Self-sensing properties of alkali activated blast furnace slag (BFS) composites reinforced with carbon fibers

In recent years, several researchers have shown the good performance of alkali activated slag cement and concretes. Besides their good mechanical properties and durability, this type of cement is a good alternative to Portland cements if sustainability is considered. Moreover, multifunctional cement composites have been developed in the last decades for their functional applications (self-sensing, EMI shielding, self-heating, etc.). In this study, the strain and damage sensing possible application of carbon fiber reinforced alkali activated slag pastes has been evaluated. Cement pastes with 0, 0.29 and 0.58 vol % carbon fiber addition were prepared. Both carbon fiber dosages showed sensing properties. For strain sensing, function gage factors of up to 661 were calculated for compressive cycles. Furthermore, all composites with carbon fibers suffered a sudden increase in their resistivity when internal damages began, prior to any external signal of damage. Hence, this material may be suitable as strain or damage sensor.

Competències mediàtiques a l’IES Dr. Balmis d’Alacant

La introducció de les TIC en l’ensenyament (les TAC) planteja molts interrogants entre els membres de la comunitat educativa, especialment entre el professorat. L’atracció del mitjà per als aprenents, la manca de reflexió en l’ús, tant per part del professorat com de l’alumnat, la necessitat d’una formació específica, l’adequació de les infraestructures al concepte i a les possibilitats que ofereix el web 2.0 i la incorporació de les aplicacions TAC en les programacions d’aula són alguns aspectes que mereixen una atenció específica i una anàlisi detinguda. La base de gran part de les respostes rau en una planificació eficaç de la formació del professorat que satisfaça les expectatives de tothom. Els projectes de centre, la utilització de plataformes educatives com Moodle i l’autoformació són sendes que ens acosten envers les solucions. En aquest treball, hi centrem l’atenció en les valoracions, les pràctiques habituals, les actituds i els coneixements relacionats amb la competència mediàtica o digital del professorat de l’IES Dr. Balmis d’Alacant. Ens basem en una enquesta realitzada en línia que aplega aquests continguts en una combinació d’ítems de resposta tancada i d’altres de resposta oberta.

Spanish Nursing Students' Practical Experience of Computer Applications in Nursing

This study aimed to determine the level of computer practical experience in a sample of Spanish nursing students. Each student was given a Spanish language questionnaire, modified from an original used previously with medical students at the Medical School of North Carolina University (USA) and also at the Education Unit of Hospital General Universitario del Mar (Spain). The 10-item self-report questionnaire probed for information about practical experience with computers. A total of 126 students made up the sample. The majority were female (80.2%; n=101). The results showed that just over half (57.1%, n=72) of the students had used a computer game (three or more times before), and that only one third (37.3%, n=47) had the experience of using a word processing package. Moreover, other applications and IT-based facilities (e.g. statistical packages, e-mail, databases, CD-ROM searches, programming languages and computer-assisted learning) had never been used by the majority of students. The student nurses' practical experience was less than that reported for medical students in previous studies.

Constrained self-organizing feature map to preserve feature extraction topology

In many classification problems, it is necessary to consider the specific location of an n-dimensional space from which features have been calculated. For example, considering the location of features extracted from specific areas of a two-dimensional space, as an image, could improve the understanding of a scene for a video surveillance system. In the same way, the same features extracted from different locations could mean different actions for a 3D HCI system. In this paper, we present a self-organizing feature map able to preserve the topology of locations of an n-dimensional space in which the vector of features have been extracted. The main contribution is to implicitly preserving the topology of the original space because considering the locations of the extracted features and their topology could ease the solution to certain problems. Specifically, the paper proposes the n-dimensional constrained self-organizing map preserving the input topology (nD-SOM-PINT). Features in adjacent areas of the n-dimensional space, used to extract the feature vectors, are explicitly in adjacent areas of the nD-SOM-PINT constraining the neural network structure and learning. As a study case, the neural network has been instantiate to represent and classify features as trajectories extracted from a sequence of images into a high level of semantic understanding. Experiments have been thoroughly carried out using the CAVIAR datasets (Corridor, Frontal and Inria) taken into account the global behaviour of an individual in order to validate the ability to preserve the topology of the two-dimensional space to obtain high-performance classification for trajectory classification in contrast of non-considering the location of features. Moreover, a brief example has been included to focus on validate the nD-SOM-PINT proposal in other domain than the individual trajectory. Results confirm the high accuracy of the nD-SOM-PINT outperforming previous methods aimed to classify the same datasets.

A three-dimensional representation method for noisy point clouds based on growing self-organizing maps accelerated on GPUs

The research described in this thesis was motivated by the need of a robust model capable of representing 3D data obtained with 3D sensors, which are inherently noisy. In addition, time constraints have to be considered as these sensors are capable of providing a 3D data stream in real time. This thesis proposed the use of Self-Organizing Maps (SOMs) as a 3D representation model. In particular, we proposed the use of the Growing Neural Gas (GNG) network, which has been successfully used for clustering, pattern recognition and topology representation of multi-dimensional data. Until now, Self-Organizing Maps have been primarily computed offline and their application in 3D data has mainly focused on free noise models, without considering time constraints. It is proposed a hardware implementation leveraging the computing power of modern GPUs, which takes advantage of a new paradigm coined as General-Purpose Computing on Graphics Processing Units (GPGPU). The proposed methods were applied to different problem and applications in the area of computer vision such as the recognition and localization of objects, visual surveillance or 3D reconstruction.

Self-Description Questionnaire II (versión breve): evidencia de fiabilidad y validez en una muestra de adolescentes chilenos

El objetivo de este estudio fue analizar la fiabilidad y validez de las puntuaciones de la versión breve del Self-Description Questionnaire II (SDQ-II-S) en población chilena. La muestra se compuso de 1255 adolescentes chilenos, con un rango de edad de 13 a 17 años (M = 15.10; DT = 1.30). El análisis factorial confirmatorio corroboró la estructura original de 11 factores correlacionados del SDQ-II-S. La multidimensionalidad del cuestionario también fue avalada por la pequeña magnitud de las correlaciones entre los 11 factores (M = 0.26). Los coeficientes alfa de Cronbach variaron desde 0.70 hasta 0.84, y se destacó una adecuada fiabilidad. Para profundizar en el análisis de la validez de constructo del SDQ-II-S, se relacionaron las puntuaciones de las diferentes escalas con puntuaciones en medidas de ansiedad (Inventario de Ansiedad Estado-Rasgo) y autoeficacia (Escala de Autoeficacia Percibida Específica de Situaciones Académicas). Los resultados pusieron de manifiesto que estos cuestionarios permiten analizar constructos diferenciados aunque relacionados. Los datos de este trabajo destacan que el SDQ-II-S presenta adecuadas propiedades psicométricas en población chilena, contrarrestando las carencias existentes en lo que respecta a la evaluación del autoconcepto, y resaltan interesantes aplicaciones tanto en el ámbito aplicado como en el de la investigación.