This paper frames the process of designing a level in a game as a series of model transformations. The transformations correspond to the application of particular design principles, such as the use of locks and keys to transform a linear mission into a branching space. It shows that by using rewrite systems, these transformations can be formalized and automated. The resulting automated process is highly controllable: it is a perfect match for a mixed-initiative approach to level generation where human and computer collaborate in designing levels. An experimental prototype that implements these ideas is presented.
DOCUMENT
A level designer typically creates the levels of a game to cater for a certain set of objectives, or mission. But in procedural content generation, it is common to treat the creation of missions and the generation of levels as two separate concerns. This often leads to generic levels that allow for various missions. However, this also creates a generic impression for the player, because the potential for synergy between the objectives and the level is not utilised. Following up on the mission-space generation concept, as described by Dormans, we explore the possibilities of procedurally generating a level from a designer-made mission. We use a generative grammar to transform a mission into a level in a mixed-initiative design setting. We provide two case studies, dungeon levels for a rogue-like game, and platformer levels for a metroidvania game. The generators differ in the way they use the mission to generate the space, but are created with the same tool for content generation based on model transformations. We discuss the differences between the two generation processes and compare it with a parameterized approach.
LINK
Nowadays, digital tools for mathematics education are sophisticated and widely available. These tools offer important opportunities, but also come with constraints. Some tools are hard to tailor by teachers, educational designers and researchers; their functionality has to be taken for granted. Other tools offer many possible educational applications, which require didactical choices. In both cases, one may experience a tension between a teacher’s didactical goals and the tool’s affordances. From the perspective of Realistic Mathematics Education (RME), this challenge concerns both guided reinvention and didactical phenomenology. In this chapter, this dialectic relationship will be addressed through the description of two particular cases of using digital tools in Dutch mathematics education: the introduction of the graphing calculator (GC), and the evolution of the online Digital Mathematics Environment (DME). From these two case descriptions, my conclusion is that students need to develop new techniques for using digital tools; techniques that interact with conceptual understanding. For teachers, it is important to be able to tailor the digital tool to their didactical intentions. From the perspective of RME, I conclude that its match with using digital technology is not self-evident. Guided reinvention may be challenged by the rigid character of the tools, and the phenomena that form the point of departure of the learning of mathematics may change in a technology-rich classroom.
LINK
In order for techniques from Model Driven Engineering to be accepted at large by the game industry, it is critical that the effectiveness and efficiency of these techniques are proven for game development. There is no lack of game design models, but there is no model that has surfaced as an industry standard. Game designers are often reluctant to work with models: they argue these models do not help them design games and actually restrict their creativity. At the same time, the flexibility that model driven engineering allows seems a good fit for the fluidity of the game design process, while clearly defined, generic models can be used to develop automated design tools that increase the development’s efficiency.
DOCUMENT
Current methods for energy diagnosis in heating, ventilation and air conditioning (HVAC) systems are not consistent with process and instrumentation diagrams (P&IDs) as used by engineers to design and operate these systems, leading to very limited application of energy performance diagnosis in practice. In a previous paper, a generic reference architecture – hereafter referred to as the 4S3F (four symptoms and three faults) framework – was developed. Because it is closely related to the way HVAC experts diagnose problems in HVAC installations, 4S3F largely overcomes the problem of limited application. The present article addresses the fault diagnosis process using automated fault identification (AFI) based on symptoms detected with a diagnostic Bayesian network (DBN). It demonstrates that possible faults can be extracted from P&IDs at different levels and that P&IDs form the basis for setting up effective DBNs. The process was applied to real sensor data for a whole year. In a case study for a thermal energy plant, control faults were successfully isolated using balance, energy performance and operational state symptoms. Correction of the isolated faults led to annual primary energy savings of 25%. An analysis showed that the values of set probabilities in the DBN model are not outcome-sensitive. Link to the formal publication via its DOI https://doi.org/10.1016/j.enbuild.2020.110289
DOCUMENT
Background:An eHealth tool that coaches employees through the process of reflection has the potential to support employees with moderate levels of stress to increase their capacity for resilience. Most eHealth tools that include self-tracking summarize the collected data for the users. However, users need to gain a deeper understanding of the data and decide upon the next step to take through self-reflection.Objective:In this study, we aimed to examine the perceived effectiveness of the guidance offered by an automated e-Coach during employees’ self-reflection process in gaining insights into their situation and on their perceived stress and resilience capacities and the usefulness of the design elements of the e-Coach during this process.Methods:Of the 28 participants, 14 (50%) completed the 6-week BringBalance program that allowed participants to perform reflection via four phases: identification, strategy generation, experimentation, and evaluation. Data collection consisted of log data, ecological momentary assessment (EMA) questionnaires for reflection provided by the e-Coach, in-depth interviews, and a pre- and posttest survey (including the Brief Resilience Scale and the Perceived Stress Scale). The posttest survey also asked about the utility of the elements of the e-Coach for reflection. A mixed methods approach was followed.Results:Pre- and posttest scores on perceived stress and resilience were not much different among completers (no statistical test performed). The automated e-Coach did enable users to gain an understanding of factors that influenced their stress levels and capacity for resilience (identification phase) and to learn the principles of useful strategies to improve their capacity for resilience (strategy generation phase). Design elements of the e-Coach reduced the reflection process into smaller steps to re-evaluate situations and helped them to observe a trend (identification phase). However, users experienced difficulties integrating the chosen strategies into their daily life (experimentation phase). Moreover, the identified events related to stress and resilience were too specific through the guidance offered by the e-Coach (identification phase), and the events did not recur, which consequently left users unable to sufficiently practice (strategy generation phase), experiment (experimentation phase), and evaluate (evaluation phase) the techniques during meaningful events.Conclusions:Participants were able to perform self-reflection under the guidance of the automated e-Coach, which often led toward gaining new insights. To improve the reflection process, more guidance should be offered by the e-Coach that would aid employees to identify events that recur in daily life. Future research could study the effects of the suggested improvements on the quality of reflection via an automated e-Coach.
DOCUMENT
Author supplied from the article: ABSTRACT Increasing global competition in manufacturing technology puts pressure on lead times for product design and production engineering. By the application of effective methods for systems engineering (engineering design), the development risks can be addressed in a structured manner to minimise chances of delay and guarantee timely market introduction. Concurrent design has proven to be effective in markets for high tech systems; the product and its manufacturing means are simultaneously developed starting at the product definition. Unfortunately, not many systems engineering methodologies do support development well in the early stage of the project where proof of concept is still under investigation. The number of practically applicable tools in this stage is even worse. Industry could use a systems engineering method that combines a structured risk approach, concurrent development, and especially enables application in the early stage of product and equipment design. The belief is that Axiomatic Design can provide with a solid foundation for this need. This paper proposes a ‘Constituent Roadmap of Product Design’, based on the axiomatic design methodology. It offers easy access to a broad range of users, experienced and inexperienced. First, it has the ability to evaluate if knowledge application to a design is relevant and complete. Secondly, it offers more detail within the satisfaction interval of the independence axiom. The constituent roadmap is based on recent work that discloses an analysis on information in axiomatic design. The analysis enables better differentiation on project progression in the conceptual stage of design. The constituent roadmap integrates axiomatic design and the methods that harmonise with it. Hence, it does not jeopardise the effectiveness of the methodology. An important feature is the check matrix, a low threshold interface that unlocks the methodology to a larger audience. (Source - PDF presented at ASME IMECE (International Mechanical Engineering Congress and Exposition
DOCUMENT
In practice, faults in building installations are seldom noticed because automated systems to diagnose such faults are not common use, despite many proposed methods: they are cumbersome to apply and not matching the way of thinking of HVAC engineers. Additionally, fault diagnosis and energy performance diagnosis are seldom combined, while energy wastage is mostly a consequence of component, sensors or control faults. In this paper new advances on the 4S3F diagnose framework for automated diagnostic of energy waste in HVAC systems are presented. The architecture of HVAC systems can be derived from a process and instrumentation diagram (P&ID) usually set up by HVAC designers. The paper demonstrates how all possible faults and symptoms can be extracted on a very structured way from the P&ID, and classified in 4 types of symptoms (deviations from balance equations, operational states, energy performances or additional information) and 3 types of faults (component, control and model faults). Symptoms and faults are related to each other through Diagnostic Bayesian Networks (DBNs) which work as an expert system. During operation of the HVAC system the data from the BMS is converted to symptoms, which are fed to the DBN. The DBN analyses the symptoms and determines the probability of faults. Generic indicators are proposed for the 4 types of symptoms. Standard DBN models for common components, controls and models are developed and it is demonstrated how to combine them in order to represent the complete HVAC system. Both the symptom and the fault identification parts are tested on historical BMS data of an ATES system including heat pump, boiler, solar panels, and hydronic systems. The energy savings resulting from fault corrections are estimated and amount 25%. Finally, the 4S3F method is extended to hard and soft sensor faults. Sensors are the core of any FDD system and any control system. Automated diagnostic of sensor faults is therefore essential. By considering hard sensors as components and soft sensors as models, they can be integrated into the 4S3F method.
DOCUMENT
Background. A number of parenting programs, aimed at improving parenting competencies, have recently been adapted or designed with the use of online technologies. Although web-based services have been claimed to hold promise for parent support, a meta-analytic review of online parenting interventions is lacking. Method. A systematic review was undertaken of studies (n = 19), published between 2000 and 2010, that describe parenting programs of which the primary components were delivered online. Seven programs were adaptations of traditional, mostly evidencebased, parenting interventions, using the unique opportunities of internet technology. Twelve studies (with in total 54 outcomes, Ntot parents = 1,615 and Ntot children = 740) were included in a meta-analysis. Results. The meta-analysis showed a statistically signifi cant medium effect across parents outcomes (ES = 0.67; se = 0.25) and child outcomes (ES = 0.42; se = 0.15). Conclusions. The results of this review show that web-based parenting programs with new technologies offer opportunities for sharing social support, consulting professionals and training parental competencies. The metaanalytic results show that guided and self-guided online interventions can make a signifi cant positive contribution for parents and children. The relation with other metaanalyses in the domains of parent education and web-based interventions is discussed.
LINK
Office well-being aims to explore and support a healthy, balanced and active work style in office environments. Recent work on tangible user interfaces has started to explore the role of physical, tangible interfaces as active interventions to explore how to tackle problems such as inactive work and lifestyles, and increasingly sedentary behaviours. We identify a fragmented research landscape on tangible Office well-being interventions, missing the relationship between interventions, data, design strategies, and outcomes, and behaviour change techniques. Based on the analysis of 40 papers, we identify 7 classifications in tangible Office well-being interventions and analyse the intervention based on their role and foundation in behaviour change. Based on the analysis, we present design considerations for the development of future tangible Office well-being design interventions and present an overview of the current field and future research into tangible Office well-being interventions to design for a healthier and active office environment.
DOCUMENT
