Systematic analysis of mobile diabetes management applications on different platforms

There are a number of mobile applications available to help patients suffering from Type 1 diabetes to manage their condition, but the quality of these applications varies greatly. This paper details the findings from a systematic analysis of these applications on three mobile platforms (Android, iOS, and Blackberry) that was conducted to establish the state of the art in mobile applications for diabetes management. The findings from this analysis will help to inform the future development of more effective mobile applications to help patients suffering from Type 1 diabetes who wish to manage their condition with a mobile application

Minimal information sensor system for indoor tracking of several persons

In this paper, we introduce an ongoing experimentation in our laboratory for indoor tracking of several persons with a minimal set of informations, based on photoelectric beam barrier sensors. Incremental design, data analysis and acceptance concerns are discussed

Visual complexity in human-machine interaction = Visuelle Komplexität in der Mensch-Maschine Interaktion

Visuelle Komplexität wird oft als der Grad an Detail oder Verworrenheit in einem Bild definiert (Snodgrass & Vanderwart, 1980). Diese hat Einfluss auf viele Bereiche des menschlichen Lebens, darunter auch solche, die die Interaktion mit Technologie invol-vieren. So wurden Effekte visueller Komplexität etwa im Straßenverkehr (Edquist et al., 2012; Mace & Pollack, 1983) oder bei der Interaktion mit Software (Alemerien & Magel, 2014) oder Webseiten (Deng & Poole, 2010; Tuch et al., 2011) nachgewie-sen. Obwohl die Erforschung visueller Komplexität bereits bis auf die Gestaltpsycho-logen zurückgeht, welche etwa mit dem Gestaltprinzip der Prägnanz die Bedeutung von Simplizität und Komplexität im Wahrnehmungsprozess verankerten (Koffka, 1935; Wertheimer, 1923), sind weder die Einflussfaktoren visueller Komplexität, noch die Zusammenhänge mit Blickbewegungen oder mentaler Beanspruchung bisher ab-schließend erforscht. Diese Punkte adressiert die vorliegende Arbeit mithilfe von vier empirischen Forschungsarbeiten. In Studie 1 wird anhand der Komplexität von Videos in Leitwarten sowie der Effekte auf subjektive, physiologische und Leistungsparameter mentaler Beanspruchung die Bedeutung des Konstruktes im Bereich der Mensch-Maschine Interaktion untersucht. Studie 2 betrachtet die dimensionale Struktur und die Bedeutung verschiedener Ein-flussfaktoren visueller Komplexität genauer, wobei unterschiedliches Stimulusmaterial genutzt wird. In Studie 3 werden mithilfe eines experimentellen Ansatzes die Auswir-kungen von Einflussfaktoren visueller Komplexität auf subjektive Bewertungen sowie eine Auswahl okularer Parameter untersucht. Als Stimuli dienen dabei einfache, schwarz-weiße Formenmuster. Zudem werden verschiedene computationale und oku-lare Parameter genutzt, um anhand dieser Komplexitätsbewertungen vorherzusagen. Dieser Ansatz wird in Studie 4 auf Screenshots von Webseiten übertragen, um die Aussagekraft in einem anwendungsnahen Bereich zu untersuchen. Neben vorangegangenen Forschungsarbeiten legen insbesondere die gefundenen Zusammenhänge mit mentaler Beanspruchung nahe, dass visuelle Komplexität ein relevantes Konstrukt im Bereich der Mensch-Maschine Interaktion darstellt. Dabei haben insbesondere quantitative und strukturelle, aber potentiell auch weitere Aspekte Einfluss auf die Bewertung visueller Komplexität sowie auf das Blickverhalten der Be-trachter. Die gewonnenen Ergebnisse erlauben darüber hinaus Rückschlüsse auf die Zusammenhänge mit computationalen Maßen, welche in Kombination mit okularen Parametern gut für die Vorhersage von Komplexitätsbewertungen geeignet sind. Die Erkenntnisse aus den durchgeführten Studien werden im Kontext vorheriger For-schungsarbeiten diskutiert. Daraus wird ein integratives Forschungsmodell visueller Komplexität in der Mensch-Maschine-Interaktion abgeleitet

The Proceedings of the 23rd Annual International Conference on Digital Government Research (DGO2022) Intelligent Technologies, Governments and Citizens June 15-17, 2022

The 23rd Annual International Conference on Digital Government Research theme is “Intelligent Technologies, Governments and Citizens”. Data and computational algorithms make systems smarter, but should result in smarter government and citizens. Intelligence and smartness affect all kinds of public values - such as fairness, inclusion, equity, transparency, privacy, security, trust, etc., and is not well-understood. These technologies provide immense opportunities and should be used in the light of public values. Society and technology co-evolve and we are looking for new ways to balance between them. Specifically, the conference aims to advance research and practice in this field. The keynotes, presentations, posters and workshops show that the conference theme is very well-chosen and more actual than ever. The challenges posed by new technology have underscored the need to grasp the potential. Digital government brings into focus the realization of public values to improve our society at all levels of government. The conference again shows the importance of the digital government society, which brings together scholars in this field. Dg.o 2022 is fully online and enables to connect to scholars and practitioners around the globe and facilitate global conversations and exchanges via the use of digital technologies. This conference is primarily a live conference for full engagement, keynotes, presentations of research papers, workshops, panels and posters and provides engaging exchange throughout the entire duration of the conference

Early diagnosis of disorders based on behavioural shifts and biomedical signals

There are many disorders that directly affect people’s behaviour. The people that are suffering from such a disorder are not aware of their situation, and too often the disorders are identified by relatives or co-workers because they notice behavioural shifts. However, when these changes become noticeable, it is often too late and irreversible damages have already been produced. Early detection is the key to prevent severe health-related damages and healthcare costs, as well as to improve people’s quality of life. Nowadays, in full swing of ubiquitous computing paradigm, users’ behaviour patterns can be unobtrusively monitored by means of interactions with many electronic devices. The application of this technology for the problem at hand would lead to the development of systems that are able to monitor disorders’ onset and progress in an ubiquitous and unobtrusive way, thus enabling their early detection. Some attempts for the detection of specific disorders based on these technologies have been proposed, but a global methodology that could be useful for the early detection of a wide range of disorders is still missing. This thesis aims to fill that gap by presenting as main contribution a global screening methodology for the early detection of disorders based on unobtrusive monitoring of physiological and behavioural data. The proposed methodology is the result of a cross-case analysis between two individual validation scenarios: stress in the workplace and Alzheimer’s Disease (AD) at home, from which conclusions that contribute to each of the two research fields have been drawn. The analysis of similarities and differences between the two case studies has led to a complete and generalized definition of the steps to be taken for the detection of a new disorder based on ubiquitous computing.Jendearen portaeran eragin zuzena duten gaixotasun ugari daude. Hala ere, askotan, gaixotasuna pairatzen duten pertsonak ez dira euren egoerataz ohartzen, eta familiarteko edo lankideek identifikatu ohi dute berau jokabide aldaketetaz ohartzean. Portaera aldaketa hauek nabarmentzean, ordea, beranduegi izan ohi da eta atzerazeinak diren kalteak eraginda egon ohi dira. Osasun kalte larriak eta gehiegizko kostuak ekiditeko eta gaixoen bizi kalitatea hobetzeko gakoa, gaixotasuna garaiz detektatzea da. Gaur egun, etengabe zabaltzen ari den Nonahiko Konputazioaren paradigmari esker, erabiltzaileen portaera ereduak era diskretu batean monitorizatu daitezke, gailu teknologikoekin izandako interakzioari esker. Eskuartean dugun arazoari konponbidea emateko teknologi hau erabiltzeak gaixotasunen sorrera eta aurrerapena nonahi eta era diskretu batean monitorizatzeko gai diren sistemak garatzea ekarriko luke, hauek garaiz hautematea ahalbidetuz. Gaixotasun konkretu batzuentzat soluzioak proposatu izan dira teknologi honetan oinarrituz, baina metodologia orokor bat, gaixotasun sorta zabal baten detekzio goiztiarrerako erabilgarria izango dena, oraindik ez da aurkeztu. Tesi honek hutsune hori betetzea du helburu, mota honetako gaixotasunak garaiz hautemateko, era diskretu batean atzitutako datu fisiologiko eta konportamentalen erabileran oinarritzen den behaketa sistema orokor bat proposatuz. Proposatutako metodologia bi balidazio egoera desberdinen arteko analisi gurutzatu baten emaitza da: estresa lantokian eta Alzheimerra etxean, balidazio egoera bakoitzari dagozkion ekarpenak ere ondorioztatu ahal izan direlarik. Bi kasuen arteko antzekotasun eta desberdintasunen analisiak, gaixotasun berri bat nonahiko konputazioan oinarrituta detektatzeko jarraitu beharreko pausoak bere osotasunean eta era orokor batean definitzea ahalbidetu du

Re-examining and re-conceptualising enterprise search and discovery capability: towards a model for the factors and generative mechanisms for search task outcomes.

Many organizations are trying to re-create the Google experience, to find and exploit their own corporate information. However, there is evidence that finding information in the workplace using search engine technology has remained difficult, with socio-technical elements largely neglected in the literature. Explication of the factors and generative mechanisms (ultimate causes) to effective search task outcomes (user satisfaction, search task performance and serendipitous encountering) may provide a first step in making improvements. A transdisciplinary (holistic) lens was applied to Enterprise Search and Discovery capability, combining critical realism and activity theory with complexity theories to one of the worlds largest corporations. Data collection included an in-situ exploratory search experiment with 26 participants, focus groups with 53 participants and interviews with 87 business professionals. Thousands of user feedback comments and search transactions were analysed. Transferability of findings was assessed through interviews with eight industry informants and ten organizations from a range of industries. A wide range of informational needs were identified for search filters, including a need to be intrigued. Search term word co-occurrence algorithms facilitated serendipity to a greater extent than existing methods deployed in the organization surveyed. No association was found between user satisfaction (or self assessed search expertise) with search task performance and overall performance was poor, although most participants had been satisfied with their performance. Eighteen factors were identified that influence search task outcomes ranging from user and task factors, informational and technological artefacts, through to a wide range of organizational norms. Modality Theory (Cybersearch culture, Simplicity and Loss Aversion bias) was developed to explain the study observations. This proposes that at all organizational levels there are tendencies for reductionist (unimodal) mind-sets towards search capability leading to fixes that fail. The factors and mechanisms were identified in other industry organizations suggesting some theory generalizability. This is the first socio-technical analysis of Enterprise Search and Discovery capability. The findings challenge existing orthodoxy, such as the criticality of search literacy (agency) which has been neglected in the practitioner literature in favour of structure. The resulting multifactorial causal model and strategic framework for improvement present opportunities to update existing academic models in the IR, LIS and IS literature, such as the DeLone and McLean model for information system success. There are encouraging signs that Modality Theory may enable a reconfiguration of organizational mind-sets that could transform search task outcomes and ultimately business performance

On the mining of artful processes

Artful processes are those processes in which the experience, intuition, and knowledge of the actors are the key factors in determining the decision making. These knowledge-intensive processes are typically carried out by the “knowledge workers”, such as professors, managers, researchers. They are often scarcely formalised or completely unknown a priori, and depend on the skills, experience, and judgment of the primary actors. Artful processes have goals and methods that change quickly over time, making them difficult to codify in the context of an enterprise application. Knowledge workers cannot be realistically expected to instruct the assistive system by modelling their artful processes: it would be time-consuming both in the initial definition and in the potential continuous revisions. To make things worse, time is the crucial resource that usually knowledge workers indeed lack. Despite the advent of structured case management tools, many enterprise processes are still “run” over emails. Thus, reverse engineering workflows of such processes and their integration with artefacts and other structured processes can accurately depict the enterprise’s process landscape. A system able to infer the models of the processes laying behind the email messages exchanged would be valuable and the result could materialise almost freely. This is the purpose of our approach, which is the core of this thesis and is named MailOfMine. Its investigation mainly resides in the Machine Learning area. More specifically, it relates to Information Retrieval (IR) and Process Mining (PM). We adopted well-known IR techniques in order to extract the activities out of the email messages. We propose a new algorithm for PM in order to discover the temporal rules that the activities adhere to: MINERful. The set of such rules, intended as temporal constraints, constitute the so called declarative modelling of workflows. Declarative models differ from the imperative in that they do not explicitly represent every possible execution that a process can be enacted through, i.e., there is no graph-like structure determining the whole evolution of a process instance, from the beginning to the end. They establish a set of constraints that must hold true, whatever the evolution of the process instance will be. What is not explicitly declared to be respected, is allowed. The reader can easily see that it is better suited to processes subject to frequent changes, with respect to the classical approach. From a more abstract perspective, this work challenges the problem of discovering highly flexible workflows (such as artful processes), out of semi-structured information (such as email messages)