Two-dimensional Sketch Research Articles

SketchCleanGAN: A generative network to enhance and correct query sketches for improving 3D CAD model retrieval systems

Given an input query, a search and retrieval system fetches relevant information from a dataset. In the Engineering domain, such a system is beneficial for tasks such as design reuse. A two-dimensional (2D) sketch is more conducive for an end user to give as a query than a three-dimensional (3D) object. Such query sketches, nevertheless, will inevitably contain defects like incomplete lines, mesh lines, overdrawn areas, missing areas, etc. Since a retrieval system’s results are only as good as the query, it is necessary to improve the query sketches.In this paper, the problem of transforming a defective CAD sketch into a defect-free sketch is addressed using Generative Adversarial Networks (GANs), which, to the best of our knowledge, has not been investigated before. We first create a dataset of 534 hand-drawn sketches by tracing the boundaries of images of CAD models. We then pair the corrected sketches with their corresponding defective sketches and use them for training a C-WGAN (Conditional Wasserstein Generative Adversarial Network), called SketchCleanGAN. We model the transformation from defective to defect-free sketch as a factorization of the defective input sketch and then translate it to the space of defect-free sketch. We propose a three-branch strategy to this problem. Ablation studies and comparisons with other state-of-the-art techniques demonstrate the efficacy of the proposed technique. Additionally, we also contribute to a dataset of around 58000 improved sketches using the proposed framework.

3D surgical planning method for lower jaw osteotomies applied to facial feminization surgery

Our proposed method uses a three-dimensional (3D) measurement approach that focuses mainly on the lower jaw from basal, lateral, and frontal views applied to the volumetric skull model derived from a computed tomography (CT) of the head. Likewise, we discuss the geometrical features and clinical considerations involved in the 3D biomodeling of the surgical osteotomy. The workflow that allowed this virtual planning to be developed was composed of medical imaging processing software, data extraction software from images, and statistical software that allows the creation and generation of curve-fitting (nonlinear regression) graphs from data. Thirty-two (32) anatomical points were positioned, sixteen (16) measurements were taken, and two-dimensional (2D) sketches in three views (frontal, lateral, and inferior) were generated to overlap in a 3D environment, which informed the cutting of the desired bone segments. Implementing a nonlinear regression curve-fitting on the contours of the original jaws allowed optimal planning of the osteotomy. Desired cutting shapes were extrapolated for the front view by third-order equations, while for the side and bottom views, log-normal distribution curves and second-order polynomial curves were used, respectively. The reduction in the mandibular volume was between 6.55 and 10.27 %, with two of the most important measurements related to vertical reduction in the lateral views and the difference to determine gonion reduction.

Semi-automated creation of reciprocal frame structures using deep learning

Systems that can transform two-dimensional (2D) sketches into 3D models while performing structural analyses are necessary for architectural sketches. To address this challenge, this paper focuses on how deep-learning algorithms can aid in this transformation process. It presents a model that uses the instance-segmentation technique with Mask RCNN to detect and distinguish two types of short beams of reciprocal frame structures (RFs) in 2D sketches and uses this information in the systematic creation of a 3D model of RFs to conduct their structural analysis. The results indicate that the model is capable of clustering beam types in 2D sketches via masking and classifying, eliminating irrelevant background objects, creating parametric RFs using masking information, and performing structural analysis. The model, which helps optimise and ease the design process, can be used by architects or engineers. This paper will inspire future work on the creation of integrated modelling systems.

A Computer Vision Framework for Structural Analysis of Hand-Drawn Engineering Sketches.

Structural engineers are often required to draw two-dimensional engineering sketches for quick structural analysis, either by hand calculation or using analysis software. However, calculation by hand is slow and error-prone, and the manual conversion of a hand-drawn sketch into a virtual model is tedious and time-consuming. This paper presents a complete and autonomous framework for converting a hand-drawn engineering sketch into an analyzed structural model using a camera and computer vision. In this framework, a computer vision object detection stage initially extracts information about the raw features in the image of the beam diagram. Next, a computer vision number-reading model transcribes any handwritten numerals appearing in the image. Then, feature association models are applied to characterize the relationships among the detected features in order to build a comprehensive structural model. Finally, the structural model generated is analyzed using OpenSees. In the system presented, the object detection model achieves a mean average precision of 99.1%, the number-reading model achieves an accuracy of 99.0%, and the models in the feature association stage achieve accuracies ranging from 95.1% to 99.5%. Overall, the tool analyzes 45.0% of images entirely correctly and the remaining 55.0% of images partially correctly. The proposed framework holds promise for other types of structural sketches, such as trusses and frames. Moreover, it can be a valuable tool for structural engineers that is capable of improving the efficiency, safety, and sustainability of future construction projects.

SketchCADGAN: A generative approach for completing partially drawn query sketches of engineering shapes to enhance retrieval system performance

Retrieval systems are commonly used to find relevant data in large datasets. In engineering, these systems are useful for locating specific engineering shapes in a large dataset of engineering components. When end users want to search for a shape, they prefer a two-dimensional (2D) sketch over a three-dimensional (3D) object. However, users lacking domain knowledge may struggle to generate a complete query sketch and provide a partially completed sketch instead. Retrieving relevant information from partially drawn sketches is difficult because they may have missing edges, partially drawn circles, holes, ovals, etc. Most retrieval systems compare the similarity between the query and items in the database, so incomplete sketches may be ineffective in finding the relevant information.To address this problem with incomplete sketches, we propose a new generative adversarial network called SketchCADGAN. This network uses a two-stage cascaded architecture, with the first network attempting to predict a CAD model image from an incomplete sketch and the second network using the CAD model image to predict a completed sketch. Both networks are trained together adversarially. Our approach is proven more effective than other advanced techniques through qualitative and quantitative comparisons. Furthermore, we present the results of the retrieval system using both partially drawn and completed sketches, and demonstrate that incorporating completed sketches from the suggested cascaded GAN architecture results in improved retrieval performance.

Doodle to Object: Practical Zero-Shot Sketch-Based 3D Shape Retrieval

Zero-shot (ZS) sketch-based three-dimensional (3D) shape retrieval (SBSR) is challenging due to the abstraction of sketches, cross-domain discrepancies between two-dimensional sketches and 3D shapes, and ZS-driven semantic knowledge transference from seen to unseen categories. Extant SBSR datasets suffer from lack of data, and no current SBSR methods consider ZS scenarios. In this paper, we contribute a new Doodle2Object (D2O) dataset consisting of 8,992 3D shapes and over 7M sketches spanning 50 categories. Then, we propose a novel prototype contrastive learning (PCL) method that effectively extracts features from different domains and adapts them to unseen categories. Specifically, our PCL method combines the ideas of contrastive and cluster-based prototype learning, and several randomly selected prototypes of different classes are assigned to each sample. By comparing these prototypes, a given sample can be moved closer to the same semantic class of samples while moving away from negative ones. Extensive experiments on two common SBSR benchmarks and our D2O dataset demonstrate the efficacy of the proposed PCL method for ZS-SBSR. Resource is available at https://github.com/yigohw/doodle2object.

Cordon of Conformity: Why DSGE Models Are Not the Future of Macroeconomics

The Rebuilding Macroeconomic Theory Project, led by David Vines and Samuel Wills (2020), is an important, albeit long overdue, initiative to rethink a failing mainstream macroeconomics. Professors Vines and Wills, who must be congratulated for stepping up to the challenge of trying to make mainstream macroeconomics relevant again, call for a new multiple-equilibrium and diverse (MEADE) paradigm for macroeconomics. Their idea is to start with simple models, ideally two-dimensional sketches, that explain mechanisms that can cause multiple equilibria. These mechanisms should then be incorporated into larger DSGE models in a new, multiple-equilibrium synthesis – to see how the fundamental pieces of the economy fit together, subject to it being “properly micro-founded”. This paper argues that the MEADE paradigm is bound to fail, because it maintains the DSGE model as the unifying framework at the center of macroeconomic analysis. The paper reviews 10 fundamental weaknesses inherent in DSGE models which make these models irreparably useless for macroeconomic policy analysis. Mainstream macroeconomics must put DSGE models, once and for all, in the Museum of Implausible Economic Models – and learn important lessons from non-DSGE macroeconomic approaches.

Current Sheets, Plasmoids and Flux Ropes in the Heliosphere

Our understanding of processes occurring in the heliosphere historically began with reduced dimensionality - one-dimensional (1D) and two-dimensional (2D) sketches and models, which aimed to illustrate views on large-scale structures in the solar wind. However, any reduced dimensionality vision of the heliosphere limits the possible interpretations of in-situ observations. Accounting for non-planar structures, e.g. current sheets, magnetic islands, flux ropes as well as plasma bubbles, is decisive to shed the light on a variety of phenomena, such as particle acceleration and energy dissipation. In part I of this review, we have described in detail the ubiquitous and multi-scale observations of these magnetic structures in the solar wind and their significance for the acceleration of charged particles. Here, in part II, we elucidate existing theoretical paradigms of the structure of the solar wind and the interplanetary magnetic field, with particular attention to the fine structure and stability of current sheets. Differences in 2D and 3D views of processes associated with current sheets, magnetic islands, and flux ropes are discussed. We finally review the results of numerical simulations and in-situ observations, pointing out the complex nature of magnetic reconnection and particle acceleration in a strongly turbulent environment.

Cordon of Conformity: Why DSGE models Are Not the Future of Macroeconomics

The Rebuilding Macroeconomic Theory Project, led by David Vines and Samuel Wills (2020), is an important, albeit long overdue, initiative to rethink a failing mainstream macroeconomics. Professors Vines and Wills, who must be congratulated for stepping up to the challenge of trying to make mainstream macroeconomics relevant again, call for a new multiple-equilibrium and diverse (MEADE) paradigm for macroeconomics. Their idea is to start with simple models, ideally two-dimensional sketches, that explain mechanisms that can cause multiple equilibria. These mechanisms should then be incorporated into larger DSGE models in a new, multiple-equilibrium synthesis – to see how the fundamental pieces of the economy fit together, subject to it being ‘properly micro-founded’. This paper argues that the MEADE paradigm is bound to fail, because it maintains the DSGE model as the unifying framework at the center of macroeconomic analysis. The paper reviews 10 fundamental weaknesses inherent in DSGE models which make these models irreparably useless for macroeconomic policy analysis. Mainstream macroeconomics must put DSGE models, once and for all, in the Museum of Implausible Economic Models – and learn important lessons from non-DSGE macroeconomic approaches.

The rebuilding macroeconomic theory project part II: multiple equilibria, toy models, and policy models in a new macroeconomic paradigm

AbstractThis issue of the Oxford Review of Economic Policy is the second in the Rebuilding Macroeconomic Theory project. The papers in the first issue proposed specific improvements to the New-Keynesian Dynamic Stochastic General Equilibrium (NK-DSGE) framework, in response to the events of the 2008 crisis. This issue goes further. We, as editors, now argue that a new multiple-equilibrium and diverse (MEADE) paradigm is needed for macroeconomics. It will emphasize that economies can have more than one stable outcome, and study why. It will require using both toy models, which enable a quick, first-pass, intuitive understanding of a question, and policy models (aka structural economic models) which develop a detailed empirical understanding of the economy. We argue that the seminal IS/LM, Solow–Swan, Ramsey, Real Business Cycle, Taylor, and Clarida/Galí/Gertler models have all been toys, as is the benchmark NK-DSGE model. In the past the models have adapted as the questions changed, and the NK-DSGE model must now do this since it has failed to capture both the salient aspects of the lead-up to the 2008 crisis and the slow recovery afterwards. The way forward in the MEADE paradigm will be to start with simple models, ideally two-dimensional sketches, that explain mechanisms that can cause multiple equilibria. These mechanisms should then be incorporated into larger DSGE models in a new, multiple-equilibrium synthesis. All of this will need to be informed by closer fidelity to the data, drawing on lessons obtained from detailed work on policy models.

Computational schemes between the exact, analytical and numerical solution in present of time—fractional ecological model

This paper investigates the accuracy of three recent computational schemes (the extended simplest method (ESEM), sech—tanh expansion method (STEM), and modified Kudryashov method (MKM)) through calculating the absolute value of error between their solutions and numerical solutions. The computational schemes claim to obtain exact traveling wave solutions of the investigated models; therefore, it supposes the numerical study for any models that have been analytically investigated under any constructed computational solutions that will be matching, but our study shows a different fact. (Khater et al Soft Computing (Submitted)) has studied the computational solutions of the time-fractional Lotka—Volterra (LV) model through the above-mentioned computational schemes. Many solutions have been obtained in different mathematical formulas such as exponential, trigonometric, hyperbolic, etc. These solutions describe the interaction between the high -frequency Langmuir and the low-frequent ion-acoustic waves with many applications in electromagnetic waves, plasma physics, and signal processing through optical fibers, coastal engineering, and fluid dynamics. This manuscript applies the trigonometric quintic B—spline scheme to the fractional LV model along with the Caputo and Fabrizio fractional derivatives and computational obtained solutions for investigating the numerical solutions under each employed analytical scheme. The numerical solutions are simulated in two-dimensional sketches to explain the relation between exact and numerical solutions. This study proves the computational fact hypotheses for obtaining exact solutions, and they all obtain computational solutions.

Models of necessity.

The way chemists represent chemical structures as two-dimensional sketches made up of atoms and bonds, simplifying the complex three-dimensional molecules comprising nuclei and electrons of the quantum mechanical description, is the everyday language of chemistry. This language uses models, particularly of bonding, that are not contained in the quantum mechanical description of chemical systems, but has been used to derive machine-readable formats for storing and manipulating chemical structures in digital computers. This language is fuzzy and varies from chemist to chemist but has been astonishingly successful and perhaps contributes with its fuzziness to the success of chemistry. It is this creative imagination of chemical structures that has been fundamental to the cognition of chemistry and has allowed thought experiments to take place. Within the everyday language, the model nature of these concepts is not always clear to practicing chemists, so that controversial discussions about the merits of alternative models often arise. However, the extensive use of artificial intelligence (AI) and machine learning (ML) in chemistry, with the aim of being able to make reliable predictions, will require that these models be extended to cover all relevant properties and characteristics of chemical systems. This, in turn, imposes conditions such as completeness, compactness, computational efficiency and non-redundancy on the extensions to the almost universal Lewis and VSEPR bonding models. Thus, AI and ML are likely to be important in rationalizing, extending and standardizing chemical bonding models. This will not affect the everyday language of chemistry but may help to understand the unique basis of chemical language.

An A Priori Measure of Visual Difficulty of 2-D Sketches Depicting 3-D Objects

Aiming to enhance understanding of visual obstacles inherent in two-dimensional (2-D) sketches used in high school spatial geometry instruction, we propose a measure of visual difficulty based on two attributes of the sketches: potentially misleading geometrical information (PMI) and potentially helpful geometrical information (PHI). The difficulty of 12 normatively oriented cube-related sketches was theoretically ranked according to their ratios, #PHI/#PMI. The ranking was compared to the actual visual difficulty as measured by the percentage of correct or desired comprehension, individual spatial ability, and study-time allocation. This procedure was repeated for unnormatively oriented sketches, obtained by vertically flipping the original sketches. In both cases, the findings substantiate #PHI/#PMI as an a priori measure of visual difficulty. Practical, theoretical, and methodological implications are inspected and discussed.

SIMULASI SISTEM KERJA BIOSEPTIC TANK BERBASIS DUA DIMENSI

In the business environment, especially in the business of selling a product, it definitely requires a user-friendly tutorial or instructions for using the product, the tutorial can be in the form of flow pictures or in the form of interactive two-dimensional (2D) or three-dimensional (3D) animation. The tutorial can function as a tool for introducing a product for buyers and potential buyers so that buyers' interest will increase and add buyer knowledge about the product. Now the author is encouraged to make a teaching aid using two-dimensional interactive animation that is user-friendly and interesting for PT. Global Core Fibertech. By using two-dimensional sketches to explain the product and use the video directly displayed the bioseptic tank's working system can allow customers to be interested in the product and not close the possibility that other competitors will gradually follow the animation method. With the design of the two-dimensional interactive animation, it is expected to increase the effectiveness, quality and intensity of its sales. With the technology used, the tools for making Adobe Flash CS6 as an application for making interactive animations, Adobe Photoshop CC as an application for making Bioseptic Tank and Actionscript sketches to move the animation process and application development methods used are Waterfall.

Exploring Biases Between Human and Machine Generated Designs

The objective of this work is to explore the possible biases that individuals may have toward the perceived functionality of machine generated designs, compared to human created designs. Toward this end, 1187 participants were recruited via Amazon mechanical Turk (AMT) to analyze the perceived functional characteristics of both human created two-dimensional (2D) sketches and sketches generated by a deep learning generative model. In addition, a computer simulation was used to test the capability of the sketched ideas to perform their intended function and explore the validity of participants' responses. The results reveal that both participants and computer simulation evaluations were in agreement, indicating that sketches generated via the deep generative design model were more likely to perform their intended function, compared to human created sketches used to train the model. The results also reveal that participants were subject to biases while evaluating the sketches, and their age and domain knowledge were positively correlated with their perceived functionality of sketches. The results provide evidence that supports the capabilities of deep learning generative design tools to generate functional ideas and their potential to assist designers in creative tasks such as ideation.

Conceptual Three-Dimensional Modeling Using Intuitive Gesture-Based Midair Three-Dimensional Sketching Technique

We introduce an intuitive gesture-based interaction technique for creating and manipulating simple three-dimensional (3D) shapes. Specifically, the developed interface utilizes low-cost depth camera to capture user's hand gesture as the input, maps different gestures to system commands and generates 3D models from midair 3D sketches (as opposed to traditional two-dimensional (2D) sketches). Our primary contribution is in the development of an intuitive gesture-based interface that enables novice users to rapidly construct conceptual 3D models. Our development extends current works by proposing both design and technical solutions to the challenges of the gestural modeling interface for conceptual 3D shapes. The preliminary user study results suggest that the developed framework is intuitive to use and able to create a variety of 3D conceptual models.

Using graph rewriting methods for the semi-automatic generation of parametric infrastructure models

For the design of large infrastructure projects such as inner-city subway tracks, it proves necessary to consider differing model scales, ranging from the scale of several kilometers down to a few millimeters. This challenge can be addressed by using multi-scale product models comprising multiple levels of detail (LoD). Ensuring consistency across the different LoDs can be achieved by applying procedural and parametric modeling techniques while creating the model. This results in a flexible multi-scale model that can be easily modified on one scale while other scales are automatically updated. However, the correct application of parametric constraints and procedural dependencies has shown to be a very complex and time-consuming process. To address this issue, this papers presents a semi-automated detailing mechanism, which is based on formal procedures based on graphs and graph transformations. This paper discusses how procedural parametric models based on two-dimensional sketches can be represented by graphs and how detailing steps in the form of parametric modeling operations can be formalized by using rule-based graph rewriting.

Deconstruction waste management through 3d reconstruction and bim: a case study

The construction industry is responsible for 50% of the solid waste generated worldwide. Governments around the world formulate legislation and regulations concerning recycling and re-using building materials, aiming to reduce waste and environmental impact. Researchers have also been developing strategies and models of waste management for construction and demolition of buildings. The application of Building Information Modeling (BIM) is an example of this. BIM is emergent technology commonly used to maximize the efficiency of design, construction and maintenance throughout the entire lifecycle. The uses of BIM on deconstruction or demolition are not common; especially the fixtures and fittings of buildings are not considered in BIM models. The development of BIM is based on two-dimensional drawings or sketches, which may not be accurately converted to 3D BIM models. In addition, previous researches mainly focused on construction waste management. There are few studies about the deconstruction waste management focusing on demolition. To fill this gap, this paper aims to develop a framework using a reconstructed 3D model with BIM, for the purpose of improving BIM accuracy and thus developing a deconstruction waste management system to improve demolition efficiency, effective recycling and cost savings. In particular, the developed as-built BIM will be used to identify and measure recyclable materials, as well as to develop a plan for the recycling process.

Muscular Arrangement and Muscle Attachment Sites in the Cervical Region of the American Barn Owl (Tyto furcata pratincola).

Owls have the largest head rotation capability amongst vertebrates. Anatomical knowledge of the cervical region is needed to understand the mechanics of these extreme head movements. While data on the morphology of the cervical vertebrae of the barn owl have been provided, this study is aimed to provide an extensive description of the muscle arrangement and the attachment sites of the muscles on the owl’s head-neck region. The major cervical muscles were identified by gross dissection of cadavers of the American barn owl (Tyto furcata pratincola), and their origin, courses, and insertion were traced. In the head-neck region nine superficial larger cervical muscles of the craniocervical, dorsal and ventral subsystems were selected for analysis, and the muscle attachment sites were illustrated in digital models of the skull and cervical vertebrae of the same species as well as visualised in a two-dimensional sketch. In addition, fibre orientation and lengths of the muscles and the nature (fleshy or tendinous) of the attachment sites were determined. Myological data from this study were combined with osteological data of the same species. This improved the anatomical description of the cervical region of this species. The myological description provided in this study is to our best knowledge the most detailed documentation of the cervical muscles in a strigiform species presented so far. Our results show useful information for researchers in the field of functional anatomy, biomechanical modelling and for evolutionary and comparative studies.

GRIDiron

We present an interactive simulation framework for authoring surgical procedures of soft tissue manipulation using physics-based simulation to animate the flesh. This interactive authoring tool can be used by clinical educators to craft three-dimensional illustrations of the intricate maneuvers involved in craniofacial repairs, in contrast to two-dimensional sketches and still photographs which are the medium used to describe these procedures in the traditional surgical curriculum. Our virtual environment also allows surgeons-intraining to develop cognitive skills for craniofacial surgery by experimenting with different approaches to reconstructive challenges, adapting stock techniques to flesh regions with nonstandard shape, and reach preliminary predictions about the feasibility of a given repair plan. We use a Cartesian grid-based embedded discretization of nonlinear elasticity to maximize regularity, and expose opportunities for aggressive multithreading and SIMD accelerations. Using a grid-based approach facilitates performance and scalability, but constrains our ability to capture the topology of thin surgical incisions. We circumvent this restriction by hybridizing the grid-based discretization with an explicit hexahedral mesh representation in regions where the embedding mesh necessitates overlap or nonmanifold connectivity. Finally, we detail how the front-end of our system can run on lightweight clients, while the core simulation capability can be hosted on a dedicated server and delivered as a network service.