Abstract Healthcare organizations operate within a network of governments, insurers, inspection services and other healthcare organizations to provide clients with the best possible care. The parties involved must collaborate and are accountable to each other for the care provided. This has led to a diversity of administrative processes that are supported by a multi-system landscape, resulting in administrative burdens among healthcare professionals. Management methods, such as Enterprise Architecture (EA), should help to develop and manage such landscapes, but they are systematic, while the network of healthcare parties is dynamic. The aim of this research is therefore to develop an EA framework that fits the dynamics of network organizations (such as long-term healthcare). This research proposal outlines the practical and scientific relevance of this research and the proposed method. The current status and next steps are also described.
From the article: Abstract: An overview of neural network architectures is presented. Some of these architectures have been created in recent years, whereas others originate from many decades ago. Apart from providing a practical tool for comparing deep learning models, the Neural Network Zoo also uncovers a taxonomy of network architectures, their chronology, and traces back lineages and inspirations for these neural information processing systems.
Onderzoeksplatform ‘Connected Learning: ’Al ruim vijftien jaar houdt De Haagse Hogeschool zich bezig met onderzoek als deel van haar missie. Terwijl onderwijs vaak geworteld is in monodisciplinaire vakgebieden, kan met onderzoek wat makkelijker gekeken worden naar domeinen in de samenleving (zorg, veiligheid, ondernemen, etc.) waarin complexe problematiek steeds vaker wél dan niet een multidisciplinaire aanpak vereist. Bijna niemand werkt nog alleen of met alleen vakgenoten aan problemen of uitdagingen. En die veranderende beroepspraktijk is bij uitstek het domein van het hoger beroepsonderwijs. Daar leiden we voor op. Het onderzoeken van en experimenteren met nieuwe uitdagingen in de praktijk verbindt ons sterker met de samenleving, het stelt ons in staat om ons beroepsonderwijs te vernieuwen en geeft docenten, onderzoekers en studenten de kans om zich te ontwikkelen door samen te werken aan vragen en uitdagingen die de toekomst van de beroepspraktijk vorm geven. Veel onderzoek wordt uitgevoerd onder begeleiding van lectoren die samenwerken met docent-onderzoekers, studenten, en professionals in het werkveld aan veelal meerjarige onderzoeksagenda’s die lijn aanbrengen in verschillende deelactiviteiten. Een van de manieren waarop De Haagse Hogeschool onderzoek organiseert is in de vorm van onderzoeksplatforms die zich richten op verschillende domeinen van de samenleving. Wij zijn ‘Connected Learning’, een onderzoeksplatform dat zich richt op leren in de netwerksamenleving - in de samenleving zelf, maar ook in de beroepspraktijk en in ons onderwijs. Aangenaam. Wat wij doen? Daar gaat dit boek over, dus daar verklappen we hier nog niets over. Wat verwacht u als u nadenkt over onze naam? Enig idee? Geen idee? Benieuwd? Lees verder om te ontdekken wat ons inspireert, uitdaagt en nieuwsgierig maakt. Sommige van onze ideeën zijn doordacht en doorleefd omdat we er al jaren onderzoek naar doen, andere zijn nieuw en dagen ons uit om er grip op te krijgen. Wij geven met dit boek een beeld van waar we staan in 2018. Zie het als een eerste kennismaking, met de nadruk op ‘eerste’: we werken graag met veel en verschillende partners. Zie het als visitekaartje van onze onderzoeksagenda. We hopen van harte dat u zich als lezer uitgenodigd voelt om met ons samen op zoek te gaan—misschien wel naar een gezamenlijke toekomst. ‘Connected Learning’ Research Platform: For over fifteen years, The Hague University of Applied Sciences has been carrying out research as part of its mission. While education is often rooted in monodisciplinary subject areas, research allows for a broader look at areas of society (care, security, entrepreneurship etc.), where complex problems more often than not require a multidisciplinary approach. Today, barely anyone works on problems or challenges alone or solely with colleagues from within the same subject area. Universities of applied sciences are uniquely placed to deal with these changes in professional practices; after all, we train the professionals who will one day enter that field. Researching and experimenting with new challenges in professional practice allows us to connect more strongly with society, enables us to be innovative in our professional training and gives lecturers, researchers and students the opportunity to develop themselves by cooperating on the challenges and issues that will shape the future of that professional practice. Most research is carried out under the guidance of professors who cooperate with lecturers/researchers, students and the professional field, mainly on long-term research agendas that provide an outline for various sub-activities. One of the ways in which research is organised at The Hague University of Applied Sciences is in the form of research platforms that focus on various areas of society. We are ‘Connected Learning’, a research platform focusing on learning in the network society — in that society as such, but also in professional practice and our education. Nice to meet you! So, what do we do? That’s what this book is about, so we’re not going to give anything away just yet. Just thinking about our name, what do you expect we do? Any ideas? Or not a clue at all? If you’d like to find out, keep reading to find out what inspires us, what challenges we face and what drives our curiosity. Some of our ideas are well-established because we’ve been researching them for years, while other, newer ideas are more challenging to grasp. This book provides an overview of where we stand in 2018. You could see it as an initial introduction, with the emphasis on “initial”; we work with many different partners, and we enjoy doing so. Alternatively, you could see it as a calling card for our research agenda. We sincerely hope that, as a reader, you feel encouraged to join us in our quest — possibly towards a joint future.
National forestry Commission (SBB) and National Park De Biesbosch. Subcontractor through NRITNational parks with large flows of visitors have to manage these flows carefully. Methods of data collection and analysis can be of help to support decision making. The case of the Biesbosch National Park is used to find innovative ways to figure flows of yachts, being the most important component of water traffic, and to create a model that allows the estimation of changes in yachting patterns resulting from policy measures. Recent policies oriented at building additional waterways, nature development areas and recreational concentrations in the park to manage the demands of recreation and nature conservation offer a good opportunity to apply this model. With a geographical information system (GIS), data obtained from aerial photographs and satellite images can be analyzed. The method of space syntax is used to determine and visualize characteristics of the network of leisure routes in the park and to evaluate impacts resulting from expected changes in the network that accompany the restructuring of waterways.
The SPRONG-collaboration “Collective process development for an innovative chemical industry” (CONNECT) aims to accelerate the chemical industry’s climate/sustainability transition by process development of innovative chemical processes. The CONNECT SPRONG-group integrates the expertise of the research groups “Material Sciences” (Zuyd Hogeschool), “Making Industry Sustainable” (Hogeschool Rotterdam), “Innovative Testing in Life Sciences & Chemistry” and “Circular Water” (both Hogeschool Utrecht) and affiliated knowledge centres (Centres of Expertise CHILL [affiliated to Zuyd] and HRTech, and Utrecht Science Park InnovationLab). The combined CONNECT-expertise generates critical mass to facilitate process development of necessary energy-/material-efficient processes for the 2050 goals of the Knowledge and Innovation Agenda (KIA) Climate and Energy (mission C) using Chemical Key Technologies. CONNECT focuses on process development/chemical engineering. We will collaborate with SPRONG-groups centred on chemistry and other non-SPRONG initiatives. The CONNECT-consortium will generate a Learning Community of the core group (universities of applied science and knowledge centres), companies (high-tech equipment, engineering and chemical end-users), secondary vocational training, universities, sustainability institutes and regional network organizations that will facilitate research, demand articulation and professionalization of students and professionals. In the CONNECT-trajectory, four field labs will be integrated and strengthened with necessary coordination, organisation, expertise and equipment to facilitate chemical innovations to bridge the innovation valley-of-death between feasibility studies and high technology-readiness-level pilot plant infrastructure. The CONNECT-field labs will combine experimental and theoretical approaches to generate high-quality data that can be used for modelling and predict the impact of flow chemical technologies. The CONNECT-trajectory will optimize research quality systems (e.g. PDCA, data management, impact). At the end of the CONNECT-trajectory, the SPRONG-group will have become the process development/chemical engineering SPRONG-group in the Netherlands. We can then meaningfully contribute to further integrate the (inter)national research ecosystem to valorise innovative chemical processes for the KIA Climate and Energy.
The bi-directional communication link with the physical system is one of the main distinguishing features of the Digital Twin paradigm. This continuous flow of data and information, along its entire life cycle, is what makes a Digital Twin a dynamic and evolving entity and not merely a high-fidelity copy. There is an increasing realisation of the importance of a well functioning digital twin in critical infrastructures, such as water networks. Configuration of water network assets, such as valves, pumps, boosters and reservoirs, must be carefully managed and the water flows rerouted, often manually, which is a slow and costly process. The state of the art water management systems assume a relatively static physical model that requires manual corrections. Any change in the network conditions or topology due to degraded control mechanisms, ongoing maintenance, or changes in the external context situation, such as a heat wave, makes the existing model diverge from the reality. Our project proposes a unique approach to real-time monitoring of the water network that can handle automated changes of the model, based on the measured discrepancy of the model with the obtained IoT sensor data. We aim at an evolutionary approach that can apply detected changes to the model and update it in real-time without the need for any additional model validation and calibration. The state of the art deep learning algorithms will be applied to create a machine-learning data-driven simulation of the water network system. Moreover, unlike most research that is focused on detection of network problems and sensor faults, we will investigate the possibility of making a step further and continue using the degraded network and malfunctioning sensors until the maintenance and repairs can take place, which can take a long time. We will create a formal model and analyse the effect on data readings of different malfunctions, to construct a mitigating mechanism that is tailor-made for each malfunction type and allows to continue using the data, albeit in a limited capacity.
