The modern monitoring and controlsystems that are currently used in most fields are based on intelligent algorithms, distributed management systems, and a new generation of communication buses. For the monitoring and...
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The present paper introduces a mathematical model for the cross-talking between microRNA and Protein. Studying the qualitative properties of the proposed model, we infer that the microRNA is an inhibitor for the Prote...
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Considering the constant growth and evolution of technology, being able to secure data is a challenge. This is why researchers find this a top research topic. Cyber-Physical systems are complex, large-scale systems th...
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The purpose of this article is to perform a comparison between two identification models: a nonlinear one referred to as HARMAX and a classical linear one, of Box-Jenkins (BJ) type. The first model modifies a classica...
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In this paper we study an ODE model on the microRNA-mRNA dynamics. We prove the existence of two equilibrium points (one with strictly positive compo-nents) and obtain a biologically consistent, sufficient asymptotic ...
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Solving the explicit model predictive control (MPC) problem entails enumerating a list of critical regions and their ancillary feedback laws. Unfortunately, their number and the time required to compute them increase ...
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As global digitization continues to grow, technology becomes more affordable and easier to use, and social media platforms thrive, becoming the new means of spreading information and news. Communities are built around...
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As global digitization continues to grow, technology becomes more affordable and easier to use, and social media platforms thrive, becoming the new means of spreading information and news. Communities are built around sharing and discussing current events. Within these communities, users are enabled to share their opinions about each event. Using Sentiment Analysis to understand the polarity of each message belonging to an event, as well as the entire event, can help to better understand the general and individual feelings of significant trends and the dynamics on online social networks. In this context, we propose a new ensemble architecture, EDSAEnsemble (Event Detection Sentiment Analysis Ensemble), that uses Event Detection and Sentiment Analysis to improve the detection of the polarity for current events from Social Media. For Event Detection, we use techniques based on Information Diffusion taking into account both the time span and the topics. To detect the polarity of each event, we preprocess the text and employ several Machine and Deep Learning models to create an ensemble model. The preprocessing step includes several word representation models: raw frequency, TFIDF, Word2Vec, and Transformers. The proposed EDSA-Ensemble architecture improves the event sentiment classification over the individual Machine and Deep Learning models. Authors
The AC-DC Energy Nodes (ADENs) concept offers a transformative approach to modernizing power grids, particularly in the context of supergrids. By centralizing power flows from diverse renewable energy sources, such as...
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In this paper, we explore how to use a Nvidia Jetson Nano and Python to create a system that detects weariness in a person's face using computer vision and machine learning techniques. The system captures the pers...
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