Development of Technologies for Local Composting of Food Waste From Universities

[Abstract] The amount of biowaste generated by university canteens (BWUC) in the faculties of the University of A Coruña (UDC) varies between 6 and 100 kg/day. In addition, the gardening services of the campus generate even higher amounts of garden waste (GrW), including pruning, which, once crushed, serves as bulking material for composting the biowaste from the canteens. Decentralized composting has been chosen with the aim of producing high quality organic fertilizers for university urban gardens while reducing the environmental burdens of both waste management and agricultural practice. Small static home composters of 340 L (SHC) for smaller amounts of generation (up to 20 kg BWUC/day) were used, while, for faculties of higher generation (up to 40 kg BWUC/day on average), the first composting stage was carried out in a closed and dynamic composter (DC). The dynamic composter was designed and built specifically for this project and its features were improved and optimized throughout the study. The pilot project was carried out in two centers of the UDC, which are known as the Philology Faculty (PF) and the School of Architecture (SA). All the organic waste generated by the canteens of these two colleges from January 2011 to July 2011 (approximately 3000 kg) was treated. Composting in SHC included a thermophilic phase that extended one month beyond the loading period for which thermophilic temperatures were also recorded. The use of the DC as the first stage in combination with static composters (SC) for the maturation stage reduced the overall thermophilic phase to 6–8 weeks. The complete maturation (Rottegrade class IV-V) was achieved after about four months in SHC and after two months when using the combined DC-SC system, if the right conditions of moisture were maintained. The chemical quality of the compost produced was compatible with Class A of Spanish legislation (equivalent to organic farmer quality) and the C/N ratio ranged from 9 to 15 depending on the relation BWUC:GrW

Siega Verde, ensemble rupestre

Le siteLe site archéologique rupestre de Siega Verde se situe dans le cours moyen de la rivière Águeda, lorsqu’elle traverse les communes de Serranillo, Martillán et Castillejo de Martín Viejo, autour du pont de La Unión, dans le canton de Ciudad Rodrigo (Province de Salamanque). Ce lieu a dû constituer au Paléolithique, un des derniers gués accessibles de la rivière avant son embouchure dans le Duero ; un territoire transitionnel entre la fosse de Ciudad Rodrigo et son plateau (fig. 1a).Déc..

Domingo García, ensemble rupestre

Le siteL’ensemble gravé de plein air de Domingo García se trouve sur la commune de Santa María la Real de Nieva (Ségovie, Castille-et-León, Espagne) au sud-est de la dépression du Duero dans la vallée de l’Eresma, un affluent de la rive gauche du Duero, à un peu plus de 40 km au nord-est de la ville de Ségovie. Cet ensemble s’étend sur plus de 110 km2 (Santos 2013 : 264) et compte au moins cinq sites contenant des gravures paléolithiques (Ripoll & Municio 1999 : 59-196, 2001 : 183, Pecci 201..

El arte paleolítico de Siega Verde (Serranillo, Salamanca, España): una sintética visión en el trigésimo aniversário de su descubrimiento

info:eu-repo/semantics/publishedVersio

Arroyo de las Almas (La Fregeneda, Salamanca): un nuevo conjunto con arte rupestre en la cuenca del Duero

info:eu-repo/semantics/publishedVersio

Arroyo de las Almas (La Fregeneda, Salamanca): un nuevo sitio con arte paleolítico al aire libre

The open-air rock art collection of Arroyo de las Almas, located next to the confluence of the Águeda and Duero rivers, has at least 600 engraved motifs with a long temporal sequence that runs from the Upper Palaeolithic to the present. We present for the first time the 21 recorded Palaeolithic motifs, all engraved by incision, and belonging to the Magdalenian period.El conjunto rupestre al aire libre del Arroyo de las Almas (La Fregeneda, Salamanca), situado junto al encuentro de los ríos Águeda y Duero, tiene, al menos, 600 motivos grabados con una amplia secuencia temporal que transcurre desde el Paleolítico Superior hasta nuestros días. Mostramos aquí, por primera vez, los 21 motivos paleolíticos, grabados todos ellos por incisión, e integrables en el Magdaleniense

Music Recommendation System Based on Ratings Obtained from Amazon

Cursos e Congresos, C-155[Abstract] In the current context of an era in which a significant portion of people are constantly living online, with various multimedia streaming platforms serving as major sources of entertainment, and with e-commerce playing also a key role, recommender systems are carving out their place as one of the most important and widely used tools for enhancing user experiences on these platforms. This work undertakes a comparative study on some of the techniques used within these systems, mainly focused on those based in collaborative filtering. Multiple recommender systems will be implemented according to each of these methods, taking for this purpose the vinyl records and CDs Amazon’s user ratingsCITIC is funded by the Xunta de Galicia through the collaboration agreement between the Consellería de Cultura, Educación, Formación Profesional e Universidades and the Galician universities for the reinforcement of the research centres of the Galician University System (CIGUS)

Active learning based on computer vision and human-robot interaction for the user profiling and behavior personalization of an autonomous social robot

Social robots coexist with humans in situations where they have to exhibit proper communication skills. Since users may have different features and communicative procedures, personalizing human-robot interactions is essential for the success of these interactions. This manuscript presents Active Learning based on computer vision and human-robot interaction for user recognition and profiling to personalize robot behavior. The system identifies people using Intel-face-detection-retail-004 and FaceNet for face recognition and obtains users" information through interaction. The system aims to improve human-robot interaction by (i) using online learning to allow the robot to identify the users and (ii) retrieving users' information to fill out their profiles and adapt the robot's behavior. Since user information is necessary for adapting the robot for each interaction, we hypothesized that users would consider creating their profile by interacting with the robot more entertaining and easier than taking a survey. We validated our hypothesis with three scenarios: the participants completed their profiles using an online survey, by interacting with a dull robot, or with a cheerful robot. The results show that participants gave the cheerful robot a higher usability score (82.14/100 points), and they were more entertained while creating their profiles with the cheerful robot than in the other scenarios. Statistically significant differences in the usability were found between the scenarios using the robot and the scenario that involved the online survey. Finally, we show two scenarios in which the robot interacts with a known user and an unknown user to demonstrate how it adapts to the situation.The research leading to these results has received funding from the projects: Robots Sociales para Estimulación Física, Cognitiva y Afectiva de Mayores (ROSES), RTI2018-096338-B-I00, funded by the Spain Ministry of Science, Innovation and Universities; Robots sociales para mitigar la soledad y el aislamiento en mayores (SOROLI), PID2021-123941OA-I00, funded by Agencia Estatal de Investigación (AEI), Spain Ministry of Science and Innovation. This publication is part of the R&D&I project PLEC2021-007819 funded by MCIN/AEI/10.13039/5011000-11033 and by the European Union NextGenerationEU/PRTR

Concept drift detection and adaptation for federated and continual learning

Smart devices, such as smartphones, wearables, robots, and others, can collect vast amounts of data from their environment. This data is suitable for training machine learning models, which can significantly improve their behavior, and therefore, the user experience. Federated learning is a young and popular framework that allows multiple distributed devices to train deep learning models collaboratively while preserving data privacy. Nevertheless, this approach may not be optimal for scenarios where data distribution is non-identical among the participants or changes over time, causing what is known as concept drift. Little research has yet been done in this field, but this kind of situation is quite frequent in real life and poses new challenges to both continual and federated learning. Therefore, in this work, we present a new method, called Concept-Drift-Aware Federated Averaging (CDA-FedAvg). Our proposal is an extension of the most popular federated algorithm, Federated Averaging (FedAvg), enhancing it for continual adaptation under concept drift. We empirically demonstrate the weaknesses of regular FedAvg and prove that CDA-FedAvg outperforms it in this type of scenarioThis research has received financial support from AEI/FEDER (EU) grant number TIN2017-90135-R, as well as the Consellería de Cultura, Educación e Ordenación Universitaria of Galicia (accreditation 2016–2019, ED431G/01 and ED431G/08, reference competitive group ED431C2018/29, and grant ED431F2018/02), and the European Regional Development Fund (ERDF). It has also been supported by the Ministerio de Universidades of Spain in the FPU 2017 program (FPU17/04154)S

A Bio-inspired Motivational Decision Making System for Social Robots Based on the Perception of the User

Nowadays, many robotic applications require robots making their own decisions and adapting to different conditions and users. This work presents a biologically inspired decision making system, based on drives, motivations, wellbeing, and self-learning, that governs the behavior of the robot considering both internal and external circumstances. In this paper we state the biological foundations that drove the design of the system, as well as how it has been implemented in a real robot. Following a homeostatic approach, the ultimate goal of the robot is to keep its wellbeing as high as possible. In order to achieve this goal, our decision making system uses learning mechanisms to assess the best action to execute at any moment. Considering that the proposed system has been implemented in a real social robot, human-robot interaction is of paramount importance and the learned behaviors of the robot are oriented to foster the interactions with the user. The operation of the system is shown in a scenario where the robot Mini plays games with a user. In this context, we have included a robust user detection mechanism tailored for short distance interactions. After the learning phase, the robot has learned how to lead the user to interact with it in a natural way.The research leading to these results has received funding from the projects: Development of social robots to help seniors with cognitive impairment (ROBSEN), funded by the Ministerio de Economia y Competitividad; and RoboCity2030-III-CM, funded by Comunidad de Madrid and cofunded by Structural Funds of the EU