A clustering-based approach for classifying data streams using graph matching by Yuxin Du, Mingshu He, Xiaojuan Wang

“…Firstly, an unsupervised clustering framework is designed, which studies the diverse distributions and category similarities of traffic data based on a limited set of features. This unsupervised clustering helps mitigate network disparities by aggregating network sessions into a few clusters with extracted primary features. …”
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PEMFC RUL Prediction for Non-Stationary Time Series Based on Crossformer Model by Ning Zhou, He Zeng, Zefei Zheng, Ke Wang, Jianxin Zhou

“…Firstly, the overall architecture adopts the Crossformer model to extract dependencies between different features and temporal dependencies. Secondly, adaptive normalization is applied to the data to mitigate the non-stationarity in the original data, thereby increasing their predictability. …”
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Risk Factors and Clinical Features of Deterioration in 739 COVID‐19 Affected Children Aged Under 14 Years in Zhuhai, China: A Multicenter, Retrospective Study by Ting Liu, Zhaojun Pan, Cheng Zhang, Fanlin Huang, Jundong Ding, Wenxiu Song, Yongwu Xie, Guang Lin

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Development of a Small Dual-Chamber Solar PV-Powered Evaporative Cooling System for Fruit and Vegetable Cooling with Techno-Economic Assessment by Macmanus Chinenye Ndukwu, Godwin Usoh, Godwin Akpan, Leonard Akuwueke, Inemesit Ekop, Promise Etim, Emmanuel Okon Sam, Linus Oriaku, Prince Omenyi, Emeka Oleka, Fidelis Abam

“…This study evaluates a solar PV-powered evaporative cooling system for vegetable cooling. The system features dual cooling chambers with two different biomass pads, operating at different temperatures. …”
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Nationally Determined Contribution Analysis of Brazil and Some Global North and South Countries by Daniella Ribeiro Pacobello, Samuel Carvalho De Benedicto, Maurício Lamano Ferreira, Cândido Ferreira da Silva Filho, Regina Márcia Longo

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Underground Personnel Positioning Method Based on Self-training and NLOS Suppression by SHAO Xiaoqiang, HAN Zehui, MA Bo, YANG Yongde, YUAN Zewen, LI Xin

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Berberine Mitigates Sepsis-Associated Acute Kidney Injury in Aged Rats by Preserving Mitochondrial Integrity and Inhibiting TLR4/NF-κB and NLRP3 Inflammasome Activations by Ruedeemars Yubolphan, Anongporn Kobroob, Apisek Kongkaew, Natthakarn Chiranthanut, Natthanicha Jinadang, Orawan Wongmekiat

“…BBR pretreatment substantially mitigated these adverse effects, suggesting that it protects against SA-AKI in aged rats by reducing oxidative stress, preserving mitochondrial integrity, and inhibiting key inflammatory pathways. …”
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A Hybrid Framework for Photovoltaic Power Forecasting Using Shifted Windows Transformer-Based Spatiotemporal Feature Extraction by Ping Tang, Ying Su, Weisheng Zhao, Qian Wang, Lianglin Zou, Jifeng Song

“…Accurate photovoltaic (PV) power forecasting is essential to mitigating the security and stability challenges associated with PV integration into power grids. …”
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Utilizing Enhanced Particle Swarm Optimization for Feature Selection in Gender-Emotion Detection From English Speech Signals by Ammar Amjad, Li-Chia Tai, Hsien-Tsung Chang

“…We extract pitch and acoustic-related statistical features from speech samples and develop separate models for gender prediction and emotion detection. …”
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A Unified Approach to Video Anomaly Detection: Advancements in Feature Extraction, Weak Supervision, and Strategies for Class Imbalance by Rui Z. Barbosa, Hugo S. Oliveira

“…Through comprehensive experimental analysis, the study examines the role of feature representations, sampling strategies, and curriculum learning in enhancing VAD performance. …”
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FedeAMR-CFF: A Federated Automatic Modulation Recognition Method Based on Characteristic Feature Fine-Tuning by Meng Zhang, Jiankun Ma, Zhenxi Zhang, Feng Zhou

“…To address the critical challenges of high data privacy leakage risks, excessive communication overhead, and data silos in automatic modulation recognition tasks, this paper proposes a federated automatic modulation recognition method based on characteristic feature fine-tuning (FedeAMR-CFF). Specifically, the clients extract representative features through distance-based metric screening, and the server aggregates model parameters via the FedAvg algorithm and fine-tunes the model using the collected features. …”
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Demonstration of 50 Gbps Long-Haul D-Band Radio-over-Fiber System with 2D-Convolutional Neural Network Equalizer for Joint Phase Noise and Nonlinearity Mitigation by Yachen Jiang, Sicong Xu, Qihang Wang, Jie Zhang, Jingtao Ge, Jingwen Lin, Yuan Ma, Siqi Wang, Zhihang Ou, Wen Zhou

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Ensemble-based multiclass lung cancer classification using hybrid CNN-SVD feature extraction and selection method. by Md Sabbir Hossain, Niloy Basak, Md Aslam Mollah, Md Nahiduzzaman, Mominul Ahsan, Julfikar Haider

“…The main contribution of this research lies in its use of a hybrid CNN-SVD (Singular Value Decomposition) method and the use of a robust voting ensemble approach, which results in superior accuracy and effectiveness for mitigating potential errors. By employing contrast-limited adaptive histogram equalization (CLAHE), contrast-enhanced images were generated with minimal noise and prominent distinctive features. …”
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Expected features of the course leader in the rehabilitation healthcare professionals' higher education: A qualitative study on students' perspectives. by Benedetto Giardulli, Laura Furri, Marco Testa, Andrea Dell'Isola, Gianluca Bertoni, Simone Battista

“…This study explored students' expected features of the course leaders in the rehabilitation healthcare professionals' higher education. …”
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Crude Oil and Hot-Rolled Coil Futures Price Prediction Based on Multi-Dimensional Fusion Feature Enhancement by Yongli Tang, Zhenlun Gao, Ya Li, Zhongqi Cai, Jinxia Yu, Panke Qin

“…Additionally, a data augmentation framework leveraging multi-dimensional feature engineering has been established. The technical indicators, volatility indicators, time features, and cross-variety linkage features are integrated to build a prediction system, and the lag feature design is used to prevent data leakage. …”
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Hybrid LSTM–Transformer Architecture with Multi-Scale Feature Fusion for High-Accuracy Gold Futures Price Forecasting by Yali Zhao, Yingying Guo, Xuecheng Wang

“…Amidst global economic fluctuations and escalating geopolitical risks, gold futures, as a pivotal safe-haven asset, demonstrate price dynamics that directly impact investor decision-making and risk mitigation effectiveness. Traditional forecasting models face significant limitations in capturing long-term trends, addressing abrupt volatility, and mitigating multi-source noise within complex market environments characterized by nonlinear interactions and extreme events. …”
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Improving the performance of machine learning algorithms for detection of individual pests and beneficial insects using feature selection techniques by Rabiu Aminu, Samantha M. Cook, David Ljungberg, Oliver Hensel, Abozar Nasirahmadi

“…The concept of explainable artificial intelligence was adopted by incorporating permutation feature importance ranking and Shapley Additive explanations values to identify the feature set that optimized a model's performance while reducing computational complexity. …”
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AI-based prediction of traffic crash severity for improving road safety and transportation efficiency by Ayman Mohamed Mostafa, Bader Aldughayfiq, Mayada Tarek, Alaa S. Alaerjan, Hisham Allahem, Murtada K. Elbashir, Mohamed Ezz, Eslam Hamouda

“…The methodology incorporates feature engineering, clustering techniques such as K-Means and HDBSCAN, with oversampling methods such as RandomOverSampler, SMOTE, Borderline-SMOTE, and ADASYN to address class imbalance, along with Correlation-Based Feature Selection (CFS) and Recursive Feature Elimination (RFE) for optimal feature selection. …”
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Mixed multi-branch feature fusion model for efficient automatic building extraction from high-resolution remote sensing images by Yaohui Liu, Shuzhe Zhang, Xinkai Wang, Taoyi Chen, Hu Jiang, Fei Su

“…Firstly, we designed a Mixed Multi-Branch Feature Fusion (MMFF) module, which performs multi-dimensional weighted fusion on the feature information captured by the Transformer. …”
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AI-Driven Detection of Alkali-Silica Reaction in Concrete Structures Using Feature-Enhanced Deep Learning Models by Yujie Wu, Mengze Wu, Tianyi Cui, Jiani Lin, Qingke Liao, Jinqiu Shu

“…A dataset of ASR-affected images was developed and augmented through feature enhancement processes, improving crack visibility and classification accuracy. …”
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