This innovative practice full paper finds that story-telling through animatronics can offer a combination of creativity and engineering in order to engage students in an inquiry-based approach to STEM learning. Animat...
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Treemaps are a popular representation to show hierarchical as well as part-to-whole relationships in data. While most students are aware of node-link representations/network diagrams based on their K-12 education, tre...
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Speed bumps are vertical raisings of the road pavement used to force drivers to slow down to ensure greater safety in traffic. However, these obstacles have disadvantages in terms of efficiency and safety, where the p...
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Speed bumps are vertical raisings of the road pavement used to force drivers to slow down to ensure greater safety in traffic. However, these obstacles have disadvantages in terms of efficiency and safety, where the presence of speed bumps can affect travel time and fuel consumption, cause traffic jams, delay emergency vehicles, and cause vehicle damage or accidents when not properly signaled. Due to these factors, the availability of geolocation information for these obstacles can benefit several applications in Intelligent Transportation System (ITS), such as Advanced Driver Assistance Systems (ADAS) and autonomous vehicles, allowing to trace more efficient routes or alert the driver of the presence of the obstacle ahead. Speed bump detection applications described in the literature employ cameras or inertial sensors, represented by accelerometers and gyroscopes. While camera-based solutions are mature with evaluation in different contextual conditions, those based on inertial sensors do not offer multi-contextual analyses, being mostly simple applications of proof of concept, not applicable in real-world scenarios. For this reason, in this work, we propose the development of a reliable speed bump detection model based on inertial sensors, capable of operating reliably in contextual variations: different vehicles, driving styles, and environments in which vehicles can travel to. For the model development and validation, we collect nine datasets with contextual variations, using three different vehicles, with three different drivers, in three different environments, in which there are three different surface types, in addition to variations in conservation state and the presence of obstacles and anomalies. The speed bumps are present in two different pavement types, asphalt and cobblestone. We use the collected data in experiments to evaluate aspects such as the influence of the placement of the sensors for vehicle data collection and the data window size. Afterwar
Despite of exciting advances in image-based rendering and novel view synthesis, it is still challenging to achieve high-resolution results that can reach production-level quality when applying such methods to the task...
Despite of exciting advances in image-based rendering and novel view synthesis, it is still challenging to achieve high-resolution results that can reach production-level quality when applying such methods to the task of stereo conversion. At the same time, only very few dedicated stereo conversion approaches exist, which also fall short in terms of the required quality. Hence, in this paper, we present a novel method for high-resolution 2D-to-3D conversion. It is fully differentiable in all of its stages and performs disparity-informed warping, consistent foreground-background compositing, and background-aware inpainting. To enable temporal consistency in the resulting video, we propose a strategy to integrate information from additional video frames. Extensive ablation studies validate our design choices, leading to a fully automatic model that outperforms existing approaches by a large margin (49-70% LPIPS error reduction). Finally, inspired from current practices in manual stereo conversion, we introduce optional interactive tools into our model, which allow to steer the conversion process and make it significantly more applicable for 3D film production.
This innovative practice full paper finds that story-telling through animatronics can offer a combination of creativity and engineering in order to engage students in an inquiry-based approach to STEM learning. Animat...
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ISBN:
(数字)9798350351507
ISBN:
(纸本)9798350363067
This innovative practice full paper finds that story-telling through animatronics can offer a combination of creativity and engineering in order to engage students in an inquiry-based approach to STEM learning. Animatronics is the art and science of bringing a story to life through robotic puppetry. Typically reserved for trained engineers with ample resources, animatronics can be an expressive yet inaccessible medium. We aim to allow students to write, create, and perform an animatronic story, learning valuable technical skills along the way. Our study, which took place over the course of eight weeks, investigates the use of our Paper Animatronics Kit in a Grade 2 and Grade 6 classroom, following the progression of their creative writing, animatronic building, and mentoring processes. We present results of our qualitative analysis of student and teacher interviews and group discussions.
Spatialized vibrotactile feedback systems deliver tactile information by placing multiple vibrotactile actuators on the body. As increasing numbers of actuators are required to adequately convey information in complic...
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Digital synthesizers typically feature a user-adjustable parameter space (i.e. the set of user-adjustable parameters) that is used to shape the sound (or timbre) of the instrument. A synthesizer patch is a snapshot of...
Digital synthesizers typically feature a user-adjustable parameter space (i.e. the set of user-adjustable parameters) that is used to shape the sound (or timbre) of the instrument. A synthesizer patch is a snapshot of the state of the instrument’s parameter space at a given time and is the representation most familiar to synthesizer users. Creating patches can often be repetitive, tedious, and complicated for synthesizers with large parameter spaces. This paper presents the creation and use of latent representations of synthesizer patches generated by training a Variational Autoencoder (VAE) on a library of existing patches. We demonstrate how to generate previously unseen patches by exploring this latent representation via interpolation through the latent space. Using the open-source synthesizer amSynth as a test bed, we evaluate reconstructed patches against a ground truth both, numerically and timbrally, as well as show how generating new patches from the latent space result in diverse yet musically pleasing timbres.
We present an exploratory data analysis approach for finite element (FE) simulations to interactively inspect measured deviations in sheet metals arising in automotive applications. Exterior car body parts consist of ...
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Indirect vision through a mirror, while bi-manually manipulating both the mirror and another tool is a relatively common way to perform operations in various types of surgery. However, learning such psychomotor skills...
Indirect vision through a mirror, while bi-manually manipulating both the mirror and another tool is a relatively common way to perform operations in various types of surgery. However, learning such psychomotor skills requires extensive training; they are difficult to teach; and they can be quite costly, for instance, for dentistry schools. In order to study the effectiveness of VR simulators for learning these kinds of skills, we developed a simulator for training dental surgery procedures, which supports tracking of eye gaze and tool trajectories (mirror and drill), as well as automated outcome scoring. We carried out a pre-/post-test study in which 30 fifth-year dental students received six training sessions in the access opening stage of the root canal procedure using the simulator. In addition, six experts performed three trials using the simulator. The outcomes of drilling performed on realistic plastic teeth showed a significant learning effect due to the training sessions. Also, students with larger improvements in the simulator tended to improve more in the real-world tests. Analysis of the tracking data revealed novel relationships between several metrics w.r.t. eye gaze and mirror use, and performance and learning effectiveness: high rates of correct mirror placement during active drilling and high continuity of fixation on the tooth are associated with increased skills and increased learning effectiveness. Larger time allocation for tooth inspections using the mirror, i.e., indirect vision, and frequency of inspection are associated with increased learning effectiveness. Our findings suggest that eye tracking can provide valuable insights into student learning gains of bi-manual psychomotor skills, particularly in indirect vision environments.
This paper proposes a novel automatic thresholding method called Automatic Salience Thresholding (AST) for creating binary masks for detecting and removing satellite streaks in night sky imagery. Our approach utilizes...
This paper proposes a novel automatic thresholding method called Automatic Salience Thresholding (AST) for creating binary masks for detecting and removing satellite streaks in night sky imagery. Our approach utilizes a combination of Gaussian filtering, a salience-based thresholding technique, morphological filtering and line detection using Probabilistic Hough Transformations to identify the satellite trail in the image. We evaluated our method on diverse datasets of night sky images containing satellite trails in varying lighting conditions. Our results show that AST outperforms the compared methods regarding accuracy and speed. Our proposed AST method provides a reliable and efficient solution for detecting satellite trails while balancing selectivity and sensitivity.
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