412 research outputs found
A BIM - GIS Integrated Information Model Using Semantic Web and RDF Graph Databases
In recent years, 3D virtual indoor and outdoor urban modelling has become an essential geospatial information framework for civil and engineering applications such as emergency response, evacuation planning, and facility management. Building multi-sourced and multi-scale 3D urban models are in high demand among architects, engineers, and construction professionals to achieve these tasks and provide relevant information to decision support systems. Spatial modelling technologies such as Building Information Modelling (BIM) and Geographical Information Systems (GIS) are frequently used to meet such high demands. However, sharing data and information between these two domains is still challenging. At the same time, the semantic or syntactic strategies for inter-communication between BIM and GIS do not fully provide rich semantic and geometric information exchange of BIM into GIS or vice-versa. This research study proposes a novel approach for integrating BIM and GIS using semantic web technologies and Resources Description Framework (RDF) graph databases. The suggested solution's originality and novelty come from combining the advantages of integrating BIM and GIS models into a semantically unified data model using a semantic framework and ontology engineering approaches. The new model will be named Integrated Geospatial Information Model (IGIM). It is constructed through three stages. The first stage requires BIMRDF and GISRDF graphs generation from BIM and GIS datasets. Then graph integration from BIM and GIS semantic models creates IGIMRDF. Lastly, the information from IGIMRDF unified graph is filtered using a graph query language and graph data analytics tools. The linkage between BIMRDF and GISRDF is completed through SPARQL endpoints defined by queries using elements and entity classes with similar or complementary information from properties, relationships, and geometries from an ontology-matching process during model construction. The resulting model (or sub-model) can be managed in a graph database system and used in the backend as a data-tier serving web services feeding a front-tier domain-oriented application. A case study was designed, developed, and tested using the semantic integrated information model for validating the newly proposed solution, architecture, and performance
Measuring the impact of COVID-19 on hospital care pathways
Care pathways in hospitals around the world reported significant disruption during the recent COVID-19 pandemic but measuring the actual impact is more problematic. Process mining can be useful for hospital management to measure the conformance of real-life care to what might be considered normal operations. In this study, we aim to demonstrate that process mining can be used to investigate process changes associated with complex disruptive events. We studied perturbations to accident and emergency (A &E) and maternity pathways in a UK public hospital during the COVID-19 pandemic. Co-incidentally the hospital had implemented a Command Centre approach for patient-flow management affording an opportunity to study both the planned improvement and the disruption due to the pandemic. Our study proposes and demonstrates a method for measuring and investigating the impact of such planned and unplanned disruptions affecting hospital care pathways. We found that during the pandemic, both A &E and maternity pathways had measurable reductions in the mean length of stay and a measurable drop in the percentage of pathways conforming to normative models. There were no distinctive patterns of monthly mean values of length of stay nor conformance throughout the phases of the installation of the hospital’s new Command Centre approach. Due to a deficit in the available A &E data, the findings for A &E pathways could not be interpreted
The mad manifesto
The “mad manifesto” project is a multidisciplinary mediated investigation into the circumstances by which mad (mentally ill, neurodivergent) or disabled (disclosed, undisclosed) students faced far more precarious circumstances with inadequate support models while attending North American universities during the pandemic teaching era (2020-2023).
Using a combination of “emergency remote teaching” archival materials such as national student datasets, universal design for learning (UDL) training models, digital classroom teaching experiments, university budgetary releases, educational technology coursewares, and lived experience expertise, this dissertation carefully retells the story of “accessibility” as it transpired in disabling classroom containers trapped within intentionally underprepared crisis superstructures. Using rhetorical models derived from critical disability studies, mad studies, social work practice, and health humanities, it then suggests radically collaborative UDL teaching practices that may better pre-empt the dynamic needs of dis/abled students whose needs remain direly underserviced.
The manifesto leaves the reader with discrete calls to action that foster more critical performances of intersectionally inclusive UDL classrooms for North American mad students, which it calls “mad-positive” facilitation techniques:
1. Seek to untie the bond that regards the digital divide and access as synonyms.
2. UDL practice requires an environment shift that prioritizes change potential.
3. Advocate against the usage of UDL as a for-all keystone of accessibility.
4. Refuse or reduce the use of technologies whose primary mandate is dataveillance.
5. Remind students and allies that university space is a non-neutral affective container.
6. Operationalize the tracking of student suicides on your home campus.
7. Seek out physical & affectual ways that your campus is harming social capital potential.
8. Revise policies and practices that are ability-adjacent imaginings of access.
9. Eliminate sanist and neuroscientific languaging from how you speak about students.
10. Vigilantly interrogate how “normal” and “belong” are socially constructed.
11. Treat lived experience expertise as a gift, not a resource to mine and to spend.
12. Create non-psychiatric routes of receiving accommodation requests in your classroom.
13. Seek out uncomfortable stories of mad exclusion and consider carceral logic’s role in it.
14. Center madness in inclusive methodologies designed to explicitly resist carceral logics.
15. Create counteraffectual classrooms that anticipate and interrupt kairotic spatial power.
16. Strive to refuse comfort and immediate intelligibility as mandatory classroom presences.
17. Create pathways that empower cozy space understandings of classroom practice.
18. Vector students wherever possible as dynamic ability constellations in assessment
LIPIcs, Volume 261, ICALP 2023, Complete Volume
LIPIcs, Volume 261, ICALP 2023, Complete Volum
Software doping – Theory and detection
Software is doped if it contains a hidden functionality that is intentionally included by the manufacturer and is not in the interest of the user or society. This thesis complements this informal definition by a set of formal cleanness definitions that characterise the absence of software doping. These definitions reflect common expectations on clean software behaviour and are applicable to many types of software, from printers to cars to discriminatory AI systems. We use these definitions to propose white-box and black-box analysis techniques to detect software doping. In particular, we present a provably correct, model-based testing algorithm that is intertwined with a probabilistic-falsification-based test input selection technique. We identify and explain how to overcome the challenges that are specific to real-world software doping tests and analyses. The most prominent example of software doping in recent years is the Diesel Emissions Scandal. We demonstrate the strength of our cleanness definitions and analysis techniques by applying them to emission cleaning systems of diesel cars. All our car related research is unified in a Car Data Platform. The mobile app LolaDrives is one building block of this platform; it supports conducting real-driving emissions tests and provides feedback to the user in how far a trip satisfies driving conditions that are defined by official regulations.Software ist gedopt wenn sie eine versteckte Funktionalität enthält, die vom Hersteller beabsichtigt ist und deren Existenz nicht im Interesse des Benutzers oder der Gesellschaft ist. Die vorliegende Arbeit ergänzt diese nicht formale Definition um eine Menge von Cleanness-Definitionen, die die Abwesenheit von Software Doping charakterisieren. Diese Definitionen spiegeln allgemeine Erwartungen an "sauberes" Softwareverhalten wider und sie sind auf viele Arten von Software anwendbar, vom Drucker über Autos bis hin zu diskriminierenden KI-Systemen. Wir verwenden diese Definitionen um sowohl white-box, als auch black-box Analyseverfahren zur Verfügung zu stellen, die in der Lage sind Software Doping zu erkennen. Insbesondere stellen wir einen korrekt bewiesenen Algorithmus für modellbasierte Tests vor, der eng verflochten ist mit einer Test-Input-Generierung basierend auf einer Probabilistic-Falsification-Technik. Wir identifizieren Hürden hinsichtlich Software-Doping-Tests in der echten Welt und erklären, wie diese bewältigt werden können. Das bekannteste Beispiel für Software Doping in den letzten Jahren ist der Diesel-Abgasskandal. Wir demonstrieren die Fähigkeiten unserer Cleanness-Definitionen und Analyseverfahren, indem wir diese auf Abgasreinigungssystem von Dieselfahrzeugen anwenden. Unsere gesamte auto-basierte Forschung kommt in der Car Data Platform zusammen. Die mobile App LolaDrives ist eine Kernkomponente dieser Plattform; sie unterstützt bei der Durchführung von Abgasmessungen auf der Straße und gibt dem Fahrer Feedback inwiefern eine Fahrt den offiziellen Anforderungen der EU-Norm der Real-Driving Emissions entspricht
Managing healthcare transformation towards P5 medicine (Published in Frontiers in Medicine)
Health and social care systems around the world are facing radical organizational, methodological and technological paradigm changes to meet the requirements for improving quality and safety of care as well as efficiency and efficacy of care processes. In this they’re trying to manage the challenges of ongoing demographic changes towards aging, multi-diseased societies, development of human resources, a health and social services consumerism, medical and biomedical progress, and exploding costs for health-related R&D as well as health services delivery. Furthermore, they intend to achieve sustainability of global health systems by transforming them towards intelligent, adaptive and proactive systems focusing on health and wellness with optimized quality and safety outcomes.
The outcome is a transformed health and wellness ecosystem combining the approaches of translational medicine, 5P medicine (personalized, preventive, predictive, participative precision medicine) and digital health towards ubiquitous personalized health services realized independent of time and location. It considers individual health status, conditions, genetic and genomic dispositions in personal social, occupational, environmental and behavioural context, thus turning health and social care from reactive to proactive. This requires the advancement communication and cooperation among the business actors from different domains (disciplines) with different methodologies, terminologies/ontologies, education, skills and experiences from data level (data sharing) to concept/knowledge level (knowledge sharing). The challenge here is the understanding and the formal as well as consistent representation of the world of sciences and practices, i.e. of multidisciplinary and dynamic systems in variable context, for enabling mapping between the different disciplines, methodologies, perspectives, intentions, languages, etc. Based on a framework for dynamically, use-case-specifically and context aware representing multi-domain ecosystems including their development process, systems, models and artefacts can be consistently represented, harmonized and integrated. The response to that problem is the formal representation of health and social care ecosystems through an system-oriented, architecture-centric, ontology-based and policy-driven model and framework, addressing all domains and development process views contributing to the system and context in question.
Accordingly, this Research Topic would like to address this change towards 5P medicine. Specifically, areas of interest include, but are not limited:
• A multidisciplinary approach to the transformation of health and social systems
• Success factors for sustainable P5 ecosystems
• AI and robotics in transformed health ecosystems
• Transformed health ecosystems challenges for security, privacy and trust
• Modelling digital health systems
• Ethical challenges of personalized digital health
• Knowledge representation and management of transformed health ecosystems
Table of Contents:
04 Editorial: Managing healthcare transformation towards P5
medicine
Bernd Blobel and Dipak Kalra
06 Transformation of Health and Social Care Systems—An
Interdisciplinary Approach Toward a Foundational
Architecture
Bernd Blobel, Frank Oemig, Pekka Ruotsalainen and Diego M. Lopez
26 Transformed Health Ecosystems—Challenges for Security,
Privacy, and Trust
Pekka Ruotsalainen and Bernd Blobel
36 Success Factors for Scaling Up the Adoption of Digital
Therapeutics Towards the Realization of P5 Medicine
Alexandra Prodan, Lucas Deimel, Johannes Ahlqvist, Strahil Birov,
Rainer Thiel, Meeri Toivanen, Zoi Kolitsi and Dipak Kalra
49 EU-Funded Telemedicine Projects – Assessment of, and
Lessons Learned From, in the Light of the SARS-CoV-2
Pandemic
Laura Paleari, Virginia Malini, Gabriella Paoli, Stefano Scillieri,
Claudia Bighin, Bernd Blobel and Mauro Giacomini
60 A Review of Artificial Intelligence and Robotics in
Transformed Health Ecosystems
Kerstin Denecke and Claude R. Baudoin
73 Modeling digital health systems to foster interoperability
Frank Oemig and Bernd Blobel
89 Challenges and solutions for transforming health ecosystems
in low- and middle-income countries through artificial
intelligence
Diego M. LĂłpez, Carolina Rico-Olarte, Bernd Blobel and Carol Hullin
111 Linguistic and ontological challenges of multiple domains
contributing to transformed health ecosystems
Markus Kreuzthaler, Mathias Brochhausen, Cilia Zayas, Bernd Blobel
and Stefan Schulz
126 The ethical challenges of personalized digital health
Els Maeckelberghe, Kinga Zdunek, Sara Marceglia, Bobbie Farsides
and Michael Rigb
Lessons from Formally Verified Deployed Software Systems (Extended version)
The technology of formal software verification has made spectacular advances,
but how much does it actually benefit the development of practical software?
Considerable disagreement remains about the practicality of building systems
with mechanically-checked proofs of correctness. Is this prospect confined to a
few expensive, life-critical projects, or can the idea be applied to a wide
segment of the software industry?
To help answer this question, the present survey examines a range of
projects, in various application areas, that have produced formally verified
systems and deployed them for actual use. It considers the technologies used,
the form of verification applied, the results obtained, and the lessons that
can be drawn for the software industry at large and its ability to benefit from
formal verification techniques and tools.
Note: a short version of this paper is also available, covering in detail
only a subset of the considered systems. The present version is intended for
full reference.Comment: arXiv admin note: text overlap with arXiv:1211.6186 by other author
Francis Marion University catalog 2023-24
Francis Marion University annually publishes a catalog with information about the university, student life, undergraduate and graduate academic programs, and faculty and staff listings
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