Two-dimensional Objects Research Articles

Deep learning fluid flow reconstruction around arbitrary two-dimensional objects from sparse sensors using conformal mappings

The usage of neural networks (NNs) for flow reconstruction (FR) tasks from a limited number of sensors is attracting strong research interest owing to NNs’ ability to replicate high-dimensional relationships. Trained on a single flow case for a given Reynolds number or over a reduced range of Reynolds numbers, these models are unfortunately not able to handle flows around different objects without re-training. We propose a new framework called Spatial Multi-Geometry FR (SMGFR) task, capable of reconstructing fluid flows around different two-dimensional objects without re-training, mapping the computational domain as an annulus. Different NNs for different sensor setups (where information about the flow is collected) are trained with high-fidelity simulation data for a Reynolds number equal to ∼300 for 64 objects randomly generated using Bezier curves. The performance of the models and sensor setups is then assessed for the flow around 16 unseen objects. It is shown that our mapping approach improves percentage errors by up to 15% in SMGFR when compared to a more conventional approach where the models are trained on a Cartesian grid and achieves errors under 3%, 10%, and 30% for predictions of pressure, velocity, and vorticity fields, respectively. Finally, SMGFR is extended to predictions of snapshots in the future, introducing the Spatiotemporal MGFR (STMGFR) task. A novel approach is developed for STMGFR involving splitting deep neural networks into a spatial and a temporal component. We demonstrate that this approach is able to reproduce, in time and in space, the main features of flows around arbitrary objects.

Artificial Visual System for Orientation Detection Based on Hubel-Wiesel Model.

The Hubel–Wiesel (HW) model is a classical neurobiological model for explaining the orientation selectivity of cortical cells. However, the HW model still has not been fully proved physiologically, and there are few concise but efficient systems to quantify and simulate the HW model and can be used for object orientation detection applications. To realize a straightforward and efficient quantitive method and validate the HW model’s reasonability and practicality, we use McCulloch-Pitts (MP) neuron model to simulate simple cells and complex cells and implement an artificial visual system (AVS) for two-dimensional object orientation detection. First, we realize four types of simple cells that are only responsible for detecting a specific orientation angle locally. Complex cells are realized with the sum function. Every local orientation information of an object is collected by simple cells and subsequently converged to the corresponding same type complex cells for computing global activation degree. Finally, the global orientation is obtained according to the activation degree of each type of complex cell. Based on this scheme, an AVS for global orientation detection is constructed. We conducted computer simulations to prove the feasibility and effectiveness of our scheme and the AVS. Computer simulations show that the mechanism-based AVS can make accurate orientation discrimination and shows striking biological similarities with the natural visual system, which indirectly proves the rationality of the Hubel–Wiesel model. Furthermore, compared with traditional CNN, we find that our AVS beats CNN on orientation detection tasks in identification accuracy, noise resistance, computation and learning cost, hardware implementation, and reasonability.

Cichlids and stingrays can add and subtract \u2018one\u2019 in the number space from one to five

The numerical understanding of cichlids and stingrays was examined regarding addition and subtraction abilities within the number space of one to five. Experiments were conducted as two-alternative forced-choice experiments, using a delayed matching to sample technique. On each trial, fish had to perform either an addition or subtraction, based on the presentation of two-dimensional objects in two distinct colors, with the color signaling a particular arithmetic process. Six cichlids and four stingrays successfully completed training and recognized specific colors as symbols for addition and subtraction. Cichlids needed more sessions than stingrays to reach the learning criterion. Transfer tests showed that learning was independent of straightforward symbol memorization. Individuals did not just learn to pick the highest or lowest number presented based on the respective color; instead, learning was specific to adding or subtracting ‘one’. Although group results were significant for both species in all tests, individual results varied. Addition was learned more easily than subtraction by both species. While cichlids learned faster than stingrays, and more cichlids than stingrays learned the task, individual performance of stingrays exceeded that of cichlids. Previous studies have provided ample evidence that fish have numerical abilities on par with those of other vertebrate and invertebrate species tested, a result that is further supported by the findings of the current study.

Moment of inertia: tricky ways

We use dimensional analysis as well as the parallel axis theorem to obtain the moment of inertia for some homogeneous two-dimensional objects. These objects should possess some sort of symmetry: they should have shapes that can be decomposed into smaller copies of themselves. In the second part of the article, it is seen that as the moment of inertia of a composed object is the summation of the moment of inertia of its decomposed parts, this may give us a shortcut to obtaining the moment of inertia of some objects.

A Novel Untethered Hand Wearable with Fine-Grained Cutaneous Haptic Feedback.

During open surgery, a surgeon relies not only on the detailed view of the organ being operated upon and on being able to feel the fine details of this organ but also heavily relies on the combination of these two senses. In laparoscopic surgery, haptic feedback provides surgeons information on interaction forces between instrument and tissue. There have been many studies to mimic the haptic feedback in laparoscopic-related telerobotics studies to date. However, cutaneous feedback is mostly restricted or limited in haptic feedback-based minimally invasive studies. We argue that fine-grained information is needed in laparoscopic surgeries to study the details of the instrument’s end and can convey via cutaneous feedback. We propose an exoskeleton haptic hand wearable which consists of five 4 × 4 miniaturized fingertip actuators, 80 in total, to convey cutaneous feedback. The wearable is described as modular, lightweight, Bluetooth, and WiFi-enabled, and has a maximum power consumption of 830 mW. Software is developed to demonstrate rapid tactile actuation of edges; this allows the user to feel the contours in cutaneous feedback. Moreover, to demonstrate the idea as an object displayed on a flat monitor, initial tests were carried out in 2D. In the second phase, the wearable exoskeleton glove is then further developed to feel 3D virtual objects by using a virtual reality (VR) headset demonstrated by a VR environment. Two-dimensional and 3D objects were tested by our novel untethered haptic hand wearable. Our results show that untethered humans understand actuation in cutaneous feedback just in a single tapping with 92.22% accuracy. Our wearable has an average latency of 46.5 ms, which is much less than the 600 ms tolerable delay acceptable by a surgeon in teleoperation. Therefore, we suggest our untethered hand wearable to enhance multimodal perception in minimally invasive surgeries to naturally feel the immediate environments of the instruments.

Development of interactive learning media in computer network using augmented reality technology

Technological development affect on aspects of education that impact on learning activities. In computer networks learning, there is still rarely media use which has an impact on students’ understanding of how to install computer networks. Current mobile phones have many features that can be used to play games, watch videos, listen to music, personal assistant, find information, GPS, and many more. One of the interesting technologies that can be developed on mobile phones is Augmented Reality. Augmented Reality (AR) is a technology that combines two-dimensional or three-dimensional virtual objects into a real three-dimensional environment and then projects these virtual objects in real time. This research discusses the development of learning media Augmented reality of computer network installation. The purpose of this research is to develop augmented reality learning media and build media that makes it easier for students to understand the process of installing computer networks that becomes an alternative as a learning media. The method used is Research and Development (R&D).

A novel approach to determine the surface area of buckspoor spider webs and other irregular-shaped two-dimensional objects

Arising from the practical need to determine the surface area of the buckspoor spider webs of Seothyra schreineri, an approach for area determination was developed based on image processing. The method rendered results that were considered valid and reliable. Aside from the present application to determine the surface area of a spider web, this approach could potentially be used to accurately determine the area of any two-dimensional shape. For each web's photograph:•The boundary of the web was outlined.•Seeded region growing was used to segment the image into a web region and a background region.•The area of the web was determined as a pixel count, and then converted to mm2.

3D object detection using improved PointRCNN

Recently, two-dimensional object detection (2D object detection) has been introduced in numerous applications such as building exterior diagnosis, crime prevention and surveillance, and medical fields. However, the distance (depth) information is not enough for indoor robot navigation, robot grasping, autonomous running, and so on, with conventional object detection. Therefore, in order to improve the accuracy of 3D object detection, this paper proposes an improvement of Point RCNN, which is a segmentation-based method using RPNs and has performed well in 3D detection benchmarks on the KITTI dataset commonly used in recognition tasks for automatic driving. The proposed improvement is to improve the network in the first stage of generating 3D box candidates in order to solve the problem of frequent false positives. Specifically, we added a Squeeze and Excitation (SE) Block to the network of pointnet++ that performs feature extraction in the first stage and changed the activation function from ReLU to Mish. Experiments were conducted on the KITTI dataset, which is commonly used in research aimed at automated driving, and an accurate comparison was conducted using AP. The proposed method outperforms the conventional method by several percent on all three difficulty levels.

Pose Detection of Aerial Image Object Based on Constrained Neural Network

Constraints often exist in the high-dimensional data output in object detection, such as the inverse vector (cos θ, sin θ) of the two-dimensional object and the attitude quaternion of the threedimensional object. The range of each component of the output value of the traditional neural network is unconstrained, which is difficult to meet the needs of practical problems. To solve this problem, this paper designed the transformation network layer according to the high dimensional space transformation theory and constructed a constrained neural network model to detect the pose of objects from a single aerial image. Firstly, in the yolov3 network structure, according to the size of the three field scales, three scale transformation network layers are added correspondingly to implement the constrained unit quaternion field. Secondly, according to the characteristics of quaternion, we proposed a special loss function. Then a new constrained neural network called the quaternion field pose network (qfiled PoseNet) model is constructed, which can predict the probability field of the object and the contained unit quaternion field respectively. Next, The object’s probability field is generated to determine the 2D bounding box of the object, and the unit quaternion field is generated to determine the 3D rotation R. Finally, combining the rotation matrix R and the 2D bounding box of the object to calculate the 3D translation T. We used our method to experiment on DOTA1.5 data set and the HSRC2016 data set respectively. The experimental results show that our method can detect the pose of the object well.

Two-dimensional THz reflectometry of a periodic structure obtained by additive technology

This paper considers the development and application of a system of reflectometry for the analysis of the homogeneity of structures manufactured by additive technologies. A system of reflectometry based on a backward wave oscillator, a two-dimensional object positioning system and an optoacoustic detector (Goley cell) is described. The results of reflectometry of the hexagonal periodic structure of cells based on acrylonitrile butadiene styrene at a wavelength of 343 microns are presented.

Kinetic analysis of the plasma sheath around an electron-emitting object with elliptic cross section.

The structure of the sheath and the current exchange of two-dimensional electron-emitting objects with elliptic cross section immersed at rest in Maxwellian plasmas are investigated with an energy-conserving stationary Vlasov-Poisson solver free of statistical noise. The parameter domains for current collection within the orbital-motion-limited (OML) regime and current emission in space-charge-limited (SCL) conditions were studied by varying the characteristic dimension of the ellipse, its eccentricity, and the emission level. The analysis reveals the correlations between the onset of the non-OML and SCL regimes and the local curvature of the ellipse. As compared to nonemitting ellipses, electron emission broadens the parameter domain for OML current collection for ions and reduces considerably the current drop for non-OML conditions. Under identical plasma environments, elliptic bodies are more prone to operate under non-OML and SCL conditions than cylinders. Their emitted current in SCL conditions can be computed accurately from well-known results for cylinders if appropriate dimensionless variables and an equivalent radius are used. The role of the eccentricity, which acts as an integrability-breaking parameter, on the filamentation of the distribution function of the attracted species is studied.

THE EFFECT OF 3D TECHNOLOGIES IN STEREOMETRY TRAINING

The software proposed in the report can be used as a technological tool in the teaching and learning of the discipline of stereometry. The aim is to improve the learning process by supporting the development of students’ creativity and spatial imagination, qualities needed in the study of spatial geometric bodies. A new boundary method is used in the generation of geometric objects. This new method uses elements of the Cavalieri Indivisible method and Isaac Newton's boundary method, thus achieving higher accuracy with respect to generated objects compared to 3D systems that use the rules of trigonometry in the construction of geometric bodies. This article performs a comparative analysis between a traditional and a new method for generating 3D geometric objects according to certain parameters and criteria. The new method involved in the analysis was proposed by the author of the report. While the traditional one is based on trigonometry. Two parameters were studied, one for accuracy in generating objects, and the second determining speed. In order to generate cylindrical bodies, are used the quadratic Bézier curve and the 3D modeling technique known as an extrusion, which transforms two-dimensional objects into three-dimensional ones.. One way to generate a prism and pyramid is by extruding polygons. This report presents a new way of constructing edged bodies. The considered technique for 3D modeling participates in the analysis of the studied methods.

On the Diffuse Interface Models for High Codimension Dispersed Inclusions

Diffuse interface models are widely used to describe the evolution of multi-phase systems of various natures. Dispersed inclusions described by these models are usually three-dimensional (3D) objects characterized by phase field distribution. When employed to describe elastic fracture evolution, the dispersed phase elements are effectively two-dimensional (2D) objects. An example of the model with effectively one-dimensional (1D) dispersed inclusions is a phase field model for electric breakdown in solids. Any diffuse interface field model is defined by an appropriate free energy functional, which depends on a phase field and its derivatives. In this work we show that codimension of the dispersed inclusions significantly restricts the functional dependency of the free energy on the derivatives of the problem state variables. It is shown that to describe codimension 2 diffuse objects, the free energy of the model necessarily depends on higher order derivatives of the phase field or needs an additional smoothness of the solution, i.e., its first derivatives should be integrable with a power greater than two. Numerical experiments are presented to support our theoretical discussion.

Periodically modulated skyrmion strings in Cu2OSeO3

Magnetic skyrmions are vortex-like spin textures, which are usually treated as two-dimensional objects. In their lattice state, they form well-ordered, hexagonal structures, which have been studied in great detail. To obtain a three-dimensional (3D) skyrmion crystal, these planes can be envisaged to be stacked up forming skyrmion strings in the third dimension. Here, we report the observation of a 3D skyrmion phase in Cu2OSeO3 by carrying out reciprocal space mapping in resonant elastic x-ray scattering. We observe regions in the magnetic field-cooling phase diagram in which the skyrmion phase apparently coexists with the conical phase. However, such a coexistence is forbidden due to symmetry arguments. Instead, the skyrmion strings themselves are periodically modulated along their axes, as confirmed by micromagnetic simulations. The periodic modulation is in fact a necessary consequence of the evolution of the skyrmion phase out of the conical state and should therefore be a universal property of skyrmion strings in chiral helimagnets.

Two-Dimensional Laser Melting of Lunar Regolith Simulant Using the MOONRISE Payload on a Mobile Manipulator.

Laser melting experiments were carried out with the MOONRISE payload, installed on the mobile manipulator, MIRA3D. The MOONRISE payload was developed to demonstrate the feasibility of additive processing of lunar regolith with the help of lasers on the Moon within a lunar surface mission in the next years. The development of hardware for the flight to the moon is well advanced and, if successful, would pave the way for the use of laser melting for production of components from regolith. The aim of the experiments described in this article was to test the planned scenario on the Moon, especially the interaction between laser payload, manipulator, and soil surface, and to identify suitable process parameters for production of two-dimensional (2D) objects. The ability to produce 2D objects is an important intermediate step on the way to produce large three-dimensional structures such as habitats, walls, or foundations. During the experiments, specimens with a size of ∼20 × 20 × 4 mm were repeatedly produced. As analog material, two synthetic lunar soils produced with the modular regolith simulant systems from Technische Universität Braunschweig (TUBS) were used. The experiments were conducted under Earth gravity and atmospheric conditions. This article describes the hardware used, procedure for carrying out the experiments, and properties of the produced samples.

Convex Polygonal Hull for a Pair of Irregular Objects

Introduction. Optimization placement problems are NP-hard. In most cases related to cutting and packing problems, heuristic approaches are used. The development of analytical methods for mathematical modeling of the problems is of paramount important for expanding the class of placement problems that can be solved optimally using state of the art NLP-solvers. The problem of placing two irregular two-dimensional objects in a convex polygonal region of the minimum size, which is a convex polygonal hull of the minimum area or perimeter, is considered. Continuous rotations and translations of non-overlapping objects are allowed. To solve the problem of optimal compaction of a pair of objects, two algorithms are proposed. The first is a sequentially search for local extrema on all feasible subdomains using a solution tree. The second algorithm searches for a locally optimal extremum on a single subdomain using a "good" feasible starting point. Purpose of the paper. Show how to construct a minimal convex polygonal hull for two continuously moving irregular objects bounded by circular arcs and line segments. Results. A mathematical model is constructed in the form of a nonlinear programming problem using the phi-function technique. Two algorithms are proposed for solving the problem of placing a pair of objects in order to minimize the area and perimeter of the enclosing polygonal area. The results of computational experiments are presented. Conclusions. The construction of a minimal convex polygonal hull for a pair of two-dimensional objects having an arbitrary spatial shape and allowing continuous rotations and translations makes it possible to speed up the process of finding feasible solutions for the problem of placing a large number of objects with complex geometry. Keywords: convex polygonal hull, irregular objects, phi-function technique, nonlinear optimization.

Development of Augmented Reality Application for Learning Computer Network Device

<span lang="EN-US">Applied augmented reality works by detecting imageries or pictures, normally called markers, by using smartphone camera that detects these preplaced markers. Augmented reality has seen wide application in various fields, one of them is education. In the field of education, augmented reality is utilized to make learning process more engaging and attractive. Starting from the problem that learning computer networks on introduce to network device which is currently still delivered conventionally. So, this research makes a solution to this problem by developing learning media using augmented reality (AR) technology, which is a technology that combines two-dimensional or three-dimensional virtual objects into a real environment and then projects these virtual objects in real time. The purpose of this research is to build AR-based applications in learning computer network devices in order to increase understanding, generate motivation and student interest. The methodology used in this research consist of Envisioning Phase(Problem Identification, Planning Phase(Planning), Developing Phase(Design), Stabilizing Phase(Testing), Deploying Phase(Implementation). This study uses 31 students as sample and the data was analyzed using the SUS(System Usability Scale). The result show </span><span lang="EN-US">evaluates the usability using SUS of 31 respondents and it can be concluded that this AR application can be accepted by these students in its use with </span><span lang="EN-US">SUS Score obtained was 78.5</span>

Performance Study of Minimax and Reinforcement Learning Agents Playing the Turn-based Game Iwoki

ABSTRACT Iwoki math is an abstract board game that consists on placing tiles and that combines the calculation of simple mathematical operations with the spatial perception of two-dimensional objects. Due to its inherent features, it is also a very challenging environment to test different artificial intelligence technologies and methods. In this paper, a series of intelligent agents with different reasoning and decision capacities have been developed based on different artificial intelligence techniques applied to game theory, such as Minimax or Reinforcement Learning. Their capabilities have been tested by playing games with each other, but also against human players, obtaining remarkable results. The experimental results ratify conclusions already known at a theoretical level but also provide a new contribution that could be the basis for future research.

A Traceability Public Service Cloud Platform Incorporating IDcode System and Colorful QR Code Technology for Important Product

At present, the epidemic situation of COVID-19 is raging rampantly in the whole world, affecting the hearts of billions of people. The new coronavirus has been detected in many foods and agricultural products. At the same time, vaccines and medicines to prevent or treat COVID-19 are also stepping up research and development and gradually put into use. The quality and safety of foods, medicines, and agricultural products are directly related to the lives and health of people. There are many potential dangers and hidden risks of accidents in the production, sale, and transportation of dangerous goods and special equipment. Therefore, it is necessary to effectively monitor and record the workflow of the above productions or goods. In this paper, we developed an important product traceability public service cloud platform (IPTPSCP) based on batch identification and record keeping with International Two-Dimensional Code Object Identifier System (IDcode) coding rules. Through a case study of the tea factory that produces and sells Xinyang Maojian tea, a test and implementation of IPTPSCP was shown by designing a colorful QR code to prevent the traceability information from being forged in batches. Judging from the overall effect of the practical application of more than a dozen settled enterprises, IPTPSCP has improved the efficiency of data collection and monitoring by about 13%. The results show that the IPTPSCP can be considered as an effective tool to guarantee the quality and safety of products. Besides, since it is not required for the enterprise to invest much money and manpower to develop software, IPTPSCP reduces the cost of implementing product traceability by about 36%.

EFFECTIVE THERMOPHYSICAL PROPERTIES OF POWDER MATERIALS DURING SINTERING UNDER ELECTRONBEAM HEATING

Background. Development of the consolidation processes of powder products using highly concentrated energy sources is impossible without a detailed analysis of the processes of thermal conditions arising in these products. Objective. The aim of the study is to select a method for calculating the thermal conductivity of a porous body, which will be established under various conditions of electron-beam sintering of molybdenum compacts, and to study the effect of the parameters of the porous structure on the thermal conductivity. Methods. An analysis of the sintering process in finite element calculations, in problems of thermal conductivity for two-dimensional and three-dimensional domains, simulating the real porous structure of molybdenum compaction and a regular porous structure with dense packing of spheres is proposed. Results. Mathematical analysis of the contribution of re-radiation to the total thermal conductivity of the porous material is performed. The obtained dependences of the relative thermal conductivity on the porosity of the material and the relative radius of contacts between its particles are presented. Conclusions. According to the results of the mathematical analysis of the conditions of heat transfer in a porous compact of molybdenum for the case of electron-beam heating, it was found that the radiant component of the thermal conductivity of a porous body with pores of the order of 2.5 μm is four orders of magnitude less than the conductive component of its thermal conductivity. Based on the results of finite element modeling of two-dimensional and three-dimensional porous objects, a significant effect of the contact area between particles on their integral thermal conductivity has been established, especially at small sizes of these contacts. At the same time, almost linear effect of porosity on thermal conductivity was established at contact radii between particles > 0.1 Rparticles. A significant influence of the uniformity of the distribution of contacts in aporous material on the uniformity of the temperature field in it is shown.