Results 101 to 110 of about 4,738,087 (364)

Traffic Anomaly Detection Algorithm for Wireless Sensor Networks Based on Improved Exploitation of the GM(1,1) Model

International Journal of Distributed Sensor Networks, 2016
As WSNs gain popularity, they are becoming more and more necessary for traffic anomaly detection. Because worms, attacks, intrusions, and other kinds of malicious behaviors can be recognized by traffic analysis and anomaly detection, WSN traffic anomaly ...
Qin Yu, Jibin Lyu, Lirui Jiang, Longjiang Li   +3 more
doaj   +1 more source

Variation and generality in encoding of syntactic anomaly information in sentence embeddings [PDF]

arXiv, 2021
While sentence anomalies have been applied periodically for testing in NLP, we have yet to establish a picture of the precise status of anomaly information in representations from NLP models. In this paper we aim to fill two primary gaps, focusing on the domain of syntactic anomalies.
arxiv  

Hydrophobicity causes anomalous migration of cystine/glutamate antiporter SLC7A11 in SDS‐PAGE with low acrylamide concentration

FEBS Open Bio, EarlyView.
SLC7A11 frequently migrates faster in SDS‐PAGE. The present study found that the high hydrophobicity of SLC7A11 causes its anomalous migration in SDS‐PAGE with a low concentration of acrylamide gel. Replacing isoleucine with asparagine reduced hydrophobicity and restored its normal migration at 55 kDa, revealing the role of hydrophobicity and gel ...
Nsengiyumva Emmanuel, Qian He, Yixin Kang, Dianbao Zhang, Min Gao, Minglin Wang, Kexin Fan, Jingwen Xiong, Shaobo Wu, Botao Fa, Zhengtao Xiao, Yingfang Niu, Jun Yao, Yilei Zhang   +13 more
wiley   +1 more source

Surface anomaly detection on island-based PV panels using edge neural networks

Zhejiang dianli
Surface anomaly detection on photovoltaic （PV） panels is crucial for their operation and maintenance， especially in island environments where challenges such as small anomaly sizes and minimal color differences are prevalent. Due to the poor accuracy and
ZHANG Yinxian, ZHANG Zhanyao, ZHANG Xiya
doaj   +1 more source

DSR -- A dual subspace re-projection network for surface anomaly detection [PDF]

arXiv, 2022
The state-of-the-art in discriminative unsupervised surface anomaly detection relies on external datasets for synthesizing anomaly-augmented training images. Such approaches are prone to failure on near-in-distribution anomalies since these are difficult to be synthesized realistically due to their similarity to anomaly-free regions.
arxiv  

UniFlow: Unified Normalizing Flow for Unsupervised Multi-Class Anomaly Detection

Information
Multi-class anomaly detection is more efficient and less resource-consuming in industrial anomaly detection scenes that involve multiple categories or exhibit large intra-class diversity.
Jianmei Zhong, Yanzhi Song
doaj   +1 more source

Understanding the Effect of Bias in Deep Anomaly Detection [PDF]

arXiv, 2021
Anomaly detection presents a unique challenge in machine learning, due to the scarcity of labeled anomaly data. Recent work attempts to mitigate such problems by augmenting training of deep anomaly detection models with additional labeled anomaly samples. However, the labeled data often does not align with the target distribution and introduces harmful
arxiv  

Using Large-Scale Anomaly Detection on Code to Improve Kotlin Compiler [PDF]

, 2020
In this work, we apply anomaly detection to source code and bytecode to facilitate the development of a programming language and its compiler. We define anomaly as a code fragment that is different from typical code written in a particular programming language.
arxiv   +1 more source

Lifelong Continual Learning for Anomaly Detection: New Challenges, Perspectives, and Insights

IEEE Access
Anomaly detection is of paramount importance in many real-world domains characterized by evolving behavior, such as monitoring cyber-physical systems, human conditions and network traffic.
Kamil Faber, Roberto Corizzo, Bartlomiej Sniezynski, Nathalie Japkowicz   +3 more
doaj   +1 more source

Application of Knowledge Graph Technology with Integrated Feature Data in Spacecraft Anomaly Detection

Applied Sciences, 2023
Given the complexity of spacecraft system structures and functions, existing data-driven methods for anomaly detection face issues of insufficient interpretability and excessive dependence on historical data.
Xiaojian Yi, Peizheng Huang, Shangjie Che   +2 more
doaj   +1 more source