Travis A. Roberts, Sourabh Karmakar, Cameron J. Turner
Additive manufacturing, or 3D printing, is a complex process that creates free-form geometric objects by sequentially placing material to construct an object, usually in a layer-by-layer process. One of the most widely used methods is Fused Deposition Modeling (FDM). FDM is used in many of the consumer-grade polymer 3D printers available today. While consumer grade machines are cheap and plentiful, they lack many of the features desired in a machine used for research purposes and are often closed-source platforms. Commercial-grade models are more expensive and are also usually closed-source platforms that do not offer flexibility for modifications often needed for research. The authors designed and fabricated a machine to be used as a test bed for research in the field of polymer FDM processes. The goal was to create a platform that tightly controls and/or monitors the FDM build parameters so that experiments can be repeated with a known accuracy. The platform offers closed loop position feedback, control of the hot end and bed temperature, and monitoring of environment temperature and humidity. Additionally, the platform is equipped with cameras and a mechanism for in-situ photogrammetry, creating a geometric record of the printing throughout the printing process. Through photogrammetry, backtracking and linking process parameters to observable geometric defects can be achieved. This paper focuses on the design of a novel mechanism for spinning the heated bed to allow for photogrammetric reconstruction of the printed part using a minimal number of cameras, as implemented on this platform.
This paper explores the relevance of the use of dragon elements in illustration design and Memphis style visual design. Through the study of the symbolic meaning of dragon elements in different cultures and the origin and characteristics of Memphis style, combined with the actual case study of illustration design, this paper discusses the correlation and interaction between dragon elements and Memphis style visual design. Research has found that the clever incorporation of dragons in illustration designs, combined with Memphis-style geometry and bright colors, can create creative, unique and appealing visuals. These findings provide new creative ideas and inspiration for illustration design.
Thea Overby Hansen, Maria Leis Jensen, Line Schack Tonnesen
et al.
This paper explores the design of an interactive installation in a science center which facilitates an embodied experience with satellite data. This addresses a central concern for experience design in museums, which is the question of how to integrate technologies well in the visitor experience, sometimes referred to as "experience blend". We present the design and evaluation of a visualization triggered by movement in a physical staircase to let visitors explore data about satellites at different orbits. The evaluation demonstrates strong experience blend, and points towards similar design opportunities for other institutions interested in finding new uses for mundane pathways through their buildings.
Scene understanding is an essential and challenging task in computer vision. To provide the visually fundamental graphical structure of an image, the scene graph has received increased attention due to its powerful semantic representation. However, it is difficult to draw a proper scene graph for image retrieval, image generation, and multi-modal applications. The conventional scene graph annotation interface is not easy to use in image annotations, and the automatic scene graph generation approaches using deep neural networks are prone to generate redundant content while disregarding details. In this work, we propose SGDraw, a scene graph drawing interface using object-oriented scene graph representation to help users draw and edit scene graphs interactively. For the proposed object-oriented representation, we consider the objects, attributes, and relationships of objects as a structural unit. SGDraw provides a web-based scene graph annotation and generation tool for scene understanding applications. To verify the effectiveness of the proposed interface, we conducted a comparison study with the conventional tool and the user experience study. The results show that SGDraw can help generate scene graphs with richer details and describe the images more accurately than traditional bounding box annotations. We believe the proposed SGDraw can be useful in various vision tasks, such as image retrieval and generation.
Giuseppe Di Battista, Walter Didimo, Luca Grilli
et al.
In a graph story the vertices enter a graph one at a time and each vertex persists in the graph for a fixed amount of time $ω$, called viewing window. At any time, the user can see only the drawing of the graph induced by the vertices in the viewing window and this determines a sequence of drawings. For readability, we require that all the drawings of the sequence are planar. For preserving the user's mental map we require that when a vertex or an edge is drawn, it has the same drawing for its entire life. We study the problem of drawing the entire sequence by mapping the vertices only to $ω+k$ given points, where $k$ is as small as possible. We show that: $(i)$ The problem does not depend on the specific set of points but only on its size; $(ii)$ the problem is NP-hard and is FPT when parameterized by $ω+k$; $(iii)$ there are families of graph stories that can be drawn with $k=0$ for any $ω$, while for $k=0$ and small values of $ω$ there are families of graph stories that can be drawn and others that cannot; $(iv)$ there are families of graph stories that cannot be drawn for any fixed $k$ and families of graph stories that require at least a certain $k$.
In the manufacturing process of heavy industrial equipment, the specific unit in the welding diagram is first manually redrawn and then the corresponding sheet metal parts are cut, which is inefficient. To this end, this paper proposes a U-net-based method for the segmentation and extraction of specific units in welding engineering drawings. This method enables the cutting device to automatically segment specific graphic units according to visual information and automatically cut out sheet metal parts of corresponding shapes according to the segmentation results. This process is more efficient than traditional human-assisted cutting. Two weaknesses in the U-net network will lead to a decrease in segmentation performance: first, the focus on global semantic feature information is weak, and second, there is a large dimensional difference between shallow encoder features and deep decoder features. Based on the CBAM (Convolutional Block Attention Module) attention mechanism, this paper proposes a U-net jump structure model with an attention mechanism to improve the network's global semantic feature extraction ability. In addition, a U-net attention mechanism model with dual pooling convolution fusion is designed, the deep encoder's maximum pooling + convolution features and the shallow encoder's average pooling + convolution features are fused vertically to reduce the dimension difference between the shallow encoder and deep decoder. The dual-pool convolutional attention jump structure replaces the traditional U-net jump structure, which can effectively improve the specific unit segmentation performance of the welding engineering drawing. Using vgg16 as the backbone network, experiments have verified that the IoU, mAP, and Accu of our model in the welding engineering drawing dataset segmentation task are 84.72%, 86.84%, and 99.42%, respectively.
The Laplacian representation recently gains increasing attention for reinforcement learning as it provides succinct and informative representation for states, by taking the eigenvectors of the Laplacian matrix of the state-transition graph as state embeddings. Such representation captures the geometry of the underlying state space and is beneficial to RL tasks such as option discovery and reward shaping. To approximate the Laplacian representation in large (or even continuous) state spaces, recent works propose to minimize a spectral graph drawing objective, which however has infinitely many global minimizers other than the eigenvectors. As a result, their learned Laplacian representation may differ from the ground truth. To solve this problem, we reformulate the graph drawing objective into a generalized form and derive a new learning objective, which is proved to have eigenvectors as its unique global minimizer. It enables learning high-quality Laplacian representations that faithfully approximate the ground truth. We validate this via comprehensive experiments on a set of gridworld and continuous control environments. Moreover, we show that our learned Laplacian representations lead to more exploratory options and better reward shaping.
Thomas Gascard, Giampaolo Pisano, Simon Doyle
et al.
The next generations of ground-based cosmic microwave background experiments will require polarisation sensitive, multichroic pixels of large focal planes comprising several thousand detectors operating at the photon noise limit. One approach to achieve this goal is to couple light from the telescope to a polarisation sensitive antenna structure connected to a superconducting diplexer network where the desired frequency bands are filtered before being fed to individual ultra-sensitive detectors such as Transition Edge Sensors. Traditionally, arrays constituted of horn antennas, planar phased antennas or anti-reflection coated micro-lenses have been placed in front of planar antenna structures to achieve the gain required to couple efficiently to the telescope optics. In this paper are presented the design concept and a preliminary analysis of the measured performances of a phase-engineered metamaterial flat-lenslet. The flat lens design is inherently matched to free space, avoiding the necessity of an anti-reflection coating layer. It can be fabricated lithographically, making scaling to large format arrays relatively simple. Furthermore, this technology is compatible with the fabrication process required for the production of large-format lumped element kinetic inductance detector arrays which have already demonstrated the required sensitivity along with multiplexing ratios of order 1000 detectors/channel.
Irene Crimaldi, Pierre-Yves Louis, Ida Germana Minelli
We consider an urn model with multiple drawing and random time-dependent addition matrix. The model is very general with respect to previous literature: the number of sampled balls at each time-step is random, the addition matrix has general random entries. For the proportion of balls of a given color, we prove almost sure convergence results and fluctuation theorems (through CLTs in the sense of stable convergence and of almost sure conditional convergence, which are stronger than convergence in distribution). Asymptotic confidence intervals are given for the limit proportion, whose distribution is generally unknown.
The Finding Byaduk creative residency is an exploratory process aimed at producing speculations into the phenomenology of digital data representations of a landscape, and the design of interfaces and expressions to embody said representations. Part of this process is inspired by design ethnography, and the consideration of how its methodologies articulate a picture of the site in question. The creative brief centred around a thought experiment on ‘affective telepresence’, finding means to remotely convey the qualities of a place using environmental sensors, digital connected technologies, and the design of embodied expressions and/or interactions. Finding Byaduk: Field Notes covers the formative and supporting phases of this project, focusing on capturing ethnographic observations of the town, and connecting these to the eventual production of artefacts as a response to the written, visual and audio recordings of Byaduk. I would like to acknowledge the traditional custodians of the land of the Gunditjmara peoples on which this project took place, and pay my respects to the Elders past, present and future. Read the full article online at: https://drawingon.org/Issue-03-04-Finding-Byaduk
En este artículo hablo de los orígenes del motion design a la vez que destaco cuáles son los proyectos más innovadores hechos por los estudios más punteros actuales. Por otro lado, aprovecho para dar a conocer los proyectos que realizamos en el estudio MODIK, a la vez que muestro nuestra metodología de trabajo.
Tanja Munz, Michael Burch, Toon van Benthem
et al.
Generalized Pythagoras trees were developed for visualizing hierarchical data, producing organic, fractal-like representations. However, the drawback of the original layout algorithm is visual overlap of tree branches. To avoid such overlap, we introduce an adapted drawing algorithm using ellipses instead of circles to recursively place tree nodes representing the subhierarchies. Our technique is demonstrated by resolving overlap in diverse real-world and generated datasets, while comparing the results to the original approach.
Jonathan X. Zheng, Samraat Pawar, Dan F. M. Goodman
Bach et al. [1] recently presented an algorithm for constructing confluent drawings, by leveraging power graph decomposition to generate an auxiliary routing graph. We identify two issues with their method which we call the node split and short-circuit problems, and solve both by modifying the routing graph to retain the hierarchical structure of power groups. We also classify the exact type of confluent drawings that the algorithm can produce as 'power-confluent', and prove that it is a subclass of the previously studied 'strict confluent' drawing. A description and source code of our implementation is also provided, which additionally includes an improved method for power graph construction.
Image tracing is a foundational component of the workflow in graphic design, engineering, and computer animation, linking hand-drawn concept images to collections of smooth curves needed for geometry processing and editing. Even for clean line drawings, modern algorithms often fail to faithfully vectorize junctions, or points at which curves meet; this produces vector drawings with incorrect connectivity. This subtle issue undermines the practical application of vectorization tools and accounts for hesitance among artists and engineers to use automatic vectorization software. To address this issue, we propose a novel image vectorization method based on state-of-the-art mathematical algorithms for frame field processing. Our algorithm is tailored specifically to disambiguate junctions without sacrificing quality.
This is the arXiv index for the electronic proceedings of the 25th International Symposium on Graph Drawing and Network Visualization (GD 2017), which was held in Boston, U.S.A., September 25-27 2017. It contains the peer-reviewed and revised accepted papers with an optional appendix.
Krishnendu Chatterjee, Rasmus Ibsen-Jensen, Josef Tkadlec
Balanced knockout tournaments are ubiquitous in sports competitions and are also used in decision-making and elections. The traditional computational question, that asks to compute a draw (optimal draw) that maximizes the winning probability for a distinguished player, has received a lot of attention. Previous works consider the problem where the pairwise winning probabilities are known precisely, while we study how robust is the winning probability with respect to small errors in the pairwise winning probabilities. First, we present several illuminating examples to establish: (a)~there exist deterministic tournaments (where the pairwise winning probabilities are~0 or~1) where one optimal draw is much more robust than the other; and (b)~in general, there exist tournaments with slightly suboptimal draws that are more robust than all the optimal draws. The above examples motivate the study of the computational problem of robust draws that guarantee a specified winning probability. Second, we present a polynomial-time algorithm for approximating the robustness of a draw for sufficiently small errors in pairwise winning probabilities, and obtain that the stated computational problem is NP-complete. We also show that two natural cases of deterministic tournaments where the optimal draw could be computed in polynomial time also admit polynomial-time algorithms to compute robust optimal draws.
Gabriele Barbagallo, Angela Madeo, Fabrice Morestin
et al.
Experimental testing on dry woven fabrics exhibits a complex set of evidences that are difficult to be completely described using classical continuum models. The aim of this paper is to show how the introduction of energy terms related to the micro-deformation mechanisms of the fabric, in particular to the bending stiffness of the yarns, helps in the modeling of the mechanical behavior of this kind of materials. To this aim, a second gradient, hyperelastic, initially orthotropic continuum theory is proposed to model fibrous composite interlocks at finite strains. In particular, the present work explores the relationship between the onset of wrinkling appearing during the simulation of the deep drawing of a woven fabric and the use of a second gradient model. It is shown that the introduction of second gradient terms accounting for the description of in-plane and out-of-plane bending rigidities, decreases the onset of wrinkles during the simulation of deep-drawing. In this work, a quadratic energy, roughly proportional to the square of the curvature of the fibers, is presented and implemented in the simulations. This simple constitutive assumption allows to clearly show the effects of the second gradient energy on both the wrinkling description and the numerical stability of the model. The results obtained in second gradient simulations are descriptive of the experimental evidence of deep drawing whose description is targeted in this work. The present paper provides additional evidence of the fact that first gradient continuum theories alone cannot be considered fully descriptive of the behavior of dry woven composite reinforcements. On the other hand, the proposed second gradient model for fibrous composite reinforcements opens the way both to the more accurate simulation of complex forming processes and to the possibility of controlling the onset of wrinkles.
This is the arXiv index for the electronic proceedings of the 24th International Symposium on Graph Drawing and Network Visualization (GD 2016), which was held in Athens, Greece, September 19-21 2016. It contains the peer-reviewed and revised accepted papers with an optional appendix.
Alan Arroyo, Dan McQuillan, R. Bruce Richter
et al.
A {\em good drawing\/} of $K_n$ is a drawing of the complete graph with $n$ vertices in the sphere such that: no two edges with a common end cross; no two edges cross more than once; and no three edges all cross at the same point. Gioan's Theorem asserts that any two good drawings of $K_n$ that have the same rotations of incident edges at every vertex are equivalent up to Reidemeister moves. At the time of preparation, 10 years had passed between the statement in the WG 2005 conference proceedings and our interest in the proposition. Shortly after we completed our preprint, Gioan independently completed a preprint.