Person:
Vanegas Peralta, Pablo Fernando

Birth Date

1972-05-28

ORCID

0000-0003-3418-7670

Scopus Author ID

25522712400

Afiliación

Universidad de Cuenca, Cuenca, Ecuador
Universidad de Cuenca, Departamento de Ciencias de la Computación, Cuenca, Ecuador
Universidad de Cuenca, Departamento de Espacio y Población, Cuenca, Ecuador
Universidad de Cuenca, Facultad de Ciencias Químicas, Cuenca, Ecuador
Universidad de Cuenca, Departamento de Ingeniería Eléctrica, Electrónica y Telecomunicaciones(DEET), Cuenca, Ecuador
KU Leuven (Katholieke Universiteit Leuven), Leuven, Bélgica

País

Ecuador

Organizational Units

Organizational Unit

Facultad de Ingeniería

La Facultad de Ingeniería, a inicios de los años 60, mediante resolución del Honorable Consejo Universitario, se formalizó la Facultad de Ingeniería de la Universidad de Cuenca, conformada por las escuelas de Ingeniería Civil y Topografía. Esta nueva estructura permitió una mayor especialización y fortalecimiento en áreas clave para el desarrollo regional. Cuenta con programas académicos reconocidos internacionalmente, que promueven y lideran actividades de investigación. Aplica un modelo educativo centrado en el estudiante y con procesos de mejora continua. Establece como prioridad una educación integra, la formación humanística es parte del programa de estudios que complementa a la sólida preparación científico-técnica. Las actividades culturales pertenecen a un programa permanente y activo al interior de nuestras dependencias, a la par de proyectos que desde el alumnado y bajo la supervisión de docentes cumplen con servicios de apoyo a nivel local y regional; promoviendo así una vinculación estrecha con la comunidad.

Job Title

Profesor (T)
Rector de la Universidad de Cuenca (2016 - 2021)
Decano de la Facultad de Ingeniería de la Universidad de Cuenca
Subdecano de la Facultad de Ingeniería de la Universidad de Cuenca
Vicerrector de Investigación y Posgrado en la Escuela Superior Politécnica de Chimborazo (ESPOCH) (2021 - )

Last Name

Vanegas Peralta

First Name

Pablo Fernando

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Search Results

Now showing 1 - 10 of 24

The design of a flexible bus line plan
(2022) Vanegas Peralta, Pablo Fernando; Vansteenwegen, Pieter; Ávila Ordóñez, Elina María; Tampére, Chris
A conventional bus service has a line plan that consists of a set of lines with fixed routes designed to operate under normal conditions. Thus, the performance of the service depends on how stable those conditions are. This paper extends the traditional concept of a line plan to provide a high-quality service, even in case of announced events. We introduce the concept of a Flexible Line Plan where some of the usual lines are replaced with alternative lines that improve the service when the conditions change. Adaptations should only be made to a subset of the lines, ensuring that the changes minimize the inconvenience for the regular passengers and, at the same time, improve the total travel time. In this study, we present a heuristic called Alternative Line Heuristic (ALH), based on Genetic Algorithms, which automatically designs these alternative lines in a three-step process. The results of this approach are tested on both benchmark and real-sized networks and clearly show how our approach contributes to improving the bus service performance.
A procedure for semi-automatic segmentation in OBIA based on the maximization of a comparison index
(SPRINGER VERLAG, 2014-06-30) Auquilla Sangolquí, Andrés Vinicio; Vanegas Peralta, Pablo Fernando
In an Object Based Image Analysis Classification (OBIA) process, the quality of the classification results are highly dependent on segmentation. However, a high number of the studies that make use of an OBIA process find the segmentation parameters by making use of trial-and-error methods. It is clear that a lack of a structured procedure to determine the segmentation parameters produces unquantified errors in the classification. This paper aims to quantify the effects of using a semi-automatic approach to determine optimal segmentation parameters. To this end, an OBIA process is performed to classify land cover types produced by both a manual and an automatic segmentation. Even though the classification using the manual segmentation outperforms the automatic segmentation, the difference is only 2%. Since the automatic segmentation is performed with optimal parameters, a procedure to accurately determine those parameters must be performed to minimize the error produced by a misjudgment in the segmentation step. © 2014 Springer International Publishing.
MILP for optimizing water allocation and reservoir location: a case study for the Machángara river basin, Ecuador
(2019) Veintimilla Reyes, Jaime Eduardo; De Meyer, Annelies; Cattryss, Dirk; Tacuri Espinoza, Víctor Eduardo; Cisneros Espinoza, Felipe Eduardo; Van Orshoven, Jos; Vanegas Peralta, Pablo Fernando
The allocation of water flowing through a river-with-reservoirs system to optimally meet spatially distributed and temporally variable demands can be conceived as a network flow optimization (NFO) problem and addressed by linear programming (LP). In this paper, we present an extension of the strategic NFO-LP model of our previous model to a mixed integer linear programming (MILP) model to simultaneously optimize the allocation of water and the location of one or more new reservoirs; the objective function to minimize only includes two components (floods and water demand), whereas the extended LP-model described in this paper, establishes boundaries for each node (reservoir and river segments) and can be considered closer to the reality. In the MILP model, each node is called a “candidate reservoir” and corresponds to a binary variable (zero or one) within the model with a predefined capacity. The applicability of the MILP model is illustrated for the Machángara river basin in the Ecuadorian Andes. The MILP shows that for this basin the water-energy-food nexus can be mitigated by adding one or more reservoirs.
Artificial neural networks applied to flow prediction: A use case for the Tomebamba river
(Elsevier Ltd, 2016) Veintimilla Reyes, Jaime Eduardo; Cisneros Espinoza, Felipe Eduardo ; Vanegas Peralta, Pablo Fernando; Veintimilla Reyes, Jaime Eduardo
The main aim of this research is to create a model based on Artificial Neural Networks (ANN) that allows predicting the flow in Tomebamba river, at real time and in a specific day of a year. As inputs, this research is using information of rainfall and flow of the stations along of the river. This information is organized in scenarios and each scenario is prepared to a specific area. For this article, we have selected two scenarios. The information is acquired from the hydrological stations placed in the watershed using an electronic system developed at real time and it supports any kind or brands of this type of sensors. The prediction works very good three days in advance. This research includes two ANN models: Backpropagation and a hybrid model between back propagation and OWO-HWO (output weight optimization–hidden weight optimization) to select the initial weights of the connection. These last two models have been tested in a preliminary research. To validate the results we are using some error indicators such as MSE, RMSE, EF, CD and BIAS. The results of this research reached high levels of reliability and the level of error is minimal. These predictions are useful to avoid floods in the city of Cuenca in Ecuador.
Air jet spray of nylon 6 membrane structures for bone tissue engineering
(ELSEVIER, 2014-06-15) Abdal-Hay, A; Vanegas Peralta, Pablo Fernando
A novel porous nylon 6 (N6) scaffold with high and low porosity was designed using a facile, one-step approach. The scaffold samples were prepared using air jet spray (AJS) to obtain high production rates as an alternative low cost, effective technique with precise thickness control. The present results show that AJS adequately produced interconnected porous networks ranging from micron to submicron scales that were observed using a scanning electron microscope. The effect of AJS on the secondary structure of N6 was examined to identify and quantify conformational changes that occurred due to processing. The mechanical properties of the fabricated samples were tested. The results of tensile tests indicated higher tensile strength of AJS scaffold than that of electrospun scaffold. © 2014 Elsevier B.V. All rights reserved.
SWE sensor integration for controlling remote sensors applied to hidrometeorological sensing
(Institute of Electrical and Electronics Engineers Inc., 2017) Veintimilla Reyes, Jaime Eduardo; Guillermo Anguisaca, Juan Carlos; Vanegas Peralta, Pablo Fernando; Estrella Maldonado, René Gustavo; Veintimilla Reyes, Jaime Eduardo
Currently, information and communicaton technology are omnipresent, the response time to cope specific events, for instance, hydrometeorological events, is becoming a crucial advantage in order to reduce to the minimal those effects. An example of the technology used to support this kind of early alert systems and the minimization of the effects related to is Sensor Web Enablement (SWE). SWE y all of its components/standards (SOS, SPS, SES y WNS) have become an highly recommended option to the aquisition, organization and visualization of the information from hydrological remote sensors. This paper proposes and SWE-based architecture, which allows to acquire, organizes and publicates hydrometeorological information also provides the possibility to establish configurations in the sensor by using the WNS standard to send alerts based in the occurrence of events, besides, task planning is also possible by using the SPS standard.
Allocating reforestation areas for sediment flow minimization: an integer programming formulation and a heuristic solution method
(2012) Vanegas Peralta, Pablo Fernando
Policy and decision makers dealing with environmental conservation and land use planning often require identifying potential sites for contributing to minimize sediment flow reaching riverbeds. This is the case of reforestation initiatives, which can have sediment flow minimization among their objectives. This paper proposes an Integer Programming (IP) formulation and a Heuristic solution method for selecting a predefined number of locations to be reforested in order to minimize sediment load at a given outlet in a watershed. Although the core structure of both methods can be applied for different sorts of flow, the formulations are targeted to minimization of sediment delivery. The proposed approaches make use of a Single Flow Direction (SFD) raster map covering the watershed in order to construct a tree structure so that the outlet cell corresponds to the root node in the tree. The results obtained with both approaches are in agreement with expert assessments of erosion levels, slopes and distances to the riverbeds, which in turn allows concluding that this approach is suitable for minimizing sediment flow. Since the results obtained with the IP formulation are the same as the ones obtained with the Heuristic approach, an optimality proof is included in the present work. Taking into consideration that the heuristic requires much less computation time, this solution method is more suitable to be applied in large sized problems.
Compactness and flow minimization requirements in reforestation initiatives: A heuristic solution method
(KLUWER ACADEMIC PUBLISHERS, 2014-01-01) Vanegas Peralta, Pablo Fernando; Wijffels Anja, Louisa María
A heuristic solution method to identify a predefined number of cells in raster maps optimizing both multiple intrinsic cell characteristics and cell patch compactness (Vanegas et al. in Lect. Notes Comput. Sci. 5072:389-404, 2008), is extended so that also spatial interaction is taken into account. Spatial interaction is e.g., present in the flow of sediment between cells in a rasterised watershed as modified by the presence or absence of tree cover in a given cell. The resulting HLC-method is elaborated and tested in the context of a site location problem for reforestation in which the following criteria are considered: (1) the sediment flow reaching the outlet of the watershed is minimized, (2) two intrinsic environmental performances of the cells are maximized/minimized, and (3) the selected cells form a compact patch. To evaluate the performance of the HLC, its results are compared to the ones obtained with an Integer Programming (IP) formulation. This comparison suggests that the HLC identifies high quality, near-to-optimal patches of cells and that its computational efficiency makes it applicable to regional sized cases. © 2011 Springer Science+Business Media, LLC.
Left ventricle myocardium segmentation in multi-slice computerized tomography
(INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS INC., 2016-10-19) Bautista Llivisaca, Mateo Sebastian; Morocho Zurita, Carlos Villie; Vanegas Peralta, Pablo Fernando
This paper briefly describes a left ventricle myocardium segmentation method in multi-slice computerized tomography images. The segmentation technique is based on level-sets deformable contours. The proposed method has two stages: in the first stage the left ventricle internal wall or endocardium is segmented. In the second stage the external wall is segmented starting with an initialization based on the endocardial segmented shape. This algorithm is intended for incorporation within a software platform for visualization and processing of cardiac images. This platform would help the diagnosis of the left ventricle hypertrophy (LVH).
Optical Flow as a Tool for Cardiac Motion Estimation
(INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS INC., 2015-07-14) Medina Molina, Ruben; Morocho Zurita, Carlos Villie; Vanegas Peralta, Pablo Fernando
A sparse based algorithm for optical flow estimation is presented and compared with several classical optical flow estimation algorithms. The comparison is performed using several video sequences available from the Middlebury benchmark where the ground truth optical flow is known. The sparse algorithm attains competitive results with average angular errors as low as 2.09° and average magnitude errors as low as 0.100. The algorithms are also tested using a 4 - D cardiac Magnetic Resonance Image (MRI) sequence. The sparse algorithm estimates an optical flow field that represents the motion of contraction during the systole interval.