158 research outputs found
Different Routes or Methods of Application for Dimensionality Reduction in Multicenter Studies Databases
Technological progress and digital transformation, which began with Big Data and Artificial
Intelligence (AI), are currently transforming ways of working in all fields, to support decision-making,
particularly in multicenter research. This study analyzed a sample of 5178 hospital patients, suffering
from exacerbation of chronic obstructive pulmonary disease (eCOPD). Because of differences in
disease stages and progression, the clinical pathologies and characteristics of the patients were
extremely diverse. Our objective was thus to reduce dimensionality by projecting the data onto a
lower dimensional subspace. The results obtained show that principal component analysis (PCA)
is the most effective linear technique for dimensionality reduction. Four patient profile groups are
generated with similar affinity and characteristics. In conclusion, dimensionality reduction is found
to be an effective technique that permits the visualization of early indications of clinical patterns with
similar characteristics. This is valuable since the development of other pathologies (chronic diseases)
over any given time period influences clinical parameters. If healthcare professionals can have access
to such information beforehand, this can significantly improve the quality of patient care, since this
type of study is based on a multitude of data-variables that can be used to evaluate and monitor the
clinical status of the patient
Gender differences in e-learning satisfaction
In line with recent research, the question this paper raises is whether or not gender differences also exist in e-learning. This study is based on a sample of 1,185 students who are doing on-line courses at the Universidad de Granada in Spain. The main conclusion is that female students are more satisfied than male students with the e-learning subjects that make up the sample. Furthermore, we find that female students assign more importance to the planning of learning, as well as to being able to contact the teacher in various ways.: Gender Studies; Evaluation Methodologies
Skewness distribution of four key altmetric indicators: an in-progress analysis across 22 fields in a national context
First of all, it should be mentioned that although this study uses a large sample of scientific publications (a total of 237,232), they are all Spanish publications. Therefore, the results may not be extrapolated. Recent studies show that altmetric indicators may have different patterns depending on the country. Countries such as Spain, France and Germany may have different altmetric patterns to Anglo-Saxon countries. However, various findings have been demonstrated that can be extrapolated to all contexts regardless of their specific features. Each altmetric indicator has its own pattern of asymmetry and is not the same in all scientific areas. The values are very different depending on the area and the indicator. Another important aspect pointed out by the study is that, compared to citations, the distributions of altmetric indicators are always less skewed and less pronounced. It also seems that citations are more similar to Twitter mentions. This paper is useful to provide a general mapping by indicator and area of the phenomenon of asymmetry in the world of altmetrics. It may be of use when establishing the field validity of certain indicators or when using statistical indicators such as averages. It will also help to decide whether it is necessary to introduce standardisation procedures for indicators such as those used by Costas and Bornmam and Leydesdorff. This work will be continued in the future using the complete Altmetric.com database and introducing a larger number of altmetric indicators
Group Classification for the Search and Identification of Related Patterns Using a Variety of Multivariate Techniques
Recently, many methods and algorithms have been developed that can be quickly adapted
to different situations within a population of interest, especially in the health sector. Success has
been achieved by generating better models and higher-quality results to facilitate decision making,
as well as to propose new diagnostic procedures and treatments adapted to each patient. These
models can also improve people’s quality of life, dissuade bad health habits, reinforce good habits,
and modify the pre-existing ones. In this sense, the objective of this study was to apply supervised
and unsupervised classification techniques, where the clustering algorithm was the key factor for
grouping. This led to the development of three optimal groups of clinical pattern based on their
characteristics. The supervised classification methods used in this study were Correspondence (CA)
and Decision Trees (DT), which served as visual aids to identify the possible groups. At the same time,
they were used as exploratory mechanisms to confirm the results for the existing information, which
enhanced the value of the final results. In conclusion, this multi-technique approach was found to be
a feasible method that can be used in different situations when there are sufficient data. It was thus
necessary to reduce the dimensional space, provide missing values for high-quality information, and
apply classification models to search for patterns in the clinical profiles, with a view to grouping the
patients efficiently and accurately so that the clinical results can be applied in other research studies
Different routes or methods of application for dimensionality reduction in multicenter studies databases
Technological progress and digital transformation, which began with Big Data and Artificial Intelligence (AI), are currently transforming ways of working in all fields, to support decision-making, particularly in multicenter research. This study analyzed a sample of 5178 hospital patients, suffering from exacerbation of chronic obstructive pulmonary disease (eCOPD). Because of differences in disease stages and progression, the clinical pathologies and characteristics of the patients were extremely diverse. Our objective was thus to reduce dimensionality by projecting the data onto a lower dimensional subspace. The results obtained show that principal component analysis (PCA) is the most effective linear technique for dimensionality reduction. Four patient profile groups are generated with similar affinity and characteristics. In conclusion, dimensionality reduction is found to be an effective technique that permits the visualization of early indications of clinical patterns with similar characteristics. This is valuable since the development of other pathologies (chronic diseases) over any given time period influences clinical parameters. If healthcare professionals can have access to such information beforehand, this can significantly improve the quality of patient care, since this type of study is based on a multitude of data-variables that can be used to evaluate and monitor the clinical status of the patient
Field Outings as Reinforcement of Teaching Methodology in Secondary Education
Recepción: 23 de marzo de 2017Aceptado: 30 de junio de 2017Correspondencia: Miguel Ángel MonteroCorreo-e: [email protected]: 0000-0002-1214-9035Revisión por pares abierta (open peer review):Dra. Karen McMullin. Trent University (Canada). ORCID: 0000-0002-1449-3550Dra. Marzia Fiorini. Università degli Studi di Cassino e del Lazio Meridionale (Italia). Identificador Dialnet: 778877En este artículo se presenta una actividad educativa diseñada para ser realizada fuera del aula, dentro de las diferentes estrategias didácticas que son desarrolladas en el proceso de enseñanza-aprendizaje, y relacionada con la realidad económica. Las salidas pedagógicas, se presentan como una metodología para enfrentarse ante contextos, ámbitos o campos de estudio en los que previamente no existen suficientes recursos didácticos específicos, donde el estudiante conocerá de primera mano y presencialmente, la realidad de un sector económico clave en el entorno donde vive. Además, permite contar con profesionales especialistas de los lugares visitados que facilitarán el correcto desarrollo del proceso educativo del alumnado y donde sus conocimientos prácticos pueden servir a los docentes en la elaboración de recursos didácticos específicos sobre la temática abordada. Mediante una revisión teórica de este proceso, a través de un enfoque constructivista, se analiza el papel protagonista que se le otorga al alumno en estas actividades, generando una dinámica diferente por la que éste es el actor principal y no un ente pasivo de la enseñanza. En la evaluación, se produce un feedback donde se evalúa al alumnado y, a su vez, el alumnado evalúa el proyecto, facilitándose así la mejora continua de la actividad. Los resultados obtenidos proporcionan un mejor desarrollo de los conocimientos económicos del estudiante, habilidades, hábitos y concepción científica del mundo en el que viven, siendo un recurso que potencia su actividad educativa.This article presents an educational activity designed to be performed outside the classroom, as part of the different teaching strategies that are carried out in the process of teaching and learning, and related to the particular economic reality. Field outings are presented as a methodology to overcome the lack of specific teaching resources in certain contexts, areas or fields of study. Students learn on first hand and in person the reality of a key economic sector in their closest own environment. The outings also allow professionals from the places they visit to participate in the correct development of the students’ learning process, and whose practical knowledge will help teachers in developing specific teaching resources on the topics addressed. Through a theoretical review of this process, from a constructivist approach, the leading role given to students in these activities is analysed, creating a different dynamic in which the student is an active participant, rather than a passive one. In the evaluation, a feedback is provided to evaluate the students and, in turn, the students evaluate the project, facilitating the continuous improvement of the experience. The results show a better development of students’ economic knowledge, skills, habits and scientific conception of the world in which they live, being a resource that enhances their learning process.Universidad de Granada. Departamento de Psicología Social. Proyecto de Innovación Docente ReiDoCre
Stricter Adherence to Dietary Approaches to Stop Hypertension (DASH) and Its Association with Lower Blood Pressure, Visceral Fat, and Waist Circumference in University Students
We are grateful to the university students for their participation in this study.How diet affects blood pressure (BP) in young adults has not been studied in sufficient depth.
For this purpose, we analyzed adherence to the Dietary Approaches to Stop Hypertension (DASH)
dietary pattern and BP in Spanish university students. The sample population of our cross-sectional
study consisted of 244 subjects (18–31 years old), who were in good health. Measurements were
taken of their systolic and diastolic BP. A food frequency questionnaire and 72 h food record were
used to assess their dietary intake in the previous year. The resulting DASH score was based on
foodstuffs that were emphasized or minimized in the DASH diet. Analysis of covariance adjusted
for potential confounding factors showed that the mean values for systolic BP, visceral fat rating,
and waist circumference (WC) of the subjects in the upper third of the DASH score were significantly
lower than those of the subjects in the lower third (for systolic BP: mean difference −4.36 mmHg,
p = 0.004; for visceral fat rating: mean difference −0.4, p = 0.024; for waist circumference: mean
difference −3.2, p = 0.019). Stricter adherence to the DASH dietary pattern led to a lower BP, visceral
fat rating, and WC values in these university students. Nevertheless, further prospective studies are
needed to confirm these results.This study was funded by the Programme Contract (2015–2017) of the Faculty of Nursing of Melilla
(University of Granada), specifically the research line “Lifestyles and health care in a multicultural population”
Exploratory Matching Model Search Algorithm (EMMSA) for Causal Analysis: Application to the Cardboard Industry
This paper aims to present a methodology for the application of matching methods in industry to measure causal effect size. Matching methods allow us to obtain treatment and control samples with their covariates as similar as possible. The matching techniques used are nearest, optimal, full, coarsened exact matching (CEM), and genetic. These methods have been widely used in medical, psychological, and economic sciences. The proposed methodology provides two algorithms to execute these methods and to conduct an exhaustive search for the best models. It uses three conditions to ensure, as far as possible, the balance of all covariates, the maximum number of units in the treatment and control groups, and the most significant causal effect sizes. These techniques are applied in the carton board industry, where the causal variable is downtime, and the outcome variable is waste generated. A dataset from the carton board industry is used, and the results are contrasted with an expert in this process. Meta-analysis techniques are used to integrate the results of different comparative studies, which could help to determine and prioritize where to reduce waste. Two machines were found to generate more waste in terms of standardized measures whose values are 0.52 and 0.53, representing 48.60 and 36.79 linear meters (LM) on average for each production order with a total downtime of more than 3000 s. In general, for all machines, the maximum average wastage for each production order is 24.98 LM and its confidence interval is [13.40;36.23] LM. The main contribution of this work is the use of causal methodology to estimate the effect of downtime on waste in an industry. Particularly relevant is the contribution of an algorithm that aims to obtain the best matching model for this application. Its advantages and disadvantages are evaluated, and future areas of research are outlined. We believe that this methodology can be applied to other industries and fields of knowledge
Gender differences in e-learning satifaction
In line with recent research, the question this paper raises is whether or not gender differences also exist in e-learning. This study is based on a sample of 1,185 students who are doing on-line courses at the Universidad de Granada in Spain. The main conclusion is that female students are more satisfied than male students with the e-learning subjects that make up the sample. Furthermore, we find that female students assign more importance to the planning of learning, as well as to being able to contact the teacher in various ways
Consumo de metal durante la Prehistoria Reciente en el centro de la Península Ibérica. Una aproximación a través del análisis de los contextos funerarios en fosa
This article is focused on the metal objects of the Chalcolithic and Bronze Age (3050-900 cal BC) documented in the Submeseta Norte and Campiña Madrileña, with special attention given to those found in pit graves. The aim of this paper is to assess whether these objects are linked with social inequalities, and, therefore, with hierarchical forms of political organization (as has been traditionally interpreted), or with kinship-based societies. For doing so, we have only used contextualized data, which have been analyzed with different statistical procedures. The results show a scarcity of metal objects, which, are also not connected with hierarchical social structures. Consequently, we propose, as an alternative explanation, the persistence of kinship-based societies during the analyzed period.El presente texto toma como objeto de análisis los productos metálicos del Calcolítico y la Edad del Bronce (3050-900 cal. BC) conocidos dentro de la Submeseta Norte y la Campiña Madrileña, con especial atención a los documentados en los enterramientos en fosa. A partir de esta base documental se ha pretendido evaluar si estos objetos están vinculados con desigualdades sociales permanentes y, por tanto, con formas de organización política jerarquizadas, tal y como se ha planteado tradicionalmente, o si se deben atribuir a comunidades de tipo segmentario. Para tal fin se han utilizado únicamente los datos contextualizados, que han sido sometidos a diversos procedimientos estadísticos. Los resultados muestran la escasez de objetos metálicos y la falta de conexión de éstos con estructuras sociales jerarquizadas. Se propone como alternativa explicativa la permanencia de las formas de organización social de tipo segmentario durante todo el tramo temporal analizado
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