The recent success of Machine Learning encouraged research using artificial neural networks (NNs) in computer graphics. A good example is the bidirectional texture function (BTF), a data-driven representation of surface materials that can encapsulate complex behaviors that would otherwise be too expensive to calculate for real-time applications, such as self-shadowing and interreflections. We propose two changes to the state-of-the-art using neural networks for BTFs, specifically NeuMIP. These changes, suggested by recent work in neural scene representation and rendering, aim to improve baseline quality, memory footprint, and performance. We conduct an ablation study to evaluate the impact of each change. We test both synthetic and real data, and provide a working implementation within the Mitsuba 2 rendering framework. Our results show that our method outperforms the baseline in all these metrics and that neural BTF is part of the broader field of neural scene representation. Project website: https://traverse-research.github.io/NeuBTF/.
DOCUMENT
In this paper, I first discuss in some detail the current use of Learning Objects and show it to be wanting. Although their use, in principle, may offer much flexibility in creating content, in practice it will not, particularly since it does not support sufficient pedagogical flexibility. Then I offer an alternative view which, in my view, is indeed capable of fulfilling all the needs of customised learning, both the need for custom content and the need for custom pedagogies. I conclude by addressing some possible criticisms of my line of reasoning. This Chapter is a remake of Necessary Conditions for the Flexible Reuse of Educational Content.
DOCUMENT
Future work processes are going to change in several aspects. The working population (at least in Western European countries) is decreasing, while average age of employees increases. Their productivity is key to continuity in sectors like healthcare and manufacturing. Health and safety monitoring, combined with prevention measures must contribute to longer, more healthy and more productive working careers. The ‘tech-optimist’ approach to increase productivity is by means of automation and robotization, supported by IT, AI and heavy capital investments. Unfortunately, that kind of automation has not yet fulfilled its full promise as productivity enhancer as the pace of automation is significantly slower than anticipated and what productivity is gained -for instance in smart industry and healthcare- is considered to be ‘zero-sum’ as flexibility is equally lost (Armstrong et al., 2023). Simply ‘automating’ tasks too often leads to ‘brittle technology’ that is useless in unforeseen operational conditions or a changing reality. As such, it is unlikely to unlock high added-value. In healthcare industry we see “hardly any focus on research into innovations that save time to treat more patients.” (Gupta Strategists, 2021). Timesaving, more than classic productivity, should be the leading argument in rethinking the possibilities of human-technology collaboration, as it allows us to reallocate our human resources towards ‘care’, ’craft’ and ’creativity’.
DOCUMENT
The aim of this paper is to design and test a smartphone application which supports personalized running experiences for less experienced runners. As a result of a multidisciplinary three-step design approach Inspirun was developed. Inspirun is a personalized running-application for Android smartphones that aims to fill the gap between running on your own (static) schedule, and having a personal trainer that accommodates the schedule to your needs and profile. With the use of GPS and Bluetooth heart rate monitor support, a user's progress gets tracked. The application adjusts the training schedule after each training session, motivating the runner without a real life coach. Results from three user studies are promising; participants were very satisfied with the personalized approach, both in the profiling and de adaptation of their training scheme.
DOCUMENT
Aim: To investigate the effects of exercise on salivary concentrations of inflammatory markers by analyzing a panel of 25 inflammatory markers in subjects who had participated in bicycle ergometer tests varying in workload and hydration status. Methods: Fifteen healthy young men (20-35 years) had performed 4 different exercise protocols of 1 hour duration in a randomly assigned cross-over design, preceded by a rest protocol. Individual workloads depended on participant's pre-assessed individual maximum workload (Wmax): rest (protocol 1), 70% Wmax in hydrated (protocol 2) and dehydrated (protocol 3) state, 50% Wmax (protocol 4) and intermittent 85%/55% Wmax in 2 min blocks (protocol 5). Saliva samples were collected before (T0) and immediately after exercise (T1), and at several time points after exercise (2 hours (T3), 3 hours (T4), 6 hours (T5) and 24 hours (T6)). Secretory Leukocyte Protease Inhibitor (SLPI), Matrix Metallopeptidase-9 (MMP-9) and lactoferrin was analyzed using a commercial ELISA kit, a panel of 22 cytokines and chemokines were analyzed using a commercial multiplex immunoassay. Data was analyzed using a multilevel mixed linear model, with multiple test correction. Results: Among a panel of 25 inflammatory markers, SLPI concentrations were significantly elevated immediately after exercise in all protocols compared to rest and higher concentrations reflected the intensity of exercise and hydration status. MMP-9 showed a significant increase in the 70% Wmax dehydrated, 50% Wmax and intermittent protocols. Conclusions: Salivary concentrations of SLPI and MMP-9 seem associated with exercise intensity and hydration status and may offer non-invasive biomarkers to study (local) inflammatory responses to different exercise intensities in human studies. sa
DOCUMENT
In software architecture, the Layers pattern is commonly used. When this pattern is applied, the responsibilities of a software system are divided over a number of layers and the dependencies between the layers are limited. This may result in benefits like improved analyzability, reusability and portability of the system. However, many layered architectures are poorly designed and documented. This paper proposes a typology and a related approach to assign responsibilities to software layers. The Typology of Software Layer Responsibility (TSLR) gives an overview of responsibility types in the software of business information systems; it specifies and exemplifies these responsibilities and provides unambiguous naming. A complementary instrument, the Responsibility Trace Table (RTT), provides an overview of the TSLR-responsibilities assigned to the layers of a case-specific layered design. The instruments aid the design, documentation and review of layered software architectures. The application of the TSLR and RTT is demonstrated in three cases.
DOCUMENT
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.
DOCUMENT
Introduction (author supplied) : In this paper we propose future mapping, an alternative approach to futures research. With future mapping we intend to overcome some of the main problems that we encountered when applying scenario thinking in the area of product design and innovation. Future mapping attempts to develop multi-layered maps of possible futures, which can be used by pro-active companies and innovation teams as an instrument to ‘navigate’ the future (Munnecke & Van der Lugt, 2006). The approach invites designers to apply their analytical, creative and emphatical skills in a dialogue about future opportunities that lay ahead. In the past few years we have taught and applied the future mapping approach with various groups of Master’s level engineering students, both in The Netherlands and Denmark. We have altered and adjusted the approach as we learned from these experiences. In this paper we will describe the current state of the approach. The paper is not meant to provide a deep theoretical overview or a thorough empirical study. Rather it is meant to provide a hands-on process description to inform about the method and to enable anyone to apply future mapping. After describing why we think future mapping is a promising direction for futures research, we will provide a concise overview of the process steps involved. Then we will describe one student project as a case example. We will discuss the various types of future maps produced by the students. We will conclude by making some general observations about using future mapping as a method for futures research, and by proposing some directions for future work.
DOCUMENT
A model for programmatic assessment in action is proposed that optimizes assessment for learning as well as decision making on learner progress. It is based on a set of assessment principles that are interpreted from empirical research. The model specifies cycles of training, assessment and learner support activities that are completed by intermediate and final moments of evaluation on aggregated data-points. Essential is that individual data-points are maximized for their learning and feedback value, whereas high stake decisions are based on the aggregation of many data-points. Expert judgment plays an important role in the program. Fundamental is the notion of sampling and bias reduction for dealing with subjectivity. Bias reduction is sought in procedural assessment strategies that are derived from qualitative research criteria. A number of challenges and opportunities are discussed around the proposed model. One of the virtues would be to move beyond the dominating psychometric discourse around individual instruments towards a systems approach of assessment design based on empirically grounded theory.
MULTIFILE
