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相关概念视频

Time-Series Graph00:54

Time-Series Graph

4.4K
A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
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Plotting of Topographic Maps01:29

Plotting of Topographic Maps

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Topographic maps represent the Earth's surface features using contour lines, which connect points of equal elevation to create a two-dimensional representation of three-dimensional terrain. Creating a topographic map requires a systematic approach.Begin by plotting a scaled grid and marking intersections corresponding to the survey's elevation data points. Assign elevation values at these intersections to build the base map. Next, determine contour levels using a consistent contour interval,...
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Introduction to Horizontal Curves01:19

Introduction to Horizontal Curves

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Horizontal curves are essential in highway and railroad design, ensuring smooth and safe transitions between straight path segments, or tangents. These curves allow vehicles to maintain speed without abrupt changes, minimizing accidents and improving travel efficiency.A horizontal curve is typically defined by its geometric relationship to two tangents that meet at an intersection point (P.I.), where a simple curve is introduced to connect them. The back tangent refers to the initial tangent...
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Methods of Obtaining Topography01:25

Methods of Obtaining Topography

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Topography involves measuring and mapping land elevations, natural features, and artificial structures to create accurate representations of the terrain. Topographic surveying relies on traditional and modern methods, each with distinct advantages and limitations.Traditional Surveying Methods:Transit stadia surveys and plane table surveys were widely used traditional surveying methods. These techniques relied on instruments like theodolites and stadia rods for measuring distances and angles,...
63
Graphical and Analytic Representation of Sinusoids01:20

Graphical and Analytic Representation of Sinusoids

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Analyzing two sinusoidal voltages with equal amplitude and period but different phases on an oscilloscope, an instrument used to display and analyze waveforms, involves a three-step process.
The first step is measuring the peak-to-peak value, which is twice the amplitude of the sinusoid. This provides information about the maximum voltage swing of the waveform.
Secondly, the period and angular frequency are determined. The period is the time taken for one complete cycle of the waveform, while...
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Thematic Layering in GIS01:30

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In the past, planning projects such as schools or public facilities required extensive manual effort to gather and compile data. Information such as property boundaries, soil characteristics, road networks, zoning regulations, and flood zones had to be sourced individually from courthouses, utility providers, and registry offices. Assembling these datasets into a coherent format often took several months, delaying project timelines.The introduction of Geographic Information Systems (GIS)...
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Updated: Jun 26, 2025

Temporal Ordering of Dynamic Expression Data from Detailed Spatial Expression Maps
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具有可扩展性和有效的时间图表表征学习与超标几何学.

Yuanyuan Xu, Wenjie Zhang, Xiwei Xu

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    概括
    此摘要是机器生成的。

    这项研究引入了一种新的基于超模几何的时间图神经网络 (STGNh),以更好地表示复杂的动态图. STGNh克服了欧几里德的局限性,在大型数据集上提供了卓越的性能.

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    科学领域:

    • 图形神经网络 图形神经网络
    • 动态系统 动态系统
    • 超标几何学 超标几何学 超标几何学

    背景情况:

    • 现实世界的图表表现出复杂的,连续的时间动态.
    • 现有的基于欧几里德的时间图神经网络 (TGNN) 与等级结构发生冲突,导致高扭曲嵌入.
    • 欧几里德空间的局限性阻碍了复杂的图形拓学的准确表示.

    研究的目的:

    • 提出一种可扩展和有效的TGNN,使用超模几何学来进行连续时间动态图 (CTDG) 表示.
    • 通过克服欧几里德的局限性来增强TGNN的表示能力.
    • 开发一个统一的框架,同时捕捉不断变化的行为和层次结构.

    主要方法:

    • 引入了一个可扩展的TGNN与超标几何 (STGNh).
    • 集成了一个基于内存的模块 (超波更新网关 - HuG) 进行高效的时间动态存储.
    • 开发了一个基于结构的模块 (超波动时间变压器 (HyT)) 用于复杂的结构捕获和节点嵌入生成.

    主要成果:

    • STGNh证明了可扩展到数十亿级图的可扩展性.
    • 该模型有效地捕捉了不断变化的行为和层次图形结构.
    • 广泛的实验表明,STGNh在各种下游任务上显著优于基线方法.

    结论:

    • 与欧几里德几何相比,超标几何学为复杂的CTDGs提供了增强的表示能力.
    • 拟议的STGNh框架为建模动态图形数据提供了强大且可扩展的解决方案.
    • 这种方法显著提高了涉及复杂时间图结构的下游任务的性能.