日期:
2020 年 — 2026 年
2020
2021
2022
2023
2024
2025
2026
影响因子:

Evolving topological colour landscape unravels the final stages of pistachio nut development and the incidence of blank nuts

不断演变的拓扑色彩景观揭示了开心果果实发育的最后阶段以及空白果实的出现情况。

Omotayo, Abdul-Hakeem; Hsieh, Fushing; Wei, Yiduo; Guzmán-Delgado, Paula; Marino, Giulia; Blanco-Ulate, Barbara

Unraveling implicit human behavioral effects on dynamic characteristics of Covid-19 daily infection rates in Taiwan

揭示台湾新冠肺炎每日感染率动态特征中隐含的人类行为影响

Chen, Ting-Li; Chou, Elizabeth P; Chen, Min-Yi; Hsieh, Fushing

Ordinal Conditional Entropy Displays Reveal Intrinsic Characteristics of the Rosenberg Self-Esteem Scale

序数条件熵显示揭示了罗森伯格自尊量表的内在特征

Furfaro, Emanuela; Hsieh, Fushing

Measuring dominance certainty and assessing its impact on individual and societal health in a nonhuman primate model: a network approach

在非人灵长类动物模型中测量优势确定性并评估其对个体和社会健康的影响:一种网络方法

McCowan, Brenda; Vandeleest, Jessica; Balasubramaniam, Krishna; Hsieh, Fushing; Nathman, Amy; Beisner, Brianne

Unraveling Hidden Major Factors by Breaking Heterogeneity into Homogeneous Parts within Many-System Problems

通过将多系统问题中的异质性分解为同质部分来揭示隐藏的主要因素

Chou, Elizabeth P; Chen, Ting-Li; Fushing, Hsieh

Learned Practical Guidelines for Evaluating Conditional Entropy and Mutual Information in Discovering Major Factors of Response-vs.-Covariate Dynamics

学习了评估条件熵和互信息以发现响应与协变量动态主要因素的实用指南

Chen, Ting-Li; Fushing, Hsieh; Chou, Elizabeth P

Livestock Informatics Toolkit: A Case Study in Visually Characterizing Complex Behavioral Patterns across Multiple Sensor Platforms, Using Novel Unsupervised Machine Learning and Information Theoretic Approaches

畜牧信息学工具包:利用新型无监督机器学习和信息论方法,对跨多个传感器平台的复杂行为模式进行可视化表征的案例研究

McVey, Catherine; Hsieh, Fushing; Manriquez, Diego; Pinedo, Pablo; Horback, Kristina

Using Clustering to Examine Inter-individual Variability in Topography of Auditory Event-Related Potentials in Autism and Typical Development

利用聚类分析研究自闭症和典型发育个体听觉事件相关电位地形图的个体间差异

Dwyer, Patrick; Wang, Xiaodong; De Meo-Monteil, Rosanna; Hsieh, Fushing; Saron, Clifford D; Rivera, Susan M

Color-complexity enabled exhaustive color-dots identification and spatial patterns testing in images

颜色复杂度使得图像中色点的全面识别和空间模式测试成为可能。

Liao, Shuting; Liu, Li-Yu; Chen, Ting-An; Chen, Kuang-Yu; Hsieh, Fushing

Mimicking Complexity of Structured Data Matrix's Information Content: Categorical Exploratory Data Analysis

模拟结构化数据矩阵信息内容的复杂性:分类探索性数据分析

Hsieh, Fushing; Chou, Elizabeth P; Chen, Ting-Li