Combining a Standardized Growth Class Assessment, UAV Sensor Data, GIS Processing, and Machine Learning Classification to Derive a Correlation with the Vigour and Canopy Volume of... by Ronald P. Dillner, Maria A. Wimmer, Matthias Porten, Thomas Udelhoven, Rebecca Retzlaff

“…The input features for ML model training comprise spectral, structural, and texture feature types generated from multispectral orthomosaics (spectral features), Digital Terrain and Surface Models (DTM/DSM- structural features), and Gray-Level Co-occurrence Matrix (GLCM) calculations (texture features). …”
Get full text

TAE Predict: An Ensemble Methodology for Multivariate Time Series Forecasting of Climate Variables in the Context of Climate Change by Juan Frausto Solís, Erick Estrada-Patiño, Mirna Ponce Flores, Juan Paulo Sánchez-Hernández, Guadalupe Castilla-Valdez, Javier González-Barbosa

“…The findings highlight the potential of integrating modern techniques to address complex, high-dimensional problems. By combining advanced prediction models and feature selection strategies, this study advances the reliability of climate forecasts and contributes to the development of effective adaptation and mitigation measures in response to climate change challenges.…”
Get full text

The digital watermarking algorithm using discrete chaotic maps by A. V. Sidorenko, I. V. Shakinko

“…Thus, the proposed algorithm can be used to solve real problems of the defense of digital images transmitted by communication channels.…”
Get full text

Postoperative complications: definition and classification by A. B. Larichev

“…Based on this definitional approach, the classification of negative events associated with the operation, taking into account the involvement of the anatomical and functional structures of the body (local, regional and systemic) is presented. Another ranked feature is the syndromic characteristic of manifestations, which involves ordering problems depending on the leading cause of their formation of central or peripheral origin, including infectious and inflammatory nature, disorders in the hemostatic system and other variable (different) situations. …”
Get full text

Portrayal of Poland and Poles in autobiographical texts written by foreign authors in the 20th and 21st centuries by Regina Lubas-Bartoszyńska

“…It deals with the 20th and 21st centuries and discusses autobiographical material in which Poland and Polish people feature most heavily (e.g., the diaries of Claudel, Gide, and Mann). …”
Get full text

THE USE OF COMPUTATIONAL SIMULATION TO INCREASE THE EFFICIENCY OF ACTIONS TO REDUCE THE LOSS OF ELECTRIC POWER by A. Grin, I. Skorokhodova, C. Chebanov, A. Grin

“…A technique and algorithm are proposed for generating information necessary for an objective assessment of the appropriateness of SMEs. A feature of the algorithm is the use of simulation to take into account the inluence of inaccuracies in the design of circuit and mode parameters, intersystem lows, changes in the network circuit for the billing period.…”
Get full text

The loop-by-loop Baikov representation — Strategies and implementation by Hjalte Frellesvig

“…We also discuss some subtleties and open problems regarding Baikov representations.…”
Get full text

ROLLING BEARING FAULT DIAGNOSIS METHOD BASED ON CONVOLUTIONAL DEEP FOREST

“…Aiming at the vibration signal of rolling bearing with problems of nonlinear,small sample size and traditional machine learning based diagnosis algorithm required expert experience,a convolutional deep forest(CDF)based rolling bearing fault diagnosis algorithm was proposed.Firstly,the one-dimensional vibration signal was preprocessed through normalization and transformation into image.Then the convolution neural network was exploited to train the image to complete the end-to-end feature extraction,and the cascade forest was used to analyze and classify the features.Finally,the effectiveness of CDF was verified on the bearing data set.The experimental results show that CDF can achieve high accuracy for small or big sample data under four loads.In addition,the accuracy of convolution neural network and CDF based on two-dimensional image are higher than one-dimensional,which proves the effectiveness of data preprocessing operation based on signal to image.…”
Get full text

基于迭代的集总经验模式分解算法的齿轮箱故障特征提取 by 姜军生, 林近山

“…Aimed at the drawback of blindly adding white noise occurring in the ensemble empirical mode decomposition（EEMD） when used to solver realistic problems,the iterative ensemble empirical mode decomposition（IEEMD） method is proposed.To begin with,the IEEMD method is introduced.Then,the EEMD method and the IEEMD method are used to analyze the signals from the realistic gearbox with a broken-tooth fault.As a result,the comparisons with the EEMD method show that the IEEMD method could produce HHT spectrum with higher time-frequency resolution and extract more and useful information from the signals.Moreover,it indicates that the IEEMD method greatly alleviates the drawback of the EEMD method and is suitable as a fault feature extraction method for gearboxes.…”
Get full text

Performance analysis of NSA control plane and user plane delay in 5G network by Dan ZHANG, Lei WANG, Xiaoqi WANG, Siyu XI

“…Different from 2G/3G/4G,the 5G network architecture contains two parts:NSA (non-standalone) and SA (standalone) networking.NSA can help network deploys faster.Low latency is a very important feature of 5G,and its implementation requires a combination of technologies.Based on the 2.6 GHz NR frame structure,combined with theoretical analysis and real case,the current situation and problems of control plane delay and user plane delay were discussed,and the delay optimization method was provided,which provided the corresponding ideas and suggestions for NSA network deployment.…”
Get full text

Fault Diagnosis of Gearboxes Based on AO-VMD and IAO-SVM by Wang Bo, Nan Xinyuan

“…Secondly, a CRITIC-TOPSIS comprehensive evaluation model based on correlation coefficient, kurtosis, envelope entropy, energy entropy is constructed to optimize IMF, and energy entropy is extracted to establish feature vectors. Finally, it is input into IAO-SVM to identify faults. …”
Get full text

Emerging societal involvement in city management: the case of Cape Town by Neil Dewar

“…This has not been without problems however. The current status of community participation in Cape Town is reviewed and explored against a theoretical model. …”
Get full text

Breaks in the Arctic ice cover: from observations to predictions by A. A. Ershova, L. N. Dyment, T. A. Alekseeva

“…Breaks (ruptures) and cracks is the distinguishing feature of any ice cover in the Arctic seas during the cold season and in the whole Arctic Basin throughout a year. …”
Get full text

Monocular depth estimation via a detail semantic collaborative network for indoor scenes by Wen Song, Xu Cui, Yakun Xie, Guohua Wang, Jiexi Ma

“…Second, a detail‒semantic collaborative structure is established, which establishes a selective attention feature map to extract details and semantic information from feature maps. …”
Get full text

A Few-shot Learning Method for Intent Analysis of Air Combat Confrontation Behaviors by PAN Ming, ZHENG Jingsong, LI Jinliang, FANG Long, YANG Yang, ZHAO Shijie

“…By integrating the attention mechanism in the Bidirectional Gated Recurrent Unit (BiGRU) , the feature learning ability of the model is improved, and adaptively assign the weight of different air combat feature information. …”
Get full text

Distributed Photovoltaic Short-Term Power Prediction Based on Personalized Federated Multi-Task Learning by Wenxiang Luo, Yang Shen, Zewen Li, Fangming Deng

“…In a distributed photovoltaic system, photovoltaic data are affected by heterogeneity, which leads to the problems of low adaptability and poor accuracy of photovoltaic power prediction models. …”
Get full text

Research on dimension measurement algorithm for parcel boxes in high-speed sorting system by Ning Dai, Jingchao Chen, Xudong Hu, Yanhong Yuan

“…The high-low layer feature fusion structure and C2f-GhostCondConv are designed on the neck of the model to achieve the selective fusion of input features at different levels with small parameter number and computational amount. …”
Get full text

An Attention-Based Spatial-Spectral Joint Network for Maize Hyperspectral Images Disease Detection by Jindai Liu, Fengshuang Liu, Jun Fu

“…However, the abundance of redundant information in hyperspectral data poses challenges in extracting significant features. To overcome the above problems, in this study we proposed an attention-based spatial-spectral joint network model for hyperspectral detection of pest-infected maize. …”
Get full text

Study on Spark Image Detection for Abrasive Belt Grinding via Transfer Learning with YOLOv8 by Jian Huang, Guangpeng Zhang

“…Aiming to solve the problems of low precision and poor efficiency caused by relying on manual experience during the manual polishing of blades, a multi-view spark image detection method based on YOLOv8 transfer learning is proposed. …”
Get full text

Optimizing cervical cancer diagnosis with accurate cell classification using modified HDFF by Pooja Patre, Dipti Verma

“…By enhancing the feature extraction process and combining multiple layers of deep learning models, the Modified HDFF method improves classification performance across various tasks, ranging from binary to multi-class problems. …”
Get full text