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Adaptive protection for active distribution networks: an approach based on fuses and relays with multiple setting groups

Barranco Carlos, Adrian Osvaldo; OROZCO, CESAR; Marin Quintero, Juan Guillermo; Mora-Flórez, Juan; Herrera Orozco, Andres Ricardo (Institute of Electrical and Electronics Engineers Inc.United States, 2023-03-30)

Protection schemes are essential in active distribution networks and microgrids’ reliable, efficient, and flexible operation. However, the protection of these networks presents significant challenges due to operational ...
Aplicación de técnicas de clustering en sonidos adventicios para mejorar la interpretabilidad y detección de estertores

Sosa, Germán D; Velásquez Clavijo, Fabián (Corporación Universidad de la Costa, 2015-01-05)

Due to the subjectivity involved currently in pulmonary auscultation process and its diagnostic to evaluate the condition of respiratory airways, this work pretends to evaluate the performance of clustering algorithms such ...
Aplicación de Técnicas de Clustering en Sonidos Adventicios para Mejorar la Interpretabilidad y Detección de Estertores

Sosa Ramírez, Germán David; Velásquez Clavijo, Fabián (Universidad de la Costa, 2015-01-05)

Debido a la subjetividad que involucra actualmente el proceso de auscultación pulmonar y su diagnóstico para evaluar la condición de las vías respiratorias de un paciente, este trabajo busca evaluar el desempeño de los ...
A Clustering Approach To Reduce The Available Bandwidth Estimation Error

Guerrero, Cesar D.; Salcedo Morillo, Dixon David; Lamos, Henry (IEEE, 2013-05-03)

The estimation of the available bandwidth (AB) in an end-to-end manner can be used in several network applications to improve their performance. Several tools send pairs of packets from one end to the other and measure the ...
Demand in the electricity market: analysis using big data

amelec, viloria; Martínez Sierra, David; Frasser Camargo, James Enrique; Batistas Zea, Karina; Fuentes-Pacheco, Jorge; Hernández Palma, Hugo; J. Kamatkar, Sadhana (Universidad de la Costa, 2019)

The traditional business model of energy companies is changing in recent years. The introduction of smart meters has led to an exponential increase in the volume of data available, and their analysis can help find consumption ...
Differential evolution clustering and data mining for determining learning routes in moodle

Viloria, Amelec; Crissien Borrero, Tito; Vargas Villa, Jesús; Torres, Maritza; García Guiliany, Jesús; Vargas Mercado, Carlos; Orellano Llinas, Nataly; Batista Zea, Karina (Springer Science and Business Media Deutschland GmbHGermany, 2019-07-30)

Data mining techniques are being widely used in the field of education from the arise of e-learning platforms like Moodle, WebCT, Claroline, and others, and the virtual learning system they entail. Information systems store ...
Hierarchical ascending classification: An application to contraband apprehensions in Colombia (2015–2016)

Lis Gutierrez, Jenny Paola; Reyna Niño, Harry Ernesto; Gaitan, Mercedes; Viloria Silva, Amelec Jesus; Santander Abril, Jairo Enrique (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2018)

An empirical study of ex post facto type was carried out using, as a primary source, the database of the Direction of Management of Control of the Subdirector of Management of Customs Control in the Dirección de Impuestos ...
Human activity recognition data analysis: history, evolutions, and new trends

Ariza Colpas, Paola Patricia; sVicario, Enrico; Oviedo Carrascal, Ana Isabel; aziz, shariq ; Piñeres Melo, Marlon Alberto; Quintero linero, Alejandra paola; PATARA, FULVIO (Multidisciplinary Digital Publishing Institute (MDPI)Switzerland, 2022-04-29)

The Assisted Living Environments Research Area–AAL (Ambient Assisted Living), focuses on generating innovative technology, products, and services to assist, medical care and rehabilitation to older adults, to increase the ...
Métodos multivariantes aplicados a la efectividad de los disolventes en la industria farmacéutica

De La Hoz, Enrique Jose; Fontalvo Herrera, Tomás; Mendoza Mendoza, Adel (Corporación Universidad de la Costa, 2018-08-01)

Introducción: Los disolventes son agentes químicos usados en la industria farmacéutica y su importancia radica en que su presencia puede acelerar o retardar la reacción de un fármaco hasta un millón de veces. Objetivo: La ...
Student performance assessment using clustering techniques

Varela Izquierdo, Noel; Sánchez Montero, Edgardo Rafael; Vásquez, Carmen; Garcia Guiliany, Jesus Enrique; Vargas Mercado, Carlos; Orellano Llinas, Nataly; Batista Zea, Karina; Palencia, Pablo (Communications in Computer and Information Science, 2019-07-26)

The application of informatics in the university system management allows managers to count with a great amount of data which, rationally treated, can offer significant help for the student programming monitoring. This ...
Supervised and unsupervised learning applied to crowdfunding

Torralba Quitian, Oscar Iván; Lis-Gutiérrez, Jenny-Paola; amelec, viloria (Universidad de la Costa, 2020-01-07)

This paper aims to establish the participation behavior of residents in the city of Bogotá between 25 and 44 years of age, to ﬁnance or seek funding for entrepreneurial projects through crowdfunding? In order to meet the ...
U-control chart-based differential evolution clustering for determining the number of clusters in k-Means

Rondón, Carlos; Romero-Pérez, Ivon; García Guliany, Jesús; Steffens Sanabria, Ernesto (Springer International Publishing AGSwitzerland, 2019)

Data are critical sources in several organizations and therefore the efficiency of access to it, sharing, extracting information and making use of that information has become an urgent necessity. Currently, data mining is ...

Envíos recientes

Adaptive protection for active distribution networks: an approach based on fuses and relays with multiple setting groups
...
Barranco Carlos, Adrian Osvaldo | 2023-03-30

Protection schemes are essential in active distribution networks and microgrids’ reliable, efficient, and flexible operation. However, the protection of these networks presents significant challenges due to operational changes, such as variations in topology, distributed energy resources connection/disconnection, and microgrid operating modes, among others. This paper proposes an adaptive protection scheme based on overcurrent devices with several setting groups based on artificial intelligence algorithms. The developed strategy is composed of two stages. In the off-line stage, a clustering technique is employed to group the active distribution network operating scenarios exhibiting similarities. The optimal settings for the protection devices are determined for each set of scenarios. On the other hand, in the on-line stage, the protection strategy’s implementation and operation, considering the active distribution network’s existing communication system, are defined. Furthermore, the approach formulates the overcurrent relay coordination as a mixed-integer non-linear optimization problem, and as a result, the optimal setting of the overcurrent protection devices is obtained. It aims to minimize the operating time, considering the transformers’ thermal limits, fuse operating curves, and overcurrent relay settings. The solution is determined by using an Augmented Lagrangian genetic algorithm. The presented protection scheme is validated on the modified IEEE 34 node test feeder, considering the main operating scenarios of the active distribution networks, such as topology changes, distributed energy resource connection/disconnection, and microgrid operating modes (on-grid and off-grid). The results obtained and its easy implementation indicates the high potential for real-life applications.

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Aplicación de técnicas de clustering en sonidos adventicios para mejorar la interpretabilidad y detección de estertores
...
Sosa, Germán D | 2015-01-05

Due to the subjectivity involved currently in pulmonary auscultation process and its diagnostic to evaluate the condition of respiratory airways, this work pretends to evaluate the performance of clustering algorithms such as k-means and DBSCAN to perform a computational analysis of lung sounds aiming to visualize a representation of such sounds that highlights the presence of crackles and the energy associated with them. In order to achieve that goal, Wavelet analysis techniques were used in contrast to traditional frequency analysis given the similarity between the typical waveform for a crackle and the wavelet sym4. Once the lung sound signal with isolated crackles is obtained, the clustering process groups crackles in regions of high density and provides visualization that might be useful for the diagnostic made by an expert. Evaluation suggests that k-means groups crackle more effective than DBSCAN in terms of generated clusters.

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Aplicación de Técnicas de Clustering en Sonidos Adventicios para Mejorar la Interpretabilidad y Detección de Estertores
...
Sosa Ramírez, Germán David | 2015-01-05

Debido a la subjetividad que involucra actualmente el proceso de auscultación pulmonar y su diagnóstico para evaluar la condición de las vías respiratorias de un paciente, este trabajo busca evaluar el desempeño de los algoritmos de clustering: k-means y DBSCAN para efectuar un análisis computacional de sonidos pulmonares con el objetivo de visualizar una representación de dichos sonidos que exalte la presencia de estertores y la energía contenida en ellos. Para este fin, se emplearon técnicas de descomposición y análisis Wavelet a diferencia del tradicional análisis en frecuencia dada la similitud entre la forma de onda de un estertor típico y la wavelet sym4. Obtenida la señal de sonido pulmonar con estertores aislados, el proceso de clustering agrupa estertores en regiones de alta presencia y ofrece una visualización que puede ser de utilidad para el diagnóstico hecho por un experto. La evaluación hecha sugiere que k-means agrupa conjuntos de estertores de forma más efectiva que DBSCAN en términos de clusters generados.

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A Clustering Approach To Reduce The Available Bandwidth Estimation Error
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Guerrero, Cesar D. | 2013-05-03

The estimation of the available bandwidth (AB) in an end-to-end manner can be used in several network applications to improve their performance. Several tools send pairs of packets from one end to the other and measure the packets' dispersion to infer the value of the AB. Given the fractal nature of Internet traffic, these measurements have significant errors that affect the accuracy of the estimation. This article presents the application of a clustering technique to reduce the estimation error of the available bandwidth in and end-to-end path. The clustering technique used is K-means which is applied to a tool called Traceband that is originally based on a Hidden Markov Model to perform the estimation. It is shown that using K-means in Traceband can improve its accuracy in 67.45% when the cross traffic is about 70% of the end-to-end capacity.

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Demand in the electricity market: analysis using big data
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amelec, viloria | 2019

The traditional business model of energy companies is changing in recent years. The introduction of smart meters has led to an exponential increase in the volume of data available, and their analysis can help find consumption patterns among electric customers to reduce costs and protect the environment. Power plants generate electricity to cover peak consumption at specific times. A set of techniques called “demand response” tries to solve this problem using artificial intelligence proposals. This document proposes a method for processing large volumes of data such as those generated by smart meters. Both for the preprocessing and for the optimization and realization of this analysis big data techniques are used. Specifically, a distributed version of the k-means algorithm and several indices of internal validation of clustering for big data in Spark. The source data correspond to the consumption of electric customers in Bogota, Colombia during the year 2018. The analysis carried out in this study about consumers helps their characterization. This greater knowledge about consumer habits and types of customers can enhance the work of utilities.

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Differential evolution clustering and data mining for determining learning routes in moodle
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Viloria, Amelec | 2019-07-30

Data mining techniques are being widely used in the field of education from the arise of e-learning platforms like Moodle, WebCT, Claroline, and others, and the virtual learning system they entail. Information systems store all activities in files or databases which, correctly processed, may offer relevant data to the teacher. This paper reports the use of data mining techniques and Differential Evolution Clustering for discovering learning routes frequently applied in the Moodle Platform. Data were obtained form 4.115 university students monitored in an online course using Moodle 3.1. Firstly, students were grouped according to the data from a final qualifications report in a course. Secondly, the data of the Moodle logs about each cluster/group of students was used separately with the aim of obtaining more specific and precise models of the students behavior in the processes. © 2019, Springer Nature Singapore Pte Ltd.

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Hierarchical ascending classification: An application to contraband apprehensions in Colombia (2015–2016)
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Lis Gutierrez, Jenny Paola | 2018

An empirical study of ex post facto type was carried out using, as a primary source, the database of the Direction of Management of Control of the Subdirector of Management of Customs Control in the Dirección de Impuestos y Aduanas Nacionales (DIAN) of Colombia and applying the hierarchical ascending classification of contraband apprehensions in Colombia (2015–2016), in order to review the effectiveness of the law 1762 2015. The large amount of data was worked using data mining techniques such as: conglomerates and clustering. Through this method, it was possible to identify six conglomerates that explain 97.14% of the data variability. Similar behaviors were identified in some areas such as the border with Venezuela, the southern border of Colombia, but not in coastal areas. Because it is common that the quantities apprehended does not have a direct relationship with the value of the same, it is necessary to identify if this situation is due to a change in the typology of contraband products, the effect of the exchange rate, or deficiencies in the valuation techniques.

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Human activity recognition data analysis: history, evolutions, and new trends
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Ariza Colpas, Paola Patricia | 2022-04-29

The Assisted Living Environments Research Area–AAL (Ambient Assisted Living), focuses on generating innovative technology, products, and services to assist, medical care and rehabilitation to older adults, to increase the time in which these people can live. independently, whether they suffer from neurodegenerative diseases or some disability. This important area is responsible for the development of activity recognition systems—ARS (Activity Recognition Systems), which is a valuable tool when it comes to identifying the type of activity carried out by older adults, to provide them with assistance. that allows you to carry out your daily activities with complete normality. This article aims to show the review of the literature and the evolution of the different techniques for processing this type of data from supervised, unsupervised, ensembled learning, deep learning, reinforcement learning, transfer learning, and metaheuristics approach applied to this sector of science. health, showing the metrics of recent experiments for researchers in this area of knowledge. As a result of this article, it can be identified that models based on reinforcement or transfer learning constitute a good line of work for the processing and analysis of human recognition activities.

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Métodos multivariantes aplicados a la efectividad de los disolventes en la industria farmacéutica
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De La Hoz, Enrique Jose | 2018-08-01

Introducción: Los disolventes son agentes químicos usados en la industria farmacéutica y su importancia radica en que su presencia puede acelerar o retardar la reacción de un fármaco hasta un millón de veces. Objetivo: La presente investigación analiza los diferentes tipos de disolventes para evaluar la existencia de grupos en los cuales se puedan identificar patrones relacionados con la efectividad de esos disolventes en la producción de fármacos. Metodología: El estudio consta de 4 fases: 1) análisis de componentes principales, 2) análisis de clúster, 3) análisis discriminante, y 4) interpretación de resultados y conclusiones. Resultados: Se identificaron tres conglomerados categorizados como supercríticos, microesféricos y biodegradables. La prueba de T de Hotelling arroja un p-valor de 0, poniendo en evidencia la diferencia entre grupos. El discriminante cuadrático arroja una precisión del 96% para la clasificación de disolventes. Conclusiones: El análisis multivariante permite modelar la efectividad de los disolventes en la industria farmacéutica, generando una metodología objetiva de decisión para la clasificación de disolventes según un enfoque de efectividad.

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Student performance assessment using clustering techniques
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Varela Izquierdo, Noel | 2019-07-26

The application of informatics in the university system management allows managers to count with a great amount of data which, rationally treated, can offer significant help for the student programming monitoring. This research proposes the use of clustering techniques as a useful tool of management strategy to evaluate the progression of the students’ behavior by dividing the population into homogeneous groups according to their characteristics and skills. These applications can help both the teacher and the student to improve the quality of education. The selected method is the data grouping analysis by means of fuzzy logic using the Fuzzy C-means algorithm to achieve a standard indicator called Grade, through an expert system to enable segmentation.

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Supervised and unsupervised learning applied to crowdfunding
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Torralba Quitian, Oscar Iván | 2020-01-07

This paper aims to establish the participation behavior of residents in the city of Bogotá between 25 and 44 years of age, to ﬁnance or seek funding for entrepreneurial projects through crowdfunding? In order to meet the proposed objective, the focus of this research is quantitative, non-experimental and transactional (2017). Through data collection and data analysis, we seek patterns of behavior of the target population. Two machine learning techniques will be used for the analysis: supervised learning (using the learning algorithm of the decision tree) and unsupervised learning (clustering). Among the main ﬁndings are that (i) most of the people who would participate as an entrepreneur and donor and entrepreneur simultaneously belong to stratum 3; (ii) Crowdfunding projects based on donations do not have a high interest on the part of Bogotans, but those in which they aspire to recover the investment.

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U-control chart-based differential evolution clustering for determining the number of clusters in k-Means
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Rondón, Carlos | 2019

Data are critical sources in several organizations and therefore the efficiency of access to it, sharing, extracting information and making use of that information has become an urgent necessity. Currently, data mining is one of the most recognized fields of research and application for carrying out such tasks. In general terms, data mining is the process of extracting useful information, previously unknown patterns and trends, from large databases. The data mining has received a great impulse in the last times motivated by different causes: (a) the development of efficient and robust algorithms for the processing of large volumes of data, (b) a cheaper computational power that allows the use of computationally intensive methods, and (c) the commercial and scientific advantages that have offered this type of techniques in the most diverse areas (Silva et al in Procedia Comput Sci 151:1219–1224 [1], Dianne and Deborah in Interactive and dynamic graphics for data analysis: with R and Gobi [2]). This paper presents an evaluation from different perspectives of a number of relevant nonsupervised quality measures.

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Listar por tema "Clustering"

Adaptive protection for active distribution networks: an approach based on fuses and relays with multiple setting groups ﻿

Aplicación de técnicas de clustering en sonidos adventicios para mejorar la interpretabilidad y detección de estertores ﻿

Aplicación de Técnicas de Clustering en Sonidos Adventicios para Mejorar la Interpretabilidad y Detección de Estertores ﻿

A Clustering Approach To Reduce The Available Bandwidth Estimation Error ﻿

Demand in the electricity market: analysis using big data ﻿

Differential evolution clustering and data mining for determining learning routes in moodle ﻿

Hierarchical ascending classification: An application to contraband apprehensions in Colombia (2015–2016) ﻿

Human activity recognition data analysis: history, evolutions, and new trends ﻿

Métodos multivariantes aplicados a la efectividad de los disolventes en la industria farmacéutica ﻿

Student performance assessment using clustering techniques ﻿

Supervised and unsupervised learning applied to crowdfunding ﻿

U-control chart-based differential evolution clustering for determining the number of clusters in k-Means ﻿

Envíos recientes

Adaptive protection for active distribution networks: an approach based on fuses and relays with multiple setting groups

Aplicación de técnicas de clustering en sonidos adventicios para mejorar la interpretabilidad y detección de estertores

Aplicación de Técnicas de Clustering en Sonidos Adventicios para Mejorar la Interpretabilidad y Detección de Estertores

A Clustering Approach To Reduce The Available Bandwidth Estimation Error

Demand in the electricity market: analysis using big data

Differential evolution clustering and data mining for determining learning routes in moodle

Hierarchical ascending classification: An application to contraband apprehensions in Colombia (2015–2016)

Human activity recognition data analysis: history, evolutions, and new trends

Métodos multivariantes aplicados a la efectividad de los disolventes en la industria farmacéutica

Student performance assessment using clustering techniques

Supervised and unsupervised learning applied to crowdfunding

U-control chart-based differential evolution clustering for determining the number of clusters in k-Means

Adaptive protection for active distribution networks: an approach based on fuses and relays with multiple setting groups

Aplicación de técnicas de clustering en sonidos adventicios para mejorar la interpretabilidad y detección de estertores

Aplicación de Técnicas de Clustering en Sonidos Adventicios para Mejorar la Interpretabilidad y Detección de Estertores

A Clustering Approach To Reduce The Available Bandwidth Estimation Error

Demand in the electricity market: analysis using big data

Differential evolution clustering and data mining for determining learning routes in moodle

Hierarchical ascending classification: An application to contraband apprehensions in Colombia (2015–2016)

Human activity recognition data analysis: history, evolutions, and new trends

Métodos multivariantes aplicados a la efectividad de los disolventes en la industria farmacéutica

Student performance assessment using clustering techniques

Supervised and unsupervised learning applied to crowdfunding

U-control chart-based differential evolution clustering for determining the number of clusters in k-Means