analizó el nivel de conocimiento, las destrezas y las actitudes de los docentes de enfermería en el uso de simuladores de alta fidelidad (SAF) en los procesos de enseñanza-aprendizaje. La literatura destacó la importancia del uso de los SAF en los programas de la enfermería y la necesidad de que los facultativos demostraran tener dominio de estas tecnologías para alcanzar los objetivos educativos (Jeffries, 2022; Organización Mundial de la Salud, 2022). Los resultados del estudio pueden servir para implementar una metodología de desarrollo profesional en las Instituciones de Educación Superior de Puerto Rico. El estudio utilizó los paradigmas cuantitativos, descriptivos y exploratorios para el análisis de los datos, integrando también una sección para recibir opiniones de los participantes. Para conocer el nivel de conocimiento, destrezas y actitudes de los docentes en el uso de simuladores de alta fidelidad (SAF) se analizaron datos de una muestra de noventa y un (n=91) participantes. En el estudio se validó un cuestionario que solicitó a los participantes contestar doce (12) reactivos mediante una escala Likert considerando los SAF en las funciones docentes. Los resultados del estudio demostraron diferencias significativas entre los niveles de conocimiento, dominio de destrezas y actitudes del docente de enfermería en el uso de los SAF considerando el grado académico más alto alcanzado y la participación en actividades de desarrollo profesional (<.05). Esto es, mientras más alto el grado académico y frecuencia en la participación en actividades de desarrollo profesional, más alto son los niveles de conocimientos, destrezas y actitudes del docente en el uso de los SAF para mejorar las competencias de los estudiantes. Además, se comprobaron correlaciones significativas (<.01) entre los constructos que sirvieron de marco teórico conceptual para el estudio. Lo que demuestra que puede ser usado por otros investigadores para estudios similares
Forecasting of Post-Graduate Students’ Late Dropout Based on the Optimal Probability Threshold Adjustment Technique for Imbalanced Data
No full textThe purpose of this research article was to contrast the benefits of the optimal probability threshold adjustment technique with other imbalanced data processing techniques, in its application to the prediction of post-graduate students’ late dropout from distance learning courses in two universities in the Ibero-American space. In this context, the optimization of the Logistic Regression, Random Forest, and Neural Network classifiers, together with different techniques, attributes, and algorithms (Hyperparameters, SMOTE, SMOTE_SVM, and ADASYN) resulted in a set of metrics for decision-making, prioritizing the reduction of false negatives. The best model was the Neural Network model in combination with SMOTE_SVM, obtaining a recall index of 0.75 and an f1-Score of 0.60. Likewise, the robustness of the Random Forest classifier for imbalanced data was demonstrated by achieving, with an optimal threshold of 0.427, very similar metrics to those obtained by the consensus of the three best models found. This demonstrates that, for Random Forest, the optimal prediction probability threshold is an excellent alternative to resampling techniques with different optimal thresholds. Finally, it is hoped that this research paper will contribute to boost the application of this simple but powerful technique, which is highly underrated with respect to data resampling techniques for imbalanced data
Implantação de geotecnolgias livres e gratuitas em uma empresa de saneamento básico
No full textO presente trabalho descreve a implantação de geotecnologias, utilizando software livre e gratuito, com a finalidade de disseminar as informações geoespaciais da Empresa Baiana de Águas e Saneamento (EMBASA). A EMBASA é a concessionária responsável pelo saneamento básico do Estado da Bahia. Este artigo descreve, além do uso e da implantação, uma análise dos custos economizados pela companhia ao longo dos anos em função da adoção do software livre e gratuito
Formal modeling and analysis of security schemes of RPL protocol using colored Petri nets
No full textIn the Internet of things (IoT), data packets are accumulated and disseminated across IoT devices without human intervention, therefore the privacy and security of sensitive data during transmission are crucial. For this purpose, multiple routing techniques exist to ensure security and privacy in IoT Systems. One such technique is the routing protocol for low power and lossy networks (RPL) which is an IPv6 protocol commonly used for routing in IoT systems. Formal modeling of an IoT system can validate the reliability, accuracy, and consistency of the system. This paper presents the formal modeling of RPL protocol and the analysis of its security schemes using colored Petri nets that applies formal validation and verification for both the secure and non-secure modes of RPL protocol. The proposed approach can also be useful for formal modeling-based verification of the security of the other communication protocols
Competitive Coevolution-Based Improved Phasor Particle Swarm Optimization Algorithm for Solving Continuous Problems
No full textCurrent- and Voltage-Actuated Transmission Line Protection Scheme Using a Hybrid Combination of Signal Processing Techniques
No full textThis paper presents a current- and voltage-driven protection scheme for transmission lines based on a hybrid mix of Stockwell transform (ST) and Hilbert transform (HT). Use of both current and voltage waveforms to detect and categorize faults, improves the reliability of this protection scheme and avoids false tripping. Current and voltage waveforms captured during a period of fault are analyzed using ST to compute a median intermediate fault index (MIFI), a maximum value intermediate fault index (MVFI), and a summation intermediate fault index (SIFI). Current and voltage signals are analyzed via applying HT to compute a Hilbert fault index (HFI). The proposed hybrid current and voltage fault index (HCVFI) is obtained from the MIFI, MVFI, SIFI, and HFI. A threshold magnitude for this hybrid current and voltage fault index (HCVFITH) is set to 500 to identify the faulty phase. The HCVFIT is selected after testing the method for various conditions of different fault locations, different fault impedances, different fault occurrence angles, and reverse flows of power. Fault classification is performed using the number of faulty phases and an index for ground detection (IGD). The ground involved in a fault is detected by comparison of peak IGD magnitude with a threshold for ground detection (THGD). THGD is considered equal to 1000 in this study. The study is carried out using a two-terminal transmission line modeled in MATLAB software. The performance of the proposed technique is better compared to a discrete wavelet transform (DWT)-based technique, a time–frequency approach, and an alienation method. Our algorithm effectively detected an AG fault, observed on a practical transmission line
An Optimized Intelligent Computational Security Model for Interconnected Blockchain-IoT System & Cities
No full textBlockchain technology may provide a potential solution to the Internet of Things (IoT) security challenges by providing a decentralized and secure method for storing, managing, and sharing data. The Secure Hash Algorithm (SHA-256) hashed value of preliminary data (block) is retained in one block along with transaction data in tree form and timestamp in a chain of blocks. However, there are observations about blockchain limitations such as higher energy consumption, secure data, self-maintenance reliance, and higher cost. These constraints can be overcome by incorporating encryption algorithms into accepting blocks of data. In this paper, we propose a secure intelligent computational model for a large-scale interconnected IoT environment; an analytical modeling technique is considered for the proposed system. The proposed system takes advantage of the potential security feature of blockchain, which is considered the most appropriate secure communication system in an IoT. A computational model is built using the proposed blockchain technology to incorporate a secure and intelligent communication system. The proposed system uses the enhanced McEliece encryption approach’s potential to link the blockchain due to the faster mode of encryption and decryption process with a highly reduced number of steps
Systematic Review of Machine Learning applied to the Prediction of Obesity and Overweight
No full textObesity and overweight has increased in the last year and has become a pandemic disease, the result of sedentary lifestyles and unhealthy diets rich in sugars, refined starches, fats and calories. Machine learning (ML) has proven to be very useful in the scientific community, especially in the health sector. With the aim of providing useful tools to help nutritionists and dieticians, research focused on the development of ML and Deep Learning (DL) algorithms and models is searched in the literature. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol has been used, a very common technique applied to carry out revisions. In our proposal, 17 articles have been filtered in which ML and DL are applied in the prediction of diseases, in the delineation of treatment strategies, in the improvement of personalized nutrition and more. Despite expecting better results with the use of DL, according to the selected investigations, the traditional methods are still the most used and the yields in both cases fluctuate around positive values, conditioned by the databases (transformed in each case) to a greater extent than by the artificial intelligence paradigm used. Conclusions: An important compilation is provided for the literature in this area. ML models are time-consuming to clean data, but (like DL) they allow automatic modeling of large volumes of data which makes them superior to traditional statistics
Integration of Sustainable Criteria in the Development of a Proposal for an Online Postgraduate Program in the Projects Area
No full textRegulatory dispersion and a utilitarian use of sustainability deepen the gap within the teaching–learning process and limit the introduction of sustainable criteria in organizations through projects. The objective of this research consisted in developing a sustainable and holistic educational proposal for an online postgraduate program belonging to the Universidad Europea del Atlántico (UNEATLANTICO) within the field of projects. The proposal was based on the instrumentalization of a model comprised of national and international bibliographic references, resulting in a sustainability guide with significant improvements in relation to the reference standard par excellence: ISO 26000:2010. This guide formed the basis of a sustainability management plan, which was key in the project methodology and during the development of sustainable objectives and descriptors for each of the subjects. Lastly, the entities, attributes, and cardinal relationships were established for the development of a physical model used to facilitate the management of all this information within a SQL database. The rigor when determining the educational program, as well as the subsequent analysis of results as supported by the literature review, presupposes the application of this methodology toward other multidisciplinary programs contributing to the adoption of good sustainability practices within the educational fiel