1752 research outputs found
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Forgery-proof user activity control using service workers on the example of an Angular browser application
No full textIn various contexts, it can be useful for providers of online platforms to monitor the activity of their users. Reasons for this are, for example, the evaluation of certain dwell times in different components, security mechanisms in the form of a maximum access time or the control of the actual active time of a user. The latter is the central requirement for the application that will be implemented in this bachelor thesis. The thesis describes the development of a service of an e-learning platform that is responsible for checking and storing the time a user actively spends in a learning module. To ensure that this also works offline, a service worker is deployed to take over the work of the server in case of a connection problem. Various techniques are also used to ensure a forgery-proof application. The following chapters explain the development based on the various requirements, the architecture with its respective components and the basics of the concepts which are used. In addition, various implementation options are discussed and finally the results are compared with the requirements
Konzeption, Realisierung und Anwendung eines generischen, plattformübergreifenden und testbaren Frameworks für wissenschaftliche Datenerhebung über mobile Endgeräte am Beispiel von Flutter
No full textMobile Endgeräte sind heutzutage weit verbreitet und werden auch im Gesundheitssektor verwendet. So gibt es Frameworks wie die TrackYourHealth API, welche unter anderem Datenerfassung über die Beantwortung von Fragebögen auf mobilen Geräten erlauben. Es gibt bereits mobile Anwendungen zu konkreten Studien auf dieser API, doch die meisten davon sind auf ein Thema beschränkt oder nur für ein Betriebssystem verfügbar. In dieser Arbeit wird ein gegnerisches Framework erstellt, um eine einfache Anbindung der TrackYourHealth API in mobile Flutter Anwendungen zu erlauben. Durch eigene Klassen und Funktionen wird die Nutzung der API erleichtert und durch die vorhandene Testumgebung sowie der gründlichen Dokumentation die Nutzung des entstandenen Frameworks erklärt. Mithilfe des entstandenen Frameworks können somit verschiedene plattformübergreifende mobile Anwendungen zur wissenschaftlichen Datenerhebung mittels der TrackYourHealth API sehr schnell und einfach erstellt werden
Cloud-based Business Intelligence Structure Solution for Multiple Datasources
No full textEs treten zunehmend größere Mengen an Daten auf, die die Möglichkeit bieten
durch genaue Analysen und Auswertungen Erkenntnisse zu erlangen. Für eine moderne
Skalierbarkeit stehen Cloud-Ressourcen zur Verfügung und durch die Option
des Einbindens verschiedener Quellen wird Flexibilität gewahrt.
Um diese Vorteile nutzen zu können, wird eine Architektur benötigt, die es erlaubt
Daten automatisiert zu aktualisieren, wodurch der manuelle Aufwand minimiert
wird. Diese Architektur beinhaltet eine von vielen Business Intelligence Lösungen
aus denen die, für die eigenen Anforderungen, ideale Lösung ausgewählt
werden muss.
Um diese Entscheidungen zu erleichtern bietet diese Ausarbeitung einen Überblick
über die Architekturvarianten Data Lake, Data Warehouse und direkte Anbindung
an ein Business Intelligence Tool. Aufsetzend auf diese Architektur bezieht ein Business
Intelligence Tool die Daten. Ein Vergleich zwischen Marktführern der Business
Intelligence Sparte vervollständigt die allgemeine Entscheidungsgrundlage.
Auf diesen Informationen aufbauend entsteht ein Prototyp den Anforderungen eines
Unternehmens entsprechend. Zunächst werden in einem Konzept die Optionen mit
den Anforderungen verglichen und eine feingranularere Architektur entworfen. Dies
führt zu einer Umsetzung auf Basis eines Data Warehouses und Microsoft Power
BI.
Das Ergebnis zeichnet sich durch einen automatisierten Vorgang aus, der Buchungsdaten
der ERP-System Module Dynamics 365 Finance/ Supply Chain Management
und zusätzliche Daten von Excel-Dateien im Sharepoint in eine Cloud Datenbank
speichert. Die Daten werden aufbereitet und über den Power BI Service in Microsoft
Teams bereitgestellt. Von dort können sie unter Berücksichtigung der jeweiligen
Berechtigungen des Benutzers eingesehen werden. Weitere Datenquellen werden
konzeptionell untersucht und für eine spätere Anbindung berücksichtig
A Systematic Analysis of Current Architectures and Apps in the Field of Mobile Crowdsensing
No full textThe broad usage of mobile devices, along with the growing number of sensors embedded in them, has considerably facilitated the implementation of crowdsensing systems. Therefore, Mobile Crowdsensing has received noteworthy attention throughout the years, which has lead to an increasing number of publications with different approaches and solutions. These solutions require further examination and classification, since there are not many scientific papers which have analyzed a large number of systems. This thesis performs a systematic analysis of current architectures and apps in the field of Mobile Crowdsensing, providing a comprehensive overview. The reviewed literature was retrieved from Google Scholar, PubMed, PsycINFO and Web of Science in accordance with the PRISMA guidelines. This resulted in 158 unique records on Mobile Crowdsensing systems, as well as 292 distinct records on Ecological Momentary Assessment apps for further analysis. There are 93 different Mobile Crowdsensing systems, whereas 69 distinct Ecological Momentary Assessment apps were determined. A detailed overview of the years in which the literature was published is presented, indicating a growing research trend in recent years. Subsequently, descriptive data about the systems, such as participatory and opportunistic sensing, website, GitHub, Ecological Momentary Intervention as well as current availability in the Google Play Store and Apple App Store is provided. Additionally, operating systems, used sensors for data acquisition, databases, computation including scalability and context-awareness are also presented. Furthermore, assessment types, e.g., signal-contingent, interval-contingent and event-contingent, followed by notification methods, e.g., push notification, auditory alerts, vibrations, SMS and flash of the camera are described. In addition, reminders, response limit and adjustable prompting are presented as well. Moreover, different incentive mechanisms are inspected, followed by categorization of use cases. Lastly, certain systems are described in more detail
Entwicklung einer mHealth-App zum Vergleich moderner Benachrichtigungstechniken
No full textPush Notifications haben sich als eine sehr effektive Benachrichtigungsmöglichkeit etabliert. Ein Entwickler, welcher Push Notifications z.B. in einer mHealth App gezielt einsetzen möchte, steht vor der Frage, welche Push Technologien es zur Auswahl gibt und wie sie im gegenseitigen Vergleich unter wichtigen Qualitätsaspekten wie Zuverlässigkeit und Skalierbarkeit des Push Dienstes und Verfügbarkeit von Push Notifications stehen, um die für ihn Bestgeeignete unter allen Alternativen abzuwägen und zu implementieren.
In dieser Arbeit ist das Ziel, ausgewählte Push Technologien Implementierungen anhand einer selbst entwickelten mHealth App auf Zuverlässigkeit, Verfügbarkeit und Skalierbarkeit zu untersuchen. Es wird mit einer Auswahl von Push Technologien wie Remote Notifications mit FCM, HTTP Long Polling und einer eigenen offenen mobile notification server (MSN) Lösung im Vergleich zu Local Notifications diskutiert, welche Push Technologie unter den Aspekten der Skalierbarkeit und Zuverlässigkeit des Dienstes und Verfügbarkeit der Push Nachrichten die bestgeeignete Push Technologie im App Kontext ist. Der jeweilige App Kontext und die Diskussion der am besten geeigneten Push Lösung werden mit einer selbst implementierten Motivationsapp unterstützt.
Um zur Forschungsfrage der geeigneten Push Technologie eine Antwort zu geben, wurde mit Hilfe der App die Zuverlässigkeit der Push Technologien getestet. Skalierbarkeit und Verfügbarkeit der jeweiligen Push Technologien wurde außerdem mit Hilfe dieser App bewertet.
Die Vorteile und Nachteile im gegenseitigen Vergleich der Push Technologien haben gezeigt, dass lokale Push Lösungen unter den gegebenen Qualitätsanforderungen am besten im App Kontext geeignet sind. Der Vergleich und die Diskussion zur bestgeeigneten Push Lösung haben allgemeingültige Eigenschaften, Vor- und Nachteile der jeweiligen Push Technologien deutlich gemacht, so dass lokale Push Lösungen unter diesen Qualitätspunkten zur Umsetzung eines App-Benachrichtungsdienstes mit Push Notifications empfehlenswert sind
Enabling runtime flexibility in data-centric and data-driven process execution engines
Full text linkContemporary process management systems support users during the execution of predefined business processes. However, when unforeseen situations occur, which are not part of the process model serving as the template for process execution, contemporary technology is often unable to offer adequate user support. One solution to this problem is to allow for ad-hoc changes to process models, i.e., changes that may be applied on the fly to a running process instance. As opposed to the widespread activity-centric process modeling paradigm, for which the support of instance-specific ad-hoc changes is well researched, albeit not properly supported by most commercial process engines, there is no corresponding support for ad-hoc changes in other process support paradigms, such as artifact-centric or object-aware process management. This article presents concepts for supporting ad-hoc changes in data-centric and data-driven processes, and gives insights into the challenges to be tackled when implementing this kind of process flexibility in the PHILharmonicFlows process execution engine. We evaluated the concepts by implementing a proof-of-concept prototype and applying it to various scenarios. The development of advanced flexibility features is highly relevant for data-centric processes, as the research field is generally perceived as having low maturity compared to activity-centric processes
Teaching Vehicles to Anticipate: A Systematic Study on Probabilistic Behavior Prediction Using Large Data Sets
Full text linkBy observing their environment as well as other traffic participants, humans are enabled to drive road vehicles safely. Vehicle passengers, however, perceive a notable difference between non-experienced and experienced drivers. In particular, they may get the impression that the latter ones anticipate what will happen in the next few moments and consider these foresights in their driving behavior. To make the driving style of automated vehicles comparable to the one of human drivers with respect to comfort and perceived safety, the aforementioned anticipation skills need to become a built-in feature of self-driving vehicles. This article provides a systematic comparison of methods and strategies to generate this intention for self-driving cars using machine learning techniques. To implement and test these algorithms we use a large data set collected over more than 30,000 km of highway driving and containing approximately 40 000 real-world driving situations. We further show that it is possible to classify driving maneuvers upcoming within the next 5 s with an Area Under the ROC Curve (AUC) above 0.92 for all defined maneuver classes. This enables us to predict the lateral position with a prediction horizon of 5 s with a median lateral error of less than 0.21 m
eSano – An eHealth Platform for Internet- and Mobile-based Interventions
Full text linkThe prevention and treatment of mental disorders and chronic somatic diseases is a core challenge for health care systems of the 21th century. Mental- and behavioral health interventions provide the means for lowering the public health burden. However, structural deficits, reluctance to use existing services, perceived stigma and further personal and environmental reasons restrict the uptake of these evidence-based approaches. Internet- and mobile-based interventions (IMIs) might overcome some of the limitations of on-site interventions by providing an anonymous, scalable, time- and location-independent, yet evidence-based approach. In order to implement digital mental and behavioral health concepts across the life-span into practice, a technical solution to support the design, creation, and execution of IMIs is needed. However, there are various conceptual, technical as well as legal challenges to implementing a corresponding software solution in the healthcare domain. Therefore, the work at hand (1) identifies these challenges and derives a number of respective requirements, (2) introduces the eHealth platform eSano, a software project developed by an interdisciplinary team of computer scientists, psychologists, therapists, and other domain experts, with the aim to serve as a flexible basis for mental and behavioral research and health care, and (3) provides technical insights into the developed platform and its approach to address the aforementioned requirements
Virtual Reality as a tool for people on the autistic spectrum
No full textWith the technological progress over the course of the last years, Virtual Reality became accessible for the mainstream. Its high level of immersion enables the realization of authentic recreations of the real world combined with a physically safe environment. While the use of Virtual Reality in the context of therapies, including the domain of autistic spectrum disorders is well documented and evidenced, the current sparse supply of actual applications for people on the autistic spectrum indicates the necessity of further development. To approach this topic, previous findings about the usage of Virtual Reality in therapies, as well as technical aspects of this matter are collected and combined to eventually outline the concept of a new application, which focuses on atypical sensory processing, a key deficit witnessed by the majority of people with an autistic spectrum disorder. The core of this work is the implementation of a prototype in order to demonstrate the challenges and possibilities of Virtual Reality for this task. The achieved result can be considered the basis for further research and development with the goal in mind to improve the daily life of people on the autistic spectrum via Virtual Reality
Degree of freedom: Individualization of mHealth apps
No full textWith the results of this work, first implementations of different incentives should be found that convince users to use medical smartphone applications more often and at best, results in a higher correctness of the data. The incentives should be customizable for each user, without compromising the collected data. Besides the created incentives, the settings can lead to a simplified usability. The app can adapt to users and respond to both physical and mental preferences, which can counteract age-related problems, for example