Continuously Generalizing Buildings to Built-up Areas by Aggregating and Growing

International audienceTo enable smooth zooming, we propose a method to continuously generalize buildings from a given start map to a smaller-scale goal map, where there are only built-up area polygons instead of individual building polygons. We name the buildings on the start map original buildings. For an intermediate scale, we aggregate the original buildings that will become too close by adding bridges. We grow (bridged) original buildings based on buffering, and simplify the grown buildings. We take into account the shapes of the buildings both at the previous map and goal map to make sure that the buildings are always growing. The running time of our method is in O(n 3), where n is the number of edges of all the original buildings. The advantages of our method are as follows. First, the buildings grow continuously and, at the same time, are simplified. Second, right angles of buildings are preserved during growing: the merged buildings still look like buildings. Third, the distances between buildings are always larger than a specified threshold. We do a case study to show the performances of our method

Sol-Gel Process and Engineering Nanostructure

The production of ceramic nanostructures and engineering of their structure are the goals of the high-tech industry. Researchers prefer the sol-gel route to control the material at the atomic scale among other methods. In this chapter, we describe the production of ceramic nanostructures in different forms such as film, fiber, glass, and powder. We also discuss about microstructures and properties of these ceramic materials and the relationship between them

Personalized 3D mannequin reconstruction based on 3D scanning

Purpose Currently, a common method of reconstructing mannequin is based on the body measurements or body features, which only preserve the body size lacking of the accurate body geometric shape information. However, the same human body measurement does not equal to the same body shape. This may result in an unfit garment for the target human body. The purpose of this paper is to propose a novel scanning-based pipeline to reconstruct the personalized mannequin, which preserves both body size and body shape information. Design/methodology/approach The authors first capture the body of a subject via 3D scanning, and a statistical body model is fit to the scanned data. This results in a skinned articulated model of the subject. The scanned body is then adjusted to be pose-symmetric via linear blending skinning. The mannequin part is then extracted. Finally, a slice-based method is proposed to generate a shape-symmetric 3D mannequin. Findings A personalized 3D mannequin can be reconstructed from the scanned body. Compared to conventional methods, the method can preserve both the size and shape of the original scanned body. The reconstructed mannequin can be imported directly into the apparel CAD software. The proposed method provides a step for digitizing the apparel manufacturing. Originality/value Compared to the conventional methods, the main advantage of the authors’ system is that the authors can preserve both size and geometry of the original scanned body. The main contributions of this paper are as follows: decompose the process of the mannequin reconstruction into pose symmetry and shape symmetry; propose a novel scanning-based pipeline to reconstruct a 3D personalized mannequin; and present a slice-based method for the symmetrization of the 3D mesh. </jats:sec

Reinforcement Learning for Scalable Train Timetable Rescheduling with Graph Representation

Train timetable rescheduling (TTR) aims to promptly restore the original operation of trains after unexpected disturbances or disruptions. Currently, this work is still done manually by train dispatchers, which is challenging to maintain performance under various problem instances. To mitigate this issue, this study proposes a reinforcement learning-based approach to TTR, which makes the following contributions compared to existing work. First, we design a simple directed graph to represent the TTR problem, enabling the automatic extraction of informative states through graph neural networks. Second, we reformulate the construction process of TTR's solution, not only decoupling the decision model from the problem size but also ensuring the generated scheme's feasibility. Third, we design a learning curriculum for our model to handle the scenarios with different levels of delay. Finally, a simple local search method is proposed to assist the learned decision model, which can significantly improve solution quality with little additional computation cost, further enhancing the practical value of our method. Extensive experimental results demonstrate the effectiveness of our method. The learned decision model can achieve better performance for various problems with varying degrees of train delay and different scales when compared to handcrafted rules and state-of-the-art solvers

Tracking gate algorithm for general nonlinear systems with target class information

Multitarget tracking in clutter usually involves data association. The traditional method to handle this problem is to construct a tracking gate for predicting the position of the target being tracked, which leads to great uncertainties of measurements-to-tracks association with the unknown class of targets. This paper proposes a new tracking gate algorithm for general nonlinear systems, where the target class information is integrated into our algorithm. Firstly, a joint probability density description of the target state and target class is given, by which the tracking gates for each target class in general nonlinear system are developed. Then, a simulation with ground formation target tracking is carried out to examine our algorithm. Compared with the traditional tracking gate, the results demonstrate that our algorithm has significantly improved the probabilities of the measurements-to-tracks association

A Simulation Method Based on Material-Drying Oven Integration for Hot Air Drying of Lentinus edodes and Its Application

In this paper, a simulation method based on material-drying oven integration was developed for the hot air-drying process of Lentinus edodes. First of all, the drying characteristics were investigated under different drying conditions, and drying kinetic models were obtained at different air temperatures, relative humidities (RHs) and air flow rates. Then, drying kinetic derivative models to predict the drying process under different working conditions were obtained and used to calculate water evaporation rate, and the rate of water evaporation was introduced into the heat and mass transfer equations to develop mathematical models based on material-drying oven integration. Using the models, the pattern of temporal changes in air temperature, RH and air flow rate at any position inside the oven and moisture ratio (MR) was obtained. Finally, the drying characteristics were worked out using the integrated models. Overall, significant non-uniformity occurred during the drying process. As drying proceeded, non-uniformity decreased. In the direction of air flow, non-uniformity was more significant at positions closer to the oven’s top and bottom. In the transverse direction, non-uniformity was more significant at positions closer to the middle. In summary, the simulation method for hot air-drying of Lentinus edodes is meaningful for guiding the structural design of the drying chamber, the optimization of the drying process and the improvement of the product quality

A 10:1 Bandwidth Cryogenic Quadruple-Ridged Flared Horn Design for Reflector Antennas in Radio Astronomy

A two port 2.4 to 24 GHz cryogenic Quadruple-Ridged Flared Horn (QRFH) Feed with 10:1 impedance bandwidth is selected for presentation and investigation in this paper. The antenna geometry is formed by using simulation-based optimization which satisfies several stringent design requirements, including impedance bandwidth and radiation characteristics of the proposed antenna. To verify the theoretical performance, a prototype of the optimized QRFH was manufactured and tested. The reflection coefficients of the antenna are below -10 dB and the mutual coupling is better than -25 dB. Meanwhile, the antenna aperture efficiency is above 55% and maximum gain is from 10.5 to 21.1dBi across the desired working frequency band. Both the simulated and measured results exhibit good agreement. To demonstrate the suitability of the proposed design in a practical environment, a prototype Cryogenic system composed of a cryogenic Dewar and a QRFH, has been designed and its performance was measured. The results showed that the physical temperature reached an acceptable level which was less than 45 K. The overall performance of the proposed QRFH feed suggests that it would be applicable to the receivers for the Square Kilometre Array (SKA) reflector antenna, and meets requirements of the SKA advanced instrumentation program (AIP)

Lead and copper-induced hormetic effect and toxicity mechanisms in lettuce (Lactuca sativa L.) grown in a contaminated soil

Lead (Pb) and copper (Cu) contamination seriously threatens agricultural production and food safety. This study aims to investigate Pb and Cu induced hormetic effect and toxicity mechanisms in lettuce (Lactuca sativa L.) and establish reliable empirical models of potentially toxic elements (PTEs) transfer in the soil–plant system. The content and distribution of Pb and Cu at subcellular levels in lettuce plants were examined using inductively coupled plasma-mass spectrometry, differential centrifugation and micro-X-ray fluorescence spectroscopy. The PTE-loaded capacity of Pb that ensures food safety was lower than that of Cu in the studied soil, but the PTE-loaded capacity of Pb that limits yield was higher than that of Cu. Lead in lettuce roots mainly accumulated in the cell wall (41%), while Cu mainly accumulated in the vacuoles (46%). The Pb and Cu were primarily distributed in the radicle of lettuce seeds under severe PTE stress, resulting in no seed development. Iron plaque formed on the root surface of lettuce seedlings and sequestered Pb and Cu via chelation. At the same concentration, lettuce was less tolerant to Cu in contaminated soil than Pb due to the higher activity of Cu ions in the soil. Lead was more phytotoxic to lettuce than Cu, however, since the radicle emerged from the seed under severe Cu levels, while it did not protrude under severe Pb levels. The potentially damaging effect of Pb in the visually healthy lettuce appeared to be higher than that of Cu under the same soil contamination level