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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Twirre is a new architecture for mini-UAV platforms designed for autonomous flight in both GPS-enabled and GPS-deprived applications. The architecture consists of low-cost hardware and software components. High-level control software enables autonomous operation. Exchanging or upgrading hardware components is straightforward and the architecture is an excellent starting point for building low-cost autonomous mini-UAVs for a variety of applications. Experiments with an implementation of the architecture are in development, and preliminary results demonstrate accurate indoor navigation
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Virtual communities are online spaces with potential of integration of (member-generated) content and conversations [7,8]. In our research project we are interested in the adoption and building of virtual communities in organized sports, that is to say in the voluntary sports clubs (VSCs) in the Netherlands. Since these VSCs have massively transferred their communication with members from paper club magazines to online channels, these virtual communities arise from the use of a growing number of websites, e-mail and social network sites (SNSs). Although virtual communities are broadly investigated, such as social communities, brand communities, and public communities, there is little scholarly interest in virtual communities of member organizations that VSCs are an example of. The study that is to be presented at SECSI 2019 concerns the clubs’ use of SNSs (ClubSNSs), such as Facebook and Twitter, within the virtual communities. These SNSs are increasingly used by the VSCs to facilitate organizational communication and to obtain a good internal climate [9]. However, academic understanding of the impact of ClubSNSs’ content and conversations on the organizational performance of the VSC is in its infancy. In our study, we examined this impact of ClubSNSs use on the involvement among members and whether we can explain this by members’ identification with the club. Furthermore, we have tried to categorize ClubSNSs by content types, such as informative, conversational or sociable ClubSNSs, and their role in stimulating the use of ClubSNSs. In this way we attempted to gain insight into the effect of types of ClubSNSs’ content and conversations on membership involvement and the mediating role of identification with the club. This insight can help VSCs to develop effective ClubSNS channels that contribute to organizational goals such as supportive and loyal membership.
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This study describes the socio-cognitive dynamics of collaborative online knowledge-building discourse among Dutch Master of Education students from the perspective of openness. A socio-cognitive openness framework consisting of four social and four cognitive components was used to analyze contributions to online collective knowledge building processes in two Knowledge Forum® databases. Analysis revealed that the contributions express a moderate level of openness, with higher social than cognitive openness. Three cognitive indicators of openness were positively associated with follow-up, while the social indicators of openness appeared to have no bearings on follow-up. Findings also suggested that teachers’ contributions were more social in nature and had less follow-up compared to students’ contributions. From the perspective of openness, the discourse acts of building knowledge and expressing uncertainty appear to be key in keeping knowledge building discourse going, in particular through linking new knowledge claims to previous claims and simultaneously inviting others to refine the contributed claim.
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Twirre V2 is the evolution of an architecture for mini-UAV platforms which allows automated operation in both GPS-enabled and GPSdeprived applications. This second version separates mission logic, sensor data processing and high-level control, which results in reusable software components for multiple applications. The concept of Local Positioning System (LPS) is introduced, which, using sensor fusion, would aid or automate the flying process like GPS currently does. For this, new sensors are added to the architecture and a generic sensor interface together with missions for landing and following a line have been implemented. V2 introduces a software modular design and new hardware has been coupled, showing its extensibility and adaptability
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This paper will discuss the process of the MA program ePedagogy / Visual Knowledge Building during the first semester of the academic year 2005 – 2006. This MA program is a joint venture between the Universities of Helsinki, Hamburg and INHOLLAND. This publication will discuss and evaluate the concrete steps (in terms of learning process) during this first semester. In particular the role of the eTutor will get special attention. This publication is based on the principle of action research. Hart & Bond defines action research as “it is a form of reflective inquiry which enables practitioners to better realise such qualities in their practice. The tests for good action research are very pragmatic ones. Does it improve the professional quality of the transactions between practitioners and clients/colleagues? This action research approach is being realised upon three main sources. As an eTutor and member of the staff of this program I weekly filled in an “Evaluation Log” in which the following questions are centralized: 1. What happened (this week) 2. Significant experience 3. Reflection 4. Actions Secondly I used a little survey which was being used by the staff to evaluate the first semester. All the three Universities filled in a form with the following questions concerning the education and organisation: Education 1. What do you consider most hindering in your teaching? 2. What do you consider most beneficial in your teaching? 3. What kind of teaching methods do you prefer in this program? 4. Do you think the course offers are attractive for the target group? 5. How do you evaluate student’s engagements and motivation in your courses? 6. What can / should be improved in terms of collaborative learning activities and processes? Organisation 1. In what specific context do you spot organisational constraints? 2. Does your organisation recognise and support the MA program? 3. What is your short-, mid- and long term vision on this program? Thirdly an important source for this action research approach was the International Seminar which was hold in the middle of February 2006. In this seminar the changes based on the questions of the questionnaire were discussed and implemented. The theoretical framework in this publication is based on the dissertation of Karel Kreijns (Sociable CSCL Environments). In this dissertation he discussed the collaborative cognitiveand epistemic performance in a CSCLE. The social presence theory takes a central position in this dissertation. In this paper the pitfalls and barriers concerning a sociable CSCLE are being discussed and evaluated. This paper describes, the interventions the staff took, in order to improve the educational context of the program. From this perspective we looked very carefully to the barriers and pitfalls in our Virtual Learning Environment (VLE). We found evidence for the fact that a good CSCLE consists at least a good balance between Content, Community and Pedagogy. In the program we emphasised our focus (too much) on content and (too) little on community and pedagogy. The community was poor because of the fact that we used three content learning systems, which didn’t stimulate the group processes. Pedagogy was too much based on individual eTutor behaviour. In January 2006, after the courses were ended, the Universities organised a little survey. In this survey was shown that we have to some interventions to improve the learning process. At the International Seminar in February 2006 eTutors and students discussed the problems. The following interventions are being considered and implemented: 1. The use of three Virtual Learning Environments should be decreased. Especially the INHOLLAND / Blackboard system doesn’t reflect the open source philosophy. Besides this the accessibility of this system is not very easy for foreign students 2. The collaborative aspect should be increased, by emphasising the interdisciplinaryand international co-operation. The formation of international subgroups is implemented.
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Background: Although principles of the health promoting school (HPS) approach are followed worldwide, differences between countries in the implementation are reported. The aim of the current study was (1) to examine the implementation of the HPS approach in European countries in terms of different implementation indicators, that is, percentage of schools implementing the HPS approach, implementation of core components, and positioning on so‐called HPS‐related spectra, (2) to explore patterns of consistency between the implementation indicators across countries, and (3) to examine perceived barriers and facilitators to the implementation of the HPS approach across countries. Methods: This study analyzed data from a survey that was part of the Schools for Health in Europe network's Monitoring Task 2020. The survey was completed by HPS representatives of 24 network member countries. Results: Large variations exist in (the influencing factors for) the implementation of the HPS approach in European countries. Observed patterns show that countries with higher percentages of schools implementing the HPS approach also score higher on the implementation of the core components and, in terms of spectra, more toward implementing multiple HPS core components, add‐in strategies, action‐oriented research and national‐level driven dissemination. In each country a unique mix of barriers and facilitators was observed. Conclusion: Countries committed to implementing the HPS approach in as many schools as possible also seem to pay attention to the quality of implementation. For a complete and accurate measurement of implementation, the use of multiple implementation indicators is desirable.
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In order to achieve more impact and efficiency on the route towards a circular economy, new business models are introduced in the value chain of construction. It is suggested that lease and performance contracts will stimulate producers to improve quality and lifetime of building products, thereby ameliorating use and reuse of products and their materials. This, since these companies know the origin and composition of the materials, and the history of use and service of the products. The advantages seem to be obvious: the user only pays for use and performance of the product e.g. light, energy, vertical transport or protection against water and wind. The producers remain the owners of products and resources, and have the possibility to reuse and recycle materials and products in an efficient manner. This requires that they provide service during the lifetime of the products, and have the obligation to take care of the perfor- mance of their products over a certain period of time.In the Netherlands these circular business models (CBMs) are already implemented at a small scale. The introduction of these models raises some fundamental questions however, which, ideally, need to be addressed before such models are implemented at a larger scale. The aim of this paper is on the one hand to describe some of these business models, and on the other hand to reflect on some fundamental questions that can be raised in relation to a shift of ownership of materials. What may be the consequences of this shift of ownership? What are the risks of agglomeration of building materials by larger companies? Among other things such a shift could potentially influence the diversity and flexibility of choice available for tenants and building owners. It may also limit future possibilities of SME’s in the supply chain of construction. Are there ways to minimize some of these risks if we decide to implement these business models at a large scale?
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The past two years I have conducted an extensive literature and tool review to answer the question: “What should software engineers learn about building production-ready machine learning systems?”. During my research I noted that because the discipline of building production-ready machine learning systems is so new, it is not so easy to get the terminology straight. People write about it from different perspectives and backgrounds and have not yet found each other to join forces. At the same time the field is moving fast and far from mature. My focus on material that is ready to be used with our bachelor level students (applied software engineers, profession-oriented education), helped me to consolidate everything I have found into a body of knowledge for building production-ready machine learning (ML) systems. In this post I will first define the discipline and introduce the terminology for AI engineering and MLOps.
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Biomimicry education is grounded in a set of natural design principles common to every known lifeform on Earth. These Life’s Principles (LPs) (cc Biomimicry 3.8), provide guidelines for emulating sustainable strategies that are field-tested over nearly four billion years of evolution. This study evaluates an exercise for teaching LPs to interdisciplinary students at three universities, Arizona State University (ASU) in Phoenix, Arizona (USA), College of Charleston (CofC) in Charleston, South Carolina (USA) and The Hague University of Applied Sciences (THUAS) in The Hague (The Netherlands) during the spring 2021 semester. Students researched examples of both biological organisms and human designs exhibiting the LPs. We gauged the effectiveness of the exercise through a common rubric and a survey to discover ways to improve instruction and student understanding. Increased student success was found to be directly linked to introducing the LPs with illustrative examples, assigning an active search for examples as part of the exercise, and utilizing direct assessment feedback loops. Requiring students to highlight the specific terms of the LP sub-principles in each example is a suggested improvement to the instructions and rubric. An iterative, face-to-face, discussion-based teaching and learning approach helps overcome minor misunderstandings. Reiterating the LPs throughout the semester with opportunities for application will highlight the potential for incorporating LPs into students’ future sustainable design process. Stevens LL, Fehler M, Bidwell D, Singhal A, Baumeister D. Building from the Bottom Up: A Closer Look into the Teaching and Learning of Life’s Principles in Biomimicry Design Thinking Courses. Biomimetics. 2022; 7(1):25. https://doi.org/10.3390/biomimetics7010025
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