Anomaly detection in high dimensional data is becoming a fundamental research problem
that has various applications in the real world. However, many existing anomaly detection …

As an important stage of life cycle management, machinery PHM (prognostics and health
management), an emerging subject in mechanical engineering, has seen a huge amount of …

Distributed stream processing systems need to support stateful processing, recover quickly
from failures to resume such processing, and reprocess an entire data stream quickly. We …

The smart grid (SG) paradigm is the next technological leap of the conventional electrical
grid, contributing to the protection of the physical environment and providing multiple …

MillWheel is a framework for building low-latency data-processing applications that is widely
used at Google. Users specify a directed computation graph and application code for …

Future buildings will offer new convenience, comfort, and efficiency possibilities to their
residents. Changes will occur to the way people live as technology involves people's lives …

It is already true that Big Data has drawn huge attention from researchers in information
sciences, policy and decision makers in governments and enterprises. As the speed of …

S4 is a general-purpose, distributed, scalable, partially fault-tolerant, pluggable platform that
allows programmers to easily develop applications for processing continuous unbounded …

Big data processing systems are evolving to be more stream oriented where each data
record is processed as it arrives by distributed and low-latency computational frameworks on …

Traffic congestion is one of the leading causes of lost productivity and decreased standard of
living in urban settings. Recent advances in artificial intelligence suggest vehicle navigation …