Suchergebnisse

Conflict and its different dimensions / Marco Vieira Gomes, Paulo Novais -- Biometrics and data protection: these data are derived from an individual / Francisco Pacheco Andrade, Teresa Coelho Moreira -- Organisational conflict and its management / Saleem Gul, Michael Klausner -- Environmental conflicts / Cristian Ioja, Mihai R. Nita, Constantina Alina Hossu -- Restorative justice and technology / Pedro Miguel Freitas, Pablo Galain Palermo -- Quality of judgment assessment / José Neves, John Zeleznikow, Henrique Vicente -- Alternative dispute resolution in civil and commercial matters in the EU / Marco Carvalho Gonçalves -- Online dispute resolution for consumers in Portugal and in the European Union: the future platform for online dispute resolution / Fernando Viana, Francisco Pacheco Andrade -- Agreement technologies for conflict resolution / Vicente Julian [and 3 others] -- Conflict resolution problem solving with bio-inspired metaheuristics: a perspective / P. B. de Moura Oliveira, E. J. Solteiro Pires -- Opinion aggregation and conflict resolution in e-government platforms: contrasting social media information through argumentation / Carlos Ivan Chesnevar [and 3 others] -- Intelligent tutoring: active monitoring and recommendation / Manuel Fernando Rodrigues [and 4 others] -- Real-time detection of pedestrians: a comparison of three segmentation algorithms in infrared video / Juan Serrano-Cuerda [and 3 others] --

It is unquestionable to say that we live in a hyper-connected world, where technology is present in all spheres of our life. Furthermore, it is the backbone for the transformation of our society, which is continually changing and requires continuous adaptation of the human being to the environment. (Durães, Carneiro, Bajo, Novais, 2016). In this paper, we present experience during the Pandemic situation with students at high school. The idea is to improve learning and motivated students to participate in the demands of the task by the teachers.

This book studies how technological solutions can be used to alleviate the current state of legal systems, with their clogged up courtrooms and inefficient conflict resolution methods. It reviews the shortcomings and disadvantages of traditional and alternative conflict resolution methods and turns to Artificial Intelligence for problem-solving techniques and solutions.The book is divided into four parts. The first part presents a general and systematic analysis of the current state of the legal systems, identifying the main problems and their causes. It then moves on to present UMCourt: a framework for testing and prototyping conflict resolution services. This framework was developed with the objective of using Artificial Intelligence techniques to build a service environment for conflict resolution. The third part of the book takes a step into the future by analyzing the use of Intelligent Environments in the support of conflict management and resolution. It describes the approach taken and the experiments performed in the Intelligent Systems Lab of the University of Minho. The final part of the book contains the conclusions and shows the potential advantages of the use of Intelligent Environments as a way to implement better conflict resolution procedures (virtual or real), in which all the participants have access to more and better information, and are able to take better informed decisions.

Productivity always was, and still is, the main goal of organizations, that being economic, governmental, military or educational. Having the means to control, detect and monitor features that have impact on productivity is a major issue, and subject to various investigation. Considering that most of the times, if not always, unconscious actions play a very important role in the way we work, study, socialize, and even in the way we have fun, the high significance of those factors becomes very clear. Monitoring unconscious actions, selecting those of them that do play a role regarding productivity, and trying to proactively take measures to improve processes, is then the goal of this work. Specifically, we are concerned about using computers peripherals to non-intrusively monitor user's actions. The term non-intrusively assumes greater importance, as we are concerned with unconscious actions, thus we need to strongly ensure that no entropy is derived by the way this process is done. Peripherals such as mouse, keyboard, touch screens, and possibly webcams and microphones can act as sensors, completely hidden from the user. As we use them daily, they somehow assume part of our life, and can be used to collect data that will be processed to get useful information regarding that particular user. We then can build a behavioral profile, for instance, that will provide a better insight of user's actions. We can predict some possibly negative features, such as stress, fatigue, level of attention, for instance. If detected or predicted, they can greatly help to better manage all the information we need, in the right way. We can suggest that someone takes a coffee break, because she/he is stressed. We can tell him/her to work/study in the morning, because the information we have collected suggests that is the period of the day that is more suitable to get better results, for that person. We can suggest postponing the following meeting, because the actual mood indicates that that person ; - ...

Series : Lecture notes in computer science, ISSN 0302-9743, vol. 8929 ; With the growing popularity of micro-task crowdsourcing platforms, new workflow-based micro-task crowdsourcing approaches are starting to emerge. Such workflows occur in legal, political and conflict resolution do-mains as well, presenting new challenges, namely in micro-task specification and human-machine interaction, which result mostly from the flow of unstruc-tured data. Domain ontologies provide the structure and semantics required to describe the data flowing throughout the workflow in a way understandable to both humans and machines. This paper presents a method for the construction of micro-task workflows from legal domain ontologies. The method is currently being employed in the context of the UMCourt project in order to formulate in-formation retrieval and conflict resolution workflows. ; This work is part-funded by FEDER Funds, by the ERDF (Eu-ropean Regional Development Fund) through the COMPETE Programme (operation-al programme for competitiveness) and by National Funds through the FCT (Portu-guese Foundation for Science and Technology) within the project FCOMP-01-0124-FEDER-028980 (PTDC/EEI-SII/1386/2012). The work of Nuno Luz is supported by the doctoral grant ...

Machine learning has been facing significant challenges over the last years, much of which stem from the new characteristics of machine learning problems, such as learning from streaming data or incorporating human feedback into existing datasets and models. In these dynamic scenarios, data change over time and models must adapt. However, new data do not necessarily mean new patterns. The main goal of this paper is to devise a method to predict a model's performance metrics before it is trained, in order to decide whether it is worth it to train it or not. That is, will the model hold significantly better results than the current one? To address this issue, we propose the use of meta-learning. Specifically, we evaluate two different meta-models, one built for a specific machine learning problem, and another built based on many different problems, meant to be a generic meta-model, applicable to virtually any problem. In this paper, we focus only on the prediction of the root mean square error (RMSE). Results show that it is possible to accurately predict the RMSE of future models, event in streaming scenarios. Moreover, results also show that it is possible to reduce the need for re-training models between 60% and 98%, depending on the problem and on the threshold used. ; This work was supported by the Northern Regional Operational Program, Portugal 2020 and European Union, trough European Regional Development Fund (ERDF) in the scope of project number 39900 - 31/SI/2017, and by FCT – Fundação para a Ciência e Tecnologia within projects UIDB/04728/2020 and UIDB/00319/2020.

15th International Conference, GDN 2015, Warsaw, Poland, June 22-26, 2015, Proceedings. ; This paper presents a novel task-oriented approach to crowdsource the drafting of a constitution. By considering micro-tasking as a particular form of crowdsourcing, it defines a workflow-based approach based on Onto2Flow, an ontology that models the basic concepts and roles to represent workflow-definitions. The approach is then applied to a prototype platform for constitution-making where human workers are requested to contribute to a set of tasks. The paper concludes by discussing previous approaches to participatory constitution-making and identifying areas for future work.

Considering that information technology penetrates all areas and domains of the public sector, it has to be considered the extension of the required regulation needed for warranting that this phenomenon becomes an advantage and not a threat. In this sense, this study has as aims to discuss certain aspects associated with fair use of emerging and disruptive technologies and (such as Artificial Intelligence, Internet of Things, Big Data) in the public sector. The emphasis may fall upon the treatment of this subject by traditional regulatory instances, such as Data Protection Regulation-GDPR, in the sense of enhancing the capacity of Governments to ensure privacy, data protection, and the protection of citizens. ; This work has been supported by FCT Fundação para a Ciência e Tecnologia within the Project Scope: ...

Fatigue, especially in its mental form, is one of the most worrying health problems nowadays. It affects not only health but also motivation, emotions and feelings and has an impact both at the individual and organizational level. Fatigue monitoring and management assumes thus, in this century, an increased importance, that should be promoted by private organizations and governments alike. While traditional approaches are mostly based on questionnaires, in this paper we present an alternative one that relies on the observation of the individual's interaction with the computer. We show that this interaction changes with the onset of fatigue and that these changes are significant enough to support the training of a neural network that can classify mental fatigue in real time. The main outcome of this work is the development of non-invasive systems for the continuous classification of mental fatigue that can support effective and efficient fatigue management initiatives, especially in the context of desk jobs. ; This work is part-funded by ERDF - European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT - Fundacao para a Ciencia e a Tecnologia (Portuguese Foundation for Science and Technology) within projects FCOMP-1-0124-FEDER-028980 (PTDC/EEISII/1386/2012) and within the Project Scope UID/CEC/00319/2013. ...

The main focus of an Intelligent environment, as with other applications of Artificial Intelligence, is generally on the provision of good decisions towards the management of the environment or the support of human decision-making processes. The quality of the system is often measured in terms of accuracy or other performance metrics, calculated on labeled data. Other equally important aspects are usually disregarded, such as the ability to produce an intelligible explanation for the user of the environment. That is, asides from proposing an action, prediction, or decision, the system should also propose an explanation that would allow the user to understand the rationale behind the output. This is becoming increasingly important in a time in which algorithms gain increasing importance in our lives and start to take decisions that significantly impact them. So much so that the EU recently regulated on the issue of a "right to explanation". In this paper we propose a Human-centric intelligent environment that takes into consideration the domain of the problem and the mental model of the Human expert, to provide intelligible explanations that can improve the efficiency and quality of the decision-making processes. ; EC - European Commission(39900 - 31/SI/2017). Northern Regional Operational Program, Portugal 2020 and European Union, trough European Regional Development Fund (ERDF) in the scope of project number 39900 - 31/SI/2017, and by FCT - Fundação para a Ciência e a Tecnologia, through projects UIDB/04728/2020 and ...

Writing style is considered the manner in which an author expresses his thoughts, influenced by language characteristics, period, school, or nation. Often, this writing style can identify the author. One of the most famous examples comes from 1914 in Portuguese literature. With Fernando Pessoa and his heteronyms Alberto Caeiro, alvaro de Campos, and Ricardo Reis, who had completely different writing styles, led people to believe that they were different individuals. Currently, the discussion of authorship identification is more relevant because of the considerable amount of widespread fake news in social media, in which it is hard to identify who authored a text and even a simple quote can impact the public image of an author, especially if these texts or quotes are from politicians. This paper presents a process to analyse the emotion contained in social media messages such as Facebook to identify the author's emotional profile and use it to improve the ability to predict the author of the message. Using preprocessing techniques, lexicon-based approaches, and machine learning, we achieved an authorship identification improvement of approximately 5% in the whole dataset and more than 50% in specific authors when considering the emotional profile on the writing style, thus increasing the ability to identify the author of a text by considering only the author's emotional profile, previously detected from prior texts. ; FCT has supported this work – Fundação para a Ciência e Tecnologia within the Project Scope: ...

Political debate - in its essence - carries a robust emotional charge, and social media have become a vast arena for voters to disseminate and discuss the ideas proposed by candidates. The Brazilian presidential elections of 2018 were marked by a high level of polarization, making the discussion of the candidates' ideas an ideological battlefield, full of accusations and verbal aggression, creating an excellent source for sentiment analysis. In this paper, we analyze the emotions of the tweets posted about the presidential candidates of Brazil on Twitter, so that it was possible to identify the emotional profile of the adherents of each of the leading candidates, and thus to discern which emotions had the strongest effects upon the election results. Also, we created a model using sentiment analysis and machine learning, which predicted with a correlation of 0.90 the final result of the election. ; FCT – Fundação para a Ciência e Tecnologia within the Project Scope: ...

Recent studies show that the elderly population has increased considerably in European society in recent years. This fact has led the European Union and many countries to propose new policies for caring services directed to this group. The current trend is to promote the care of the elderly in their own homes, thus avoiding inverting resources on residences. With this in mind, there are now new solutions in this direction, which try to make use of the continuous advances in computer science. This paper tries to advance in this area by proposing the use of a personal assistant to help older people at home while carrying out their daily activities. The proposed personal assistant is called ME(3)CA, and can be described as a cognitive assistant that offers users a personalised exercise plan for their rehabilitation. The system consists of a sensorisation platform along with decision-making algorithms paired with emotion detection models. ME(3)CA detects the users' emotions, which are used in the decision-making process allowing for more precise suggestions and an accurate (and unbiased) knowledge about the users' opinion towards each exercise.

The progressive ageing of population combined with the need for comfort in situations of disease and disability are pushing healthcare organizations and governments to find new solutions to enable people to live longer in their preferred environment, while having access to quality healthcare services. iGenda is an Ambient Assisted Living platform that provides constant monitoring to people with this type of needs. The use of a Computer-Interpretable Guideline model for decision making is one of the features of this platform. The model used to represent Clinical Practice Guidelines gathers a set of features that make guidelines more dynamic and easily implementable. The model is defined using Ontology Web Language, profiting from the existing constructors provided by this language. It is based on a set of primitive tasks, namely Plans, Actions, Questions and Decisions. Focusing on decision support, a method for dealing with incomplete information about the clinical parameters of a health record is presented. The objective is to keep a continuous flow of information through the decision process and assuring that an outcome is always achieved. The usefulness of the integration of guideline recommendations with a reason mechanism capable of handling incomplete information is demonstrated through a case study about the diagnosis of metabolic syndrome. ...