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Context: Nowadays, companies are challenged by increasing market dynamics, rapid changes and disruptive participants entering the market. To survive in such an environment, companies must be able to quickly discover product ideas that meet the needs of both customers and the company and deliver these products to customers. Dual-track agile is a new type of agile development that combines product discovery and delivery activities in parallel, iterative, and cyclical ways. At present, many companies have difficulties in finding and establishing suitable approaches for implementing dual-track agile in their business context.
Objective: In order to gain a better understanding of how product discovery and product delivery can interact with each other and how this interaction can be implemented in practice, this paper aims to identify suitable approaches to dual-track agile.
Method: We conducted a grey literature review (GLR) according to the guidelines to Garousi et al.
Results: Several approaches that support the integration of product discovery with product delivery were identified. This paper presents a selection of these approaches, i.e., the Discovery-Delivery Cycle model, Now-Next-Later Product Roadmaps, Lean Sprints, Product Kata, and Dual-Track Scrum. The approaches differ in their granularity but are similar in their underlying rationales. All approaches aim to ensure that only validated ideas turn into products and thus promise to lead to products that are better received by their users.
Selecting a suitable development method for a specific project context is one of the most challenging activities in process design. To extend the so far statistical construction of hybrid development methods, we analyze 829 data points to investigate which context factors influence the choice of methods or practices. Using exploratory factor analysis, we derive five base clusters consisting of up to 10 methods. Logistic regression analysis then reveals which context factors have an influence on the integration of methods from these clusters in the development process. Our results indicate that only a few context factors including project/product size and target application domain significantly influence the choice. This summary refers to the paper “Determining Context Factors for Hybrid Development Methods with Trained Models”. This paper was published in the proceedings of the International Conference on Software and System Process in 2020.
Der Masterstudiengang Human-Centered Computing der Hochschule Reutlingen ist geprägt durch die Zusammenarbeit von Mensch und Computer. Eine wichtige Rolle an der Schnittstelle spielt die Sensorik, die der diesjährigen Konferenz Informatics Inside das Motto „perceive(it)“ verleiht. Dabei hebt das Wortspiel „it“ für die Informationstechnologie und die englische Übersetzung des Personalpronomens „es“ die Dualität der Wahrnehmung der Informationstechnologie durch den Menschen und der Realität durch den Computer hervor. Das Spannungsfeld zwischen künstlichen Sinneserweiterungen und der intelligenten Verarbeitung von Sensordaten ermöglicht unzählige Anwendungen für digitale Medien, virtuelle Welten, realitätsnahe Simulationen, computergestützte Arbeitsprozesse sowie intelligente Assistenzsysteme in der Produktion, im Haushalt, in der Medizin und in der Mobilität. Meine Aufmerksamkeit gilt hierbei der praxisnahen Forschung als Motor für diesen technischen Fortschritt.
Unternehmen wenden insbesondere bei IT-nahen Projekten seit einigen Jahren auch im Controlling verstärkt ein agiles Vorgehen an. Erfahrungen zeigen jedoch, dass dies nicht bei allen Projekten in jedem Unternehmen funktioniert. Hybride Ansätze, die agile mit klassischen Projekt-Management-Methoden verbinden, bieten eine Lösung.
The situation in the markets is changing rapidly and competition in the business sector is increasing rapidly. As a result, corporate marketing decisions are based on creating greater value for the consumer, which creates competitiveness and provides an advantage in competing for future customer loyalty. The purpose of this study is to determine whether there is a link between marketing communication tools and consumer perceived value in pursuit of consumer loyalty. Qualitative (observational research) and quantitative (a questionnaire survey) research methods were used to investigate the problem empirically. The observational research elucidated the value provided to the consumer by the research objects through marketing communication tools, supplementing the key questions for the quantitative study. Correlation and regression analysis were used in the study, with the results showing a statistically significant relationship between marketing communication tools and consumer perceived value in terms of user loyalty. It has also been determined that the greatest and strongest relationship in consumer value creation through marketing communication tools is the appropriate, mutually coordinated and complementary use of a package of marketing communication tools to achieve synergies that create the preconditions for increasing consumer loyalty in a competitive market.
Access to clinical information during interventions is an important aspect to support the surgeon and his team in the OR. The OR-Pad research project aims at displaying clinically relevant information close to the patient during surgery. With the OR-Pad system, the surgeon shall be able to access case-specific information, displayed on a sterile-packaged, portable display device. Therefore, information shall be prepared before surgery and also be available afterwards. The project follows an user-centered design process. Within the third iteration, the interaction concept was finalized, resulting in an application that can be used in two modes, mobile and intraoperative, to support the surgeon before/after and during surgery, respectively. By supporting the surgeon perioperatively, it is expected to improve the information situation in the OR and thereby the quality of surgical results. Based on this concept, the system architecture was designed in detail, using a client-server architecture. Components, communication interfaces, exchanged data, and intended standards for data exchange of the OR-Pad system including connecting systems were conceived. Expert interviews by using a clickable prototype were conducted to evaluate the concepts.
The paper explains a workflow to simulate the food energy water (FEW) nexus for an urban district combining various data sources like 3D city models, particularly the City Geography Markup Language (CityGML) data model from the Open Geospatial Consortium, Open StreetMap and Census data. A long term vision is to extend the CityGML data model by developing a FEW Application Domain Extension (FEW ADE) to support future FEW simulation workflows such as the one explained in this paper. Together with the mentioned simulation workflow, this paper also identifies some necessary FEW related parameters for the future development of a FEW ADE. Furthermore, relevant key performance indicators are investigated, and the relevant datasets necessary to calculate these indicators are studied. Finally, different calculations are performed for the downtown borough Ville-Marie in the city of Montréal (Canada) for the domains of food waste (FW) and wastewater (WW) generation. For this study, a workflow is developed to calculate the energy generation from anaerobic digestion of FW and WW. In the first step, the data collection and preparation was done. Here relevant data for georeferencing, data for model set-up, and data for creating the required usage libraries, like food waste and wastewater generation per person, were collected. The next step was the data integration and calculation of the relevant parameters, and lastly, the results were visualized for analysis purposes. As a use case to support such calculations, the CityGML level of detail two model of Montréal is enriched with information such as building functions and building usages from OpenStreetMap. The calculation of the total residents based on the CityGML model as the main input for Ville-Marie results in a population of 72,606. The statistical value for 2016 was 89,170, which corresponds to a deviation of 15.3%. The energy recovery potential of FW is about 24,024 GJ/year, and that of wastewater is about 1,629 GJ/year, adding up to 25,653 GJ/year. Relating values to the calculated number of inhabitants in Ville-Marie results in 330.9 kWh/year for FW and 22.4 kWh/year for wastewater, respectively.
Towards Automated Surgical Documentation using automatically generated checklists from BPMN models
(2021)
The documentation of surgeries is usually created from memory only after the operation, which is an additional effort for the surgeon and afflicted with the possibility of imprecisely, shortend reports. The display of process steps in the form of checklists and the automatic creation of surgical documentation from the completed process steps could serve as a reminder, standardize the surgical procedure and save time for the surgeon. Based on two works from Reutlingen University, which implemented the creation of dynamic checklists from Business Process Modelling Notation (BPMN) models and the storage of times at which a process step was completed, a prototype was developed for an android tablet, to expand the dynamic checklists by functions such as uploading photos and files, manual user entries, the interception of foreseeable deviations from the normal course of operations and the automatic creation of OR documentation.
Purpose
Computerized medical imaging processing assists neurosurgeons to localize tumours precisely. It plays a key role in recent image-guided neurosurgery. Hence, we developed a new open-source toolkit, namely Slicer-DeepSeg, for efficient and automatic brain tumour segmentation based on deep learning methodologies for aiding clinical brain research.
Methods
Our developed toolkit consists of three main components. First, Slicer-DeepSeg extends the 3D Slicer application and thus provides support for multiple data input/ output data formats and 3D visualization libraries. Second, Slicer core modules offer powerful image processing and analysis utilities. Third, the Slicer-DeepSeg extension provides a customized GUI for brain tumour segmentation using deep learning-based methods.
Results
The developed Slicer-DeepSeg was validated using a public dataset of high-grade glioma patients. The results showed that our proposed platform’s performance considerably outperforms other 3D Slicer cloud-based approaches.
Conclusions
Developed Slicer-DeepSeg allows the development of novel AI-assisted medical applications in neurosurgery. Moreover, it can enhance the outcomes of computer-aided diagnosis of brain tumours. Open-source Slicer-DeepSeg is available at github.com/razeineldin/Slicer-DeepSeg.
Die Bereitstellung klinischer Informationen im Operationssaal ist ein wichtiger Aspekt zur Unterstützung des chirurgischen Teams. Die roboter-assistierte Ösophagusresektion ist ein besonders komplexer Eingriff, der Potenzial zur workflowbasierten Unterstützung bietet. Wir präsentieren erste Ergebnisse der Entwicklung eines Checklisten-Tools mit der zugrundeliegenden Modellierung des chirurgischen Workflows und Informationsbedarf der Chirurgen. Das Checklisten-Tool zeigt hierfür die durchzuführenden Schritte chronologisch an und stellt zusätzliche Informationen kontextadaptiert bereit. Eine automatische Dokumentation von Start- und Endzeiten einzelner OP-Phasen und Schritte soll zukünftige Prozessanalysen der Operation ermöglichen.