Stephan Jüngling

ORCID: 0000-0002-2969-7257
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About
Contact & Profiles
Research Areas
  • Digital Transformation in Industry
  • Software Engineering Techniques and Practices
  • Big Data and Business Intelligence
  • Machine Learning in Healthcare
  • Software Engineering Research
  • Service-Oriented Architecture and Web Services
  • Smart Cities and Technologies
  • Educational Assessment and Pedagogy
  • Infrastructure Maintenance and Monitoring
  • Digital Innovation in Industries
  • Hand Gesture Recognition Systems
  • Advanced Database Systems and Queries
  • Scheduling and Optimization Algorithms
  • Teaching and Learning Programming
  • Online Learning and Analytics
  • Explainable Artificial Intelligence (XAI)
  • University-Industry-Government Innovation Models
  • Robotics and Automated Systems
  • Green IT and Sustainability
  • AI-based Problem Solving and Planning
  • Human Mobility and Location-Based Analysis
  • Spaceflight effects on biology
  • Semantic Web and Ontologies
  • Model-Driven Software Engineering Techniques
  • Business Process Modeling and Analysis

FHNW University of Applied Sciences and Arts
2015-2024

The Swiss Federal Administration uses for its IT projects primarily the project management method HERMES 5, which has originally a sequential approach. With introduction of agile scenario 'customized application (agile)' Steering Unit answered on increasing demand software development with SCRUM. 5 and SCRUM are different methods there general as well topic-specific challenges involved in combining them. focus this research is requirements engineering discipline investigates how two can be...

10.1109/es.2015.17 article EN 2015-10-01

There are quite some machine learning (ML) models, frameworks, AI-based services or products from different IT solution providers available, which can be used as building blocks to embed and use in architectures of companies. However, the path initial prototypical proof concept solutions until deployment proven systems into operational environment remains a major challenge. The potential software components using ML knowledge engineering (KE) is huge majority small medium enterprises still...

10.3390/app12126073 article EN cc-by Applied Sciences 2022-06-15

In this paper, we compare two projects from the cities of Basel and Shenzhen, which are transforming – or in case Shenzhen already has their public transportation fossil-fuelled to electric vehicles (EVs) only. so doing, derive different processes that could be reused as templates for many other both Switzerland, China elsewhere. Moreover, address far-end goal actually reaching Sustainable Development Goals (SDGs) within cities, propose vision a sharable platform Smart City Brain will allow...

10.29007/zrbr article EN EPiC series in computing 2023-05-26

Background The use of smartphone apps in cancer patients undergoing systemic treatment can promote the early detection symptoms and therapy side effects may be supported by machine learning (ML) for timely adaptation therapies reduction adverse events unplanned admissions. Objective We aimed to create an Early Warning System (EWS) predict situations where supportive interventions become necessary prevent visits. For this, dynamically collected standardized electronic patient reported outcome...

10.3389/fdgth.2024.1443987 article EN cc-by Frontiers in Digital Health 2024-08-14

In autumn 2014 the Bachelor of Science programme "Business Information Technology (BSc BIT)" was launched. BIT is about application information technology in business with focus on building systems. Since start it can be observed that a considerable number students face difficulties modules related to programming and mathematics at beginning study. order help potential applicants understand kind competencies abstract thinking are needed for BSc ahead start, web based self-assessment test...

10.20319/pijtel.2018.22.149169 article EN cc-by-nc PUPIL International Journal of Teaching Education and Learning 2018-08-28

<sec> <title>BACKGROUND</title> Recently the use of smartphone apps has been implemented in clinical trials with cancer patients undergoing systemic treatment. This approach demonstrated feasibility those early detection symptoms and therapy side effects. Early positive effects (a) enabling timely adaption current therapies (b) reducing number acute admissions. </sec> <title>OBJECTIVE</title> study aimed to create an Warning System (EWS) for improvement digital monitoring patients. The...

10.2196/preprints.52556 preprint EN 2023-09-12
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