Zoekresultaten

Advancing industry through design

Design educators and industry partners are critical knowledge managers and co-drivers of change, and design graduate and post-graduate students can act as catalysts for new ideas, energy, and perspectives. In this article, we will explore how design advances industry development through the lens of a longitudinal inquiry into activities carried out as part of a Dutch design faculty-industry collaboration. We analyze seventy-five (75) Master of Science (MSc) thesis outcomes and seven (7) Doctorate (PhD) thesis outcomes (five in progress) to identify ways that design activities have influenced advances in the Dutch aviation industry over time. Based on these findings, we then introduce an Industry Design Framework, which organizes the industry/design relationship as a three-layered system. This novel approach to engaging industry in design research and design education has immediate practical value and theoretical significance, both in the present and for future research. https://doi.org/10.1016/j.sheji.2019.07.003 LinkedIn: https://www.linkedin.com/in/christine-de-lille-8039372/

Guideline for user interface design of explainable AI

This guide was developed for designers and developers of AI systems, with the goal of ensuring that these systems are sufficiently explainable. Sufficient here means that it meets the legal requirements from AI Act and GDPR and that users can use the system properly. Explainability of decisions is an important requirement in many systems and even an important principle for AI systems [HLEG19]. In many AI systems, explainability is not self-evident. AI researchers expect that the challenge of making AI explainable will only increase. For one thing, this comes from the applications: AI will be used more and more often, for larger and more sensitive decisions. On the other hand, organizations are making better and better models, for example, by using more different inputs. With more complex AI models, it is often less clear how a decision was made. Organizations that will deploy AI must take into account users' need for explanations. Systems that use AI should be designed to provide the user with appropriate explanations. In this guide, we first explain the legal requirements for explainability of AI systems. These come from the GDPR and the AI Act. Next, we explain how AI is used in the financial sector and elaborate on one problem in detail. For this problem, we then show how the user interface can be modified to make the AI explainable. These designs serve as prototypical examples that can be adapted to new problems. This guidance is based on explainability of AI systems for the financial sector. However, the advice can also be used in other sectors.

Public Private Learning Communities

Decision making on (dis)continuation of long-term treatment in mental health services is an interpersonal negotiationrather than an objective process

Background: Research into termination of long-term psychosocial treatment of mental disorders is scarce. Yearly 25% of people in Dutch mental health services receive long-term treatment. They account for many people, contacts, and costs. Although relevant in different health care systems, (dis)continuation is particularly problematic under universal health care coverage when secondary services lack a fixed (financially determined) endpoint. Substantial, unaccounted, differences in treatment duration exist between services. Understanding of underlying decisional processes may result in improved decision making, efficient allocation of scarce resources, and more personalized treatment.

A Study of Tradeoffs in Airport Coordinated Surface Operations

Airports represent the major bottleneck in the air traffic management system with increasing traffic density. Enhanced levels of automation and coordination of surface operations are imperative to reduce congestion and to improve efficiency. This paper addresses the problem of comparing different control strategies on the airport surface to investigate their impacts and benefits. We propose an optimization approach to solve in a unified manner the coordinated surface operations problem on network models of an actual hub airport. Controlled pushback time, taxi reroutes and controlled holding time (waiting time at runway threshold for departures and time spent in runway crossing queues for arrivals) are considered as decisions to optimize the ground movement problem. Three major aspects are discussed:1) benefits of incorporating taxi reroutes on the airport performance metrics; 2) priority of arrivals and departures in runway crossings; 3) tradeoffs between controlled pushback and controlled holding time for departures. A preliminary study case is conducted in a model based on operations of Paris Charles De-Gaulle airport under the most frequently used configuration. Airport is modeled using a node-link network structure. Alternate taxi routes are constructed based on surface surveillance records with respect to current procedural factors. A representative peak-hour traffic scenario is generated using historical data. The effectiveness of the proposed optimization methods is investigated.

Exploring the barriers, facilitators and needs to use patient outcomes in district nursing care: A multi-method qualitative study

Aim and objectives: To provide an in-depth insight into the barriers, facilitators and needs of district nurses and nurse assistants on using patient outcomes in district nursing care. Background: As healthcare demands grow, particularly in district nursing, there is a significant need to understand how to systematically measure and improve patient outcomes in this setting. Further investigation is needed to identify the barriers and facilitators for effective implementation. Design: A multi-method qualitative study. Methods: Open-ended questions of a survey study (N = 132) were supplemented with in-depth online focus group interviews involving district nurses and nurse assistants (N = 26) in the Netherlands. Data were analysed using thematic analysis. Results: Different barriers, facilitators and needs were identified and compiled into 16 preconditions for using outcomes in district nursing care. These preconditions were summarised into six overarching themes: follow the steps of a learning healthcare system; provide patient-centred care; promote the professional's autonomy, attitude, knowledge and skills; enhance shared responsibility and collaborations within and outside organisational boundaries; prioritise and invest in the use of outcomes; and boost the unity and appreciation for district nursing care. Conclusions: The preconditions identified in this study are crucial for nurses, care providers, policymakers and payers in implementing the use of patient outcomes in district nursing practice. Further exploration of appropriate strategies is necessary for a successful implementation. Relevance to clinical practice: This study represents a significant step towards implementing the use of patient outcomes in district nursing care. While most research has focused on hospitals and general practitioner settings, this study focuses on the needs for district nursing care. By identifying 16 key preconditions across themes such as patient-centred care, professional autonomy and unity, the findings offer valuable guidance for integrating a learning healthcare system that prioritises the measurement and continuous improvement of patient outcomes in district nursing.