Análisis de datos etnográficos, antropológicos y arqueológicos: una aproximación desde las humanidades digitales y los sistemas complejos

La llegada de las Ciencias de la Computación, el Big Data, el Análisis de Datos, el Aprendizaje Automático y la Minería de Datos ha modificado la manera en que se hace ciencia en todos los campos científicos, dando lugar, a su vez, a la aparición de nuevas disciplinas tales como la Mecánica Computacional, la Bioinformática, la Ingeniería de la Salud, las Ciencias Sociales Computacionales, la Economía Computacional, la Arqueología Computacional y las Humanidades Digitales –entre otras. Cabe destacar que todas estas nuevas disciplinas son todavía muy jóvenes y están en continuo crecimiento, por lo que contribuir a su avance y consolidación tiene un gran valor científico. En esta tesis doctoral contribuimos al desarrollo de una nueva línea de investigación dedicada al uso de modelos formales, métodos analíticos y enfoques computacionales para el estudio de las sociedades humanas tanto actuales como del pasado.El Ministerio de Ciencia e Innovación • Proyecto SimulPast – “Transiciones sociales y ambientales: simulando el pasado para entender el comportamiento humano” (CSD2010-00034 CONSOLIDER-INGENIO 2010). • Proyecto CULM – “Modelado del cultivo en la prehistoria” (HAR2016-77672-P). • Red de Excelencia SimPastNet – “Simular el pasado para entender el comportamiento humano” (HAR2017-90883-REDC). • Red de Excelencia SocioComplex – “Sistemas Complejos Socio-Tecnológicos” (RED2018-102518-T). La Consejería de Educación de la Junta de Castilla y León • Subvención a la línea de investigación “Entendiendo el comportamiento humano, una aproximación desde los sistemas complejos y las humanidades digitales” dentro del programa de apoyo a los grupos de investigación reconocidos (GIR) de las universidades públicas de Castilla y León (BDNS 425389

Knowledge Transfer in Commercial Feature Extraction for the Retail Store Location Problem

Location is the most important strategic decision in retailing. The location problem is markedly complex and multicriteria. One of the key factors to consider is the so-called balanced tenancy —i.e., the degree to which neighboring businesses complement each other. There are several network-based methodologies that formalize the notion of balanced tenancy by capturing the spatial interactions between different commercial sectors in cities. Some of these methodologies provide indices that have been successfully used as input features in location recommendation systems. However, from a predictive perspective, it is still unknown which of the indices provides best results. In this work, we analyze the performance of six of these indices on a set of nine Spanish cities. Our results show that the combined use of all of them in an ensemble model such as random forest significantly improves predictive accuracy. In addition, we explore the effect of knowledge transfer between cities from two different perspectives: 1) quantify how much the quality of solutions degrades when the balanced tenancy of a city is explored through the indices obtained from another city; 2) investigate the interest of network consensus approaches for knowledge transfer in retailing.Spanish Ministry of Science, Innovation and Universities through Excellence Network under Grant RED2018-102518-T, in part by the Spanish State Research Agency under Grant PID2020-118906GB-I00/AEI/10.13039/501100011033, and in part by the Junta de Castilla y León Consejería de Educación under Grant BDNS 425389

Let’s go fishing: A quantitative analysis of subsistence choices with a special focus on mixed economies among small-scale societies

The transition to agriculture is regarded as a major turning point in human history. In the present contribution we propose to look at it through the lens of ethnographic data by means of a machine learning approach. More specifically, we analyse both the subsistence economies and the socioecological context of 1290 societies documented in the Ethnographic Atlas with a threefold purpose: (i) to better understand the variability and success of human economic choices; (ii) to assess the role of environmental settings in the configuration of the different subsistence economies; and (iii) to examine the relevance of fishing in the development of viable alternatives to cultivation. All data were extracted from the publicly available cross-cultural database D-PLACE. Our results suggest that not all subsistence combinations are viable, existing just a subset of successful economic choices that appear recurrently in specific ecological systems. The subsistence economies identified are classified as either primary or mixed economies in accordance with an information-entropy-based quantitative criterion that determines their degree of diversification. Remarkably, according to our results, mixed economies are not a marginal choice, as they constitute 25% of the cases in our data sample. In addition, fishing seems to be a key element in the configuration of mixed economies, as it is present across all of them.Spanish Ministry of Science and Innovation: Excellence Networks (HAR2017-90883-REDC) (VA, DZ, JC, JMG) and (RED2018-102518-T) (VA, JMG), as well as the CULM Project (HAR2016-77672-P) (DZ, JC); from the Catalan Government - AGAUR through 2017 SGR 212 (DZ); from the Junta de Castilla y León – Consejería de Educación through BDNS 425389 (VA, JMG); and from the Research Foundation – Flanders (FWO) through the NASA project (VA, JC, JMG). In addition, this work was partially supported by the European Social Fund, as VA is the recipient of a predoctoral grant from the Department of Education of Junta de Castilla y León. Lastly, the publication fee was partially supported by the CSIC Open Access Publication Support Initiative through its Unit of Information Resources for Research (URICI). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Comparative study of classification algorithms for quality assessment of resistance spot welding joints from preand post-welding inputs

Resistance spot welding (RSW) is a widespread manufacturing process in the automotive industry. There are different approaches for assessing the quality level of RSW joints. Multi-input-single-output methods, which take as inputs either the intrinsic parameters of the welding process or ultrasonic nondestructive testing variables, are commonly used. This work demonstrates that the combined use of both types of inputs can significantly improve the already competitive approach based exclusively on ultrasonic analyses. The use of stacking of tree ensemble models as classifiers dominates the classification results in terms of accuracy, F-measure and area under the receiver operating characteristic curve metrics. Through variable importance analyses, the results show that although the welding process parameters are less relevant than the ultrasonic testing variables, some of the former provide marginal information not fully captured by the latter

Explainable machine learning for project management control

Project control is a crucial phase within project management aimed at ensuring —in an integrated manner— that the project objectives are met according to plan. Earned Value Management —along with its various refinements— is the most popular and widespread method for top-down project control. For project control under uncertainty, Monte Carlo simulation and statistical/machine learning models extend the earned value framework by allowing the analysis of deviations, expected times and costs during project progress. Recent advances in explainable machine learning, in particular attribution methods based on Shapley values, can be used to link project control to activity properties, facilitating the interpretation of interrelations between activity characteristics and control objectives. This work proposes a new methodology that adds an explainability layer based on SHAP —Shapley Additive exPlanations— to different machine learning models fitted to Monte Carlo simulations of the project network during tracking control points. Specifically, our method allows for both prospective and retrospective analyses, which have different utilities: forward analysis helps to identify key relationships between the different tasks and the desired outcomes, thus being useful to make execution/replanning decisions; and backward analysis serves to identify the causes of project status during project progress. Furthermore, this method is general, model-agnostic and provides quantifiable and easily interpretable information, hence constituting a valuable tool for project control in uncertain environments

Plataforma web para torneos de juegos 2x2

[ES] En este trabajo presentamos una plataforma web diseñada para introducir la teoría de juegos en el aula mediante torneos 2x2. La aplicación está inspirada en el torneo de Axelrod celebrado en 1980 (dilema del prisionero iterado). La plataforma web que hemos desarrollado no solo permite reproducir las condiciones del torneo original de Axelrod, sino que ofrece la posibilidad de configurar la matriz de pagos de cualquier otro juego 2x2. Un torneo comienza cuando el administrador determina el tipo de juego introduciendo la matriz de pagos. A continuación, los alumnos se incorporan y pueden diseñar y probar sus estrategias en NetLogo. Posteriormente, eligen la mejor estrategia, la envían y finaliza el torneo, confrontándose todas las estrategias enviadas. Además de la funcionalidad principal, la aplicación permite almacenar resultados y llevar a cabo más de un torneo simultáneamente. La aplicación, que puede ser descargada en el enlace: https://github.com/JoseBarbero/PlataformaTorneos2x2, cumple un doble objetivo: introducir al alumno en el estudio de la teoría de juegos y enseñarle a formalizar, (ya que las distintas estrategias habrán de formalizarse y traducirse a código en NetLogo). Estos dos aspectos son de especial interés en ingeniería, donde por un lado nos encontramos con múltiples problemas estratégicos, y por otro lado, es fundamental el desarrollo del pensamiento abstracto y de la capacidad de formalización como paso previo a la programación en los diversos lenguajes. No obstante, nuestra herramienta puede emplearse en un contexto disciplinar mucho más amplio que el de la ingeniería, ya que en disciplinas como la economía, la biología, la sociología, la psicología, etc., los problemas estratégicos son también frecuentes.Barbero Aparicio, J.; Ahedo García, V.; Santos Martín, J. (2020). Plataforma web para torneos de juegos 2x2. Editorial Universitat Politècnica de València. 863-871. https://doi.org/10.4995/INN2019.2019.10264OCS86387

Quantifying the relationship between food sharing practices and socio-ecological variables in small-scale societies: A cross-cultural multi-methodological approach

This article presents a cross-cultural study of the relationship among the subsistence strategies, the environmental setting and the food sharing practices of 22 modern small-scale societies located in America (n = 18) and Siberia (n = 4). Ecological, geographical and economic variables of these societies were extracted from specialized literature and the publicly available D-PLACE database. The approach proposed comprises a variety of quantitative methods, ranging from exploratory techniques aimed at capturing relationships of any type between variables, to network theory and supervised-learning predictive modelling. Results provided by all techniques consistently show that the differences observed in food sharing practices across the sampled populations cannot be explained just by the differential distribution of ecological, geographical and economic variables. Food sharing has to be interpreted as a more complex cultural phenomenon, whose variation over time and space cannot be ascribed only to local adaptation.Spanish Ministry of Science, Innovation and Universities: SimulPast Project (CSD2010-00034 CONSOLIDER-INGENIO 2010), (VA, JC, EB, DZ, MM, JMG), Consolider Excellence Network (HAR2017-90883-REDC) (VA, JC, EB, DZ, MM, JMG), and CULM Project (HAR2016-77672-P)(DZ, JC, MM)

Mapping the scientific structure of organization and management of enterprises using complex networks

Understanding the scientific and social structure of a discipline is a fundamental aspect for scientific evaluation processes, identifying trends and niches, and balancing the trade-off between exploitation and exploration in research. In the present contribution, the production of doctoral theses is used as a proxy to analyze the scientific structure of the knowledge area of business organization in Spain. To that end, a complex networks approach is selected, and two different networks are built: (i) the social network of co-participation in thesis examining committees and thesis supervision, and (ii) a bipartite network of theses and thesis descriptors. The former has a modular structure that is partially explained by thematic specialization in different subdisciplines. The latter serves to assess the interdisciplinary structure of the discipline, as it enables the characterization of affinity levels between fields, research poles and thematic clusters. Our results have implications for the scientific evaluation and formal definition of related fields.Spanish Ministry of Science, Innovation and Universities (RED2018-102518-T), the Spanish State Research Agency (PID2020-118906GB-I00 and PID2020-119894GB-I00 via AEI/10.13039/501100011033), the Junta de Castilla y León – Consejería de Educación (BU055P20), Fundación La Caixa (2020/00062/001) and from NVIDIA Corporation and its donation of the TITAN Xp GPUs that facilitated this research. This work was partially supported by the European Social Fund, as the authors José Miguel Ramírez-Sanz, José Luis Garrido-Labrador and Alicia Olivares-Gil are the recipient of a predoctoral grant from the Department of Education of Junta de Castilla y León (VA) (ORDEN EDU/875/2021). In addition, this work was also partially supported by the Generalitat Valenciana via its Conselleria de Innovación, Universidades, Ciencia y Sociedad Digital, as Adrián Arnaiz is recipicient of a predoctoral grant

El impacto del Camino de Santiago en el ámbito académico: análisis de las tesis doctorales jacobeas en España

Este trabajo presenta un estudio inicial sobre el impacto del Camino de Santiago en la literatura científica, más específicamente, en las tesis doctorales. En concreto, se aporta un análisis descriptivo de los datos más significativos de todas aquellas tesis doctorales que guardan alguna relación con el Camino de Santiago y que han sido defendidas en España hasta finales del año 2021. En particular, los datos considerados incluyen el momento y lugar de defensa de cada tesis, así como sus descriptores temáticos —códigos UNESCO—. Para la recopilación de estos datos se ha consultado la base de datos TESEO, el repositorio del Ministerio de Educación, Cultura y Deporte en el que se almacenan todas las tesis doctorales españolas.Los autores agradecen el apoyo y financiación del Ministerio de Ciencia e Innovación a través de sus redes de excelencia (HAR2017-90883-REDC and RED2018-102518-T) y del proyecto PID2020-118906GB-I00, y de la Junta de Castilla y León – Consejería de Educación (BDNS 425389). Asimismo, este trabajo ha sido parcialmente financiado por el Fondo Social Europeo, a través de la concesión del contrato predoctoral de Silvia Díaz de la Fuente por medio de la Consejería de Educación de la Junta de Castilla y León

La identificación de enlaces ausentes como competición Kaggle para la enseñanza de teoría de redes

En este trabajo describimos una competición en Kaggle en la que los alumnos afrontan el reto de predecir un número de enlaces ausentes de una red social de usuarios que califican películas. Las competiciones “InClass” de Kaggle son una herramienta de gamificación poderosa que puede aprovecharse para mejorar la motivación y el interés de los alumnos mediante el trabajo competitivo en equipo. En esta contribución, mostramos cómo convertir un problema de ciencia de las redes en un problema de clasificación que puede beneficiarse de la infraestructura que ofrece Kaggle.Los autores agradecen la financiación del Ministerio de Ciencia e Innovación español (RED2018‐102518‐T), del Ministerio de Economía, Industria y Competitividad (HAR2017-90883-REDC), de la Agencia Española de Investigación (PID2020- 118906GB-I00/AEI/10.13039/501100011033) de la Junta de Castilla y León – Consejería de Educación (BDNS 425389) y de la Fundación la Caixa (2020/00062/001)