International Telemetering Conference Proceedings / October 20-23, 2003 / Riviera Hotel and Convention Center, Las Vegas, Nevada / The cost of telemetry collection is significantly reduced by unmanned store and forward systems made possible using 622MHz OC-12 networks. Networks are readily available to telemetry system architects. The in-band control of remote unmanned collection platforms is handled through a Java browser interface. Data from many telemetry channels are collected and temporarily stored on a digital disk system designed around the OC-12 network. The I/O, storage, and network components are configured, set, and initialized remotely. Recordings are started and stopped on command and can be made round-the-clock. Files of stored, time stamped data are delivered at the rate of OC-12 to a distribution center.

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Master of Science / Department of Electrical & Computer Engineering / Steve Warren / Handgrip contractions are a standard exercise modality to evaluate muscular system performance. Most conventional ergometer systems that collect handgrip contraction data are manually controlled, placing a burden on the researcher to guide subject activity while recording the resultant data. Further, post-processing tools for this type of experiment are not standardized within the domain, which requires investigators to process their data with multiple tool sets and often create custom tool sets for that purpose. This can make experimental data difficult to compare and correlate, even within the same research group. This thesis presents updates to a hand-forearm ergometer system that automate the control and data-acquisition processes as well as provide a tool set to post process hand contraction data. The automated system utilizes a LabVIEW virtual instrument as the system centerpiece; it provides the subject/researcher interfaces and coordinates data acquisition from both traditional and new sensors. The tool set also incorporates a collection of MATLAB scripts that allow the investigator to post process these data in a standard way, such as automating the processes of noise floor removal, burst start/stop time identification, and mean/median frequency calculation in electromyograms (EMGs). The tool set has proven to be a viable support resource for experimental studies performed by the Kansas State University Human Exercise Physiology lab that target muscle fatigue in human forearms. Initial data acquired during these tests indicate the viability of the system to acquire consistent and physiologically meaningful data while providing a usable tool set for follow-on data analyses.

M. Tech. (Information Technology, Faculty of Applied and Computer Sciences, Vaal University of Technology / The number of students passing computer programming modules at Higher Education Institutions (HEIs) in South Africa at first year level is low. Only with the second attempt do most students pass. This delay results in students completing their three-year undergraduate qualification in four or even five years. One potential contribution towards addressing this problem is the introduction of a collaborative (cooperative) pedagogical approach where students develop software in teams, known in the Information Technology (IT) sector as pair-programming. This study endeavoured to investigate the impact of pair-programming on the academic progress of students registered for the Information Technology qualification at HEIs in South Africa. The study warranted the selection of action research as the most appropriate research strategy. Multi-methods data collection was carried out over two consecutive semesters. The data collection methods included a semi-structured interview, observations and empirical assessment. The participants were students registered for the Information Systems module, which focuses on software development. Pair-programming was introduced to one group of software development students, while a second group continued with the normal solo-programming approach. Semi-structured interviews were held with the students before commencement and after completion of the pair-programming intervention, to establish a change, if any, in the academic performance, attitude and enjoyment level of students introduced to pair-programming compared to those who continued with solo-programming. Observations were conducted throughout the course of the practical sessions over both semesters. Empirical assessments were done by means of tests given to both groups of students during the practical sessions, three tests per semester. Data analysis techniques included t-tests and thematic analysis. The findings concluded that pair-programming had a significant positive impact on the academic progress of IT students, including an increase in the enjoyment level and a more positive attitude towards software development.

L'identité des personnes dans l'espace numérique n'est pas définissable d'une seule manière, et son mode d'expression est multiple. En effet, un individu peut disposer de plusieurs identités dans le numérique et jouer des rôles sociaux différents suivant les contextes sociaux auxquels il est confronté. Mais quels peuvent être les effets de l'usage de ces masques identitaires ? L'identité des personnes dans le cadre des réseaux sociaux renvoie au questionnement de soi, et des autres. Le versant individualiste et le versant communautaire de cette identité constituent la trame de la construction identitaire de l'utilisateur. Aussi, il apparaît que la richesse mais aussi la complexité des réseaux tiennent au fait que le droit confond individu et identité. Le droit repose en effet sur une conception essentialiste de l'identité, par laquelle chacun est acteur de sa propre trajectoire. Mais l'individu ne vit pas seul, il vit en groupe et il est saisi dans un réseau de relations sociales. Aussi, concevoir une identité personnelle en marge de la réalité numérique revient à distinguer la personne de la notion de présence en ligne qui est éminemment déclarative et performative. Cela amène à reconsidérer la place de l'identité dans l'espace numérique. Pour appréhender la question de la construction de l'identité personnelle dans les réseaux sociaux, il faudra aborder les différentes approches qui visent à assurer à chacun une identité qui soit conforme à ses désirs. Il sera également nécessaire d'adapter les mesures existantes à la réalité virtuelle, afin d'établir un régime de l'identité personnelle plus sécurisé et respectueux des droits de la personnalité de chaque utilisateur. / The identity of people in the digital space cannot be defined in one way. Its mode of expression is multiple. In fact, an individual can have several identities in the digital environment. It can also play different social roles according to social contexts that it faces. But what are effects of using identity masks ? The individual's identity within the social networks refers to the self-questioning, and others. The individualistic side and the community side of this identity are the foundation of the building of user's identity. Moreover, it appears that the wealth and the complexity of networks are the result of the confusion made by the law between individual and identity. In fact, the law is based on an essentialist conception of identity, by which each player has its own trajectory. But the individual does not live alone, he lives in a group and it is part of a network of social relations. The identity is made in the interaction of a claimed identity for oneself and assigned by others. Also, develop a personal identity on the fringes of the digital reality is to distinguish the person of the concept of online presence which is eminently declarative and performative.All this leads to reconsider the place of identity in the digital space. To understand the question of the construction of personal identity in social network, different approaches will be detailed. Those approaches are aimed to ensure everyone an identity according his wishes. Also, it will be necessary to adapt the existing measures to the virtual reality, in order to establish a more secure regime of personal identity, in respect of the rights of each user's personnality.

Les événements distribués, se déroulant sur plusieurs jours et/ou sur plusieurs lieux, tels que les conventions, festivals ou croisières, sont de plus en plus populaires ces dernières années et attirant des milliers de participants. Les programmes de ces événements sont généralement très denses, avec un grand nombre d'activités se déroulant en parallèle. Ainsi, choisir les activités à entreprendre est devenu un véritable défi pour les participants. Les systèmes de recommandation peuvent constituer une solution privilégiée dans ce genre d'environnement. De nombreux travaux en recommandation se sont concentrés sur la recommandation personnalisée d'objets spatiaux (points d'intérêts immuables dans le temps ou événements éphémères) indépendants les uns des autres. Récemment, la communauté scientifique s'est intéressée à la recommandation de séquences de points d'intérêts, exploitant des motifs comportementaux des utilisateurs et incorporant des contraintes spatio-temporelles pour recommander un itinéraire de points d'intérêts. Néanmoins, très peu de travaux se sont intéressés à la problématique de la recommandation de séquence d'activités, problème plus difficile du fait du caractère éphémère des objets à recommander. Dans cette thèse, nous proposons tout d'abord une formalisation du problème de la recommandation de séquences d'activités. Dans ce cadre, nous proposons et discutons une classification des types d'influences pouvant avoir un impact sur l'estimation de l'intérêt des utilisateurs dans les activités. Ensuite, nous proposons ANASTASIA, une approche de recommandation personnalisée de séquences d'activités lors des événements distribués. Notre approche est basée sur trois composants clés : (1) l'estimation de l'intérêt d'un utilisateur pour une activité, prenant en compte différentes influences, (2) l'intégration de motifs comportementaux d'utilisateurs basés sur leurs historiques d'activités et (3) la construction d'un planning ou séquence d'activités prenant en compte les contraintes spatio-temporelles de l'utilisateur et des activités. Nous explorons ainsi des méthodes issus de l'apprentissage de séquences et de l'optimisation discrète pour résoudre le problème. Enfin, nous démontrons le manque de jeu de données librement accessibles pour l'évaluation des algorithmes de recommandation d'événements et de séquences d'événements. Nous pallions à ce problème en proposant deux jeux de données, librement accessibles, que nous avons construits au cours de la thèse: Fantasy_db et DEvIR. Fantasy_db comporte des données de participation à des événements lors d'une croisière, recueillies lors d'une étude utilisateur, tandis que DEvIR réunit des données de participation au Comic Con de San Diego, convention majeure dans le domaine. / Multi-day events such as conventions, festivals, cruise trips, to which we refer to as distributed events, have become very popular in recent years, attracting hundreds or thousands of participants. Their programs are usually very dense, making it challenging for the attendees to make a decision which events to join. Recommender systems appear as a common solution in such an environment. While many existing solutions deal with personalised recommendation of single items, recent research focuses on the recommendation of consecutive items that exploits user's behavioural patterns and relations between entities, and handles geographical and temporal constraints. In this thesis, we first formulate the problem of recommendation of activity sequences, classify and discuss the types of influence that have an impact on the estimation of the user's interest in items. Second, we propose an approach (ANASTASIA) to solve this problem, which aims at providing an integrated support for users to create a personalised itinerary of activities. ANASTASIA brings together three components, namely: (1) estimation of the user’s interest in single items, (2) use of sequential influence on activity performance, and (3) building of an itinerary that takes into account spatio-temporal constraints. Thus, the proposed solution makes use of the methods based on sequence learning and discrete optimisation. Moreover, stating the lack of publicly available datasets that could be used for the evaluation of event and itinerary recommendation algorithms, we have created two datasets, namely: (1) event attendance on board of a cruise (Fantasy_db) based on a conducted user study, and (2) event attendance at a major comic book convention (DEvIR). This allows to perform evaluation of recommendation methods, and contributes to the reproducibility of results.

During the 21st century, the use of digital services has exploded. Companies are getting better at collecting and using data for their own gain. The increased collection of data has contributed to increased privacy concerns among many. This paper examines how a person’s attitude and knowledge about data collection can affect their online behavior. To examine this, a questionnaire survey was conducted. The study's results indicate that there is a paradoxical behavior among the respondents, since most people have a negative view of data collection, but do not take measures to reflect this attitude. Furthermore, the result suggests that knowledge about data collection acts as the primary motivator for taking measures to protect their data.   Keywords: Data collection, online behaviour, privacy paradox, GDPR, attitude, knowledge, privacy concerns / Under 2000-talet har användningen av digitala tjänster exploderat. Företag blir bättre på att samla in och använda data för deras egen vinning. Den ökade datainsamlingen har bidragit till en ökad oro kring personlig data hos många. Denna uppsats undersöker hur internetanvändares attityd och kunskap kring datainsamling kan påverka deras online-beteende. För att undersöka detta utfördes en enkätundersökning. Studiens resultat indikerar att det finns ett paradoxalt beteende hos respondenterna då de flesta har en negativ syn till datainsamling men vidtar inte åtgärder för att spegla denna attityd. Vidare tyder resultatet på att kunskap kring datainsamling agerar som den primära motivatorn för att vidta åtgärder för att skydda deras data.   Nyckelord: Datainsamling, online-beteende, Privacy Paradox, GDPR, attityd, kunskap. integritets-oro

Este texto sugere sobre como calcular um tamanho de amostra com base no uso de um instrumento de coleta de dados formado por itens categóricos. Os argumentos para esta sugestão estão embasados nas teorias da Combinatória e da Paraconsistência. O propósito é sugerir um procedimento de cálculo simples e prático para obter um tamanho de amostra aceitável para coletar informações, organizá-las e analisar dados de uma aplicação de um instrumento de coleta de dados médicos baseado, exclusivamente, em itens discretos (itens categóricos), ou seja, cada item do instrumento é considerado como uma variável não-paramétrica com um número finito de categorias. Na Área de Saúde, é muito comum usar instrumentos para levantamento com base nesse tipo de itens: protocolos clínicos, registros hospitalares, questionários, escalas e outras ferramentas para inquirição consideram uma sequência organizada de itens categóricos. Uma fórmula para o cálculo do tamanho da amostra foi proposta para tamanhos de população desconhecidos e um ajuste dessa fórmula foi proposto para populações de tamanho conhecido. Pôde-se verificar, com exemplos práticos, a possibilidade de uso de ambas as fórmulas, o que permitiu considerar a praticidade de uso nos casos em que se tem disponível pouca ou nenhuma informação sobre a população de onde a amostra será coletada. / This text suggests how to calculate a sample size based on the use of a data collection instrument consisting of categorical items. The arguments for this suggestion are based on theories of Combinatorics and Paraconsistency. The purpose is to suggest a practical and simple calculation procedure to obtain an acceptable sample size to collect information, organize it and analyze data from an application of an instrument for collecting medical data, based exclusively on discrete items (categorical items), i.e., each item of the instrument is considered as a non-parametric variable with finite number of categories. In the health care it is very common to use survey instruments on the basis of such items: clinical protocols, hospital registers, questionnaires, scales and other tools for hearing consider a sequence of items organized categorically. A formula for calculating the sample size was proposed for a population of unknown size, and an adjusted formula has been proposed for population of known size. It was seen, with practical examples, the possibility of using both formulas, allowing to consider the practicality of the use in cases that have little or no information available about the population from which the sample is collected

Este texto sugere sobre como calcular um tamanho de amostra com base no uso de um instrumento de coleta de dados formado por itens categóricos. Os argumentos para esta sugestão estão embasados nas teorias da Combinatória e da Paraconsistência. O propósito é sugerir um procedimento de cálculo simples e prático para obter um tamanho de amostra aceitável para coletar informações, organizá-las e analisar dados de uma aplicação de um instrumento de coleta de dados médicos baseado, exclusivamente, em itens discretos (itens categóricos), ou seja, cada item do instrumento é considerado como uma variável não-paramétrica com um número finito de categorias. Na Área de Saúde, é muito comum usar instrumentos para levantamento com base nesse tipo de itens: protocolos clínicos, registros hospitalares, questionários, escalas e outras ferramentas para inquirição consideram uma sequência organizada de itens categóricos. Uma fórmula para o cálculo do tamanho da amostra foi proposta para tamanhos de população desconhecidos e um ajuste dessa fórmula foi proposto para populações de tamanho conhecido. Pôde-se verificar, com exemplos práticos, a possibilidade de uso de ambas as fórmulas, o que permitiu considerar a praticidade de uso nos casos em que se tem disponível pouca ou nenhuma informação sobre a população de onde a amostra será coletada. / This text suggests how to calculate a sample size based on the use of a data collection instrument consisting of categorical items. The arguments for this suggestion are based on theories of Combinatorics and Paraconsistency. The purpose is to suggest a practical and simple calculation procedure to obtain an acceptable sample size to collect information, organize it and analyze data from an application of an instrument for collecting medical data, based exclusively on discrete items (categorical items), i.e., each item of the instrument is considered as a non-parametric variable with finite number of categories. In the health care it is very common to use survey instruments on the basis of such items: clinical protocols, hospital registers, questionnaires, scales and other tools for hearing consider a sequence of items organized categorically. A formula for calculating the sample size was proposed for a population of unknown size, and an adjusted formula has been proposed for population of known size. It was seen, with practical examples, the possibility of using both formulas, allowing to consider the practicality of the use in cases that have little or no information available about the population from which the sample is collected

Healthcare systems have assimilated information and communication technologies in order to improve the quality of healthcare and patient's experience at reduced costs. The increasing digitalization of people's health information raises however new threats regarding information security and privacy. Accidental or deliberate data breaches of health data may lead to societal pressures, embarrassment and discrimination. Information security and privacy are paramount to achieve high quality healthcare services, and further, to not harm individuals when providing care. With that in mind, we give special attention to the category of Mobile Health (mHealth) systems. That is, the use of mobile devices (e.g., mobile phones, sensors, PDAs) to support medical and public health. Such systems, have been particularly successful in developing countries, taking advantage of the flourishing mobile market and the need to expand the coverage of primary healthcare programs. Many mHealth initiatives, however, fail to address security and privacy issues. This, coupled with the lack of specific legislation for privacy and data protection in these countries, increases the risk of harm to individuals. The overall objective of this thesis is to enhance knowledge regarding the design of security and privacy technologies for mHealth systems. In particular, we deal with mHealth Data Collection Systems (MDCSs), which consists of mobile devices for collecting and reporting health-related data, replacing paper-based approaches for health surveys and surveillance. This thesis consists of publications contributing to mHealth security and privacy in various ways: with a comprehensive literature review about mHealth in Brazil; with the design of a security framework for MDCSs (SecourHealth); with the design of a MDCS (GeoHealth); with the design of Privacy Impact Assessment template for MDCSs; and with the study of ontology-based obfuscation and anonymisation functions for health data. / Information security and privacy are paramount to achieve high quality healthcare services, and further, to not harm individuals when providing care. With that in mind, we give special attention to the category of Mobile Health (mHealth) systems. That is, the use of mobile devices (e.g., mobile phones, sensors, PDAs) to support medical and public health. Such systems, have been particularly successful in developing countries, taking advantage of the flourishing mobile market and the need to expand the coverage of primary healthcare programs. Many mHealth initiatives, however, fail to address security and privacy issues. This, coupled with the lack of specific legislation for privacy and data protection in these countries, increases the risk of harm to individuals. The overall objective of this thesis is to enhance knowledge regarding the design of security and privacy technologies for mHealth systems. In particular, we deal with mHealth Data Collection Systems (MDCSs), which consists of mobile devices for collecting and reporting health-related data, replacing paper-based approaches for health surveys and surveillance.