A short paper on the whats and the hows of learning technology standardization
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This paper reports about preparatory work for future standardization that is carried out through an EU coordination and support action titled IM-SAFE. It focuses on applied digital technologies for monitoring and safety, including predictive maintenance of bridges and tunnels. Amidst the improved affordability of digitalization technologies and techniques, the biggest challenge in monitoring and maintenance of bridges and tunnels is no longer about collecting data as much as possible, but about obtaining and exploiting meaningful data throughout the lifecycle of the built assets. An effective and efficient data-driven approach is important to al-low both human experts and computers to make accurate diagnostics, predictions, and decisions. Further standardization is seen as an important part to reach that goal. The work in IM-SAFE related to ICT standardization focuses on the following topics: (1) the general requirements and preconditions for high quality and cost-effective acquisition, transmission, storage and processing of monitoring datasets to ensure the data is fully accessible and machine-interpretable; (2) the relations between the future standards in structural engineering with the open ICT standards for interoperability, especially on Internet of Things (IoT), Building Information Model (BIM), Geographical Information System (GIS), and Semantic Linked Data (LD); (3) a common design of IT platforms to manage monitoring and asset management data of transport infrastructures; (4) the ways to facilitate data analytics technologies, including AI, to be applied for monitoring and asset management of transport infrastructures, and to assess the added value of data-driven approach next to physics-based modelling. With regard to these topics, this paper reports the outcomes from the expert and stakeholder consultations that recently took place within the IM-SAFE pan-European Community of Practice.
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This study proposes a framework to measure touristification of consumption spaces, consisting of concentration of retail capital, business displacement and standardization of the consumption landscape. This framework is tested using business registration data and rent price estimates for consumption spaces in Amsterdam between 2005 and 2020. Touristification emerges from concentrations of retail capital and standardization, but occurs without causing significant business displacement. A cluster analysis identifies different variations of touristification. Besides the more typical cases these include nightlife areas, gentrifying consumption spaces and specialized retail areas. This suggests that local contingencies cause consumption spaces to respond differently to increasing tourism.
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Data is widely recognized as a potent catalyst for advancing healthcare effectiveness, increasing worker satisfaction, and mitigating healthcarecosts. The ongoing digital transformation within the healthcare sector promises to usher in a new era of flexible patient care, seamless inter-provider communication, and data-informed healthcare practices through the application of data science. However, more often than not data lacks interoperability across different healthcare institutions andare not readily available for analysis. This inability to share data leads to a higher administrative burden for healthcare providers and introduces risks when data is missing or when delays occur. Moreover, medical researchers face similar challenges in accessing medical data due to thedifficulty of extracting data from applications, a lack of standardization, and the required data transformations before it can be used for analysis. To address these complexities, a paradigm shift towards a data-centricapplication landscape is essential, where data serves as the bedrock of the healthcare infrastructure and is application agnostic.In short, a modern way to think about data in general is to go from an application driven landscape to a data driven landscape, which willallow for better interoperability and innovative healthcare solutions.
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Data is widely recognized as a potent catalyst for advancing healthcare effectiveness, increasing worker satisfaction, and mitigating healthcare costs. The ongoing digital transformation within the healthcare sector promises to usher in a new era of flexible patient care, seamless inter-provider communication, and data-informed healthcare practices through the application of data science. However, more often than not data lacks interoperability across different healthcare institutions and are not readily available for analysis. This inability to share data leads to a higher administrative burden for healthcare providers and introduces risks when data is missing or when delays occur. Moreover, medical researchers face similar challenges in accessing medical data due to thedifficulty of extracting data from applications, a lack of standardization, and the required data transformations before it can be used for analysis. To address these complexities, a paradigm shift towards a data-centric application landscape is essential, where data serves as the bedrock of the healthcare infrastructure and is application agnostic. In short, a modern way to think about data in general is to go from an application driven landscape to a data driven landscape, which will allow for better interoperability and innovative healthcare solutions.In the current project the research group Digital Transformation at Hanze University of Applied Sciences works together with industry partners to build an openEHR implementation for a Groningen-based mental healthcare provider.
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In December of 2004 the Directorate General for Research and Technological Development (DG RTD) of the European Commission (EC) set up a High-Level Expert Group to propose a series of measures to stimulate the reporting of Intellectual Capital in research intensive Small and Medium-Sized Enterprises (SMEs). The Expert Group has focused on enterprises that either perform Research and Development (R&D), or use the results of R&D to innovate and has also considered the implications for the specialist R&D units of larger enterprises, dedicated Research & Technology Organizations and Universities. In this report the Expert Group presents its findings, leading to six recommendations to stimulate the reporting of Intellectual Capital in SMEs by raising awareness, improving reporting competencies, promoting the use of IC Reporting and facilitating standardization.
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The growing sophistication, frequency and severity of cyberattacks targeting all sectors highlight their inevitability and the impossibility of completely protecting the integrity of critical computer systems. In this context, cyber-resilience offers an attractive alternative to the existing cybersecurity paradigm. We define cyber-resilience as the capacity to withstand, recover from and adapt to the external shocks caused by cyber-risks. This article seeks to provide a broader organizational understanding of cyber-resilience and the tensions associated with its implementation. We apply Weick's (1995) sensemaking framework to examine four foundational tensions of cyber-resilience: a definitional tension, an environmental tension, an internal tension, and a regulatory tension. We then document how these tensions are embedded in cyber-resilience practices at the preparatory, response and adaptive stages. We rely on qualitative data from a sample of 58 cybersecurity professionals to uncover these tensions and how they reverberate across cyber-resilience practices.
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Despite changing attitudes towards animal testing and current legislation to protect experimental animals, the rate of animal experiments seems to have changed little in recent years. On May 15–16, 2013, the In Vitro Testing Industrial Platform (IVTIP) held an open meeting to discuss the state of the art in alternative methods, how companies have, can, and will need to adapt and what drives and hinders regulatory acceptance and use. Several key messages arose from the meeting. First, industry and regulatory bodies should not wait for complete suites of alternative tests to become available, but should begin working with methods available right now (e.g., mining of existing animal data to direct future studies, implementation of alternative tests wherever scientifically valid rather than continuing to rely on animal tests) in non-animal and animal integrated strategies to reduce the numbers of animals tested. Sharing of information (communication), harmonization and standardization (coordination), commitment and collaboration are all required to improve the quality and speed of validation, acceptance, and implementation of tests. Finally, we consider how alternative methods can be used in research and development before formal implementation in regulations. Here we present the conclusions on what can be done already and suggest some solutions and strategies for the future.
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Clinical Decision Support Systems (CDSS) are increasingly developed for hospital nursing practice, yet their impact on decision-making, workflow efficiency, and patient outcomes remains complex. This rapid review synthesizes findings from 21 studies, highlighting both the benefits and challenges of CDSS implementation focused on three key areas. CDSS can enhance nursing decision-making by reducing variability and improving standardization, but there are concerns about system usability and the tendency to override recommendations. While CDSS improve workflow efficiency by prioritizing tasks, issues such as alert fatigue and poor interoperability with hospital systems hinder their potential. Patient outcomes benefit from CDSS-driven medication safety and risk prevention, yet adherence to recommendations varies among nurses. These findings underscore the need for user-centered CDSS that align with nursing values. Future research should explore long-term effectiveness, implementation strategies and best practices for integrating CDSS into nursing workflows.
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PURPOSE: In 2018, the SARCUS working group published a first article on the standardization of the use of ultrasound to assess muscle. Recommendations were made for patient positioning, system settings and components to be measured. Also, shortcomings in knowledge were mentioned. An important issue that still required standardization was the definition of anatomical landmarks for many muscles.METHODS: A systematic search was performed in Medline, SCOPUS and Web of Sciences looking for all articles describing the use of ultrasound in the assessment of muscle not described in the first recommendations, published from 01/01/2018 until 31/01/2020. All relevant terms used for older people, ultrasound and muscles were used.RESULTS: For 39 muscles, different approaches for ultrasound assessment were found that likely impact the values measured. Standardized anatomical landmarks and measuring points were proposed for all muscles/muscle groups. Besides the five already known muscle parameters (muscle thickness, cross-section area, pennation angle, fascicle length and echo-intensity), four new parameters are discussed (muscle volume, stiffness, contraction potential and microcirculation). The former SARCUS article recommendations are updated with this new information that includes new muscle groups.CONCLUSIONS: The emerging field of ultrasound assessment of muscle mass only highlights the need for a standardization of measurement technique. In this article, guidelines are updated and broadened to provide standardization instructions for a large number of muscles.
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