Topology optimization-based visual element configuration method for exhibition display design

Sentinel-1A SAR and sentinel-2A MSI data fusion for urban ecosystem service mapping

Modeling of trees group is one of the key issues of building virtual forest environment. A new model of trees group with spatial characteristics is proposed. The model focusing on describing the spatial structure of tree populations and their topology relations, takes into account the overall distribution of trees group. In the process of modeling, TIN is used to interconnect roots of adjacent trees so as to form Delaunay triangulation networks. Rule-based method is used to establish single tree model with data from the sample plots. Compact octree is used to divide up the model so as to effectively simulate and analyze trees environment in three dimensions. Finally the tree model and modeling method are realized by Visual C++ and OpenGL. The modeling method is tested by measurement data.

Landform recognition is one of the most significant aspects of geomorphology research, which is the essential tool for landform classification and understanding geomorphological processes. Watershed object-based landform recognition is a new spot in the field of landform recognition. However, in the relevant studies, the quantitative description of the watershed generally focused on the overall terrain features of the watershed, which ignored the spatial structure and topological relationship, and internal mechanism of the watershed. For the first time, we proposed an effective landform recognition method from the perspective of the watershed spatial structure, which is separated from the previous studies that invariably used terrain indices or texture derivatives. The slope spectrum method was used herein to solve the uncertainty issue of the determination on the watershed area. Complex network and P–N terrain, which are two effective methodologies to describe the spatial structure and topological relationship of the watershed, were adopted to simulate the spatial structure of the watershed. Then, 13 quantitative indices were, respectively, derived from two kinds of watershed spatial structures. With an advanced machine learning algorithm (LightGBM), experiment results showed that the proposed method showed good comprehensive performances. The overall accuracy achieved 91.67% and the Kappa coefficient achieved 0.90. By comparing with the landform recognition using terrain indices or texture derivatives, it showed better performance and robustness. It was noted that, in terms of loess ridge and loess hill, the proposed method can achieve higher accuracy, which may indicate that the proposed method is more effective than the previous methods in alleviating the confusion of the landforms whose morphologies are complex and similar. In addition, the LightGBM is more suitable for the proposed method, since the comprehensive manifestation of their combination is better than other machine learning methods by contrast. Overall, the proposed method is out of the previous landform recognition method and provided new insights for the field of landform recognition; experiments show the new method is an effective and valuable landform recognition method with great potential as well as being more suitable for watershed object-based landform recognition.

HI-Light: A Glass-Waveguide-Based "Shell-and-Tube" Photothermal Reactor Platform for Converting CO2 to Fuels.

Information about the relative size of spatial regions is often easily accessible and, when combined with other types of spatial information, it can be practically very useful. In this paper we combine a simple framework for reasoning about qualitative size relations with the Region Connection Calculus RCC-8, a widely studied approach for qualitative spatial reasoning with topological relations. Reasoning about RCC-8 relations is NP-hard, but a large maximal tractable subclass of RCC-8 called H8 was identified. Interestingly, any constraint in RCC-8 - H8 can be consistently reduced to a constraint in Ĥ8, when an appropriate size constraint between the spatial regions is supplied. We propose an O(n3) time path-consistency algorithm based on a novel technique for combining RCC-8 constraints and relative size constraints, where n is the number of spatial regions. We prove its correctness and completeness for deciding consistency when the input contains topological constraints in Ĥ8. We also provide results on finding a consistent scenario in O(n3) time both for combined topological and relative size constraints, and for topological constraints alone. This is an O(n 2 ) improvement over the known methodsKeywordsSpatial RegionBasic RelationTopological RelationSpatial ReasoningSize ConstraintThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Engineering waveguide surface by gradient etching for uniform light scattering in photocatalytic applications

Spatiotemporal data is multi-dimensional, including time dimension, space dimension, and attribute dimension. Because the spatial characteristics, attribute characteristics, associations, etc. of information objects change with time dimension, various topological relationships are intertwined. The existing spatio-temporal data structure model is difficult to express the temporal and spatial characteristics of information objects and the dynamic evolution of spatiotemporal relationships. Not conducive to the query of time and space nodes. On the other hand, the space-time model mostly stays in the theoretical stage and lacks practical application. The main work of this research is as follows:1. For the spurious coupling of spatiotemporal relationship of existing spatiotemporal data, reconstruct spatiotemporal data, design spatiotemporal data structure, and sort out spatiotemporal relationship. 2.A multi-timeline ground state correction model based on region contour is proposed, which reduces the storage redundancy of spatial information, improves the efficiency of information query, and improves the scalability of the system. 3.Design and implement a time-space-based hierarchical spatiotemporal correlation information system, which flexibly switches the spatiotemporal background of information objects at different time nodes, realizes the dynamic linkage of spatiotemporal data, and facilitates data analysis and data mining of spatiotemporal objects.

Visual design is a crucial tool for communicating ideas through images rather than words or printed text. It enables readers to visually interpret and understand information, potentially solving problems across various life aspects. Traditional reading patterns usually flow from left to right and from top to bottom, while some Asian scripts are written in horizontal rows from left to right or in vertical columns from top to bottom. Lines guide the eye between sections and visual elements, while white space allows the eye to rest and focus on targeted areas. The purpose of arranging the five elements of layout design—text, images, lines, shapes, and white space—is to capture the reader's attention and effectively convey information. In this study, researchers conducted a visual content analysis of a poster with 40 Generation Z respondents to investigate their reading direction. This generation is known for its frequent use of various gadgets and preference for short, simple text to comprehend content. The researchers intentionally designed a vertical banner-sized poster representing the Asian Winter Olympics as a sample. The events included Sapporo 1972 and Nagano 1998 in Japan, PyeongChang 2018 in South Korea, and Beijing 2022 in China. The poster is segmented into four sections from top to bottom, each depicting one of the Winter Olympics events from 1972 to 2022. Coding categories were developed to analyse text layout, lines, and white space. However, the colours and images of these emblems and symbols of the Winter Olympic Games were predetermined, so colours and images were not examined in this study. This exploratory study of Generation Z offers an analytical approach to understanding the reading orientation of Generation Z and serves as a basis for future research. Additionally, several informants tended to scan the poster for information, even though it was not indicated that the poster could be interacted with via an app on their mobile phones.

The research of parallel mechanism (PM) configuration involves many problems. From topology to configuration, dimensional constraint, etc., how to establish the relationship between topology and configuration with effective methods is a long-term challenge for the configuration design. In this paper, the chemical molecular spatial structure (CMSS) is linked with the configuration of symmetrical parallel mechanism (SPM). Starting from the methane molecule (CH4), a spatial structural topological relation is obtained. Based on graph theory and the spatial structural topological relation, a new expression method with topological graph and its kinematic pair adjacency matrix for spatial SPM is proposed. Then, the expression and analysis for the characteristics of spatial SPM are obtained. Finally, by taking the 3-RPS PM and the 3-RRC PM as examples, the effectiveness and corresponding consistency of the proposed expression method are successfully verified. The proposed new expression method paves the way for the subsequent digital and automated design and analysis of the SPM configuration.

STModelViz: A 3D spatiotemporal GIS using a constraint-based approach

High concentrating photovoltaic (HCPV) technology plays a more and more important role in solar power generation due to its extremely high efficiency. However, the efficiency of the HCPV module can be reduced by many factors. Especially, there are not enough researches and knowledge on the light intensity distribution and non-uniform illumination of different wavelengths of light concentrated by Fresnel lens. It is generally considered that the maximum power of multi-junction solar cell is achieved when the cell is placed on the focal plane of Fresnel lens. But it is proved to be incorrect by our research. When light beams of different wavelengths go through the Fresnel lens, their light spot distributions on the optical axis are not the same as those when they have different refractive indexes in Fresnel lens. At the same time, the triple-junction solar cell consists of three sub-cells which absorb light beams of different wavelengths respectively. Therefore, the performance of triple-junction cells would be influenced by the light distribution along the optical axis, this is exactly what we want to study in this work. The method of simulating the light tracing is used to calculate and analyze the light intensity distribution and non-uniform characteristics of different wavelengths of light concentrated by Fresnel lens. Combined with them from the circuit network model of a triple-junction solar cell, the electrical performances of triple-junction solar cell at different positions along the optical axis are studied. It is found from the simulation that the performance of cell does not reach the best state when cell is placed on the focal plane. The power of cell on the focal plane reaches only 0.41 W while the maximum point arrives at 0.69 W. The high non-uniformity of light on cell surface when cell is placed on the focal plane causes the decline of power. And an outdoor HCPV testing system with the ability to change the distance between Fresnel lens and the cell is conducted. The experimental results and the simulation results match well, therefore our simulation approach is verified. It shows that the module achieves the maximum power on either side of the focal plane, and the output power can increase more than 20% after optimization. It is a result after equilibrium between light intensity and uniformity on cell surface.

The utilization of street view big data is increasingly being used to uncover visual characteristics and spatial perceptions of urban streets. However, there is a lack of studies that combine street view big data for perceptual evaluation in underdeveloped ethnic areas and better street quality. This study integrates deep learning methods to create a human–computer confrontational model for perception score, with a focus on the central city of Lhasa in Tibet. Pearson correlation analysis was conducted on six dimensions of perception data (beautiful, wealthy, safe, lively, boring and depressing) and visual elements. The streets in the top 20% for both visual elements and perceptual scores were identified to reveal areas with high visual element proportions and high perceptual scores. The spatial distribution characteristics and correlation between visual elements and street perceptions were thoroughly analyzed. The findings of this study reveal that the central city of Lhasa exhibited high percentages of visual elements in buildings (88.23%), vegetation (89.52%), and poles (3.14%). Out of the six perceptions examined, the highest scores were for boring (69.70) and depressing (67.76) perceptions, followed by beautiful (60.66) and wealthy (59.91) perceptions, with lively (56.68) and safe (50.64) perceptions receiving the lowest scores. Visual components like roads (−0.094), sidewalks (−0.031), fences (−0.036), terrain (−0.020), sky (−0.098), cars (−0.016), and poles (−0.075) were observed to have a significant deterring effect on the boring perception, while other visual elements showed a positive influence. This investigation seeks to provide valuable insights for the design and advancement of urban streets in marginalized ethnic localities, addressing a void in perception research of urban streets in such areas.

Topology optimization has been present in modern engineering for several decades, becoming an important tool for solving design problems. Today, it is difficult to imagine progress in engineering design without the search for new approaches to the generation of optimal structural topologies and the development of efficient topological optimization algorithms. The generation of topologies for structures under random loads is one of many research problems where topology optimization is present. It is important to predict the topologies of structures in the case of load uncertainty, since random load changes can significantly affect resulting topologies. This paper proposes an easy-to-implement numerical approach that allows the prediction of the resulting topologies of structures. The basic idea is to transform a random loads case into the deterministic problem of multiple loads. The concept of equivalent load scheme (ELS) is introduced. Instead of generating hundreds of loads applied at random, the selection of a few representative load cases allows the reduction of the numerical effort of the computations. The numerical implementation of proposed concepts is based on the cellular automaton mimicking colliding bodies, which has been recently introduced as an efficient structural topology generator. The examples of topology optimization under randomly applied loads, performed for both plane and spatial structures, have been selected to illustrate the proposed concepts. Confirmed by results of numerical simulations, the efficiency, versatility and ease of implementation of the proposed concept can make an original contribution to research in topological optimization under loads applied in a random manner.

Effects of deforestation and reforestation on landscape spatial structure in boreal Saskatchewan, Canada

Characteristics of spatial and temporal changes in ecosystem service value and threshold effect in Henan along the Yellow River, China