Results 51 to 60 of about 1,104 (139)

Residual Life Assessment of Oil‐Immersed Insulating Paper by FTIR Feature Interpretability Evolution

High Voltage, Volume 11, Issue 3, Page 761-770, June 2026.
ABSTRACT The ageing of insulating paper escalates the peril of insulation failure in oil‐impregnated‐paper power equipment. Consequently, the real‐time monitoring and non‐destructive assessment of insulating paper condition assume paramount significance.
Guangyi Liu, Yanan Liu, Chen Zhang, Jian Li, Zhengyong Huang, Feipeng Wang, Huaqiang Li, Jinghui Gao, Lisheng Zhong   +8 more
wiley   +1 more source

Reduced Genetic Load and Inbreeding in Reintroduced African Wild Dogs Reflect the Benefits of Admixture

Molecular Ecology, Volume 35, Issue 12, June 2026.
ABSTRACT Conservation translocations have become important assets in saving African wild dogs (Lycaon pictus) from local extinction, which have declined drastically due to anthropogenic pressures. In South Africa, wild dogs were eradicated except for a small, isolated population remaining in Kruger National Park.
L. Tensen, X. Wang, J. Watermeyer, C. du Plessis   +3 more
wiley   +1 more source

HLoOP—Hyperbolic 2-Space Local Outlier Probabilities

IEEE Access
Hyperbolic geometry has recently garnered considerable attention in machine learning due to its ability to embed hierarchical graph structures with low distortions for further downstream processing.
Clemence Allietta, Jean-Philippe Condomines, Jean-Yves Tourneret, Emmanuel Lochin   +3 more
doaj   +1 more source

An Improved Forward-Looking Sonar 3D Visualization Scheme of Underwater Objects

IEEE Access, 2019
This paper presents an improved scheme for forward-looking sonar (FLS) visualization, including an echo acquisition method, a global threshold based on local outlier factor and a reconstruction method.
Teng Zeng, Chunhua Zhang, Yong Huang, Peng Wang   +3 more
doaj   +1 more source

Exploring the Relationship Between Emotion and Bodily Activity With Machine Learning

Psychophysiology, Volume 63, Issue 6, June 2026.
ABSTRACT Human experiences of bodily activity relate to their emotional state; however, exactly how is yet to be fully explored. We aim to conceptually model this relationship between bodily activity and subjective emotional experience using machine learning models.
Roydon Goldsack, W. Bastiaan Kleijn, Hedwig Eisenbarth   +2 more
wiley   +1 more source

Sysmon event logs for machine learning-based malware detection

Cyber Security and Applications
Malware poses a significant threat to modern computing environments, necessitating advanced detection techniques that can adapt to evolving attack methods.
Riki Mi’roj Achmad, Dyah Putri Nariswari, Baskoro Adi Pratomo, Hudan Studiawan   +3 more
doaj   +1 more source

Physical Layer Detection of Malicious Relays in LTE-A Network Using Unsupervised Learning

IEEE Access, 2020
For Long Term Evolution Advanced (LTE-A) network, although there exist many studies that focus on improving the performance with relays, security issues are often neglected.
Yeliz Yengi, Adnan Kavak, Huseyin Arslan
doaj   +1 more source

Synergistic Dual‐Electron Transfer in MXene Microneedles for Ultrasensitive Continuous Glucose Monitoring

Small Structures, Volume 7, Issue 4, April 2026.
We developed a Christmas tree‐inspired GTA‐MNs patch for continuous glucose monitoring. Its trilayer architecture enables a synergistic dual electron transfer mechanism, significantly enhancing sensitivity and detection range. Integrated with wireless electronics and machine learning calibration, the system provides real‐time, accurate glycemic ...
Xiaoxing Wang, Hai Peng, Hui Xiao, Heng Li, Jiaoao He, Lijuan Chen, Xiaopei Qiu, Kang Wang, Xiaolin Hu, Xinlin Guo, Wenjing Liu, Jingzhi Wu, Pingyun Li, Shunyi Xia, Qiuxuan Xia, Jianzhi Zhou, Yang Luo, Hong Zhang   +17 more
wiley   +1 more source

HADA: A Hybrid Anomaly Detection Approach Using Unsupervised Machine Learning

Engineering Reports, Volume 8, Issue 3, March 2026.
Overview of HADA, an unsupervised fraud detection pipeline that preprocesses and scales transaction data, applies PCA for dimensionality reduction, scores anomalies using Isolation Forest, selects anomalous transactions via thresholding, and clusters the selected anomalies using Agglomerative Hierarchical Clustering (AHC) to produce interpretable ...
Francis Thiong'o, Lawrence Nderu, Ronald Waweru Mwangi, Isaac Nyabisa Oteyo   +3 more
wiley   +1 more source

Hybrid Sampling and Ensemble Learning for Food Safety Sampling Inspection Classification

Journal of Food Protection
Food safety sampling inspection is critical for risk prevention in complex supply chains. However, extreme class imbalance, where unqualified samples are significantly outnumbered by qualified ones, biases machine learning (ML) models to prioritize ...
Ke Qin, Xiaoting Dai, Linhai Wu
doaj   +1 more source