Las ciencias básicas en la formación del ingeniero : el caso del Álgebra Lineal

Ángela Mercedes Martín Sánchez (biografía): Doctora en Ciencias Pedagógicas, Universidad de Camagüey, Cuba. Maestrías en Ciencias de la Educación, mención Enseñanza de la Matemática Media Superior y en Matemática Pura, en las Universidades de Camagüey y Universidad Autónoma de Santo Domingo (UASD), respectivamente. Egresada de la Escuela de Química de la Facultad de Ciencias de la UASD. Investigadora Titular del MESCyT en el área de Matemática Educativa. Coautora de la investigación que obtuvo el Premio Nacional de la Academia de Ciencias de Cuba 2009 y 2018. Miembro asociado del Comité Latinoamericano de Matemática Educativa (CLAME). Coordinadora de la Cátedra de Algebra y profesora de Matemática en UNAPEC.// Olga Lidia Pérez González (biografía): Doctora en Ciencias Pedagógicas. Premio Nacional Pablo Miquel de enseñanza de la Matemática, de la Sociedad Cubana de Matemática y Computación; Premio Nacional Academia de Ciencias de Cuba 2009 y 2018. Directora del Grupo de Investigaciones de Matemática Educativa de la UC. Presidente del Comité Latinoamericano de Matemática Educativa (CLAME).El siglo XXI se ha caracterizado por profundas transformaciones en la educación superior, producto de los crecientes cambios mundiales en los ámbitos económico, científico, social, cultural y político. Entre esas transformaciones cabe destacar la implementación del enfoque basado en competencias en las carreras de ingeniería, que ha creado gran expectativa y un movimiento renovador en los profesores de las asignaturas del área de las ciencias básicas; lo que ha instado a la comunidad académica del nivel superior a buscar una visión estratégica para el proceso de formación, con el objetivo de prever el panorama en el cual se desempeñarán los ingenieros en el futuro. La experiencia dice que no todos los aspectos de la asignatura Matemática tienen la misma importancia para el futuro ingeniero; por tanto, es necesario, analizar convenientemente la cuestión del ordenamiento racional de la información conceptual que éste necesita; lamentablemente, falta la integración de los contenidos. Además, por lo general el proceso está orientado al aprendizaje de cada uno de los conceptos por separado, al desarrollo de habilidades de generalización y a la comprensión desde la relación parte/todo; de manera que se limita el trabajo independiente y la creatividad de los estudiantes

Optimized Network for Detecting Burr-Breakage in Images of Milling Workpieces

[EN] Quality standards fulfilment is an essential task in manufacturing processes that involves high costs. One target is to avoid the presence of burrs in the edge of machine workpieces, which reduce the quality of the products. Furthermore, they are not easily removed since the part can even be damaged. In this paper, we propose an optimized Convolutional Neural Network, to detect the presence of burrs in images of milling parts. Its design is focused on the optimization of classification (accuracy) and performance metrics (training time and number of trainable parameters). The proposed architecture identifies burrs with a 91.16\% accuracy in the test set, outperforming existing models as EfficientNetB0. It also reduces the number of trainable parameters from other models as AlexNet by 1.5 million. The prediction process just takes 48.39 milliseconds per image. Finally, in order to check if the model gets a high activation in the region of interest, a visual explanation of the model is also carried out by using Gradient-weighted Class Activation Mapping.S

Facilitating the learning process in parallel computing by using instant messaging

[EN] Parallel Programming skills may require a long time to acquire. “Think in parallel” is a skill that requires time, efort, and experience. In this work, we propose to facilitate the students’ learning process in parallel programming by using instant messaging. Our aim was to fnd out whether students’ interaction through instant messaging tools is benefcial for the learning process. In order to do so, we asked several students of an HPC course of the Master’s degree in Computer Science of the University of León to develop a specifc parallel application, each of them using a diferent application program interface: OpenMP, MPI, CUDA, or OpenCL. Even though the used APIs are diferent, there are common points in the design process. We encouraged students to interact with each other by using Gitter, an instant messaging tool for GitHub users. Our analysis of the communications and results demonstrate that the direct interaction of students through the Gitter tool has a positive impact on the learning process.SIMinisterio de Ciencia, Innovación y UniversidadesEuropean Commission Erasmus+ (2018-1-ES01-KA201-050939

A robot-based surveillance system for recognising distress hand signal

[EN] Unfortunately, there are still cases of domestic violence or situations where it is necessary to call for help without arousing the suspicion of the aggressor. In these situations, the help signal devised by the Canadian Women's Foundation has proven to be effective in reporting a risky situation. By displaying a sequence of hand signals, it is possible to report that help is needed. This work presents a vision-based system that detects this sequence and implements it in a social robot, so that it can automatically identify unwanted situations and alert the authorities. The gesture recognition pipeline presented in this work is integrated into a cognitive architecture used to generate behaviours in robots. In this way, the robot interacts with humans and is able to detect if a person is calling for help. In that case, the robot will act accordingly without alerting the aggressor. The proposed vision system uses the MediaPipe library to detect people in an image and locate the hands, from which it extracts a set of hand landmarks that identify which gesture is being made. By analysing the sequence of detected gestures, it can identify whether a person is performing the distress hand signal with an accuracy of 96.43%.SIAgencia Estatal de InvestigaciónEDMAR Project PID2021-126592OB-C21 funded by MCIN/AEI/10.13039/501100011033 and by ERDF A way of making Europ

Burr detection and classification using RUSTICO and image processing

.Machined workpieces must satisfy quality standards such as avoid the presence of burrs in edge finishing to reduce production costs and time. In this work we consider three types of burr that are determined by the distribution of the edge shape on a microscopic scale: knife-type (without imperfections), saw-type (presence of small splinters that could be accepted) and burr-breakage (substantial deformation that produces unusable workpieces). The proposed method includes RUSTICO to classify automatically the edge of each piece according to its burr type. Experimental results validate its effectiveness, yielding a 91.2% F1-Score and identifying completely the burr-breakage type.S

Dataset for herding and predator detection with the use of robots

[EN] Precision livestock farming involves the use of new technologies to improve the performance of farms with low profit margins. Since extensive livestock farming is demanding work requiring continuous supervision, it has not improved as drastically as agriculture. Furthermore, nowadays the world is more aware of the importance of respecting biodiversity and reducing the carbon footprint, for which sustainable animal production is recommended. This is the case of small livestock farms, generally located in unpopulated areas and with difficult generational replacement, due to the tasks involved. The use of robots and other devices equipped with intelligent systems can be useful to the farmer in his daily work. In this way, livestock, specifically flocks of sheep, can be monitored and the presence of potential predators such as the wolf identified. Encountering said predator can be avoided by moving the herd to other, safer pasture areas. This work presents a dataset that contains images and videos that allow detecting, classifying and analyzing flocks of sheep and one of their usual predators, wolves. The dataset includes videos of flocks in different locations, with different lighting conditions and different types of sheep. In addition, it contains images of wolves in natural spaces, which are not usually included in the most common datasets used in computer vision. This dataset can be very useful for the work being carried out in extensive precision livestock farming, to develop intelligent systems, such as a robot, that allow autonomous monitoring and control of a herd. Furthermore, it can be used to analyze animal behavior in the presence of a robot, since some of the images have been acquired with the cameras of a quadruped robot.SIGrant TED2021-132356B-I00 funded by MCIN/AEI/10.13039/501100011033 and by the ``European Union NextGenerationEU/PRTR''.Publicación en abierto financiada por el Consorcio de Bibliotecas Universitarias de Castilla y León (BUCLE), con cargo al Programa Operativo 2014ES16RFOP009 FEDER 2014-2020 DE CASTILLA Y LEÓN, Actuación:20007-CL - Apoyo Consorcio BUCL

¿Contribuye la didáctica del álgebra lineal a que los estudiantes identifiquen los espacios vectoriales como una estructura sistémica?

Considerando como antecedente que en el proceso de enseñanza aprendizaje de los espacios vectoriales existen dificultades con la concepción didáctica de los profesores para que los estudiantes identifiquen y utilicen los conceptos que se abordan en este tema, se realiza un diagnóstico para valorar los criterios de profesores y estudiantes en relación a la enseñanza de este tema. Se utiliza una metodología cuantitativa y cualitativa, se realiza un estudio descriptivo. Se asume como marco teórico la relación entre conocimiento común, especializado y propedéutico del contenido. Se concluye que la didáctica que sustenta el trabajo de los docentes no contribuye a que los estudiantes identifiquen los espacios vectoriales como una estructura sistémica

Is maize B chromosome preferential fertilization controlled by a single gene?

In previous work, genotypes for high and low B chromosome transmission rate were selected from a native race of maize. It was demonstrated that the B transmission is genetically controlled. The present work reports the fourth and fifth generations of selection and the F1 hybrids between the lines. The native B is characterized by a constant behaviour, with normal meiosis and nondisjunction in 100% of postmeiotic mitosis. It is concluded that genetic variation for B transmission between the selected lines is due to the preferential fertilization process. The F1 hybrids show intermediate B transmission rate between the lines. They are uniform, the variance of the selected character being one order of magnitude lower than that of the native population. In addition, 0B×2B and 2B×2B crosses were made to study the effect of the presence of B chromosomes in the female parent, resulting in non-significant differences. Several crosses were made both in Buenos Aires and in Madrid to compare the possible environmental effect, but significant differences were not found. Our results are consistent with the hypothesis of a single major gene controlling B transmission rate in maize, which acts in the egg cell at the haploid level during fertilization. It is also hypothesized that maize Bs use the normal maize fertilization process to promote their own transmission.Facultad de Ciencias Agrarias y Forestale

Estimation of lamb weight using transfer learning and regression

Meat production needs of accurate measurement of livestock weight. In lambs, traditional scales are still used to weigh live animals, which is a tedious process for the operators and stressful for the animal. In this paper, we propose a method to estimate the weight of live lambs automatically, fast, non-invasive and affordably. The system only requires a camera like those that can be found in mobile phones. Our approach is based on the use of a known Convolutional Neural Network architecture (Xception) pre-trained on the ImageNet dataset. The acquired knowledge during training is used to estimate the weight, which is known as transfer learning. The best results are achieved with a model that receives the image, the sex of the lamb and the height from where the image is taken. A mean absolute error (MAE) of 0.58 kg and an R2 of 0.96 were obtained, improving on current techniques. Only one image and two values specified by the user (sex and height) allow to estimate with a minimum error the optimal weight of a lamb, maximising the economic profit

From feelings of imprisonment to group cohesion: A qualitative analysis of group analytic psychotherapy with dual diagnosed patients admitted to an acute inpatient psychiatric unit

Objectives: Group cohesion, the establishment of hope, and the expression of feelings have been said to be the basic ingredients of group psychotherapy. To date, there is few literature describing therapeutic processes in short stay settings such as acute psychiatric wards and with special patient groups such as addictions. Our goal with this study is to describe and analyze group processes in such contexts. Methods: We used a qualitative methodology combining constant comparative methods and hermeneutical triangulation to analyze therapeutic narratives in the context of a group analytic process carried following Foulkes' and Yalom's styles. Results: The results provide a picture of the therapeutic process including the use of norms to strengthen group cohesion facilitating the expression of emotions in early stages of group development. Conclusions: This analysis is intended to be a guide for practitioners implementing group therapy in contexts involving several constraints, such as acute psychiatric wards