Influence of digital technologies on the quality of life by modelling the risk of flooding of territories by flood waters

Every year, there are many floods on the planet, which have a significant impact on ensuring the safety of people and affects the quality of life. The development of modern modelling technologies makes it possible to predict various scenarios for the development of the situation and reduce the likelihood of negative consequences. This issue is especially relevant for settlements located in the immediate vicinity of hydroelectric power plants, since by regulating discharge costs from hydroelectric power plants, it is possible to safely pass flood waters avoiding flooding of residential buildings and infrastructure, but this requires knowing the flooding zones at different water levels and discharge costs. This paper presents the results of solving the problem of modelling the dynamics of flood waters within the boundaries of the settlement of Krasnoyarsk. To calculate the flooded areas, the TUFLOW program was used in the Surface-water Modelling System modelling environment, as well as neural network forecasting using the NeuroPro software product. The simulation results made it possible to predict local flooding of the settlement during the flood of 2021 and take preventive measures to reduce the risk of flooding.

GANana: Unsupervised Domain Adaptation for Volumetric Regression of Fruit

3D reconstruction of fruit is important as a key component of fruit grading and an important part of many size estimation pipelines. Like many computer vision challenges, the 3D reconstruction task suffers from a lack of readily available training data in most domains, with methods typically depending on large datasets of high-quality image-model pairs. In this paper, we propose an unsupervised domain-adaptation approach to 3D reconstruction where labelled images only exist in our source synthetic domain, and training is supplemented with different unlabelled datasets from the target real domain. We approach the problem of 3D reconstruction using volumetric regression and produce a training set of 25,000 pairs of images and volumes using hand-crafted 3D models of bananas rendered in a 3D modelling environment (Blender). Each image is then enhanced by a GAN to more closely match the domain of photographs of real images by introducing a volumetric consistency loss, improving performance of 3D reconstruction on real images. Our solution harnesses the cost benefits of synthetic data while still maintaining good performance on real world images. We focus this work on the task of 3D banana reconstruction from a single image, representing a common task in plant phenotyping, but this approach is general and may be adapted to any 3D reconstruction task including other plant species and organs.

Can Strategic Behaviour Facilitate Confusion Resolution? The Interplay Between Confusion and Metacognitive Strategies in Betty’s Brain

Confusion may benefit learning when it is resolved or partially resolved. Metacognitive strategies (MS) may help learners to resolve confusion when it occurs during learning and problem solving. This study examined the relationship between confusion and MS that students evoked in Betty’s Brain, a computer-based learning-by-modelling environment where elementary and middle school students learn science by building causal maps. Participants were sixth graders. Emotion data were collected from real-time observations by trained researchers. MS and task performance information were determined by analyzing the action logs. Pre- and post-tests were used to assess learning gains. The results revealed that the use of MS was a function of the state of student confusion. However, confusion resolution was not related to MS behaviour, and MS did not moderate the effect of confusion on student task performance in Betty’s Brain or on learning gains.

Virtual Gas Turbines Part I: A Top-Down Geometry Modelling Environment for Turbomachinery Application

The gas turbine engine design involves multi-disciplinary, multi-fidelity iterative design-analysis processes. These highly intertwined processes are nowadays incorporated in automated design frameworks to facilitate high-fidelity, fully coupled, large-scale simulations. The most tedious and time-consuming step in such simulations is the construction of a common geometry database that ensures geometry consistency at every step of the design iteration, is accessible to multi-disciplinary solvers and allows system-level analysis. This paper presents a novel design-intent-driven geometry modelling environment that is based on a top-down feature-based geometry model generation method. The geometry features in this modelling environment are organised in a turbomachinery feature taxonomy. They produce a tree-like logical structure representing the engine geometry, wherein abstract features outline the engine architecture, while lower-level features define the detailed geometry. This top-down flexible feature-tree arrangement enables the design intent to be preserved throughout the design process, allows the design to be modified freely and supports the design intent variations to be propagated throughout the geometry model automatically. The application of the proposed feature-based geometry modelling environment is demonstrated by generating a whole-engine computational geometry model. This geometry modelling environment provides an efficient means of rapidly populating complex turbomachinery assemblies. The generated engine geometry is fully scalable, easily modifiable and is re-usable for generating the geometry models of new engines or their derivatives. This capability also enables fast multi-fidelity simulation and optimisation of various gas turbine systems.

Agent-Oriented Modelling for Blockchain Application Development: Feasibility Study

Blockchain application development has received much attention nowadays. As development is complex and challenging, a systematic approach is needed to improve the product, services, and process quality. Despite the introduction of techniques, there are still inadequate models for demonstrating the blockchain's internal architecture. Hence, there is a gap when developing the blockchain application, a gap in the modelling environment of a blockchain development application. This paper introduces a new insight into blockchain application development through Agent-Oriented Modelling (AOM). AOM is a methodology for complex socio-technical system development, and we believe that it can reduce the complexity of implementing the blockchain application. In this paper, the AOM is used to model a blockchain-based "win a fortune" system, which includes smart contract development. It showcases the feasibility of adopting AOM to model a blockchain enabling application. A usability survey among the novices has further validated the usability and benefits of AOM in the blockchain enabling application development.

Visual Tea: EVES: Vision as Touch

<p><b>It could be said that the eye plays a relatively passive role in the creation of a design. Our fingers and hands are more capable of drawing, and our voice can be used to communicate our ideas or expressions. Our eyes, however, are a consuming function. They absorb light and allow us to understand, but they do not play an active role. This body of work aims to challenge this conception through a body of design research and self-testing.</b></p> <p>By incorporating eye-tracking deeper within these methods, we can begin to discern this technology’s possibilities as a method that encompasses the visual experience as an active input. This thesis is segmented into the two areas of eye tracking utilisation within VR and the design process; passive and active. The passive investigations act as an intermediate phase to understand the extents of eye-tracking as a technology. In comparison, the active investigations act as the culmination and embodiment of this thesis as a whole.</p> <p>The research will explore the Eye-tracking Voxel Environment Sculptor’s (EVES) development that incorporates eye-tracking as an active design actor. Through the development of EVES, the extent to which eye-tracking can be implemented as an active design medium is investigated. The eye-tracking data garnered from the designer within EVES is directly utilised as an input within a modelling environment to manipulate and sculpt voxels. In addition to modelling input, eye-tracking is also explored in its usability in the Virtual Reality User Interface. Eyetracking is implemented within EVES to this extent to test the limits and possibilities of eye-tracking and the Human-Computer Interface within the realm of Virtual Reality Aided Design.</p>

Visual Tea: EVES: Vision as Touch

<p><b>It could be said that the eye plays a relatively passive role in the creation of a design. Our fingers and hands are more capable of drawing, and our voice can be used to communicate our ideas or expressions. Our eyes, however, are a consuming function. They absorb light and allow us to understand, but they do not play an active role. This body of work aims to challenge this conception through a body of design research and self-testing.</b></p> <p>By incorporating eye-tracking deeper within these methods, we can begin to discern this technology’s possibilities as a method that encompasses the visual experience as an active input. This thesis is segmented into the two areas of eye tracking utilisation within VR and the design process; passive and active. The passive investigations act as an intermediate phase to understand the extents of eye-tracking as a technology. In comparison, the active investigations act as the culmination and embodiment of this thesis as a whole.</p> <p>The research will explore the Eye-tracking Voxel Environment Sculptor’s (EVES) development that incorporates eye-tracking as an active design actor. Through the development of EVES, the extent to which eye-tracking can be implemented as an active design medium is investigated. The eye-tracking data garnered from the designer within EVES is directly utilised as an input within a modelling environment to manipulate and sculpt voxels. In addition to modelling input, eye-tracking is also explored in its usability in the Virtual Reality User Interface. Eyetracking is implemented within EVES to this extent to test the limits and possibilities of eye-tracking and the Human-Computer Interface within the realm of Virtual Reality Aided Design.</p>

Parametric Point Cloud Slicing for Facade Retrofitting

Current commitments by European governments seek to improve energy consumption as a means to reduce carbon emissions from building stock by 2050. Within such context, retrieving reliable three-dimensional contours from point clouds becomes an important step in developing facade retrofitting solutions since facade retrofitting projects often make use of as-built 3D models to help reduce inaccuracies by narrowing interpretation and measurement errors. This work aims to provide a method that uses topology-based parametric modelling for reconstructing building envelopes from point clouds. Through a semi-automated process that gives permanent visual feedback, the user adjusts parameters to custom standards of acceptability. A solution under the form of a Grasshopper definition delivers building envelope 3D contours in various file formats as a means for increasing interoperability. The main contributions of this work consist of a parametric reconstruction workflow capable of solving building topology for retrieving 3D contours, a strategy to bypass point cloud occlusion, and a strategy for converting those contours into an IFC model directly from the parametric modelling environment.