L'explotació de roques silícies procedents de Tous al llarg de la prehistòria. Estat de la qüestió sobre les recerques arqueològiques desenvolupades fins a l'actualitat

L'entorn geogràfic de l'actual municipi de Tous compren una part de la zona sud-occidental de la conca d'Òdena que es caracteritza en l'àmbit geològic per les formacions de roques silícies que afloren en superfície i la disposició de sílex en les terrasses fluvials dels seus rius. Les investigacions arqueològiques que s'han dut a terme fins ara posen de manifest que els grups neandertals del Abric Romaní haurien exercit una explotació de recursos fa més de 50.000 anys i que la seva explotació hauria tingut una continuïtat al llarg de la Prehistòria recent per l'aparició d'un elevat nombre de jaciments coneguts com a tallers de sílex. Així mateix, l'explotació de sílex hauria implicat diferents dinàmiques d'ocupació humana del territori de Tous al llarg de la Prehistòria

Components Interoperability through Mediating Connector Patterns

A key objective for ubiquitous environments is to enable system interoperability between system's components that are highly heterogeneous. In particular, the challenge is to embed in the system architecture the necessary support to cope with behavioral diversity in order to allow components to coordinate and communicate. The continuously evolving environment further asks for an automated and on-the-fly approach. In this paper we present the design building blocks for the dynamic and on-the-fly interoperability between heterogeneous components. Specifically, we describe an Architectural Pattern called Mediating Connector, that is the key enabler for communication. In addition, we present a set of Basic Mediator Patterns, that describe the basic mismatches which can occur when components try to interact, and their corresponding solutions.Comment: In Proceedings WCSI 2010, arXiv:1010.233

Robustness-Driven Resilience Evaluation of Self-Adaptive Software Systems

An increasingly important requirement for certain classes of software-intensive systems is the ability to self-adapt their structure and behavior at run-time when reacting to changes that may occur to the system, its environment, or its goals. A major challenge related to self-adaptive software systems is the ability to provide assurances of their resilience when facing changes. Since in these systems, the components that act as controllers of a target system incorporate highly complex software, there is the need to analyze the impact that controller failures might have on the services delivered by the system. In this paper, we present a novel approach for evaluating the resilience of self-adaptive software systems by applying robustness testing techniques to the controller to uncover failures that can affect system resilience. The approach for evaluating resilience, which is based on probabilistic model checking, quantifies the probability of satisfaction of system properties when the target system is subject to controller failures. The feasibility of the proposed approach is evaluated in the context of an industrial middleware system used to monitor and manage highly populated networks of devices, which was implemented using the Rainbow framework for architecture-based self-adaptation

A survey on extremism analysis using natural language processing: definitions, literature review, trends and challenges

Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature.Extremism has grown as a global problem for society in recent years, especially after the apparition of movements such as jihadism. This and other extremist groups have taken advantage of different approaches, such as the use of Social Media, to spread their ideology, promote their acts and recruit followers. The extremist discourse, therefore, is reflected on the language used by these groups. Natural language processing (NLP) provides a way of detecting this type of content, and several authors make use of it to describe and discriminate the discourse held by these groups, with the final objective of detecting and preventing its spread. Following this approach, this survey aims to review the contributions of NLP to the field of extremism research, providing the reader with a comprehensive picture of the state of the art of this research area. The content includes a first conceptualization of the term extremism, the elements that compose an extremist discourse and the differences with other terms. After that, a review description and comparison of the frequently used NLP techniques is presented, including how they were applied, the insights they provided, the most frequently used NLP software tools, descriptive and classification applications, and the availability of datasets and data sources for research. Finally, research questions are approached and answered with highlights from the review, while future trends, challenges and directions derived from these highlights are suggested towards stimulating further research in this exciting research area.CRUE-CSIC agreementSpringer Natur

A framework for selecting workflow tools in the context of composite information systems

When an organization faces the need of integrating some workflow-related activities in its information system, it becomes necessary to have at hand some well-defined informational model to be used as a framework for determining the selection criteria onto which the requirements of the organization can be mapped. Some proposals exist that provide such a framework, remarkably the WfMC reference model, but they are designed to be appl icable when workflow tools are selected independently from other software, and departing from a set of well-known requirements. Often this is not the case: workflow facilities are needed as a part of the procurement of a larger, composite information syste m and therefore the general goals of the system have to be analyzed, assigned to its individual components and further detailed. We propose in this paper the MULTSEC method in charge of analyzing the initial goals of the system, determining the types of components that form the system architecture, building quality models for each type and then mapping the goals into detailed requirements which can be measured using quality criteria. We develop in some detail the quality model (compliant with the ISO/IEC 9126-1 quality standard) for the workflow type of tools; we show how the quality model can be used to refine and clarify the requirements in order to guarantee a highly reliable selection result; and we use it to evaluate two particular workflow solutions a- ailable in the market (kept anonymous in the paper). We develop our proposal using a particular selection experience we have recently been involved in, namely the procurement of a document management subsystem to be integrated in an academic data management information system for our university.Peer ReviewedPostprint (author's final draft

A Reusable Component for Communication and Data Synchronization in Mobile Distributed Interactive Applications

In Distributed Interactive Applications (DIA) such as multiplayer games, where many participants are involved in a same game session and communicate through a network, they may have an inconsistent view of the virtual world because of the communication delays across the network. This issue becomes even more challenging when communicating through a cellular network while executing the DIA client on a mobile terminal. Consistency maintenance algorithms may be used to obtain a uniform view of the virtual world. These algorithms are very complex and hard to program and therefore, the implementation and the future evolution of the application logic code become difficult. To solve this problem, we propose an approach where the consistency concerns are handled separately by a distributed component called a Synchronization Medium, which is responsible for the communication management as well as the consistency maintenance. We present the detailed architecture of the Synchronization Medium and the generic interfaces it offers to DIAs. We evaluate our approach both qualitatively and quantitatively. We first demonstrate that the Synchronization Medium is a reusable component through the development of two game applications, a car racing game and a space war game. A performance evaluation then shows that the overhead introduced by the Synchronization Medium remains acceptable.Comment: In Proceedings WCSI 2010, arXiv:1010.233

Towards Self-Adaptive Software for Wildfire Monitoring with Unmanned Air Vehicles.

Wildfires have evolved significantly over the last decades, burning increasingly large forest areas every year. Smart cyber-physical systems like small Unmanned Air Vehicles (UAVs) can help to monitor, predict, and mitigate wildfires. In this paper, we present an approach to build control software for UAVs that allows autonomous monitoring of wildfires. Our proposal is underpinned by an ensemble of artificial intelligence techniques that include: (i) Recurrent Neural Networks (RNNs) to make local UAV predictions about how the fire will spread over its surrounding area; and (ii) Deep Reinforcement Learning (DRL) to learn policies that will optimize the operation of the UAV team.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech

Using learning by doing methodology for teaching multi-agent systems

[EN] In recent years the teaching of subjects related to Artificial Intelligence has grown notably in higher education degrees. This is the case of the discipline of multi-agent systems, which usually is part of the majority of master's degrees in Artificial Intelligence. Multi-agent systems (MAS) offer solutions for distributed decision making, where a set of autonomous intelligent agents must reach an agreement to solve a problem. These types of problems are usually complex and distributed, difficult to abstract and simplify for classroom teaching. The main problem that teachers of this subject have to face, is to be able to integrate the whole set of related techniques and algorithms in a practical example that is easy to understand and address within the framework of the planning of a course. This paper deals with the use of the "learning by doing" methodology in a subject of multi-agent systems in the Master's Degree in Artificial Intelligence at the Universitat Politècnica de València. This methodology is applied by avoiding master classes to focus on practice. The classes become a scientific-technological experience. The students and the teacher are a team working with a common purpose, seeking to achieve a goal. To do this, the whole course has been reformulated, proposing the students to solve different typical problems of the MAS area on the same domain, in this case the improvement of urban mobility and the efficient use of energy in the cities. It is considered to be a sufficiently current topic that can motivate the student to participate and propose solutions. To achieve this objective, a multi-agent system tool has been developed that allows students to simulate the different situations proposed and develop solutions. The tool provides them with an urban simulation environment where they can easily introduce their own strategies to be carried out by each simulation agent. In this way, students are proposed different challenges where they can develop negotiation strategies to simulate the operation of urban taxi fleets, and cooperation strategies, where different agents help each other to achieve a common goal. This tool, called SimFleet, has been developed in an open way and published as open source, so that it can be used by any teaching team that wishes to do so, and even receive external contributions and improvements thanks to its open character. This learning by doing methodology supported by the SimFleet simulation tool has been applied in two consecutive academic years obtaining better results in student assessment and learning than in previous courses. Furthermore, the results of the student satisfaction surveys have shown a notable increase when using these technologies, which reinforces the idea that this type of learning is more useful and more satisfactory for students.This work was partially supported by MINECO/FEDER RTI2018-095390-B-C31 project of the Spanish government.Palanca Cámara, J.; Jordán, J.; Julian Inglada, VJ. (2021). Using learning by doing methodology for teaching multi-agent systems. IATED. 3866-3871. https://doi.org/10.21125/inted.2021.0794S3866387

Urbanism and privatization: the case of Madrid's street cleaning system (1975 – 2000)

The aim of this paper is to shed light on the effects of the only privatisation that existed in the street cleaning service in Madrid. Framed within the international processes of privatisation since the 1970s and through a search in historical archives, it analyses the political-administrative and social factors that influenced this privatisation and its consequences on labour relations in the sector. Finally, the hypothesis of the planning of the privatisation of the service, the existence of differences with the political parties in the municipal government of Madrid and the effects of privatisation on the dualisation of working conditions affecting the further development of the service in the different districts of Madrid are tested. JEL Code: H75, I18, N9.publicad

Model integration and decision-making for self-adaptation in mobile robotics

Software Engineering today is increasingly faced with the challenge of creating systems that involve both software and physical systems -- or CPS -- from robotic systems, to autonomous vehicles, to increasingly sophisticated medical devices. In such systems, physical and software components are deeply intertwined, each operating on different spatial and temporal scales, exhibiting multiple and distinct behavioral modalities, and interacting with each other in a myriad of ways that change with context. CPS often need to self-adapt their structure and behavior at run time to respond to changes in their operating environment. Existing approaches to engineering self-adaptation have at their core a set of models used to support reasoning about when and how to best adapt the system at run time. Combining information from such models to feed run-time analysis and planning processes for self-adaptation in pure software systems is relatively straightforward because all the models describe software. However, models in a CPS are much more heterogeneous in terms of representation, semantics, and facet of the domain that they capture (e.g., energy consumption, software architecture, physical space, safety). This heterogeneity poses a fundamental challenge in bringing together the information of these models to support self-adaptation in CPS. This challenge is complicated by the inherent uncertainty that arises both from the imprecision of the models, as well as the variability and lack of predictability of the environment. This talk provides an overview of a model-based synthesis and quantitative verification approach to decision-making for self-adaptation that has been applied to the domain of mobile service robots.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech