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Danzas y Cumbias, protagonistas de la tradición

Carnaval de Barranquilla S.A.S. (Carnaval de Barranquilla S. A. S., 2019)

Las danzas y cumbias fueron protagonistas en el Festival de la Tradición, que en la Plaza de la Paz convocó la participación de congos, garabatos, grupos de mapalé, son de negros y cumbiambas para presentar en todo su ...
El daño al buen nombre y a la honra en la presentación pública de personas capturadas por parte de los miembros de la policía nacional

Peña Márquez, Jorge Manuel; Rondón Rincón, Esperanza; Valdés Beltrán, Brenda Julienne (Universidad de la CostaDerecho, 2019)

In accordance with this research work, in the first part, a general look at the concept of Damage was made, then a legal and doctrinal approach was attempted from the point of view of the violation of the right to a good ...
The data envelopment analysis to determine efficiency of Latin American countries for greenhouse gases control in electric power generation

Sánchez, Leadina; Vásquez, Carmen; Viloria Silva, Amelec Jesus (International Journal of Energy Economics and Policy, 2018)

The objective of this research is to determine the efficiency of Latin American countries for the control of greenhouse gas (GHG) emissions due to the generation of electrical energy using the Data Envelopment Analysis. A ...
Data Envelopment Analysis to measure relative performance based on key indicators from a supply network with reverse logistics

Ardila Gamboa, César David; Ballesteros Riveros, Frank Alexander (Corporación Universidad de la Costa, 2018-12-20)

Introduction− Data Envelopment Analysis (DEA) is used to measure the relative performance of a series of distribution centers (DCs), using key indicators based on reverse logistics for a company that produces electric ...
Data from a photovoltaic system using fuzzy logic and the P&O algorithm under sudden changes in solar irradiance and operating temperature

Robles Algarin, Carlos Arturo; Rodriguez Alvarez, Omar; Ospino Castro, Adalberto Jose (Data in Brief, 2018-11-05)

This article presents the data of a PV system using fuzzy logic and the perturb and observe (P&O) algorithm, under sudden changes in the solar irradiance and the operating temperature of a PV module. The mathematical ...
Data from multimodal functions based on an array of photovoltaic modules and an approximation with artificial neural networks as a scenario for testing optimization algorithms

Robles Algarín, Carlos; Restrepo-Leal, Diego; Ospino C., Adalberto (Corporación Universidad de la Costa, 2019)

This paper presents the data of multimodal functions that emulate the performance of an array of five photovoltaic modules under partial shading conditions. These functions were obtained through mathematical modeling and ...
Data leakage detection using dynamic data structure and classification techniques

Guevara Maldonado, César Byron (Corporación Universidad de la Costa, 2015-01-05)

Data leakage is a permanent problem in public and private institutions around the world; particularly, identifying the information leakage efficiently. In order to solve this problem, this paper poses an adaptable data ...
Data mining and association rules to determine twitter trends

Silva, Jesús; Vargas, Jesús; Natteri, Domingo; Flores Marín, Darío Enrique; Pineda, Omar; Ahumada, Bridy; Valero, Lesbia (Corporación Universidad de la Costa, 2020)

Opinion mining has been widely studied in the last decade due to its great interest in the field of research and countless real-world applications. This research proposes a system that combines association rules, generalization ...
Data mining and neural networks to determine the financial market prediction

Silva, Jesus; García Guliany, Jesús; Hernandez, Lissette; Portillo, Rafael; Varela, Noel; Hernandez Palma, Hugo Gaspar; Redondo Bilbao, Osman; Valero, Lesbia (Universidad de la Costa, 2020-03-05)

Predicting stock market movements has been a complex task for years by gaining the increasing interest of researchers and investors present all around the world. These have tried to get ahead of the way in order to know ...
Data mining and social network analysis on Twitter

Silva, Jesus; Varela, Noel; Ovallos-Gazabon, David; H, H; Cazallo-Antunez, Ana; Redondo Bilbao, Osman; ORELLANO LLINAS, NATALY; Pineda Lezama, Omar Bonerge (Universidad de la Costa, 2020-03-05)

The emergence of a networked social structure in the last decade of twentieth century is accelerated by the evolution of information technologies and, in particular, the Internet has given rise to the full emergence of ...
Data mining applied in school dropout prediction

amelec, viloria; García Guliany, Jesús; Niebles Núñez, William; H, H; Niebles Nuñez, Leonardo David (Journal of Physics: Conference Series, 2020)

In recent years, many studies have emerged about regarding the topic of school failure, showing a growing interest in determining the multiple factors that may influence it [1]. Most of the researches that attempt to solve ...
Data mining techniques and multivariate analysis to discover Patterns in university final researches

amelec, viloria; Rodríguez López, Jorge; García Leyva, Diana Margarita; Vargas Mercado, Carlos; Hernández-Palma, Hugo; ORELLANO LLINAS, NATALY; Arrozola David, Mónica; Velasquez Rodriguez, Javier (Procedia Computer Science, 2019)

The aim of this study is to extract knowledge from the final researches of the Mumbai University Science Faculty. Five classification models were applied: Vector Support Machines, Neural Networks, Decision Tree, Random ...
Data mining to identify risk factors associated with university students dropout

Viloria Silva, Amelec Jesus; Castro Sarmiento, Alex; María Santodomingo, Nicolás; María Santodomingo, Nicolas Elias; Márquez Blanco, Norka; Cadavid Basto, Wilmer; Hernández P, Hugo; Navarro Beltrán, Jorge; de la Hoz Hernández, Juan; Romero, Ligia (Communications in Computer and Information Science, 2019-07-26)

. This paper presents the identification of university students dropout patterns by means of data mining techniques. The database consists of a series of questionnaires and interviews to students from several universities ...
Data on the diagnosis of the management of the primary waste from electrical and electronic equipment in health care institutions in Barranquilla, Colombia

Gandara-Perez, Helen Marcela; Lubo-Hoyos, Nelson Enrique; Castilla-Acevedo, Samir; Fuentes Gandara, Fabio Armando (Corporación Universidad de la Costa, 2020-08-27)

Economic and technological development advances exponentially, and the implementation of new technologies in the health sector has become a source of waste for electrical and electronic equipment (WEEE). Electrical and ...
Data processing for direct marketing through Big Data

amelec, viloria; Varela, Noel; MALDONADO PEREZ, DOYREG; Pineda Lezama, Omar Bonerge (Universidad de la Costa, 2020-01-07)

Traditional marketing performs promotion through various channels such as news in newspapers, radio, etc., but those promotions are aimed at all people, whether or not interested in the product or service being promoted. ...
Data sciences and teaching methods—learning

Silva, Jesus; Portillo, Rafael; Hernandez, Ana Emilia; Varela, Noel; Martinez Caraballo, Hugo; Hernández Palma, Hugo Gaspar; Redondo Bilbao, Osman; Leon Castro, Nadia (Universidad de la Costa, 2020-03-05)

Data Science (DS) is an interdisciplinary field responsible for extracting knowledge from the data. This discipline is particularly complex in the face of Big Data: large volumes of data make it difficult to store, process ...
Data set on wind speed, wind direction and wind probability distributions in Puerto Bolivar - Colombia

Valencia Ochoa, Guillermo; Núñez Alvarez, José; Vanegas Chamorro, Marley (Corporación Universidad de la Costa, 2019)

This paper presents wind speed and direction data measured with a weather station located in Puerto Bolivar, department of La Guajira, situated in the extreme north of Colombia, whose geographic coordinates are 12 110 N ...
Data supporting the assessment of biomass based electricity and reduced ghg emissions in Cuba

Sagastume Gutierrez, Alexis; Cabello Eras, Juan Jose; Vandecasteele A., Carlo H. (Data In Brief, 2018-02-25)

Assessing the biomass based electricity potential of developing nations like Cuba can help to reduce the fossil fuels dependency and the greenhouse gas emissions. The data included in this study present the evolution ...
Data supporting the evaluation of the energy recovery potential of thermoelectric generators in diesel engines

Ramírez, Rafael; Sagastume, Alexis; Cabello Eras, Juan José; Hernandez, Brando; Duarte Forero, Jorge (Data in Brief, 2019-12-30)

Power generation with thermoelectric devices in internal combustion engines is an alternative to recover some of the energy loss with the exhausts. This data article supports a study that assesses the potentialities of ...
Data supporting the forecast of electricity generation capacity from non-conventional renewable energy sources in Colombia

Sagastume, Alexis; BALBIS MOREJON, MILEN; Cabello Eras, Juan José; Cabello Ulloa, Mario Javier; Rey-Martínez, Francisco Javier; Rueda-Bayona, Juan Gabriel (Data in Brief, 2019-12-05)

The data included in this study was calculated based on data provided by the national project registry provided by the Colombian government. The data forecasts the evolution of the power generation capacity registered in ...

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Danzas y Cumbias, protagonistas de la tradición
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Carnaval de Barranquilla S.A.S. | 2019

Las danzas y cumbias fueron protagonistas en el Festival de la Tradición, que en la Plaza de la Paz convocó la participación de congos, garabatos, grupos de mapalé, son de negros y cumbiambas para presentar en todo su esplendor lo mejor de sus coreografías, vestuario, parafernalia y ritmo al bailar ante propios y visitantes. 127 agrupaciones folclóricas hicieron de este evento el abreboca de la riqueza cultural que se apreció en los multitudinarios desfiles del Carnaval de Barranquilla.

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El daño al buen nombre y a la honra en la presentación pública de personas capturadas por parte de los miembros de la policía nacional
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Peña Márquez, Jorge Manuel | 2019

In accordance with this research work, in the first part, a general look at the concept of Damage was made, then a legal and doctrinal approach was attempted from the point of view of the violation of the right to a good name and the right to the honor in the public presentation of people captured by the members of the National Police, the exposure to media of the indicted who fully enjoy the presumption of innocence and who have not been defeated in a trial, the legal consequences that they can lead to the State and to these Judicial Police officials, and finally to conclude, some jurisprudential concepts were presented about the legal criteria that the Constitutional Court took into account to safeguard the fundamental rights violated here. Thus it can be said that the violation of the right to a good name and the right to honor by the National Police is constant, when a captured person has been presented who has not been defeated in a fair trial exercising his right to defense and exposing his body of evidence, from the outset is treated as alleged guilty before the media and social networks. Although the right to good name and right to honor has had a strict study at international and national level. This right has its pillars in the Political Constitution and through the constitutionality block adhesion of international treaties, the State in its legislation and in compliance with guarantor has tried to regulate in Colombia the prohibition of abstaining from judicial servants to present in public to the accused, accused or accused as responsible, but this activity is repeated by the National Police officials

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The data envelopment analysis to determine efficiency of Latin American countries for greenhouse gases control in electric power generation
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Sánchez, Leadina | 2018

The objective of this research is to determine the efficiency of Latin American countries for the control of greenhouse gas (GHG) emissions due to the generation of electrical energy using the Data Envelopment Analysis. A positivist epistemic position is assumed, and a methodology of evaluative character is used, comprising five (5) phases. The results show that the countries that are located on the efficient frontier have common police like the increase in the share of renewable energies, and diversification of the energy matrix, which means a better control of GHG emissions. It is possible to determine the efficiency of the public policies established by the countries of Latin America for the control of GHG emissions. In conclusion, the countries that are located on the efficient frontier are those that generate electricity with predominantly renewable sources or, at least, use natural gas as a fuel in greater proportion.

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Data Envelopment Analysis to measure relative performance based on key indicators from a supply network with reverse logistics
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Ardila Gamboa, César David | 2018-12-20

Introduction− Data Envelopment Analysis (DEA) is used to measure the relative performance of a series of distribution centers (DCs), using key indicators based on reverse logistics for a company that produces electric and electronic supplies in Colombia.Objective−The aim is to measure the relative perfor-mance of distribution centers based on Key Performance Indicators (KPI) from a supply network with reverse logistics.Methodology−A DEA model is applied through 5 steps: KPIs selection; Data collection for all 18 DCs in the net-work; Build and run the DEA model; Identify the DCs that will be the focus of improvement; Analyze the DCs that restrict or diminish the total performance of the system.Results− KPIs are defined, data is collected and KPI’s for each DCs are presented. The DEA model is run and the relative efficiencies for each DCs are determined. A frontier analysis is made and DCs that limit or reduce the performance of the system are analyzed to find options for improving the system.Conclusions−Reverse logistics, brings numerous ad-vantages for companies. The analysis of the indicators allows logistics managers involved to make relevant deci-sions for higher performance. The DEA model identifies which DCs have a relative superior and inferior perfor-mance, making it easier to make informed decisions to change, increase or decrease resources, and activities or apply best practices that optimize the performance of the network.

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Data from a photovoltaic system using fuzzy logic and the P&O algorithm under sudden changes in solar irradiance and operating temperature
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Robles Algarin, Carlos Arturo | 2018-11-05

This article presents the data of a PV system using fuzzy logic and the perturb and observe (P&O) algorithm, under sudden changes in the solar irradiance and the operating temperature of a PV module. The mathematical modeling of the PV module, the dc-dc converter and the fuzzy and P&O controllers were discussed in our previous work entitled “Fuzzy logic based MPPT controller for a PV System” (Algarín et al., 2017) [1]. Data are presented for six cases with different operating conditions: in the first case the two controllers were evaluated for standard test conditions with constant solar irradiance of 1000 W/m2 and constant temperature of 25 °C. In the remaining five cases sudden increases and decreases were made in the operating conditions of the PV module. Finally, the theoretical data of the PV system are presented, which can be used as a reference to analyze the data obtained with the two controllers in the six cases. Data are provided in Supplementary material in Tables 1–7.

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Data from multimodal functions based on an array of photovoltaic modules and an approximation with artificial neural networks as a scenario for testing optimization algorithms
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Robles Algarín, Carlos | 2019

This paper presents the data of multimodal functions that emulate the performance of an array of five photovoltaic modules under partial shading conditions. These functions were obtained through mathematical modeling and represent the P–V curves of a photovoltaic module with several local maximums and a global maximum. In addition, data from a feedforward neural network are shown, which represent an approximation of the multimodal functions that were obtained with mathematical modeling. The modeling of multimodal functions, the architecture of the neural network and the use of the data were discussed in our previous work entitled “Search for Global Maxima in Multimodal Functions by Applying Numerical Optimization Algorithms: A Comparison Between Golden Section and Simulated Annealing” [1]. Data were obtained through simulations in a C code, which were exported to DAT files and subsequently organized into four Excel tables. Each table shows the voltage and power data for the five modules of the photovoltaic array, for multimodal functions and for the approximation of the multimodal functions implemented by the artificial neural network. In this way, a dataset that can be used to evaluate the performance of optimization algorithms and system identification techniques applied in multimodal functions was obtained.

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Data leakage detection using dynamic data structure and classification techniques
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Guevara Maldonado, César Byron | 2015-01-05

Data leakage is a permanent problem in public and private institutions around the world; particularly, identifying the information leakage efficiently. In order to solve this problem, this paper poses an adaptable data structure based on human behavior using all the activities executed within the computer system. When applying this structure, the normal behavior is modeled for each user, so in this way, detects any abnormal behavior in real time. Moreover, this structure enables the application of several classification techniques such as decision trees (C4.5), UCS, and Naive Bayes, these techniques have proven efficient outcomes in intrusion detection. In the testing of this model, a scenario demonstrating the proposal’s effectiveness with real information from a government institution was designed so as to establish future lines of work.

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Data mining and association rules to determine twitter trends
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Silva, Jesús | 2020

Opinion mining has been widely studied in the last decade due to its great interest in the field of research and countless real-world applications. This research proposes a system that combines association rules, generalization of rules, and sentiment analysis to catalog and discover opinion trends in Twitter [1]. The sentiment analysis is used to favor the generalization of the association rules. In this sense, an initial set of 1.6 million tweets captured in an undirected way is first summarized through text mining in an input set for the algorithms of rules and sentiment analysis of 158,354 tweets. On this last group, easily interpretable standard and generalized sets of rules are obtained about characters, which were revealed as an interesting result of the system.

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Data mining and neural networks to determine the financial market prediction
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Silva, Jesus | 2020-03-05

Predicting stock market movements has been a complex task for years by gaining the increasing interest of researchers and investors present all around the world. These have tried to get ahead of the way in order to know the levels of return and thus reduce the risk they face in investments [1]. Capital markets are areas of fundamental importance for the development of economies and their good management that favors the transition from savings to investment through the purchase and sale of shares [2]. These actions are so important that they are influenced by economic, social, political, and cultural variables. Therefore, it is reasonable to consider the value of an action in an instant not as a deterministic variable but as a random variable, considering its temporal trajectory as a stochastic process.

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Data mining and social network analysis on Twitter
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Silva, Jesus | 2020-03-05

The emergence of a networked social structure in the last decade of twentieth century is accelerated by the evolution of information technologies and, in particular, the Internet has given rise to the full emergence of what has been called the Information Age [1] or the Information Society. Social media is yet another example of people’s extraordinary ability to generate, disseminate and exchange meanings in collective interpersonal communication with a massive, real-time networked system where everything tends to be connected. The analysis of the climate of opinion on Twitter is presented around the Common Core State Standards (CCSS), one of the most ambitious educational reforms of the last 50 years in USA.

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Data mining applied in school dropout prediction
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amelec, viloria | 2020

In recent years, many studies have emerged about regarding the topic of school failure, showing a growing interest in determining the multiple factors that may influence it [1]. Most of the researches that attempt to solve this issue [2] are focused on determining the factors that most affect the performance of students (dropout and failure) at the different educational levels (basic, middle and higher education) through the use of the large amount of information that current computer equipment allows to store in databases. All these data constitute a real gold mine of valuable information about students. But, identifying and finding useful and hidden information in large databases is a difficult task [3]. A very promising solution to achieve this goal is the use of knowledge mining techniques or data mining in education, which has resulted in so-called Educational Data Mining (EDM) [4]. This new area of research is concerned with the development of methods for exploring data in education, as well as the use of these methods to better understand students and the contexts where they learn [5].

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Data mining techniques and multivariate analysis to discover Patterns in university final researches
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amelec, viloria | 2019

The aim of this study is to extract knowledge from the final researches of the Mumbai University Science Faculty. Five classification models were applied: Vector Support Machines, Neural Networks, Decision Tree, Random Forest and Powering; considering the Experiment Design and Multivariate Analysis Lines. Results showed that for the Experiment Design line, the most accurate model was Random Forest with 71.48% predictions that are correct respecting to the total. Regarding the Multivariate Analysis line, there was no significant difference in overall accuracy, fluctuating by 97%.

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Data mining to identify risk factors associated with university students dropout
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Viloria Silva, Amelec Jesus | 2019-07-26

. This paper presents the identification of university students dropout patterns by means of data mining techniques. The database consists of a series of questionnaires and interviews to students from several universities in Colombia. The information was processed by the Weka software following the Knowledge Extraction Process methodology with the purpose of facilitating the interpretation of results and finding useful knowledge about the students. The partial results of data mining processing on the information about the generations of students of Industrial Engineering from 2016 to 2018 are analyzed and discussed, finding relationships between family, economic, and academic issues that indicate a probable desertion risk in students with common behaviors. These relationships provide enough and appropriate information for the decision-making process in the treatment of university dropout.

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Data on the diagnosis of the management of the primary waste from electrical and electronic equipment in health care institutions in Barranquilla, Colombia
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Gandara-Perez, Helen Marcela | 2020-08-27

Economic and technological development advances exponentially, and the implementation of new technologies in the health sector has become a source of waste for electrical and electronic equipment (WEEE). Electrical and electronic equipment must be replaced periodically, either due to a technological update or to improve medical treatments, which ultimately leads to the generation of this type of waste. This work aimed to conduct exploratory research on the current situation of the handling of this type of waste in Barranquilla, Colombia, considering the limited information related to the management of biomedical WEEE in the city. Sixty health care institutions (HCIs), including hospitals and clinics, odontological centres and ophthalmological centres, participated favourably in the surveys concerning the management of WEEE. Through this work, it was possible to establish a working staff level of knowledge on WEEE disposal and the framework for the management and temporary collection of this waste. Therefore, the data are useful for proposing strategies for the integral management of electrical and electronic waste in both small and large populations.

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Data processing for direct marketing through Big Data
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amelec, viloria | 2020-01-07

Traditional marketing performs promotion through various channels such as news in newspapers, radio, etc., but those promotions are aimed at all people, whether or not interested in the product or service being promoted. This method usually leads to high expenses and a low response rate by potential customers. That is why, nowadays, because there is a very competitive market, mass marketing is not safe, hence specialists are focusing efforts on direct marketing. This method studies the characteristics, needs and also selects a group of customers as a target for the promotion. Direct marketing uses predictive modeling from customer data, with the aim of selecting the most likely to respond to promotions. This research proposes a platform for the processing of data ﬂows for target customer selection processes and the construction of required predictive response models.

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Data sciences and teaching methods—learning
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Silva, Jesus | 2020-03-05

Data Science (DS) is an interdisciplinary field responsible for extracting knowledge from the data. This discipline is particularly complex in the face of Big Data: large volumes of data make it difficult to store, process and analyze with standard computer science technologies. The new revolution in Data Science is already changing the way we do business, healthcare, politics, education and innovation. This article describes three different teaching and learning models for Data Science, inspired by the experiential learning paradigm.

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Data set on wind speed, wind direction and wind probability distributions in Puerto Bolivar - Colombia
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Valencia Ochoa, Guillermo | 2019

This paper presents wind speed and direction data measured with a weather station located in Puerto Bolivar, department of La Guajira, situated in the extreme north of Colombia, whose geographic coordinates are 12 110 N 71 550 W. A wind speed and direction sensor, a barometric pressure sensor, and a temperature sensor were used to obtain the presented data. These data were taken at the height of 10 m, which is the highest point of the weather station. The data taken by the meteorological station correspond to a period of 20 years (1993e2013), with hourly frequency. For the missing data, a mathematical model to estimate the Julian averages was developed, allowing to calculate the frequency histograms and four types of probability distributions for these data. Also, the representative wind roses were generated, taking into account the averages in each of the 12 months of the year.

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Data supporting the assessment of biomass based electricity and reduced ghg emissions in Cuba
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Sagastume Gutierrez, Alexis | 2018-02-25

Assessing the biomass based electricity potential of developing nations like Cuba can help to reduce the fossil fuels dependency and the greenhouse gas emissions. The data included in this study present the evolution of electricity production and greenhouse gas emissions in Cuba. Additionally, the potentialities to produce biomass based electricity by using the most significant biomass sources in Cuba are estimated. Furthermore, estimations of the potential reductions of greenhouse gas emissions, resulting from implementing the biomass based electricity potential of the different sources discussed in the study, are included. Results point to the most promising biomass sources for electricity generation and their potential to reduce GHG emissions

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Data supporting the evaluation of the energy recovery potential of thermoelectric generators in diesel engines
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Ramírez, Rafael | 2019-12-30

Power generation with thermoelectric devices in internal combustion engines is an alternative to recover some of the energy loss with the exhausts. This data article supports a study that assesses the potentialities of energy recovery with thermoelectric generators in diesel engines and its influence on gaseous emissions. To this end, a set of experiments was developed with a thermoelectric generator and a waffle heat exchanger. The experimental design included nine operation points of the engine to characterize the energy recovery of the thermoelectric generator under different exploitation conditions. Three different fuels (i.e., diesel, B5, and B10) were used. The experiments were developed in a test bench with three data acquisition systems to measure the operational variables (e.g., electric power generation, pressure drop, temperature, etc.). Moreover, a gas analyzer (BrainBee AGS-688), Bacharach gas analyzer (PCA 400), and a smoke meter (BrainBee OPA100) were used to measure exhaust emissions.

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Data supporting the forecast of electricity generation capacity from non-conventional renewable energy sources in Colombia
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Sagastume, Alexis | 2019-12-05

The data included in this study was calculated based on data provided by the national project registry provided by the Colombian government. The data forecasts the evolution of the power generation capacity registered in non-conventional renewable energy source projects in three scenarios of implementation of the power generation capacity registered in the projects. Results can be used to benchmark non-conventional renewable energy sources in Colombia, interpret the effectiveness of renewable policies, and monitor the evolution of non-conventional renewable-based power generation. The data presented in the article relates to the research study: A look to the electricity generation from nonconventional renewable energy sources in Colombia .

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