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.
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With the development of Enterprise Architecture (EA) as a discipline, measuring and understanding its value for business and IT has become relevant. In this paper a framework for categorizing the benefits of EA, the Enterprise Architecture Value Framework (EAVF), is presented and based on this framework, a measurability maturity scale is introduced. In the EAVF the value aspects of EA are expressed using the four perspectives of the Balanced Scorecard with regard to the development of these aspects over time, defining sixteen key areas in which EA may provide value. In its current form the framework can support architects and researchers in describing and categorizing the benefits of EA. As part of our ongoing research on the value of EA, two pilots using the framework have been carried out at large financial institutions. These pilots illustrate how to use the EAVF as a tool in measuring the benefits of EA.
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Over the past decade, journalists have created in-depth interactive narratives to provide an alternative to the relentless 24-hour news cycle. Combining different media forms, such as text, audio, video, and data visualisation with the interactive possibilities of digital media, these narratives involve users in the narrative in new ways. In journalism studies, the convergence of different media forms in this manner has gained significant attention. However, interactivity as part of this form has been left underappreciated. In this study, we scrutinise how navigational structure, expressed as navigational cues, shapes user agency in their individual explorations of the narrative. By approaching interactive narratives as story spaces with unique interactive architectures, in this article, we reconstruct the architecture of five Dutch interactive narratives using the walkthrough method. We find that the extensiveness of the interactive architectures can be described on a continuum between closed and open navigational structures that predetermine and thus shape users’ trajectories in diverse ways.
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We present a novel architecture for an AI system that allows a priori knowledge to combine with deep learning. In traditional neural networks, all available data is pooled at the input layer. Our alternative neural network is constructed so that partial representations (invariants) are learned in the intermediate layers, which can then be combined with a priori knowledge or with other predictive analyses of the same data. This leads to smaller training datasets due to more efficient learning. In addition, because this architecture allows inclusion of a priori knowledge and interpretable predictive models, the interpretability of the entire system increases while the data can still be used in a black box neural network. Our system makes use of networks of neurons rather than single neurons to enable the representation of approximations (invariants) of the output.
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Neighborhood image processing operations on Field Programmable Gate Array (FPGA) are considered as memory intensive operations. A large memory bandwidth is required to transfer the required pixel data from external memory to the processing unit. On-chip image buffers are employed to reduce this data transfer rate. Conventional image buffers, implemented either by using FPGA logic resources or embedded memories are resource inefficient. They exhaust the limited FPGA resources quickly. Consequently, hardware implementation of neighborhood operations becomes expensive, and integrating them in resource constrained devices becomes unfeasible. This paper presents a resource efficient FPGA based on-chip buffer architecture. The proposed architecture utilizes full capacity of a single Xilinx BlockRAM (BRAM36 primitive) for storing multiple rows of input image. To get multiple pixels/clock in a user defined scan order, an efficient duty-cycle based memory accessing technique is coupled with a customized addressing circuitry. This accessing technique exploits switching capabilities of BRAM to read 4 pixels in a single clock cycle without degrading system frequency. The addressing circuitry provides multiple pixels/clock in any user defined scan order to implement a wide range of neighborhood operations. With the saving of 83% BRAM resources, the buffer architecture operates at 278 MHz on Xilinx Artix-7 FPGA with an efficiency of 1.3 clock/pixel. It is thus capable to fulfill real time image processing requirements for HD image resolution (1080 × 1920) @103 fcps.
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When conducting research in and for the creative industries, there are a wealth of different possible research approaches that can be taken - reflecting the diverse nature of the disciplines (design, arts and crafts, advertising, architecture, fashion, film, music, TV, radio performing arts, publishing and interactive software) and academic contexts (art schools, business schools and universities) involved. The result is that there are variations in the emphasis and approach taken to how students are taught to link theory with practice, and how they view and engage with the concept ʻresearchʼ. The need for understanding and awareness of a range of approaches is critical for anyone learning about and working within design, business and the creative industries today.
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How and where can Dutch design entrepreneurs find work in Germany? This was the question DutchDFA put to the research team at Inholland University of Applied Sciences in February 2010. But the researchers took a different angle, and generated unexpected data, revealing patterns, and valuable new insights into practicing design and architecture abroad.
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Uit onderzoek naar het smartphonegebruik in het hoger onderwijs blijkt dat studenten vrijwel allemaal een smartphone mee naar de les hebben (Sumuer, 2021) en dat zij negatieve gevoelens ervaren als zij hun smartphone niet binnen bereik hebben (Wood et al., 2018). Hoewel je smartphones kunt gebruiken om studiedoelen te bereiken, blijkt ook dat studenten worden afgeleid door berichten via social-media e.d. of nieuwsberichten (Chen & Yan, 2016). Het roept de vraag op wat we weten van smartphonegebruik in het hoger onderwijs en of daar in navolging van het primair en voortgezet onderwijs ook een smartphoneverbod moet komen? In deze publicatie van het Lectoraat Teaching Learning & Technology| Hogeschool Inholland, ben je in 7 minuten 'bijgepraat' over het toestaan of verbieden van Smartphone-gebruik in het hoger onderwijs.
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In this article a generic fault detection and diagnosis (FDD) method for demand controlled ventilation (DCV) systems is presented. By automated fault detection both indoor air quality (IAQ) and energy performance are strongly increased. This method is derived from a reference architecture based on a network with 3 generic types of faults (component, control and model faults) and 4 generic types of symptoms (balance, energy performance, operational state and additional symptoms). This 4S3F architecture, originally set up for energy performance diagnosis of thermal energy plants is applied on the control of IAQ by variable air volume (VAV) systems. The proposed method, using diagnosis Bayesian networks (DBNs), overcomes problems encountered in current FDD methods for VAV systems, problems which inhibits in practice their wide application. Unambiguous fault diagnosis stays difficult, most methods are very system specific, and finally, methods are implemented at a very late stage, while an implementation during the design of the HVAC system and its control is needed. The IAQ 4S3F method, which solves these problems, is demonstrated for a common VAV system with demand controlled ventilation in an office with the use of a whole year hourly historic Building Management System (BMS) data and showed it applicability successfully. Next to this, the influence of prior and conditional probabilities on the diagnosis is studied. Link to the formal publication via its DOI https://doi.org/10.1016/j.buildenv.2019.106632
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