Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Selected Data About Geographic Locations01:25

Selected Data About Geographic Locations

28
Geographic Information Systems (GIS) rely on two core types of data: spatial data and attribute data.Spatial DataSpatial data defines the physical location of features within a coordinate system, typically expressed in terms of latitude and longitude. It provides precise positioning for elements like roads, rivers, or buildings.Attribute DataAttribute data complements spatial data by adding descriptive information about these features. For example, a road's spatial data includes its start and...
28
Levels of Use of a GIS01:29

Levels of Use of a GIS

56
Geographic Information Systems (GIS) operate across three levels of application, each representing an increasing degree of complexity: data management, analysis, and prediction. These levels reflect the expanding functionality and versatility of GIS technology in handling spatial data for diverse purposes.Data ManagementAt its foundational level, GIS serves as a tool for data management, enabling the input, storage, retrieval, and organization of spatial data. This level is often employed in...
56
Manipulation and Analysis01:21

Manipulation and Analysis

28
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
28
Factorial Design02:01

Factorial Design

13.0K
Factorial Analysis is an experimental design that applies Analysis of Variance (ANOVA) statistical procedures to examine a change in a dependent variable due to more than one independent variable, also known as factors. Changes in worker productivity can be reasoned, for example, to be influenced by salary and other conditions, such as skill level. One way to test this hypothesis is by categorizing salary into three levels (low, moderate, and high) and skills sets into two levels (entry level...
13.0K
Design Example: Alignment of a Road Line Using GIS01:17

Design Example: Alignment of a Road Line Using GIS

51
The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...
51
Stereotype Content Model02:16

Stereotype Content Model

14.7K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.7K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

A novel c-Met inhibitor containing chiral pyrrolidine side chain and its application as anti-tumor agents.

European journal of medicinal chemistry·2026
Same author

Long-Term Glycemic Exposure, Control Status and Cognitive Function in Older Adults: A Longitudinal Study.

Diabetes, obesity & metabolism·2026
Same author

Gut microbiome restructuring in laryngeal squamous cell carcinoma identifies stable microbial biomarkers with diagnostic potential.

Frontiers in oncology·2026
Same author

Body mass index modifies cardiovascular risk trajectory: a Chinese longitudinal cohort study.

BMC public health·2026
Same author

Association of Inflammation-Related Biomarkers With Symptom Burden Subgroups in Patients With Gastrointestinal Cancers: A Latent Profile Analysis.

Cancer nursing·2026
Same author

HNMT promotes the motility-associated structures of breast cancer cells through the PI3K/Akt signaling pathway to promote tumor progression.

Histology and histopathology·2026

相关实验视频

Updated: Jul 12, 2025

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.1K

一个基于基本空间绘图和双边生成对抗网络的社会推模型.

Suqi Zhang1, Ningjing Zhang2, Wenfeng Wang2

  • 1School of Information Engineering, Tianjin University of Commerce, Tianjin 300134, China.

Entropy (Basel, Switzerland)
|October 28, 2023
PubMed
概括
此摘要是机器生成的。

本研究引入了一种新的社会推模型 (MBSGAN),该模型有效地融合了用户交互和社交网络数据. 通过利用双边生成对抗网络,MBSGAN提高了推质量,特别是在稀缺数据的情况下.

关键词:
生成性的对抗性网络.非线性绘图是指非线性绘图.推算法推算法推算法社会建议是社会建议.

更多相关视频

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

599
Author Spotlight: Investigating the Effects of Mind-Body-Movement Practices on Brain Function
06:17

Author Spotlight: Investigating the Effects of Mind-Body-Movement Practices on Brain Function

Published on: January 26, 2024

2.0K

相关实验视频

Last Updated: Jul 12, 2025

Modeling the Functional Network for Spatial Navigation in the Human Brain
05:55

Modeling the Functional Network for Spatial Navigation in the Human Brain

Published on: October 13, 2023

1.1K
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

599
Author Spotlight: Investigating the Effects of Mind-Body-Movement Practices on Brain Function
06:17

Author Spotlight: Investigating the Effects of Mind-Body-Movement Practices on Brain Function

Published on: January 26, 2024

2.0K

科学领域:

  • 计算机科学 计算机科学
  • 人工智能的人工智能
  • 机器学习 机器学习

背景情况:

  • 社交推系统旨在通过社交联系来改进推,特别是当用户与项目交互数据稀缺时.
  • 从互动和社会空间中有效地融合异质信息是社会推的一个关键挑战.

研究的目的:

  • 提出一个新的社会推模型,MBSGAN,它解决了融合互动和社会信息的挑战.
  • 通过有效地挖掘和利用互动和社交空间中的异质信息来提高推绩效.

主要方法:

  • 提出一个基础空间绘图,以整合交互和社交空间,克服信息异质性.
  • 在互动和社交空间内构建双边生成对抗网络 (GAN).
  • 使用生成器进行候选样本选择和区分器来区分积极/消极的例子来学习复杂的信息.

主要成果:

  • 与其他八种社会推模型相比,拟议的MBSGAN模型显示出更高的有效性.
  • 在四个公共数据集 (Douban,FilmTrust,Ciao,Epinions) 中,MBSGAN的表现也超过了六个基于网络的生成对抗模型.

结论:

  • MBSGAN模型有效地融合了异构的互动和社会信息,以改善社会推.
  • 使用双边GAN和基层空间绘制是利用社会数据增强推系统的一个有希望的方法.