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Flexible runtime support of business processes under rolling planning horizons
No full textThis work has been motivated by the needs we discovered when analyzing real-world processes from the healthcare domain that have revealed high flexibility demands and complex temporal constraints. When trying to model these processes with existing languages, we learned that none of the latter was able to fully address these needs. This motivated us to design TConDec-R, a declarative process modeling language enabling the specification of complex temporal constraints. Enacting business processes based on declarative process models,however, introduces a high complexity due to the required optimization of objective functions, the handling of various temporal constraints, the concurrent execution of multiple process instances, the management of crossinstance constraints, and complex resource allocations. Consequently, advanced user support through optimized schedules is required when executing the instances of such models. In previous work, we suggested a method for generating an optimized enactment plan for a given set of process instances created from a TConDec-R model. However, this approach was not applicable to scenarios with uncertain demands in which the enactment of newly created process instances starts continuously over time, as in the considered healthcare scenarios. Here, the process instances to be planned within a specific timeframe cannot be considered in isolation from the ones planned for future timeframes. To be able to support such scenarios, this article significantly extends our previous work by generating optimized enactment plans under a rolling planning horizon. We evaluate the approach by applying it to a particularly challenging healthcare process scenario, i.e., the diagnostic procedures required for treating patients with ovarian carcinoma in a Woman Hospital. The application of the approach to this sophisticated
scenario allows avoiding constraint violations and effectively managing shared resources, which contributes to reduce the length of patient stays in the hospital
Clinical and Cost-Effectiveness of PSYCHOnlineTHERAPY: Study Protocol of a Multicenter Blended Outpatient Psychotherapy Cluster Randomized Controlled Trial for Patients With Depressive and Anxiety Disorders
Full text linkIntroduction: Internet- and mobile-based interventions (IMIs) and their integration into routine psychotherapy (i.e., blended therapy) can offer a means of complementing psychotherapy in a flexible and resource optimized way.
Objective: The present study will evaluate the non-inferiority, cost-effectiveness, and safety of two versions of integrated blended psychotherapy for depression and anxiety compared to standard cognitive behavioral therapy (CBT).
Methods: A three-armed multicenter cluster-randomized controlled non-inferiority trial will be conducted comparing two implementations of blended psychotherapy (PSYCHOnlineTHERAPYfix/flex) compared to CBT. Seventy-five outpatient psychotherapists with a CBT-license will be randomized in a 1:1:1 ratio. Each of them is asked to include 12 patients on average with depressive or anxiety disorders resulting in a total sample size of N = 900. All patients receive up to a maximum of 16 psychotherapy sessions, either as routine CBT or alternating with Online self-help sessions (fix: 8/8; flex: 0–16). Assessments will be conducted at patient study inclusion (pre-treatment) and 6, 12, 18, and 24 weeks and 12 months post-inclusion. The primary outcome is depression and anxiety severity at 18 weeks post-inclusion (post-treatment) using the Patient Health Questionnaire Anxiety and Depression Scale. Secondary outcomes are depression and anxiety remission, treatment response, health-related quality of life, patient satisfaction, working alliance, psychotherapy adherence, and patient safety. Additionally, several potential moderators and mediators including patient characteristics and attitudes toward the interventions will be examined, complemented by ecological day-to-day digital behavior variables via passive smartphone sensing as part of an integrated smart-sensing sub-study. Data-analysis will be performed on an intention-to-treat basis with additional per-protocol analyses. In addition, cost-effectiveness and cost-utility analyses will be conducted from a societal and a public health care perspective. Additionally, qualitative interviews on acceptance, feasibility, and optimization potential will be conducted and analyzed.
Discussion: PSYCHOnlineTHERAPY will provide evidence on blended psychotherapy in one of the largest ever conducted psychotherapy trials. If shown to be non-inferior and cost-effective, PSYCHOnlineTHERAPY has the potential to innovate psychotherapy in the near future by extending the ways of conducting psychotherapy. The rigorous health care services approach will facilitate a timely implementation of blended psychotherapy into standard care
Design and feasibility study for automatic testing of WCAG 2.1 criteria
No full textThis thesis focuses on the automatic testing of the WCAG 2.1 guidelines and their criteria and discusses the possibilities regarding guidelines with contextual criteria, as well as simpler criteria of the WCAG 2.1
Development of a Microservice-based Approach for Workflow-supported Data Collection
No full textSince smart devices like smartphones are increasingly present in daily life, there is great potential using them as a source for data collection. Other work shows for example that by utilizing smartphones combined with Mobile Crowdsensing (MCS) and Ecological Momentary Assessments (EMA) for data collection in a mHealth context, valuable data can be gathered which can provide new insights for the treatment of chronic disorders. Furthermore, using the gathered data, feedback can be generated for patients suffering from these disorders to help them get better control of their medical condition.
To enable these data collection procedures, a scalable and reliable backend is needed to handle a varying amount of users in different use cases. Therefore, the usage of a microservice architecture with a central orchestration system providing a RESTful interface has been suggested in previous work.
This thesis proposes such a distributed, microservice-based approach for data collection using BPMN workflows to model control and data flow between these services, so that they can be orchestrated by the open-source workflow engine Zeebe and monitored using respective workflow monitoring tools. With this approach, generic data collection procedures in various contexts gathering questionnaire and sensor data can be supported by providing a RESTful interface, enabling both frontend components to allow for participation on these kind of data collection platforms as well as other tools to retrieve gathered data and perform analysis functions on it, thus potentially revealing new insights in the respective domain.
A subset of the features considered in the proposed concept are subsequently implemented and discussed, using an existing frontend implementation as a guideline for the implemented features
Towards Measuring and Quantifying the Comprehensibility of Process Models - The Process Model Comprehension Framework
Full text linkProcess models constitute crucial artifacts in modern information systems and, hence, the proper comprehension of these models is of utmost importance in the utilization of such systems. Generally, process models are considered from two different perspectives: process modelers and readers. Both perspectives share similarities and differences in the comprehension of process models (e.g., diverse experiences when working with process models). The literature proposed many rules and guidelines to ensure a proper comprehension of process models for both perspectives. As a novel contribution in this context, this paper introduces the Process Model Comprehension Framework (PMCF) as a first step towards the measurement and quantification of the perspectives of process modelers and readers as well as the interaction of both regarding the comprehension of process models. Therefore, the PMCF describes an Evaluation Theory Tree based on the Communication Theory as well as the Conceptual Modeling Quality Framework and considers a total of 96 quality metrics in order to quantify process model comprehension. Furthermore, the PMCF was evaluated in a survey with 131 participants and has been implemented as well as applied successfully in a practical case study including 33 participants. To conclude, the PMCF allows for the identification of pitfalls and provides related information about how to assist process modelers as well as readers in order to foster and enable a proper comprehension of process models
Entwicklung eines Rahmenwerks zur Konzistenzsicherung in einem browserbasierten P2P-Netzwerk
No full textKonsensus-Algorithmen sind ein wichtiger Bestandteil vieler verteilter Anwendungen und kommen häufig bei verteilten Datenbanken und Blockchain zum Einsatz. Sie sorgen dafür, dass bei jedem Teilnehmer der selbe Zustand in der Anwendung vorherrscht und dass Zugriffe der Teilnehmer auf die Anwendung auf jedem Knoten in der selben, korrekten Reihenfolge ausgeführt werden. Obwohl die Zahl browserbasierter Anwendungen wie Progressive Web Apps steigt, ist Konsensus für den Browser bisher kein viel beachtetes Thema. Daher beschäftigt sich diese Arbeit mit der Realisierbarkeit von Konsensus für browserbasierte Anwendungen und deren Potential.
Die Bachelorarbeit bietet einen Überblick über den Konsensus-Algorithmus Raft und den Aufbau eines P2P-Netzwerks via WebRTC. Sie schafft eine Basis für die Entwicklung von verteilten Anwendungen, welche Konsensus über ein P2P-
Netzwerk benötigen und rein browserbasiert sind.
Ziel dieser Bachelorarbeit ist es, ein SDK zu entwickeln, welches Konsensus in einem browserbasierten P2P-Netzwerk ermöglicht und damit die Realisierbarkeit von Konsensus in einem solchen Netzwerk zu zeigen. Die für das Projekt benötigten Technologien, WebRTC und Raft, werden erklärt und die Vorgehensweise sowie Anforderungen an das SDK und dessen Konzeption dokumentiert
Checklist-based Support of Knowledge Workers in Robotic Process Automation Projects
Full text linkRobotic Process Automation (RPA) is the rule-based automation of business process tasks by software robots mimicking human interactions. RPA projects often fail or do not achieve the expected benefits due to a missing support of the humans developing the robots. In practice, such software robots are often developed and configured by knowledge workers without any IT background. These non-IT experts require appropriate development and configuration support. The aim of this paper is to provide a checklist-based support of knowledge workers in conducting RPA projects. After an initial design, which is based on interviews with knowledge workers, an exploratory RPA case
study in industry, and surveys among bot users, the checklist is improved in three iterations with comprehensive user feedback. The finally obtained checklist is evaluated in six RPA projects in industrial practice showing satisfying results. In particular, no project has failed and the expected full time equivalents savings, reduction of errors, and improvement of process speed have been achieved. Altogether, the checklist enables smooth process support of knowledge workers in RPA projects
Predicting the Time Until a Vehicle Changes the Lane Using LSTM-Based Recurrent Neural Networks
Full text linkTo plan safe and comfortable trajectories for automated vehicles on highways, accurate predictions of traffic situations are needed. So far, a lot of research effort has been spent on detecting lane change maneuvers rather than on estimating the point in time a lane change actually happens. In practice, however, this temporal information might be even more useful. This paper deals with the development of a system that accurately predicts the time to the next lane change of surrounding vehicles on highways using long short-term memory-based recurrent neural networks. An extensive evaluation based on a large real-world data set shows that our approach is able to make reliable predictions, even in the most challenging situations, with a root mean squared error around 0.7 seconds. Already 3.5 seconds prior to lane changes the predictions become highly accurate, showing a median error of less than 0.25 seconds. In summary, this article forms a fundamental step towards downstreamed highly accurate position predictions
Konzeption und Entwicklung eines iOS-Frameworks zur Selbstbestimmung der Tinnitusfrequenz von Tinnituspatienen
No full textIn Rahmen dieser Bachelorarbeit wurde ein iOS-Framework zur Selbstbestimmung der Tinnitusfrequenz von Tinnituspatienten konzipiert und entwickelt. In diesem Framework wird dem Nutzer mit Hilfe eines Messverfahrens die eigenständige Bestimmung der subjektiven Tinnitusfrequenz ermöglicht. Diese kann anschließend offline oder, bei vorhandener Registrierung, online gespeichert werden. Die online Speicherung der Ergebnisse inklusive Metadaten, ermöglicht nicht nur die Erforschung von Tinnitus, sondern auch auf den gesammelten Daten aufbauende Therapien. Die mit dem Framework erreichte Bestimmung der Tinnitusfrequenz stellt die Basis verschiedenster auditorischer Therapien dar
Augmented Reality als Unterstützung im Straßenverkehr bei vorliegender Autismus-Spektrum-Störung
No full textDiese Arbeit soll zunächst einen Überblick über die verschiedenen Formen der Autismus-Spektrum-Störung bieten und im weiteren Verlauf soll eine Anwendung für die Microsoft HoloLens entwickelt werden, die eine Hilfestellung für von der Störung betroffene im Straßenverkehr bietet. Zunächst sollen über eine Bilderkennung und die integrierte Kamera in der HoloLens, die einzelnen Objekte, welche auf dem auszuwertenden Bild zu sehen sind, klassifiziert werden. Der Fokus liegt hierbei besonders auf Fahrzeugen im Straßenverkehr. Auf entsprechende Gefahrensituationen soll hingewiesen werden und bei einem Verlust des Fokus soll dieser dann wieder auf das entsprechende Objekt geleitet werden. Die Alltagstauglichkeit und der effektive Nutzen der Anwendung soll dann in einem Versuch mit Probanden, die von einer Autismus-Spektrum-Störung betroffen sind, validiert werden