Welcome message from the Editor-in-Chief and Co-Editor-in-Chief

@article{Jia2013WelcomeMF,
  title={Welcome message from the Editor-in-Chief and Co-Editor-in-Chief},
  author={Xiaohua Jia and Hua Wang},
  journal={EAI Endorsed Trans. Scalable Inf. Syst.},
  year={2013},
  volume={2},
  pages={e1}
}
EAI Endorsed Transactions on Scalable Information Systems is a new open access scholarly archival journal that is committed to the timely publication of high-quality original research papers on all aspects of scalable communications theories, technologies, systems, and applications. Original contributions that have not been published and are not currently under consideration by any other journal are solicited. All submissions will go through a rigorous peer-review process, and will be reviewed… 
7 Citations

A Novel Isolation-Based Outlier Detection Method

TLDR
An isolation-based outlier detection method, called Entropy-based Greedy Isolation Tree (EGiTree), is proposed, which exploits a half-baked isolation tree, which is constructed via three entropy-based heuristics, to identify outliers.

Entropy Isolation Forest Based on Dimension Entropy for Anomaly Detection

  • Liefa LiaoBin Luo
  • Computer Science
    Communications in Computer and Information Science
  • 2019
TLDR
An improved anomaly detection method E-iForest (entropy-isolation forest) based on dimension entropy is proposed, which has better detection effect, has better speed in high-capacity datasets, is more stable than iForest and is more robust to the noise features.

Elimination of multidimensional outliers for a compression chiller using a support vector data description

TLDR
This paper presents an automatic anomaly detection method using a support vector data description (SVDD) and finds the ANNSVDD is found to be better than ANNraw in terms of the model reliability and reproducibility.

Multivariate outlier detection in medicare claims payments applying probabilistic programming methods

TLDR
This paper proposes a novel method for fraud detection that focuses on discovering outliers in Medicare payment data using multiple predictors as model inputs and shows that the successful detection of these possibly fraudulent activities can provide effective and meaningful results for further investigation within various medical specialties.

Mining Multispectral Aerial Images for Automatic Detection of Strategic Bridge Locations for Disaster Relief Missions

TLDR
An image mining technique based on multispectral aerial images for automatic detection of strategic bridge locations for disaster relief missions and is believed to be able to help accelerate and enhance the effectiveness of the relief missions carried out during disasters.

References

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A flexible payment scheme and its role-based access control

TLDR
This work uses RBAC to manage the new payment scheme and improve its integrity, and analyzes its role-based access control (RBAC) to reduce conflicts of different roles and decrease complexities of administration.

Injecting purpose and trust into data anonymisation

TLDR
This paper proposes a much finer level anonymisation scheme with regard to the data requester's trust value and specific application purpose and prioritize the attributes for anonymisation based on how important and critical they are related to the specified application purposes.

Et al

TLDR
A large population-based survey of veterans and nondeployed controls found evidence of a deployment-related Gulf War syndrome by factor analysis in Air Force veterans and controls.