Anomaly detection is a problem with applications for a wide variety of domains; it involves
the identification of novel or unexpected observations or sequences within the data being …

In the field of wireless sensor networks, those measurements that significantly deviate from
the normal pattern of sensed data are considered as outliers. The potential sources of …

Multimodal time series (MTS) anomaly detection is crucial for maintaining the safety and
stability of working devices (eg, water treatment system and spacecraft), whose data are …

摘要信息感知作为物联两的基本功能. 是物联网信息“全面感知” 的手段. 信息交互是物联网应用
与服务的基础, 是物联网“物物互联” 的目的. 随着物联网研究热潮的兴起, 以传统无线传感器网络 …

In the statistics community, outlier detection for time series data has been studied for
decades. Recently, with advances in hardware and software technology, there has been a …

In this paper we propose a novel observer-based method to improve the safety and security
of connected and automated vehicle (CAV) transportation. The proposed method combines …

The task of anomaly detection in data is one of the main challenges in data science because
of the wide plethora of applications and despite a spectrum of available methods …

Over the past few years, wireless sensor networks have gained significant attention. They
have been distributed in the real world in order to collect valuable raw sensed data. Due to …

Temporal data mining deals with the harvesting of useful information from temporal data.
New initiatives in health care and business organizations have increased the importance of …

Enormous data are continuously collected by the structural health monitoring system of civil
infrastructures. The structural health monitoring data inevitably involve anomalies caused by …