Now showing items 1-20 of 491

1D Convolutional Neural Network for Detecting Ventricular Heartbeats

Suárez-León, A. A.; Núñez, José R. (Universidad de la Costa, 2020)

This paper shows a novel approach for detecting ventricular heartbeats using a 1D Convolutional Neural Network (1D-CNN). The algorithm input is the raw ECG signal, i.e., no signal pre-processing nor feature extraction are ...
A case of food supply chain management with AHP, DEMATEL, and TOPSIS

Ortiz Barrios, Miguel Angel; Miranda‐De la Hoz, Carlos; Meza López, Pedro; Petrillo, Antonella; De Felice, Fabio (Universidad de la Costa, 2019-08-27)

The bullwhip effect leads to considerable inefficiencies along the food supply chain such as missed production schedules, poor customer service, excessive inventory, and misguided capacity plans. To tackle this problem, ...
A case of food supply chain management with ahp, dematel, and topsis

Ortiz Barrios, Miguel Angel; Miranda‐De la Hoz, Carlos; Meza López, Pedro; Petrillo, Antonella; De Felice, Fabio (Universidad de la Costa, 2019-08-27)

The bullwhip effect leads to considerable inefficiencies along the food supply chain such as missed production schedules, poor customer service, excessive inventory, and misguided capacity plans. To tackle this problem, ...
A color fusion model based on Markowitz portfolio optimization for optic disc segmentation in retinal images

Escorcia-Gutierrez, Jose; Torrents-Barrena, Jordina; Gamarra, Margarita; Romero-Aroca, Pedro; Valls, Aida; Puig, Domenec (Corporación Universidad de la Costa, 2021-07-15)

Retinal disorders are a severe health threat for older adults because they may lead to vision loss and blindness. Diabetic patients are particularly prone to suffer from Diabetic Retinopathy. Identifying relevant structural ...
A comprehensive study of biofilms growing on the built heritage of a caribbean industrial city in correlation with construction materials

Gallego Cartagena, Euler; MORILLAS, HECTOR; Maguregui, Maite; Patiño Camelo, Karen Lisana; Marcaida, Iker; MORGADO GAMERO, WENDY BEATRIZ; O. Silva, Luis F.; Madariaga, Juan Manuel (Universidad de la Costa, 2019)

Biodeteriogens growing on constructions belonging to the built heritage is one of the leading natural pathologies that cause aesthetical and in some cases, physical-geochemical problems in the materials. In this study, for ...
A FAHP-VIKOR approach for supporting the selection of tomography equipment in LMIC hospitals: a case study

Ortíz-Barrios, Miguel; Jaramillo-Rueda, Natalia; Petrillo, Antonella; Fernández-Mendoza, Zaury; Vidal-Pacheco, Lucelys (Corporación Universidad de la Costa, 2021)

Computerized Tomography Scanners (CT-SCAN) provide detailed cross-sectional images of the human body which are employed for the easier detection and further analysis of abnormalities concerning the functionality and structure ...
A fuzzy logic proposal for diagnosis multiple incipient faults in a power transformer

Fernández Blanco, Juan Carlos; Corrales Barrios, Luis Benigno; Hernández González, Félix Herminio; Benitez Pina, Israel Francisco; Núñez Alvarez, José Ricardo (Corporación Universidad de la Costa, 2021)

For the safety and continuity of service in industrial electrical systems, the availability of transformers is essential. For this reason, it is necessary to develop intelligent fault diagnosis techniques to reduce repair ...
A generic materials and operations planning approach for inventory turnover optimization in the chemical industry

Coronado-Hernández, Jairo R.; Romero-Conrado, Alfonso R.; Ochoa-González, Olmedo; Quintero-Arango, Humberto; Vargas, Ximena; Gatica, Gustavo (Corporación Universidad de la Costa, 2020)

Chemical industries usually involve continuous and large-scale production processes that require demanding inventory control systems. This paper aims to show the results of the implementation of a mixed-integer programming ...
A hybrid fuzzy multi-criteria decision making model for selecting a sustainable supplier of forklift filters: a case study from the mining industry

Ortiz-Barrios, Miguel; Cabarcas Reyes, Juan Carlos; Ishizaka, Alessio; Barbati, Maria; Jaramillo-Rueda, Natalia; Carrascal-Zambrano, Giovani de Jesús (Corporación Universidad de la Costa, 2020-07-30)

Supplier selection has long been a strategic cornerstone for the advancement of companies from the mining sector due to its impact on many sectors as inventory management, production planning, maintenance scheduling, ...
A hybrid fuzzy multi-criteria decision-making model to evaluate the overall performance of public emergency departments: a case study

Ortiz Barrios, Miguel Angel; Alfaro-Saiz, Juan-Jose (Corporación Universidad de la Costa, 2020-10-05)

Performance evaluation is relevant for supporting managerial decisions related to the improvement of public emergency departments (EDs). As di®erent criteria from ED context and several alternatives need to be considered, ...
A mathematical model for the optimization of the non-metallic mining supply chain in the mining district of Calamarí-Sucre (Colombia)

Ospina-Mateus, Holman; Montero-Perez, Jairo; Acevedo-Chedid, Jaime; Salas-Navarro, Katherinne; Morales-Londoño, Natalie (Corporación Universidad de la Costa, 2020)

This article presents a mathematical model of the Supply chain of non-metallic mining. The model considers uncertainty scenarios in materials, elements for capacity planning in a multilevel chain and with multiple products. ...
A method for estimating the age of people in forensic medicine using multivariable statistics

BARRAZA SALCEDO, MARÍA DEL SOCORRO; Parody Muñoz, Alexander Elias; Borré-Ortiz, Yeis Miguel; amelec, viloria; Cervera Cárdenas, Jorge Eduardo (Corporación Universidad de la Costa, 2020-09-08)

The present study seeks to generate a regression model that allows estimating the age of individuals in the city of Barranquilla (Colombia) from the stages of people’s teeth, in order to generate a tool to help forensic ...
A method for the prediction of the shrinkage in roasted and ground coffee using multivariable statistics

Parody Muñoz, Alexander Elias; Charris, Dhizzy; amelec, viloria; Cervera Cárdenas, Jorge Eduardo; Hernandez, Hugo (Corporación Universidad de la Costa, 2020-09-08)

This study seeks to determine the influence of process variables: consumption percentage in the mixture, pasilla percentage in the mixture, storage time, humidity percentage in the product for consumption, humidity percentage ...
A methodology to estimate baseline energy use and quantify savings in electrical energy consumption in higher education institution buildings: Case study, Federal University of Itajubá (UNIFEI)

Ocampo Batlle, Eric Alberto; Escobar Palacio, José Carlos; Silva Lora, Electo Eduardo; Martínez Reyes, Arnaldo Martín; Melian Moreno, Maurish; Balbis Morejón, Milen (Universidad de la Costa, 2020-01-20)

Accurately forecasting energy consumption in a building is an important strategy for achieving the goal of reducing energy demand and improving energy efficiency. University campuses represent specific groups of diverse ...
A mho type phase comparator relay guideline using phase comparison technique for a power system

González-Cueto Cruz, José Antonio; Garcia Sánchez, Zaid; Crespo Sanchez, Gustavo; Hernández Herrera, Hernán; Silva Ortega, Jorge I; Martínez Díaz, Vicente Leonel (Corporación Universidad de la Costa, 2021-04)

This paper presents a mho distance relay simulation based on the phase comparison technique using a typical electrical power systems analysis software for two cases: when the operation state is close to the static voltage ...
A multicriteria decision‐making framework for assessing the performance of gynecobstetrics departments: a case study

Ortiz Barrios, Miguel Ángel; Gutiérrez‐Severiche, Edward; Cómbita‐Niño, Dayana; Jiménez, Genett; Ishizaka, Alessio; Barbati, María; Herrera-Fontalvo, Zulmeira (Corporación Universidad de la Costa, 2021-02)

Gynecobstetrics departments (GDs) oversee diagnosing, monitoring, and treating female reproductive diseases as well as assisting women during pregnancy. Their importance motivates the creation of suitable performance ...
A multiple criteria decision-making approach for increasing the preparedness level of sales departments against COVID-19 and future pandemics: A real-world case

Ortiz-Barrios, Miguel; Borrego-Areyanes, Arlen Alaine; Gómez-Villar, Iván Darío; De Felice, Fabio; Petrillo, Antonella; Gul, Muhammet; YUCESAN, Melih (Corporación Universidad de la Costa, 2021)

The impact of the pandemic and the lockdown has been more devastating than expected on the world economy. It is essential to formulate strategies in real-time. In this research, a multicriteria decision-making model for ...
A new formulation for strength characteristics of steel slag aggregate concrete using an artificial intelligence-based approach

Awoyera, Paul; Mansouri, Iman; Abraham, Ajith (Corporación Universidad de la Costa, 2021)

Studies examining nanoparticles (NPs) and hazardous elements (HEs) contained in suspended sediments (SSs) are vital for watershed administration and ecological impact evaluation. The biochemical consequence of titanium-n ...
A new methodology incorporating public participation within Cuba's ICZM program

Milanés Batista, Celene; Abelardo Planas, José; Pelot, Ronald; Núñez Alvarez, José Ricardo (Universidad de la Costa, 2020-01-20)

Although public participation (PP) has influenced some integrated coastal zone management (ICZM) programs around the world, researchers have rarely analyzed this component specifically inside an ICZM cycle. Furthermore, ...
A practical methodology of design of off-line reservoirs for reducing maximum water levels in urban channels

Coronado-Hernández, Oscar E.; Coronado-Hernandez, Jairo R.; Gustavo, Gatica (Corporación Universidad de la Costa, 2020)

Flooding can often occur in many places due to the increasing trend of rainfall events (climate change), the urbanization process of a catchment area, or by an undersized urban channel. Reservoirs are used for limiting ...

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1D Convolutional Neural Network for Detecting Ventricular Heartbeats
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Suárez-León, A. A. | 2020

This paper shows a novel approach for detecting ventricular heartbeats using a 1D Convolutional Neural Network (1D-CNN). The algorithm input is the raw ECG signal, i.e., no signal pre-processing nor feature extraction are involved. The output of the 1D-CNN is filtered using a combination of linear and nonlinear filters to produce the final output. The MIT-BIH arrhythmia database was used for both algorithm training/tuning and evaluation. The assessment methodology followed the interpatient paradigm, where the algorithm was trained and evaluated using independent subsets. The performance of the proposed method was evaluated for two tasks; QRS detection, and heartbeat classification. QRS detection resulted in a sensitivity of 99.0% and a positive predictivity of 96.5%. The performance assessment of the ventricular ectopic beat detection resulted in a sensitivity of 85.8% and a positive predictivity of 64.5%. Although there is still room for improvement, the results suggest that convolutional neural networks are a promising approach for building heartbeat classifiers.

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A case of food supply chain management with AHP, DEMATEL, and TOPSIS
...
Ortiz Barrios, Miguel Angel | 2019-08-27

The bullwhip effect leads to considerable inefficiencies along the food supply chain such as missed production schedules, poor customer service, excessive inventory, and misguided capacity plans. To tackle this problem, it is necessary, apart from other interventions, to continuously monitor the performance of food suppliers so that the demand information flow, order batching, transportation planning, and inventory management can be substantially improved. Therefore, supplier assessment has then become critical decision‐making support for identifying and addressing inefficiencies of food providers, which ends up reducing the variation of several key logistics parameters for upstream members of the food supply chain. In addition, such assessment is of multicriteria nature given the presence of several criteria from different domains and various food suppliers. With these considerations in mind, this paper proposes a hybrid approach integrating the analytic hierarchy process (AHP), decision‐making trial and evaluation laboratory (DEMATEL), and the technique for order of preference by similarity to ideal solution (TOPSIS) for evaluating the performance of pork suppliers. Thereby, the economic and operational burden caused by the bullwhip effect throughout the pork supply chain can be alleviated. AHP was first used to determine the criteria and subcriteria weights. Then DEMATEL was applied to assess the interdependence and feedback between the decision elements. Finally, TOPSIS was implemented to discriminate between high‐performance and low‐performance pork suppliers. A case study from the Colombian pork supply chain is presented to validate the proposed approach. The results of this study evidenced that the most important criterion was the “service level” and the most influencing factor was the “financial profile.” In addition, based on the supplier assessment results, improvement plans, and new negotiation, strategies were established for each supplier in order to diminish the bullwhip effect along the pork supply chain.

LEER
A case of food supply chain management with ahp, dematel, and topsis
...
Ortiz Barrios, Miguel Angel | 2019-08-27

The bullwhip effect leads to considerable inefficiencies along the food supply chain such as missed production schedules, poor customer service, excessive inventory, and misguided capacity plans. To tackle this problem, it is necessary, apart from other interventions, to continuously monitor the performance of food suppliers so that the demand information flow, order batching, transportation planning, and inventory management can be substantially improved. Therefore, supplier assessment has then become critical decision‐making support for identifying and addressing inefficiencies of food providers, which ends up reducing the variation of several key logistics parameters for upstream members of the food supply chain. In addition, such assessment is of multicriteria nature given the presence of several criteria from different domains and various food suppliers. With these considerations in mind, this paper proposes a hybrid approach integrating the analytic hierarchy process (AHP), decision‐making trial and evaluation laboratory (DEMATEL), and the technique for order of preference by similarity to ideal solution (TOPSIS) for evaluating the performance of pork suppliers. Thereby, the economic and operational burden caused by the bullwhip effect throughout the pork supply chain can be alleviated. AHP was first used to determine the criteria and subcriteria weights. Then DEMATEL was applied to assess the interdependence and feedback between the decision elements. Finally, TOPSIS was implemented to discriminate between high‐performance and low‐performance pork suppliers. A case study from the Colombian pork supply chain is presented to validate the proposed approach. The results of this study evidenced that the most important criterion was the “service level” and the most influencing factor was the “financial profile.” In addition, based on the supplier assessment results, improvement plans, and new negotiation, strategies were established for each supplier in order to diminish the bullwhip effect along the pork supply chain.

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A color fusion model based on Markowitz portfolio optimization for optic disc segmentation in retinal images
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Escorcia-Gutierrez, Jose | 2021-07-15

Retinal disorders are a severe health threat for older adults because they may lead to vision loss and blindness. Diabetic patients are particularly prone to suffer from Diabetic Retinopathy. Identifying relevant structural components in color fundus images like the optic disc (OD) is crucial to diagnose retinal diseases. Automatic OD detection is complex because of its location in an area where blood vessels converge, and color distribution is uneven. Several image processing techniques have been developed for OD detection so far, but vessel segmentation is sometimes required, increasing computational complexity and time. Moreover, precise OD segmentation methods utilize complex algorithms that need special hardware or extensive labeled datasets. We propose an OD detection approach based on the Modern Portfolio Theory of Markowitz to generate an innovative color fusion model. Specifically, the training phase calculates the optimal weights for each color channel. A fusion of weighted color channels is then applied in the testing phase. This approach acts as a powerful and real-time preprocessing stage. We use four heterogeneous datasets to validate the presented methodology. Three out of four datasets are publicly available (i.e., DRIVE, Messidor, and HRF), and the last corresponds to an in–house dataset acquired from Hospital Universitari Sant Joan de Reus (Spain). Two different segmentation methods are presented and compared with state-of-the-art computer vision techniques to analyze the model performance. An outstanding accuracy and overlap above 0.9 and 80%, respectively, and a minimal execution time of 0.05 s are reached. Therefore, our model could be integrated into daily clinical practice to accelerate the diagnosis of Diabetic Retinopathy due to its simplicity, performance, and speed.

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A comprehensive study of biofilms growing on the built heritage of a caribbean industrial city in correlation with construction materials
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Gallego Cartagena, Euler | 2019

Biodeteriogens growing on constructions belonging to the built heritage is one of the leading natural pathologies that cause aesthetical and in some cases, physical-geochemical problems in the materials. In this study, for the first time, the chemical composition of construction materials of the built heritage from an industrialized city (Barranquilla) of Colombia have been evaluated in correlation with the algal, cyanobacterial and fungal biodeteriogens present in biofilms by applying a multianalytical methodology. To achieve this objective, samples of biofilms and construction material were taken from different historical and modern constructions. For the mineralogical characterization of the construction materials, X-ray diffraction, Raman microscopy and energy dispersive X-ray fluorescence spectrometry (EDXRF) were used. In addition, microscopic observations and cultures were employed for the microbiological characterization. Most of the construction materials analyzed belong to calcareous mortars, and others to different types of cement (portlandite, ettringite and larnite identification). The EDXRF analysis through single point and imaging strategies allowed to identify differences in the elemental composition of the external and internal parts of the materials. The role of certain elements in the mortars, which will assist the growth of specific microorganisms, is also discussed in this work. The main biodeteriogens identified in the biofilms were cyanobacteria Oscillatoria sp., Lyngbya sp., Leptolyngbya sp. and Ascomycota Aspergillus niger, Aspergillus fumigatus, Penicillium sp. and Fusarium sp fungi. These microorganisms promote biodeterioration processes causing aesthetic, physical and chemical damage to the façades of the studied buildings. The mineralogical composition of the construction material together with environmental conditions contributes to the development of biofilms on the constructions and monuments of Barranquilla city. The results obtained in this study will be used in the future to design and implement conservation protocols and strategies useful to preserve the built heritage of Caribbean cities with similar climate conditions, geographical position and kind of construction materials

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A FAHP-VIKOR approach for supporting the selection of tomography equipment in LMIC hospitals: a case study
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Ortíz-Barrios, Miguel | 2021

Computerized Tomography Scanners (CT-SCAN) provide detailed cross-sectional images of the human body which are employed for the easier detection and further analysis of abnormalities concerning the functionality and structure of the skeleton, tissues, and organs. However, the appropriate CT-SCAN selection is an arduous task considering the complexity and high cost of these medical devices. This decision is even more sharpener in hospitals from Low-and-Middle-Income-Countries (LMIC) where the available budget is usually restricted and correct resource allocation should be therefore ensured while granting the greatest impact on the timeliness and efficacy of healthcare services. In this framework, multiple criteria from diverse fields need to be taken into account to satisfy the intricate requirements of users. In this regard, it is necessary to fully elicit the expectations of stakeholders as well as identify their importance in an overall decision-making context. To address these gaps, this study proposes a novel integration between the Fuzzy Analytic Hierarchy Process (FAHP) and VIKOR methods for the CT-SCAN selection problem. Initially, a Multi-Criteria Decision-Making (MCDM) model will be designed for selecting the most suitable CT-SCAN option for a particular LMIC hospital. Then IF-AHP will be applied to calculate the relative priorities of criteria and sub-criteria under uncertainty. Ultimately, VIKOR will be implemented for obtaining an overall decision-making context. To address these gaps, this study proposes a novel integration between the Fuzzy Analytic Hierarchy Process (FAHP) and VIKOR methods for the CT-SCAN selection problem. Initially, a Multi-Criteria Decision-Making (MCDM) model will be designed for selecting the most suitable CT-SCAN option for a particular LMIC hospital. Then IF-AHP will be applied to calculate the relative priorities of criteria and sub-criteria under uncertainty. Ultimately, VIKOR will be implemented for obtaining an overall appropriateness index per CT-SCAN candidate and thereby identifying the most pertinent one (s) for a specific LMIC medical institution. © 2021, Springer Nature Switzerland AG.

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A fuzzy logic proposal for diagnosis multiple incipient faults in a power transformer
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Fernández Blanco, Juan Carlos | 2021

For the safety and continuity of service in industrial electrical systems, the availability of transformers is essential. For this reason, it is necessary to develop intelligent fault diagnosis techniques to reduce repair and maintenance costs. Recently, several methods have been developed that use artificial intelligence techniques such as neural networks, support vector machines, hybrid techniques, etc., for the diagnosis of faults in power transformers using gas analysis. These methods, although they present very good results, encounter restrictions to determine the precise moment before the occurrence of multiple fault of small magnitude and are difficult to implement in practice. This document proposes a method to diagnose multiple incipient faults in a power transformer using fuzzy logic. The proposal, based on historical data from the composition of the gases dissolved in the oil, achieves a performance in the classification of multiple incipient fault of 98.3%. With reliable samples of dissolved gas, it guarantees an overall rate of accuracy in detecting incipient faults that is superior to that obtained by the most successful conventional methods in the industry. The proposal does not encounter generalization difficulties and constitutes a simple solution that allows determining the state of the transformer in service without affecting the continuity of the electricity supply.

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A generic materials and operations planning approach for inventory turnover optimization in the chemical industry
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Coronado-Hernández, Jairo R. | 2020

Chemical industries usually involve continuous and large-scale production processes that require demanding inventory control systems. This paper aims to show the results of the implementation of a mixed-integer programming model (MIP) based on the Generic Materials and Operations Planning Problem (GMOP) for optimizing the inventory turnover in a fertilizer company. Results showed significant improvements for Inventory Turnover Ratios and overall costs when compared with an empirical production planning method.

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A hybrid fuzzy multi-criteria decision making model for selecting a sustainable supplier of forklift filters: a case study from the mining industry
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Ortiz-Barrios, Miguel | 2020-07-30

Supplier selection has long been a strategic cornerstone for the advancement of companies from the mining sector due to its impact on many sectors as inventory management, production planning, maintenance scheduling, financial resources and environment. In this regard, expert decision-makers should deem a number of performance conflicting criteria and supplier alternatives. Moreover, choosing a suitable Multi-Criteria Decision Making (MCDM) approach has become a key strategic consideration for supplier selection. Hence, this paper presents a combination of powerful MCDM methods to select the most suitable supplier of forklift filters. The Fuzzy Analytic Hierarchy Process (FAHP) is first used to calculate the initial weights of criteria and sub-criteria under uncertainty, followed by the implementation of Fuzzy Decision Making Trial and Evaluation Laboratory (FDEMATEL) to assess the interrelations and feedback between them. The fuzzy theory is used in both AHP and DEMATEL methods to represent the human vagueness when making judgments. Then, FAHP and FDEMATEL are combined to obtain the final contributions of both criteria and sub-criteria on the basis of interrelations and uncertainty. Finally, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used to rank the supplier alternatives. To validate the effectiveness of the proposed framework, a case study is presented. The results evidence that quality criterion is the most crucial aspect when selecting suppliers of forklift filters.

LEER
A hybrid fuzzy multi-criteria decision-making model to evaluate the overall performance of public emergency departments: a case study
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Ortiz Barrios, Miguel Angel | 2020-10-05

Performance evaluation is relevant for supporting managerial decisions related to the improvement of public emergency departments (EDs). As di®erent criteria from ED context and several alternatives need to be considered, selecting a suitable Multicriteria Decision-Making (MCDM) approach has become a crucial step for ED performance evaluation. Although some methodologies have been proposed to address this challenge, a more complete approach is still lacking. This paper bridges this gap by integrating three potent MCDM methods. First, the Fuzzy Analytic Hierarchy Process (FAHP) is used to determine the criteria and sub-criteria weights under uncertainty, followed by the interdependence evaluation via fuzzy DecisionMaking Trial and Evaluation Laboratory (FDEMATEL). The fuzzy logic is merged with AHP and DEMATEL to illustrate vague judgments. Finally, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is used for ranking EDs. This approach is validated in a real 3-ED cluster. The results revealed the critical role of Infrastructure (21.5%) in ED performance and the interactive nature of Patient safety (C þ R ¼ 12:771). Furthermore, this paper evidences the weaknesses to be tackled for upgrading the performance of each ED.

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A mathematical model for the optimization of the non-metallic mining supply chain in the mining district of Calamarí-Sucre (Colombia)
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Ospina-Mateus, Holman | 2020

This article presents a mathematical model of the Supply chain of non-metallic mining. The model considers uncertainty scenarios in materials, elements for capacity planning in a multilevel chain and with multiple products. The mathematical model is collaborative and maximizes the profits of the actors in the supply chain. The model is implemented in Calamarí-Sucre mining district (Colombia). The scenario is applied to the extraction, processing, storage, and distribution of limestone. To solve the model, the GAMS software was used through libraries of relaxed mixed nonlinear programming - RMINLP and the DICOPT solver. The results indicate that the greatest benefits occur in a scenario of the high provision of raw materials. The equity in the economic benefits show a dynamics of vertical integration in the sector. The model applied to non-metallic mining complexes helps determine optimal strategies and decisions in different echelons.

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A method for estimating the age of people in forensic medicine using multivariable statistics
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BARRAZA SALCEDO, MARÍA DEL SOCORRO | 2020-09-08

The present study seeks to generate a regression model that allows estimating the age of individuals in the city of Barranquilla (Colombia) from the stages of people’s teeth, in order to generate a tool to help forensic doctors in the identification of bodies in a high degree of decomposition. The model showed that sex and teeth 23, 27, 38, and 47 have a statistically significant relationship with age, and although the model has a medium level of explanation (adjusted R-square of 56%), it is a very useful tool for estimating the age of the inhabitants of Barranquilla given that the current standards are based on studies carried out in other countries with genotypic and phenotypic characteristics that differ from Barranquilla people.

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A method for the prediction of the shrinkage in roasted and ground coffee using multivariable statistics
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Parody Muñoz, Alexander Elias | 2020-09-08

This study seeks to determine the influence of process variables: consumption percentage in the mixture, pasilla percentage in the mixture, storage time, humidity percentage in the product for consumption, humidity percentage in the pasilla, humidity percentage in roasted coffee, average humidity in finished product, average color in roasted coffee, and average color in finished product, for the shrinkage of packed coffee in a coffee processing plant of Arabica type. Using a multiple linear regression model, the study stated that the variables of humidity percentage of roasted coffee and color of roasted coffee have a statistically significant relationship with a confidence of 95% (p-value < 0.05). It was concluded that these variables explain 99.95% of the variability in the shrinkage, and the relation of the shrinkage with the humidity percentage is inversely proportional, but the relation of this variable with the color of roasted coffee is directly proportional. The tests applied to the model wastes proved that the model is suitable for predicting the shrinkage in the process.

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A methodology to estimate baseline energy use and quantify savings in electrical energy consumption in higher education institution buildings: Case study, Federal University of Itajubá (UNIFEI)
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Ocampo Batlle, Eric Alberto | 2020-01-20

Accurately forecasting energy consumption in a building is an important strategy for achieving the goal of reducing energy demand and improving energy efficiency. University campuses represent specific groups of diverse buildings with significant energy consumption. Therefore, they provide an excellent testbed to characterize and understand the energy consumption of a group of mixed-use buildings. This paper presents a novel methodology that considers the recommendations of ISO 50001: 2011 and ISO 50006: 2014 for establishing energy baselines and energy performance indicators in higher education institution buildings to identify electrical energy consumption reduction potentials in buildings and establish energy management strategies related to electricity use. The study was implemented in three buildings at the Federal University of Itajubá (José Rodrigues Seabra Campus). Several methods and indicators were evaluated to monitor and measure energy performance in buildings. A wide range of factors that influence operating system energy consumption in the buildings were studied and taken into account, such as the types of activities carried out in the building, weather conditions, building materials, air conditioning system and occupancy, since these contribute directly and indirectly to the difficulty of accurately measuring the building’s energy consumption. The results showed that potential annual savings in electric energy consumption for the campus could be around 9.6%, which translates into a R$ 93,647.2 economic value and a 20.3 tCO2eq emissions reduction without economic investment. It was concluded that the methodology proposed for establishing and monitoring an energy efficiency indicator can be applied to any institute of higher education because it is flexible and adaptable since each institute can define the period of analysis for the indicator. This research is expected to provide theoretical guidance and a practical data reference for relevant evaluations of building energy efficiency.

LEER
A mho type phase comparator relay guideline using phase comparison technique for a power system
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González-Cueto Cruz, José Antonio | 2021-04

This paper presents a mho distance relay simulation based on the phase comparison technique using a typical electrical power systems analysis software for two cases: when the operation state is close to the static voltage limit and during a dynamic perturbation in the system. The paper evaluates the impedance variations caused by complex voltage values, the mho polarization, and the comparator operating region into the complex plane. In addition, the paper found the information for the dynamic perturbations from the outputs considering a mid-term stability program. The simulation of the mho-phase comparator in the static voltage proximity limit detects unit distance elements with impedance measured close to reach the threshold in the steady-state. Dynamic mho simulations in the complex plane are successfully tested by plotting time phase difference curves on the comparator input signals. Relay programmers can use these curves to analyze other phase comparators applications and the corresponding models in the complex plane.

LEER
A multicriteria decision‐making framework for assessing the performance of gynecobstetrics departments: a case study
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Ortiz Barrios, Miguel Ángel | 2021-02

Gynecobstetrics departments (GDs) oversee diagnosing, monitoring, and treating female reproductive diseases as well as assisting women during pregnancy. Their importance motivates the creation of suitable performance evaluation approaches for identifying weaknesses and designing focused interventions. Therefore, the aim of this paper is twofold: (a) provide an approach for GD performance evaluation and (b) propose interventions tackling the GDs’ weaknesses. The fuzzy analytic hierarchy process (FAHP) was first applied to calculate the initial criteria and subcriteria weights under vagueness. Then, the decision‐making trial and evaluation laboratory (DEMATEL) was implemented to evaluate interrelations. FAHP and DEMATEL were later combined to estimate the final criteria and subcriteria weights under vagueness and interdependency. Finally, the technique for order of preference by similarity to ideal solution (TOPSIS) was used to rank the GDs and detect improvement opportunities. A case study of a cluster including three GDs is presented to validate the proposed approach. The results evidenced that patient safety and service quality are the most critical aspects in GD performance evaluation. The results from this application can be used by healthcare managers for designing focused interventions targeting improved performance of GDs. This paper fully exploits the advantages of FAHP, DEMATEL, and TOPSIS methods for evaluating performances of GDs. Furthermore, this study presents a novel decision‐making model representing the multifactorial context of the GD performance.

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A multiple criteria decision-making approach for increasing the preparedness level of sales departments against COVID-19 and future pandemics: A real-world case
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Ortiz-Barrios, Miguel | 2021

The impact of the pandemic and the lockdown has been more devastating than expected on the world economy. It is essential to formulate strategies in real-time. In this research, a multicriteria decision-making model for increasing the preparedness level of sales departments when facing COVID-19 waves and future pandemics is proposed. The model is comprised of 8 criteria, 29 sub-criteria, and 7 alternatives. The study is based on the integration of the AHP and TOPSIS techniques. AHP is used for calculating the criteria and sub-criteria weights. While, TOPSIS is used for calculating the preparedness level, ranking the companies, and identifying the weaknesses that should be addressed for increasing their effectiveness in the current market scenario. The model is developed with the aid of an experts’ group from the electrical appliance sector and studies from the reported literature. This application is completely novel in the literature and has been applied in the wild with remarkable companies in Colombia. A case study in the electrical appliance sector is presented as a pilot study but it should be noted that the methodology is flexible and scalable in any scenario.

LEER
A new formulation for strength characteristics of steel slag aggregate concrete using an artificial intelligence-based approach
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Awoyera, Paul | 2021

Studies examining nanoparticles (NPs) and hazardous elements (HEs) contained in suspended sediments (SSs) are vital for watershed administration and ecological impact evaluation. The biochemical consequence of titanium-nanoparticles (Ti-NPs) from SSs in Colombia's Magdalena River was examined utilizing an innovative approach involving nanogeochemistry in this study. In general, the toxicity and the human health risk assessment associated with the presence of some Ti-NPs + HEs in SSs from riverine systems need to be determined with a robust analytical procedure. The mode of occurrence of Ti-NPs, total Ti and other elements contained within SSs of the Magdalena River were evaluated through advanced electron microscopy (field emission scanning electron microscope-FE-SEM and high resolution transmission electron microscope-HR-TEM) coupled with an energy dispersive X-ray microanalysis system (EDS); X-Ray Diffractions (XRD); and inductively coupled plasma-mass pectrometry (ICP-MS). This work showed that enormous quantities of Ti-NPs were present in the river studied and that they displayed diverse eochemical properties and posed various possible ecological dangers. Ti-NP contamination indices must be established for measuring the environmental magnitudes of NP contamination and determining contamination rank among rivers. Finally, SS contamination guidelines must be recommended on an international level. This study contributes to the scientific understanding of the relationship of HE and Ti-NP dynamics from SSs in riverine systems around the world.Keywords Titanium-nanoparticles, Rutile and Anatase nano-minerals, Particle mode of occurrence, Size-dependent properties, Nanomineral–water interface, Surface particle geochemistry.

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A new methodology incorporating public participation within Cuba's ICZM program
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Milanés Batista, Celene | 2020-01-20

Although public participation (PP) has influenced some integrated coastal zone management (ICZM) programs around the world, researchers have rarely analyzed this component specifically inside an ICZM cycle. Furthermore, the approach for integrating environmental energy planning tools within the ICZM Programs for the Small Island Developing States (SIDS) has presented an ongoing challenge for specialists involved in management issues. In Cuba, plans for coastal development are supported by land use planning activities and environmental planning tools. However, the functions and outputs of those tools are “non-obvious”, precluding sufficient integration among them. As these aforementioned actions have not been systematically carried out in the Cuban territory, and the systems of inter-institutional relationships with local communities have presented some insufficiencies, the national marine-terrestrial interphase has suffered some negative environmental impacts impossible to be solved by the national authorities. Designing a new methodology that incorporates PP and environmental energy planning tools in the stages of an ICZM program is the objective of this article. The methodology was named MePuPa and has improved current tools for land use planning and ICZM in Cuba. Previously selected “Local Indicators of Environmental Sustainability”, applied in two geo-systemic units in the southeastern region of Cuba, were used to demonstrate the methodology. The qualitative and qualitative methods in the proposed MePuPa were also applied. Finally, the MePuPa methodology was tested for four of its five stages. Six advantages and five learned lessons were identified during the Preparation to Proposal stages. MePuPa resulted in a useful local management tool for environmental energy planning, ICZM, economic and agricultural activities, strategic ecosystems recovery, as well as improvements to the governance and decision-making processes in one SIDS.

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A practical methodology of design of off-line reservoirs for reducing maximum water levels in urban channels
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Coronado-Hernández, Oscar E. | 2020

Flooding can often occur in many places due to the increasing trend of rainfall events (climate change), the urbanization process of a catchment area, or by an undersized urban channel. Reservoirs are used for limiting flooding since they can store an enough water volume. This research presents a practical procedure for sizing off-line reservoirs with an application in urban channels for places with space limitations. A complete formulation is presented, which can be easily used for designers and engineers for computing dimensions of off-line reservoirs. The formulation is applied to a case study located at the Cartagena de Indias, Colombia.

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