A Framework for Profiling based on Music and Physiological State

The IoT (Internet of Things) is an emergent technological area with distinct chal-lenges, which has been addressed by the world research community. This disser-tation proposes the use of a knowledge-based framework capable of supporting the representation and handling of devices along with some autonomous inter-action with the human being, for creating added value and opportunities in IoT. With usability in mind, the objective lays in an attempt to characterize users’ physiological status mainly through music in a profiling approach. The idea is to produce a solution able to customize the environment by musical suggestions to the actual scenarios or mood that the users lie in. Such system can be trained to understand different physiological data to then infer musical suggestions to the users. One of the adopted methods in this work explores that thought, on whether the usage of a person’s physiological state can wield adequate sensorial stimulation to be usefully used thereafter. Another question considered in this work is whether it is possible to use such collected data to build user’s musical playlists and profile that tries to use the user’s physiological state to predict his or her emotional state with the objective to reach a well-being situation

Methods and techniques for analyzing human factors facets on drivers

Mención Internacional en el título de doctorWith millions of cars moving daily, driving is the most performed activity worldwide. Unfortunately, according to the World Health Organization (WHO), every year, around 1.35 million people worldwide die from road traffic accidents and, in addition, between 20 and 50 million people are injured, placing road traffic accidents as the second leading cause of death among people between the ages of 5 and 29. According to WHO, human errors, such as speeding, driving under the influence of drugs, fatigue, or distractions at the wheel, are the underlying cause of most road accidents. Global reports on road safety such as "Road safety in the European Union. Trends, statistics, and main challenges" prepared by the European Commission in 2018 presented a statistical analysis that related road accident mortality rates and periods segmented by hours and days of the week. This report revealed that the highest incidence of mortality occurs regularly in the afternoons during working days, coinciding with the period when the volume of traffic increases and when any human error is much more likely to cause a traffic accident. Accordingly, mitigating human errors in driving is a challenge, and there is currently a growing trend in the proposal for technological solutions intended to integrate driver information into advanced driving systems to improve driver performance and ergonomics. The study of human factors in the field of driving is a multidisciplinary field in which several areas of knowledge converge, among which stand out psychology, physiology, instrumentation, signal treatment, machine learning, the integration of information and communication technologies (ICTs), and the design of human-machine communication interfaces. The main objective of this thesis is to exploit knowledge related to the different facets of human factors in the field of driving. Specific objectives include identifying tasks related to driving, the detection of unfavorable cognitive states in the driver, such as stress, and, transversely, the proposal for an architecture for the integration and coordination of driver monitoring systems with other active safety systems. It should be noted that the specific objectives address the critical aspects in each of the issues to be addressed. Identifying driving-related tasks is one of the primary aspects of the conceptual framework of driver modeling. Identifying maneuvers that a driver performs requires training beforehand a model with examples of each maneuver to be identified. To this end, a methodology was established to form a data set in which a relationship is established between the handling of the driving controls (steering wheel, pedals, gear lever, and turn indicators) and a series of adequately identified maneuvers. This methodology consisted of designing different driving scenarios in a realistic driving simulator for each type of maneuver, including stop, overtaking, turns, and specific maneuvers such as U-turn and three-point turn. From the perspective of detecting unfavorable cognitive states in the driver, stress can damage cognitive faculties, causing failures in the decision-making process. Physiological signals such as measurements derived from the heart rhythm or the change of electrical properties of the skin are reliable indicators when assessing whether a person is going through an episode of acute stress. However, the detection of stress patterns is still an open problem. Despite advances in sensor design for the non-invasive collection of physiological signals, certain factors prevent reaching models capable of detecting stress patterns in any subject. This thesis addresses two aspects of stress detection: the collection of physiological values during stress elicitation through laboratory techniques such as the Stroop effect and driving tests; and the detection of stress by designing a process flow based on unsupervised learning techniques, delving into the problems associated with the variability of intra- and inter-individual physiological measures that prevent the achievement of generalist models. Finally, in addition to developing models that address the different aspects of monitoring, the orchestration of monitoring systems and active safety systems is a transversal and essential aspect in improving safety, ergonomics, and driving experience. Both from the perspective of integration into test platforms and integration into final systems, the problem of deploying multiple active safety systems lies in the adoption of monolithic models where the system-specific functionality is run in isolation, without considering aspects such as cooperation and interoperability with other safety systems. This thesis addresses the problem of the development of more complex systems where monitoring systems condition the operability of multiple active safety systems. To this end, a mediation architecture is proposed to coordinate the reception and delivery of data flows generated by the various systems involved, including external sensors (lasers, external cameras), cabin sensors (cameras, smartwatches), detection models, deliberative models, delivery systems and machine-human communication interfaces. Ontology-based data modeling plays a crucial role in structuring all this information and consolidating the semantic representation of the driving scene, thus allowing the development of models based on data fusion.I would like to thank the Ministry of Economy and Competitiveness for granting me the predoctoral fellowship BES-2016-078143 corresponding to the project TRA2015-63708-R, which provided me the opportunity of conducting all my Ph. D activities, including completing an international internship.Programa de Doctorado en Ciencia y Tecnología Informática por la Universidad Carlos III de MadridPresidente: José María Armingol Moreno.- Secretario: Felipe Jiménez Alonso.- Vocal: Luis Mart

Reducing Extrinsic Burdens on Players of Digital Games: An Integrated Framework

Increasingly complex gameplay and gameworlds are placing greater demands on players, while grander approaches to help them cope, such as heads-up displays (HUDs), maps, notifications, and real-time statistics, may often create even more layers of complexity, and thus burdens, further detaching players from core gameplay. In this article, we distinguish between ‘intrinsic’ (fundamental to gameplay) and ‘extrinsic’ (peripheral or extraneous to gameplay) game elements, where the latter may be seen to increase burdens on players unnecessarily, subsequently affecting engagement. We propose a framework, comprising core, interaction, and interface layers, that reveals how extrinsicality may be minimised to better facilitate intrinsic gameplay and engagement

Socio-technical analysis and design of digital workplaces to foster employee health

Recent socio-technical developments caused by ongoing digitalization (e.g., robotic process automation, artificial intelligence, anthropomorphic systems) or the COVID-19 pandemic (e.g., an increasing number of remote working employees and hence, increasing number of virtual collaboration) change the work environment and culture. Digital and smart workplace technol-ogies facilitate business processes and provide tools for efficient communication and (virtual) collaboration, “increasing the productivity of the workforce in the information age” (Attaran et al. 2019, p. 1). Especially in times of the COVID-19 pandemic, digital technologies play a crucial role in keeping us socially close, connected, and collaborative while increasing the phys-ical distance between humans. However, this development affects the health of employees (Tarafdar et al. 2013). In research, for example, it has long been known that the increased usage of digital technologies and media (DTM) may cause stress, leading to potentially harmful reac-tions in individuals. Research has noted this specific form of stress as technostress (Ayyagari et al. 2011; Tarafdar et al. 2007; Tarafdar et al. 2011; Tarafdar et al. 2019), which is an umbrella term for causes, negative organizational outcomes, and negative humanistic outcomes resulting from the use of DTM at work. The simultaneous consideration of humanistic (e.g., well-being, equality) and organizational outcomes (e.g., efficiency, productivity) is an integral part of a socio-technical system (Beath et al. 2013; Mumford 2006), which is at the core of the IS discipline (Bostrom et al. 2009; Chiasson and Davidson 2005). However, a review from Sarker et al. (2019) regarding published research articles in one of the top journals within the IS community revealed that most reviewed studies (91%) had focused exclusively on instrumental goals. They conclude that “many IS researchers have forgotten or ignored the premise that technologies need to benefit humankind overall (Majchrzak et al. 2016), not just their economic condition” (Sarker et al. 2019, p. 705). Especially as humanistic outcomes can lead to even more positive instrumental outcomes. Hence, Sarker et al. (2019) call for focusing on the connection between humanistic and instru-mental outcomes, enabling a positive synergy resulting from this interplay. For this reason, this dissertation adopts a socio-technical perspective. It aims to conduct re-search that links instrumental outcomes with humanistic objectives to ultimately achieve a healthier use of DTMs at the digital workplace. It is important to note that the socio-technical perspective considers both the technical component and the social component privileging nei-ther one of them and sees outcomes resulting from the reciprocal interaction between those two.Therefore, the dissertation focuses on the interaction while applying pluralistic methodological approaches from qualitative (e.g., semi-structured interviews, focus group discussions) and quantitative research (e.g., collection from a field study or survey research). It provides a theo-retical contribution applying both behavioral research (i.e., analysis of cause-and-effect rela-tionships) and design-oriented research (i.e., instructions for designing socio-technical information systems). Overall, this work addresses four different areas within the reciprocal interaction between the social and technical components: the role of the technical component, the role of the social component, DTMs fostering a fit between the technical and social compo-nents, and the imminent misfit between these two due to ongoing digitalization. First, to contribute to an understanding of the technical component’s role, this thesis presents new knowledge on the characteristics and features of DTM and their influence on employee health and productivity. Research on the design of digital workplaces examined different design approaches, in which information exchange and sharing documents or project support were regarded (Williams and Schubert 2018). However, the characteristics of DTM also play an es-sential role in the emergence of technostress (Dardas and Ahmad 2015). This thesis presents ten characteristics of DTM that affect technostress at an individual’s workplace, including a measurement scale and analysis on how these characteristics affect technostress. Besides, also, the provision of functional features by DTMs can affect instrumental outcomes or humanistic objectives. For example, affording users with certain kinds of autonomy regarding the config-uration of DTM while they work towards their goals could have a tremendous effect on pursu-ing goals and well-being (Patall et al. 2008; Ryan and Deci 2000). Therefore, this thesis presents knowledge regarding the design of DTM on the benefits of affording users with autonomy. Furthermore, it shows that merely affording more autonomy can have positive effects above and beyond the positive effects of the actualization of affordance. Second, to contribute to an understanding of the social component’s role, this thesis presents new knowledge on contextual and individual factors of social circumstances and their influence on employee health and productivity. In this context, the influence of the COVID-19 pandemic on the intensity of technostress among employees is considered, as work became more digital almost overnight. Therefore, this thesis provides empirical insights into digital work and its context in times of the COVID-19 pandemic and its effect on employees’ well-being, health, and productivity. Furthermore, measures to steer the identified effects if the situation in the course of the COVID-19 pandemic persists or comparable disruptive situations should re-occur are discussed. On the other hand, this research takes a closer look at the effect of an individual preference regarding coping styles in dealing with upcoming technostress. A distinction is made between the effects of two different coping styles, namely active-functional and dysfunctional, on strain as a humanistic outcome and productivity as an instrumental outcome. In the course of this, evidence is provided that coping moderates the relationship between the misfit within the socio-technical system and strain as proposed by the psychological theory of job demands-resources model (Demerouti et al. 2001). Third, to contribute to a successful fit between the technical and social components, this thesis presents frameworks and guidelines on the design of DTM, which understand the social com-ponent (here the user and her/his environment) and adjust accordingly to the needs of their users. Therefore, the thesis provides knowledge on the design of DTMs that support users in applying stress management techniques and build the foundation for stress-sensitive systems (i.e., systems that aim to mitigate stress by applying intervention measures on the social and technical component (Adam et al. 2017)). As a matter of fact, a framework for collecting and storing data (e.g., on the user and her/his environment) is developed and experiences with im-plementing a prototype for life-integrated stress assessment are reported. The experiences from this and the existing knowledge in the literature will finally be aggregated to a mid-range design theory for mobile stress assessment. To contribute to the fourth and last aspect, the imminent misfit within the socio-technical sys-tem due to ongoing digitalization, this thesis presents new knowledge regarding digital work demands that potentially affect both employees’ health and instrumental outcomes. The current version of technostress’s theoretical foundation was introduced more than ten years ago by Tarafdar et al. (2007). However, the interaction with and use of DTM has considerably changed along with the societal and individual expectations. Therefore, this thesis puts the current con-cept of technostress to test. As a result, a new theory of digital stress, as an extension of the concept of technostress, is proposed with twelve dimensions – instead of five dimensions within the concept of Tarafdar et al. (2007) – that could be hierarchically structured in four higher-order factors. This theory holistically addresses the current challenges that employees have to deal with digitalization. To sum up, this dissertation contributes to the IS community’s knowledge base by providing knowledge regarding the interaction between employees and their digital workplace to foster the achievement of humanistic and instrumental outcomes. It provides both behavioral research and design-oriented research while using pluralistic methodological approaches. For this pur-pose, this thesis presents knowledge about the different components within the socio-technical system, design knowledge on DTMs fostering the fit between these components, and an under-standing of an upcoming misfit due to the ongoing digitalization. Overall, this research aims to support the successful change towards a healthy digital workplace in the face of digitalization

Detecção de anomalias na partilha de ficheiros em ambientes empresariais

File sharing is the activity of making archives (documents, videos, photos) available to other users. Enterprises use file sharing to make archives available to their employees or clients. The availability of these files can be done through an internal network, cloud service (external) or even Peer-to-Peer (P2P). Most of the time, the files within the file sharing service have sensitive information that cannot be disclosed. Equifax data breach attack exploited a zero-day attack that allowed arbitrary code execution, leading to a huge data breach as over 143 million user information was presumed compromised. Ransomware is a type of malware that encrypts computer data (documents, media, ...) making it inaccessible to the user, demanding a ransom for the decryption of the data. This type of malware has been a serious threat to enterprises. WannaCry and NotPetya are some examples of ransomware that had a huge impact on enterprises with big amounts of ransoms, for example WannaCry reached more than 142,361.51$in ransoms. In this dissertation, we purpose a system that can detect file sharing anomalies like ransomware (WannaCry, NotPetya) and theft (Equifax breach), and also their propagation. The solution consists of network monitoring, the creation of communication profiles for each user/machine, an analysis algorithm using machine learning and a countermeasure mechanism in case an anomaly is detected.Partilha de ficheiros é a atividade de disponibilizar ficheiros (documentos, vídeos, fotos) a utilizadores. As empresas usam a partilha de ficheiros para disponibilizar ficheiros aos seus utilizadores e trabalhadores. A disponibilidade destes ficheiros pode ser feita a partir de uma rede interna, serviço de nuvem (externo) ou até Ponto-a-Ponto. Normalmente, os ficheiros contidos no serviço de partilha de ficheiros contêm dados confidenciais que não podem ser divulgados. O ataque de violação de dados realizado a Equifax explorou uma vulnerabilidade de dia zero que permitiu execução de código arbitrário, levando a que a informação de 143 milhões de utilizadores fosse comprometida. Ransomware é um tipo de malware que cifra os dados do computador (documentos, multimédia...) tornando-os inacessíveis ao utilizador, exigindo a este um resgate para decifrar esses dados. Este tipo de malware tem sido uma grande ameaça às empresas atuais. WannaCry e NotPetya são alguns exemplos de Ransomware que tiveram um grande impacto com grandes quantias de resgate, WannaCry alcançou mais de 142,361.51$ em resgates. Neste tabalho, propomos um sistema que consiga detectar anomalias na partilha de ficheiros, como o ransomware (WannaCry, NotPetya) e roubo de dados (violação de dados Equifax), bem como a sua propagação. A solução consiste na monitorização da rede da empresa, na criação de perfis para cada utilizador/máquina, num algoritmo de machine learning para análise dos dados e num mecanismo que bloqueie a máquina afetada no caso de se detectar uma anomalia.Mestrado em Engenharia de Computadores e Telemátic

Autonomy in the AAL : between law and ethics

The growth of Silver Economy calls for a paradigm shift in senior care, where active and healthy ageing is a primary goal. It also coincides with the rapid development of new technologies – AAL being one of them. The AAL combines the advances in the emerging technologies with the need to promote healthy and active ageing experience. This master thesis focuses on the value of individual autonomy and its importance in the context of senior care. The main argument of this research is that individual autonomy is a crucial element in attaining the goal of active and healthy ageing. However, the impact of AAL technology on individual autonomy is uncertain. On one side, AAL's main goal is to enable independent and autonomous living for as long as possible, while on the other side, the AAL by its very design limits individual autonomy. Individual autonomy in the AAL is enabled through legal and ethical norms. The nature of the AAL technology and the contexts and norms under which it operates are dynamic and constantly changing. Therefore, legal regulation needs to be augmented by ethical norms that are fit to meet the ever-changing character of this emerging technology. In particular, ethical technology design principles have a great potential to address the novelty of the AAL and the challenges that European data protection legislation is failing to tackle

Ubiquitous computing and natural interfaces for environmental information

Dissertação apresentada na Faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para obtenção do Grau de Mestre em Engenharia do Ambiente, perfil Gestão e Sistemas AmbientaisThe next computing revolution‘s objective is to embed every street, building, room and object with computational power. Ubiquitous computing (ubicomp) will allow every object to receive and transmit information, sense its surroundings and act accordingly, be located from anywhere in the world, connect every person. Everyone will have the possibility to access information, despite their age, computer knowledge, literacy or physical impairment. It will impact the world in a profound way, empowering mankind, improving the environment, but will also create new challenges that our society, economy, health and global environment will have to overcome. Negative impacts have to be identified and dealt with in advance. Despite these concerns, environmental studies have been mostly absent from discussions on the new paradigm. This thesis seeks to examine ubiquitous computing, its technological emergence, raise awareness towards future impacts and explore the design of new interfaces and rich interaction modes. Environmental information is approached as an area which may greatly benefit from ubicomp as a way to gather, treat and disseminate it, simultaneously complying with the Aarhus convention. In an educational context, new media are poised to revolutionize the way we perceive, learn and interact with environmental information. cUbiq is presented as a natural interface to access that information

Generierung menschlicher Verhaltensprofile mittels unüberwachter Methoden zur Bewertung des Gesundheitszustandes

In the context of ambient assisted living, implementation of human behavior profiling is expected to occur through pervasive computing. As for information extraction from measured data, the typical way are supervised methods. However, due to the low adaptivity and high dependency on lab-setting, and the necessity of data labeling and model training, these types of methods are limited in human behavior profiling in real-life scenarios. Therefore, simple and unobtrusive sensors are relied upon to obtain daily behavior information. In spite of the incomplete observation, these sensors are able to provide key information. Thus, unsupervised methods have to be designed based on this measurement. In contrast to supervised data analysis, unsupervised methods have inherent advantages: Firstly, data labeling and training are not necessary. Secondly, they are more adaptive, making them suitable for use by different individuals. Thirdly, unknown knowledge might be discovered. In order to propose unsupervised methods for human behavior profiling that can be practically applied, the following research is conducted in this doctoral thesis: First, abstractions of events and patterns of in-home behavior scenario are defined. Second, the discovering algorithm is derived, whereby regularly occurring sensor events that can represent lifestyle patterns can be discovered. Third, with the lifestyle depicted, the change of human behavior is modeled to present the variance of lifestyle. Aiming to investigate the effectiveness of these methods, they are applied to the datasets obtained in GAL-NATARS study, which is carried out in the setting of real-life, and their effectiveness is evaluated through comparison with medical assessment results.Im Rahmen von Ambient Assisted Living sollen menschliche Verhaltensprofile durch den Pervasive Computing generiert werden. Zur Extraktion von Informationen aus Messdaten werden typischerweise überwachte Methoden verwendet. In Bezug sind diese Methoden wegen ihrer geringen Anpassungsfähigkeit, hohen Abhängigkeit von Laborumgebungen, der Notwendigkeit der Kennzeichnung und der Lernphase in realen Szenarien zur Generierung von menschliche Verhaltensprofile sehr eingeschränkt. Daher sollten einfache und unauffällige Sensoren verwendet werden, um täglich Verhaltensinformationen zu erhalten. Trotz der unvollständigen Beobachtung sind diese Sensoren in der Lage, die wichtige Informationen zu liefern. Hierfür sind unüberwachte Methoden notwendig, die auf der Grundlage dieser Messungen ausgeführt werden. Im Gegensatz zur überwachten Datenanalyse, haben unüberwachte Methoden folgende Vorteile: Zum einen sind keine Kennzeichnung von Daten und keine Lernphase erforderlich. Zweitens sind sie anpassungsfähiger, so dass sie für die Verwendung bei verschiedenen Individuen geeignet sind. Drittens können siebisher unbekanntes Wissen entdecken. Zur Entwicklung von praktisch anwendbaren unüberwachten Methoden für die Generierung menschlicher Verhaltensprofile, wird in dieser Doktorarbeit die folgende Forschung durchgeführt: Erstens, Definition von Abstraktionen für Ereignisse und Muster häuslichen Verhaltens. Zweitens wird ein Entdeckungsalgorithmus abgeleitet, der regelmäßig auftretende Sensorereignisse, die Lebensgewohnheiten darstellen können, entdecken kann. Drittens, wird mit den so gewonnenen Lebensgewohnheiten, die Änderung des menschlichen Verhaltens modelliert, um die Varianz des Lebensstils abzubilden. Mit dem Ziel, die Wirksamkeit dieser Methoden zu untersuchen, werden sie auf Datensätze aus dem Feld, gesammelt in der GAL-NATARS Studie durchgeführt wird, angewendet. Ihre Wirksamkeit wird durch den Vergleich mit den Ergebnissen der medizinischen Beurteilung bewertet