Big data analytics:Computational intelligence techniques and application areas

Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment

An environment for studying visual emotion perception

Visual emotion perception is the ability of recognizing and identifying emotions through the visual interpretation of a situation or environment. In this paper we propose an innovative environment for supporting this type of studies, aimed at replacing current pencil-and-paper approaches. Besides automatizing the whole process, this environment provides new features that can enrich the study of emotion perception. These new features are especially interesting for the field of Human-Compute Interaction and Affective computing as they quantify the effects of experiencing different emotional dimensions on the individual’s interaction with the computer.This work has been supported by COMPETE: POCI-01-0145-FEDER-007043 and FCT Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013.info:eu-repo/semantics/publishedVersio

Human-computer interaction in intelligent tutoring systems

Due to the rapid evolution of society, citizens are constantly being pressured to obtain new skills through training. The need for qualified people has grown exponentially, which means that the resources for education/training are significantly more limited, so it's necessary to create systems that can solved this problem. The implementation of Intelligent Tutoring Systems (ITS) can be one solution. Besides, ITS aims to enable users to acquire knowledge and develop skills in a specific field. To achieve this goal, the ITS should learn how to react to the actions and needs of the users, and this should be achieved in a non-intrusive and transparent way. In order to provide personalized and adapted system, it is necessary to know the preferences and habits of users. Thus, the ability to learn patterns of behaviour becomes an essential aspect for the successful implementation of an ITS. In this article, we present the student model of an ITS, in order to monitor the user's biometric behaviour and their learning style during e-learning activities. In addition, a machine learning categorization model is presented that oversees student activity during the session. Additionally, this article highlights the main biometric behavioural variations for each activity, making these attributes enable the development of machine learning classifiers to predict users' learning preferences. These results can be instrumental in improving ITS systems in e-learning environments and predict user behaviour based on their interaction with computers or other devices.This work has been supported by FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2019

Different strokes for different folks? Revealing the physical characteristics of smartphone users from their swipe gestures

Anthropometrics show that the lengths of many human body segments follow a common proportional relationship. To know the length of one body segment - such as a thumb - potentially provides a predictive route to other physical characteristics, such as overall standing height. In this study, we examined whether it is feasible that the length of a person’s thumb could be revealed from the way in which they complete swipe gestures on a touchscreen-based smartphone.From a corpus of approx. 19000 swipe gestures captured from 178 volunteers, we found that people with longer thumbs complete swipe gestures with shorter completion times, higher speeds and with higher accelerations than people with shorter thumbs. These differences were also observed to exist between our male and female volunteers, along with additional differences in the amount of touch pressure applied to the screen.Results are discussed in terms of linking behavioural and physical biometrics. Keywords: Touchscreen gestures, behavioral biometrics, physical biometrics<br/

Usability in biometric recognition systems

Mención Internacional en el título de doctorBiometric recognition, which is a technology already mature, grows nowadays in several contexts, including forensics, access controls, home automation systems, internet, etc. Now that technology is moving to mobile scenarios, biometric recognition is being also integrated in smartphones, tablets and other mobile devices as a convenient solution for guaranteeing security, complementing other methods such as PIN or passwords. Nevertheless, the use of biometric recognition is not as spread as desired and it is still unknown for a wide percentage of the population. It has been demonstrated [1] that some of the possible reasons for the slow penetration of biometrics could be related to usability concerns. This could lead to various drawbacks like worst error rates due to systems misuses and it could end with users rejecting the technology and preferring other approaches. This Thesis is intended to cover this topic including a study of the current state of the art, several experiments analysing the most relevant usability factors and modifications to a usability evaluation methodology. The chosen methodology is the H-B interaction, carried out by Fernandez-Saavedra [2], based on the ISO/IEC 19795 [3], the HBSI [4], the ISO 9241-210 [5] and on Common Criteria [6]. Furthermore, this work is focused on dealing with accessibility concerns in biometric recognition systems. This topic, usually included into the usability field, has been addressed here separately, though the study of the accessibility has followed the same steps as the usability study: reviewing the state of the art, pointing and analysing the main influential factors and making improvements to the state of the art. The recently published standard EN 301 549 – “Accessibility requirements suitable for public procurement of ICT products and services in Europe” [7] has been also analysed. These two topics have been overcome through the well-known user-centric-design approach. In this way, first the influential factors have been detected. Then, they have been isolated (when possible) and measured. The results obtained have been then interpreted to suggest new updates to the H-B interaction. This 3-steps approach has been applied cyclically and the factors and methodology updated after each iteration. Due to technology and usability trends, during this work, all the systems/applications developed in the experiments have been thought to be mobile directly or indirectly. The biometric modalities used during the experiments performed in this Thesis are those pointed as suitable for biometric recognition in mobile devices: handwritten recognition signature, face and fingerprint recognition. Also, the scenarios and the applications used are in line with the main uses of biometrics in mobile environments, such as sign documents, locking/unlocking devices, or make payments. The outcomes of this Thesis are intended to guide future developers in the way of designing and testing proper usable and accessible biometrics. Finally, the results of this Thesis are being suggested as a new International Standard within ISO/IEC/JTC1/SC37 – Biometric Recognition, as standardization is the proper way of guaranteeing usability and accessibility in future biometric systems. The contributions of this Thesis include: • Improvements to the H-B interaction methodology, including several usability evaluations. • Improvements on the accessibility of the ICT (Information and Communications Technology) products by means of the integration of biometric recognition systems • Adaptation and application of the EN 301 549 to biometric recognition systems.El reconocimiento biométrico, que es una tecnología ya madura, crece hoy en día en varios contextos, incluyendo la medicina forense, controles de acceso, sistemas de automatización del hogar, internet, etc. Ahora que la tecnología se está moviendo a los escenarios móviles, el reconocimiento biométrico está siendo también integrado en los teléfonos inteligentes, tabletas y otros dispositivos móviles como una solución conveniente para garantizar la seguridad, como complemento de otros métodos de seguridad como el PIN o las contraseñas. Sin embargo, el uso del reconocimiento biométrico es todavía desconocido para un amplio porcentaje de la población. Se ha demostrado [1] que algunas de las posibles razones de la lenta penetración de la biometría podrían estar relacionadas con problemas de usabilidad. Esto podría dar lugar a diversos inconvenientes, ofreciendo un rendimiento por debajo de lo esperado debido al mal uso de los sistemas y podría terminar con los usuarios rechazando la tecnología y prefiriendo otros enfoques. Esta tesis doctoral trata este tema incluyendo un estudio del estado actual de la técnica, varios experimentos que analizan los factores de usabilidad más relevantes y modificaciones a una metodología de evaluación de la usabilidad, la "H-B interaction" [2] basada en la ISO / IEC 19795 [3], el HBSI [4], la ISO 9241 [5] y Common Criteria [6]. Además, este trabajo se centra también en los problemas de accesibilidad de los sistemas de reconocimiento biométrico. Este tema, que por lo general se incluye en el campo de la usabilidad, se ha tratado aquí por separado, aunque el estudio de la accesibilidad ha seguido los mismos pasos que el estudio de usabilidad: revisión del estado del arte, análisis de los principales factores influyentes y propuesta de cambios en la metodología H-B interaction. Han sido también analizados los requisitos de accesibilidad para las Tecnologías de la Información y la Comunicación (TIC) en Europa, bajo la norma EN 301 549 [7]. Estos dos temas han sido estudiados a través de un enfoque centrado en el usuario (User Centric Design - UCD). De esta manera, se han detectado los factores influyentes. A continuación, dichos factores han sido aislados (cuando ha sido posible) y medidos. Los resultados obtenidos han sido interpretados para sugerir nuevos cambios a la metodología H-B interaction. Este enfoque de 3 pasos se ha aplicado de forma cíclica a los factores y a la metodología después de cada iteración. Debido a las tendencias tecnológicas y de usabilidad, durante este trabajo, todos los sistemas / aplicaciones desarrolladas en los experimentos se han pensado para ser móviles, directa o indirectamente. Las modalidades utilizadas durante los experimentos realizados en esta tesis doctoral son las que se señalaron como adecuados para el reconocimiento biométrico en dispositivos móviles: la firma manuscrita, la cara y el reconocimiento de huellas dactilares. Además, los escenarios y las aplicaciones utilizadas están en línea con los principales usos de la biometría en entornos móviles, como la firma de documentos, el bloqueo / desbloqueo de dispositivos, o hacer pagos. Los resultados de esta tesis tienen como objetivo orientar a los futuros desarrolladores en el diseño y evaluación de la usabilidad y la accesibilidad en los sistemas de reconocimiento biométrico. Por último, los resultados de esta tesis doctoral se sugerirán como un nuevo estándar de ISO / IEC / JTC1 / SC37 - Biometric Recognition, ya que la normalización es la manera adecuada de garantizar la usabilidad y la accesibilidad en los futuros sistemas biométricos. Las contribuciones de esta tesis incluyen: • Mejora de la metodología de evaluación H-B interaction, incluyendo varias evaluaciones de usabilidad. • Mejora de la accesibilidad de los sistemas de información / electrónicos mediante la integración de sistemas biométricos y varias evaluaciones. • Adaptación y aplicación de la norma de accesibilidad EN 301 549 al campo de los sistemas biométricos.Programa Oficial de Doctorado en Ingeniería Eléctrica, Electrónica y AutomáticaPresidente: Patrizio Campisi.- Secretario: Enrique Cabellos Pardo.- Vocal: Marcos Faundez Zanu

Electronic Identity in Europe: Legal challenges and future perspectives (e-ID 2020)

This deliverable presents the work developed by the IPTS eID Team in 2012 on the large-encompassing topic of electronic identity. It is structured in four different parts: 1) eID: Relevance, Le-gal State-of-the-Art and Future Perspectives; 2) Digital Natives and the Analysis of the Emerging Be-havioral Trends Regarding Privacy, Identity and Their Legal Implications; 3) The "prospective" use of social networking services for government eID in Europe; and 4) Facial Recognition, Privacy and Iden-tity in Online Social Networks.JRC.J.3-Information Societ

A neural network to classify fatigue from human-computer interaction

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.info:eu-repo/semantics/publishedVersio

Context acquisition in auditory emotional recognition studies

This paper describes an environment to assess auditory emotional recognition based on a mobile application. The primary aim of this work is to provide a valuable instrument that can be used both in research and clinical settings, responding to the strong need of validated measures of emotional processing, especially in Portugal. The secondary aim is to acquire and study the participants' interaction behavior with the technological device (e.g. touch patterns, touch intensity), in search for a relationship with medical conditions, cognitive impairments, auditory emotional recognition capacities or socio-demographic indicators. This will establish the basis for the prediction of such aspects as a function of an individual's interaction with technological devices, potentially providing new diagnostic tools.This work has been supported by FCT-Fundacao para a Ciencia e Tecnologia within the Project Scope UID/ CEC/00319/2013 and Grant PTDC/MHN-PCN/3606/2012. The work of Davide Carneiro is supported by a post-doctoral Grant by FCT (SFRH/BPD/109070/2015). The work of Ana P. Pinheiro is supported by FCT Investigator Grant IF/00334/2012 funded by Fundacao para a Ciencia e a Tecnologia (FCT, Portugal).info:eu-repo/semantics/publishedVersio

Extending the Predictive Capabilities of Hand-oriented Behavioural Biometric Systems

The discipline of biometrics may be broadly defined as the study of using metrics related to human characteristics as a basis for individual identification and authentication, and many approaches have been implemented in recent years for many different scenarios. A sub-section of biometrics, specifically known as soft biometrics, has also been developing rapidly, which focuses on the additional use of information which is characteristic of a user but not unique to one person, examples including subject age or gender. Other than its established value in identification and authentication tasks, such useful user information can also be predicted within soft biometrics modalities. Furthermore, some most recent investigations have demonstrated a demand for utilising these biometric modalities to extract even higher-level user information, such as a subject\textsc{\char13}s mental or emotional state. The study reported in this thesis will focus on investigating two soft biometrics modalities, namely keystroke dynamics and handwriting biometrics (both examples of hand-based biometrics, but with differing characteristics). The study primarily investigates the extent to which these modalities can be used to predict human emotions. A rigorously designed data capture protocol is described and a large and entirely new database is thereby collected, significantly expanding the scale of the databases available for this type of study compared to those reported in the literature. A systematic study of the predictive performance achievable using the data acquired is presented. The core analysis of this study, which is to further explore of the predictive capability of both handwriting and keystroke data, confirm that both modalities have the capability for predicting higher level mental states of individuals. This study also presents the implementation of detailed experiments to investigate in detail some key issues (such as amount of data available, availability of different feature types, and the way ground truth labelling is established) which can enhance the robustness of this higher level state prediction technique

Distributed authentication to preserve privacy through smart card based biometric matching

Bibliography: pages 135-139.This thesis focuses on privacy concerns, specifically those relating to the storage and use of biometrics. These concerns result from the fact that biometric information is unique. This uniqueness makes the biometric a very strong identifier increasing the possibility that it could be used to monitor an individual's activities. An expert can extract considerable information from a biometric scan, ranging from the age or gender to whether the individual has certain diseases