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Using state space grids for analysing teacher–student interaction in an intervention

This paper highlights the use of State Space Grids (SSGs) for studying real-time classroom discourse in an intervention targeting professional development. State Space Grid analysis is both a powerful way to visualise patterns in interactional data, and a starting point for further quantitative analysis. In the present study SSGs were used to explore patterns in teacher–student interactions. The study shows the importance of using micro-level time-serial data and illustrates how change in interactions during and after an intervention can be studied. SSG analysis was applied to study interaction in terms of the coupling of a teacher and a student variable: autonomy support and musical creativity. Video data from 40 music lessons of five teachers and their classes was used as input for plotting teacher–student interactions in SSGs, consisting of two dimensions. SSGs allow visualising change in the situation of interactions in the grid and identifying change in patterns to different grid areas. The findings show how interactions tended to settle in areas representing more productive interaction for all but one class. We discuss the benefits of using SSGs in intervention studies and the implications for educational practice and research of using this time-serial approach.

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Reconfigurable Equiplets Operating System A Hybrid Architecture to Combine Flexibility and Performance for Manufacturing

Author supplied: Abstract—The growing importance and impact of new technologies are changing many industries. This effect is especially noticeable in the manufacturing industry. This paper explores a practical implementation of a hybrid architecture for the newest generation of manufacturing systems. The papers starts with a proposition that envisions reconfigurable systems that work together autonomously to create Manufacturing as a Service (MaaS). It introduces a number of problems in this area and shows the requirements for an architecture that can be the main research platform to solve a number of these problems, including the need for safe and flexible system behaviour and the ability to reconfigure with limited interference to other systems within the manufacturing environment. The paper highlights the infrastructure and architecture itself that can support the requirements to solve the mentioned problems in the future. A concept system named Grid Manufacturing is then introduced that shows both the hardware and software systems to handle the challenges. The paper then moves towards the design of the architecture and introduces all systems involved, including the specific hardware platforms that will be controlled by the software platform called REXOS (Reconfigurable EQuipletS Operating System). The design choices are provided that show why it has become a hybrid platform that uses Java Agent Development Framework (JADE) and Robot Operating System (ROS). Finally, to validate REXOS, the performance is measured and discussed, which shows that REXOS can be used as a practical basis for more specific research for robust autonomous reconfigurable systems and application in industry 4.0. This paper shows practical examples of how to successfully combine several technologies that are meant to lead to a faster adoption and a better business case for autonomous and reconfigurable systems in industry.

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Reconfigurable Equiplets Operating System A Hybrid Architecture to Combine Flexibility and Performance for Manufacturing

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Space-time analytics of human physiology for urban planning.

Recent advancements in mobile sensing and wearable technologies create new opportunities to improve our understanding of how people experience their environment. This understanding can inform urban design decisions. Currently, an important urban design issue is the adaptation of infrastructure to increasing cycle and e-bike use. Using data collected from 12 cyclists on a cycle highway between two municipalities in The Netherlands, we coupled location and wearable emotion data at a high spatiotemporal resolution to model and examine relationships between cyclists' emotional arousal (operationalized as skin conductance responses) and visual stimuli from the environment (operationalized as extent of visible land cover type). We specifically took a within-participants multilevel modeling approach to determine relationships between different types of viewable land cover area and emotional arousal, while controlling for speed, direction, distance to roads, and directional change. Surprisingly, our model suggests ride segments with views of larger natural, recreational, agricultural, and forested areas were more emotionally arousing for participants. Conversely, segments with views of larger developed areas were less arousing. The presented methodological framework, spatial-emotional analyses, and findings from multilevel modeling provide new opportunities for spatial, data-driven approaches to portable sensing and urban planning research. Furthermore, our findings have implications for design of infrastructure to optimize cycling experiences.

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Co-creating fashion spaces

Recent developments in digital technology and consumer culture have created new opportunities for retail and brand event concepts which create value by offering more than solely marketing or transactions, but rather a place where passion is shared. This chapter will define the concept of ‘fashion space’ and consumer experience, and delves into strategies for creating experiences that both align with a brand’s ethos and identity and build brand communities. It will provide insight on creating strong shared brand experiences that integrate physical and digital spaces, AR and VR. These insights can be used for consumer spaces but also for media and buyer events, runway shows, test labs and showrooms. Since its launch in 2007, international fashion brand COS has focused on creating fashion spaces that build and reinforce a COS fashion community. COS retail stores with their extraordinary architecture, both traditional and contemporary, contribute stories and facilitate intense brand experiences. Moreover, COS’ dedication to share the artistic inspirations of its people led to collaborating on interactive and multi-sensory installations which allow consumers to affectively connect to the brand’s personality and values. Thus, the brand was able to establish itself firmly in the lifestyle of its customers, facilitating and developing their aesthetics and values. This is an Accepted Manuscript of a book chapter published by Routledge/CRC Press in "Communicating Fashion Brands. Theoretical and Practical Perspectives" on 03-03-2020, available online: https://www.routledge.com/Communicating-Fashion-Brands-Theoretical-and-Practical-Perspectives/Huggard-Cope/p/book/9781138613560. LinkedIn: https://nl.linkedin.com/in/overdiek12345

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Building and building systems energy prediction models to enhance energy flexibility control

The built environment requires energy-flexible buildings to reduce energy peak loads and to maximize the use of (decentralized) renewable energy sources. The challenge is to arrive at smart control strategies that respond to the increasing variations in both the energy demand as well as the variable energy supply. This enables grid integration in existing energy networks with limited capacity and maximises use of decentralized sustainable generation. Buildings can play a key role in the optimization of the grid capacity by applying demand-side management control. To adjust the grid energy demand profile of a building without compromising the user requirements, the building should acquire some energy flexibility capacity. The main ambition of the Brains for Buildings Work Package 2 is to develop smart control strategies that use the operational flexibility of non-residential buildings to minimize energy costs, reduce emissions and avoid spikes in power network load, without compromising comfort levels. To realise this ambition the following key components will be developed within the B4B WP2: (A) Development of open-source HVAC and electric services models, (B) development of energy demand prediction models and (C) development of flexibility management control models. This report describes the developed first two key components, (A) and (B). This report presents different prediction models covering various building components. The models are from three different types: white box models, grey-box models, and black-box models. Each model developed is presented in a different chapter. The chapters start with the goal of the prediction model, followed by the description of the model and the results obtained when applied to a case study. The models developed are two approaches based on white box models (1) White box models based on Modelica libraries for energy prediction of a building and its components and (2) Hybrid predictive digital twin based on white box building models to predict the dynamic energy response of the building and its components. (3) Using CO₂ monitoring data to derive either ventilation flow rate or occupancy. (4) Prediction of the heating demand of a building. (5) Feedforward neural network model to predict the building energy usage and its uncertainty. (6) Prediction of PV solar production. The first model aims to predict the energy use and energy production pattern of different building configurations with open-source software, OpenModelica, and open-source libraries, IBPSA libraries. The white-box model simulation results are used to produce design and control advice for increasing the building energy flexibility. The use of the libraries for making a model has first been tested in a simple residential unit, and now is being tested in a non-residential unit, the Haagse Hogeschool building. The lessons learned show that it is possible to model a building by making use of a combination of libraries, however the development of the model is very time consuming. The test also highlighted the need for defining standard scenarios to test the energy flexibility and the need for a practical visualization if the simulation results are to be used to give advice about potential increase of the energy flexibility. The goal of the hybrid model, which is based on a white based model for the building and systems and a data driven model for user behaviour, is to predict the energy demand and energy supply of a building. The model's application focuses on the use case of the TNO building at Stieltjesweg in Delft during a summer period, with a specific emphasis on cooling demand. Preliminary analysis shows that the monitoring results of the building behaviour is in line with the simulation results. Currently, development is in progress to improve the model predictions by including the solar shading from surrounding buildings, models of automatic shading devices, and model calibration including the energy use of the chiller. The goal of the third model is to derive recent and current ventilation flow rate over time based on monitoring data on CO₂ concentration and occupancy, as well as deriving recent and current occupancy over time, based on monitoring data on CO₂ concentration and ventilation flow rate. The grey-box model used is based on the GEKKO python tool. The model was tested with the data of 6 Windesheim University of Applied Sciences office rooms. The model had low precision deriving the ventilation flow rate, especially at low CO2 concentration rates. The model had a good precision deriving occupancy from CO₂ concentration and ventilation flow rate. Further research is needed to determine if these findings apply in different situations, such as meeting spaces and classrooms. The goal of the fourth chapter is to compare the working of a simplified white box model and black-box model to predict the heating energy use of a building. The aim is to integrate these prediction models in the energy management system of SME buildings. The two models have been tested with data from a residential unit since at the time of the analysis the data of a SME building was not available. The prediction models developed have a low accuracy and in their current form cannot be integrated in an energy management system. In general, black-box model prediction obtained a higher accuracy than the white box model. The goal of the fifth model is to predict the energy use in a building using a black-box model and measure the uncertainty in the prediction. The black-box model is based on a feed-forward neural network. The model has been tested with the data of two buildings: educational and commercial buildings. The strength of the model is in the ensemble prediction and the realization that uncertainty is intrinsically present in the data as an absolute deviation. Using a rolling window technique, the model can predict energy use and uncertainty, incorporating possible building-use changes. The testing in two different cases demonstrates the applicability of the model for different types of buildings. The goal of the sixth and last model developed is to predict the energy production of PV panels in a building with the use of a black-box model. The choice for developing the model of the PV panels is based on the analysis of the main contributors of the peak energy demand and peak energy delivery in the case of the DWA office building. On a fault free test set, the model meets the requirements for a calibrated model according to the FEMP and ASHRAE criteria for the error metrics. According to the IPMVP criteria the model should be improved further. The results of the performance metrics agree in range with values as found in literature. For accurate peak prediction a year of training data is recommended in the given approach without lagged variables. This report presents the results and lessons learned from implementing white-box, grey-box and black-box models to predict energy use and energy production of buildings or of variables directly related to them. Each of the models has its advantages and disadvantages. Further research in this line is needed to develop the potential of this approach.

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Building and building systems energy prediction models to enhance energy flexibility control

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Creating circular, efficient and symbiotic cities

The ‘Grand Challenges’ of our times, like climate change, resource depletion, global inequity, and the destruction of wildlife and biodiversity can only be addressed by innovating cities. Despite the options of tele-working, tele-trading and tele-amusing, that allow people to participate in ever more activities, wherever they are, people are resettling in cities at an unprecedented speed. The forecasted ‘rurification’ of society did not occur. Technological development has drained rural society from its main source of income, agriculture, as only a marginal fraction of the labour force is employed in agriculture in the rich parts of the world. Moreover, technological innovation created new jobs in the IT and service sectors in cities. Cities are potentially far more resource efficient than rural areas. In a city transport distances are shorter, infrastructures can be applied to provide for essential services in a more efficient way and symbiosis might be developed between various infrastructures. However, in practice, urban infrastructures are not more efficient than rural infrastructures. This paper explores the reasons why. It digs into the reasons why the symbiotic options that are available in cities are not (sufficiently) utilised. The main reason for this is not of an economic nature: Infrastructure organisations are run by experts who are part of a strong paradigmatic community. Dependence on other organisations is regarded as limiting the infrastructure organisation’s freedom of action to achieve its own goals. Expert cultures are transferred in education, professional associations, and institutional arrangements. By 3 concrete examples of urban systems, the paper will analyse how various paradigms of experts co-evolved with evolving systems. The paper reflects on recent studies that identified professional education as the initiation into such expert paradigms. It will thereby relate lack of urban innovation to the monodisciplinary education of experts and the strong institutionalised character of expertise. https://doi.org/10.1007/978-3-319-63007-6_43 LinkedIn: https://www.linkedin.com/in/karelmulder/

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Creating circular, efficient and symbiotic cities

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Assessing the multi-layered value of urban development policy

Abstract. In recent years circular economy has become more important for the development of many places including cities. Traditionally, urban development policies have mainly been aiming to improve the socio-economic wellbeing of neighbourhoods. However, technical and ecologic aspects have their effects too and need to go hand in hand. This paper is based on an urban area experiment in the Dutch city of Utrecht. In order to assess urban area developments, typically rather straight-forward quantitative indicators have been used. However, it has proved more complicated to assess multifaceted developments of the area studied in this paper. With the City Model Canvas a multi-layered model is being used to better assess the impact of the urban development being studied. Key findings include that the project studied resulted in more space for companies from the creative industry and the settlement of local ‘circular’ entrepreneurs and start-ups, although it remains unclear to what extent these benefit from each other’s presence. The increase in business activity resulted in more jobs, but it is again unclear whether this led to more social inclusion. From an environmental point of view the project activities resulted in less raw materials being used, although activities and public events bring nuisance to the surrounding neighbourhoods.

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Assessing the multi-layered value of urban development policy

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Museumchronotopics: on the representation of the past in museums

Many visitor studies make social background variables the central point of departure to explain participation patterns. How the past is 'staged', however, also has an influence on those to whom it appeals. This relational perspective calls for new conceptual tools to grasp empirical reality. Inspired by the historical philosophy of Georg Simmel and the literary theory of Mikhail Bakhtin a number of concepts which enable us to grasp the subtle relationship between museum presentations and visitors are presented. Bakhtin's notion of chronotopy serves as a key concept. By linking museum presentations and visitor perceptions with each other, it is also possible to identify certain tendencies within the contemporary museum landscape.

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Green data centres in the Netherlands

Green data centres are the talk of the day. But who in fact is involved in developing green data centres? What is their contribution? And what does this contribution constitute in practical terms? This article states which stakeholders are involved in green data centres in the Netherlands, what their involvement is and what effect their involvement has. The article starts by giving the definitions for sustainability and by determining the stakeholders and their possibilities in this field. Next, we examine the actual impact of each stakeholder for arriving at greener data centres. This leads to a number of conclusions for achieving a larger degree of sustainability.

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Products 39

Using state space grids for analysing teacher–student interaction in an intervention

Reconfigurable Equiplets Operating System A Hybrid Architecture to Combine Flexibility and Performance for Manufacturing

Space-time analytics of human physiology for urban planning.

Co-creating fashion spaces

Building and building systems energy prediction models to enhance energy flexibility control

Creating circular, efficient and symbiotic cities

Assessing the multi-layered value of urban development policy

Museumchronotopics: on the representation of the past in museums

Green data centres in the Netherlands

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Using state space grids for analysing teacher–student interaction in an intervention

Reconfigurable Equiplets Operating System A Hybrid Architecture to Combine Flexibility and Performance for Manufacturing

Space-time analytics of human physiology for urban planning.

Co-creating fashion spaces

Building and building systems energy prediction models to enhance energy flexibility control

Creating circular, efficient and symbiotic cities

Assessing the multi-layered value of urban development policy

Museumchronotopics: on the representation of the past in museums

Green data centres in the Netherlands