SE-MSLC: Semantic Entropy-Driven Keyword Analysis and Multi-Stage Logical Combination Recall for Search Engine [0.03%]
基于语义熵的关键词分析和多阶段逻辑组合召回的搜索引擎技术(SE-MSLC)
Haihua Lu,Liang Yu,Yantao He et al.
Haihua Lu et al.
Information retrieval serves as a critical methodology for accurately and efficiently obtaining the required information from massive amounts of data. In this paper, we propose an information retrieval framework (SE-MSLC) that utilizes info...
Healthcare Expenditure and COVID-19 in Europe: Correlation, Entropy, and Functional Data Analysis-Based Prediction of Hospitalizations and ICU Admissions [0.03%]
欧洲的卫生支出和COVID-19：相关性、熵和基于函数数据分析的住院及ICU床位预测模型
Patrycja Hęćka,Wiktor Ejsmont,Marek Biernacki
Patrycja Hęćka
This article aims to analyze the correlation between healthcare expenditure per capita in 2021 and the sum of the number of hospitalized patients, ICU admissions, confirmed COVID-19 cases, and deaths in a selected period of time. The analys...
Detection of Significant Seismic Quiescence Patterns in the Mexican Subduction Zone Using Extended Schreider Algorithms [0.03%]
基于扩展施莱德算法的墨西哥俯冲带显著地震宁静模式识别研究
Carlos Carrizales-Velazquez,Jennifer Perez-Oregon,Israel Reyes-Ramírez et al.
Carlos Carrizales-Velazquez et al.
This study investigates the implementation of Schreider's quiescence algorithm and two variants that utilize spatiotemporal data to identify patterns of seismic quiescence. These patterns are of particular interest as they may serve as prec...
Reconstructing Hyperspectral Images from RGB Images by Multi-Scale Spectral-Spatial Sequence Learning [0.03%]
基于多尺度谱-空间序列学习的RGB图像重建成高光谱图像方法
Wenjing Chen,Lang Liu,Rong Gao
Wenjing Chen
With rapid advancements in transformers, the reconstruction of hyperspectral images from RGB images, also known as spectral super-resolution (SSR), has made significant breakthroughs. However, existing transformer-based methods often strugg...
Ying Chang,Rui Wang,Peng Han et al.
Ying Chang et al.
Earthquake forecast and risk assessment are of key importance in reducing casualties and property losses. However, they have not been fully achieved due to the complexity of earthquakes. Numerous studies have explored the correspondence of ...
Lightweight Quantum Authentication and Key Agreement Scheme in the Smart Grid Environment [0.03%]
智能电网环境中的轻量级量子认证和密钥协商方案
Zehui Jiang,Run-Hua Shi
Zehui Jiang
Smart grids leverage smart terminal devices to collect information from the user side, achieving accurate load forecasting and optimized dispatching of power systems, effectively improving power supply efficiency and reliability while reduc...
Fault Diagnosis of Planetary Gearboxes Based on LSTM Improved via Feature Extraction Using VMD, Fusion Entropy, and Random Forest [0.03%]
基于VMD特征提取、融合熵和随机森林的LSTM在行星齿轮箱故障诊断中的应用研究
Xin Xia,Haoyu Sun,Aiguo Wang
Xin Xia
Extracting effective fault features from the complex vibration signals of planetary gearboxes is the key to conducting efficient fault diagnosis, and it involves signal processing, feature extraction, and feature selection. In this paper, a...
Entropy and Chaos-Based Modeling of Nonlinear Dependencies in Commodity Markets [0.03%]
基于熵和混沌的 commodity 市场非线性依赖关系建模
Irina Georgescu,Jani Kinnunen
Irina Georgescu
This study explores the nonlinear dynamics and interdependencies among major commodity markets-Gold, Oil, Natural Gas, and Silver-by employing advanced chaos theory and information-theoretic tools. Using daily data from 2020 to 2024, we est...
On the Monotonicity of Relative Entropy: A Comparative Study of Petz's and Uhlmann's Approaches [0.03%]
相对熵单调性的比较研究：Petz方法和Uhlmann方法的对比
Santiago Matheus,Francesco Bottacin,Edoardo Provenzi
Santiago Matheus
We revisit the monotonicity of relative entropy under the action of quantum channels, a foundational result in quantum information theory. Among the several available proofs, we focus on those by Petz and Uhlmann, which we reformulate withi...
Fault Diagnosis of Wind Turbine Rotating Bearing Based on Multi-Mode Signal Enhancement and Fusion [0.03%]
基于多模式信号增强与融合的风电机组旋转轴承故障诊断方法研究
Shaohu Ding,Guangsheng Zhou,Xinyu Wang et al.
Shaohu Ding et al.
Wind turbines operate under harsh conditions, heightening the risk of rotating bearing failures. While fault diagnosis using acoustic or vibration signals is feasible, single-modal methods are highly vulnerable to environmental noise and sy...