Results 41 to 50 of about 5,201 (163)

ANK1 and EPB41 Variants and The Risk of Steroid‐Induced Osteonecrosis

Arthritis &Rheumatology, Accepted Article.
Objective Steroid‐induced osteonecrosis of the femoral head (SONFH) is a refractory skeletal disorder influenced by genetic and environmental factors. However, conclusive pathogenic genetic evidence remains elusive due to the limited exploration of rare damaging variants. In this study, we aimed to identify rare variants associated with SONFH.
Shengbao Chen, Xianmin Zhu, Zhongzhong Chen, Wei Chen, Hussam Alkaissi, Zeng Zhang, Yun Gao, Junhui Yin, Xiangtian Yu, Qiong Fu, Youshui Gao, Zhenzhong Zhu, Qianying Cai, Pengwei Zhang, Weibin Chen, Xin Zhao, Xiaojin Wu, Karel Pacak, Dongxu Jin, Chunde Bao, Zhengping Zhuang, Changqing Zhang   +21 more
wiley   +1 more source

Improving Influenced Outlierness(INFLO) Outlier Detection Method [PDF]

, 2013
Anomaly detection refers to the process of finding outlying records from a given dataset.This process is a subject of increasing interest among analysts. Anomaly detection is a subject of interest in various knowledge domains.
Suman, Shashwat
core  

Steganographer Identification

, 2019
Conventional steganalysis detects the presence of steganography within single objects. In the real-world, we may face a complex scenario that one or some of multiple users called actors are guilty of using steganography, which is typically defined as the
Breunig, Chen, Cortes, Erdogmus, Filler, Filler, Filler, Fridrich, Fridrich, Fridrich, Fridrich, Gretton, Guo, Hetzl, Holub, Holub, Holub, Holub, Ker, Ker, Ker, Ker, Ker, Ker, Ker, Ker, Kodovsky, Li, Li, Liu, Muandet, Pearson, Pevny, Pevný, Pevný, Pevný, Pevný, Rokach, Sahu, Sallee, Scholkopf, Shi, Song, Westfeld, Wu, Wu, Wu   +46 more
core   +1 more source

Short‐Term Multi‐Horizon Line Loss Rate Forecasting of a Distribution Network Using Attention‐GCN‐LSTM

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Accurately predicting line loss rates is crucial for effective management in distribution networks, particularly for short‐term multihorizon forecasts ranging from 1 hour to 1 week. In this study, we propose attention‐GCN–LSTM, a novel method that integrates graph convolutional networks (GCN), long short‐term memory (LSTM) and a three‐level ...
Jie Liu, Yijia Cao, Yong Li, Yixiu Guo, Wei Deng   +4 more
wiley   +1 more source

Optimasi Algoritma K-Nearest Neighbors Berdasarkan Perbandingan Analisis Outlier (Berbasis Jarak, Kepadatan, LOF)

Jurnal Nasional Teknik Elektro dan Teknologi Informasi
Pertumbuhan data yang terjadi saat ini berpengaruh terhadap analisis data di berbagai bidang, seperti astronomi, bisnis, kedokteran, pendidikan, dan finansial.
Fitri Ayuning Tyas, Mahda Nurayuni, Hidayatur Rakhmawati   +2 more
doaj   +1 more source

New Supernova Candidates from SDSS-DR7 of Spectral Survey

, 2009
The letter presents 25 discovered supernova candidates from SDSS-DR7 with our dedicated method, called Sample Decrease, and 10 of them were confirmed by other research groups, and listed in this letter.
A-Li Luo, Abazajian, Abazajian, Blondin, Chao Wu, Fu-Chao Wu, Liang-Ping Tu, Madgwick, Markus M, Nugent, Yong-Heng Zhao, York   +11 more
core   +1 more source

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

High Voltage, EarlyView.
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

Model-free detection of unique events in time series

Scientific Reports, 2022
Recognition of anomalous events is a challenging but critical task in many scientific and industrial fields, especially when the properties of anomalies are unknown.
Zsigmond Benkő, Tamás Bábel, Zoltán Somogyvári   +2 more
doaj   +1 more source

Local Subspace-Based Outlier Detection using Global Neighbourhoods

, 2016
Outlier detection in high-dimensional data is a challenging yet important task, as it has applications in, e.g., fraud detection and quality control. State-of-the-art density-based algorithms perform well because they 1) take the local neighbourhoods of ...
Bäck, Thomas, van Leeuwen, Matthijs, van Stein, Bas   +2 more
core   +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