Moving Metric Detection and Alerting System at eBay

At eBay, there are thousands of product health metrics for different domain teams to monitor. We built a two-phase alerting system to notify users with actionable alerts based on anomaly detection and alert retrieval. In the first phase, we developed an efficient anomaly detection algorithm, called Moving Metric Detector (MMD), to identify potential alerts among metrics with distribution agnostic criteria. In the second alert retrieval phase, we built additional logic with feedbacks to select valid actionable alerts with point-wise ranking model and business rules. Compared with other trend and seasonality decomposition methods, our decomposer is faster and better to detect anomalies in unsupervised cases. Our two-phase approach dramatically improves alert precision and avoids alert spamming in eBay production.Comment: The work is oral presented on the AAAI-20 Workshop on Cloud Intelligence, 202

Molecular brewing: molecular structural effects involved in barley malting and mashing

Ten barley samples containing varied protein contents were subject to malting followed by mashing to investigate molecular effects of both barley starch and starch- protein interactions on malting and mashing performances, and the underlying mechanism. Starch granular changes were examined using differential scanning calorimetry and scanning electron microscopy. The molecular fine structures of amylose and amylopectin from unmalted and malted grain were obtained using size-exclusion chromatography. The results showed that both amylose and amylopectin polymers were hydrolyzed at the same time during malting. Protein and amylose content in both unmalted and malted barley significant negatively correlated with fermentable sugar content after mashing. While protein content is currently the main criterion for choosing malting varieties, this study shows that information about starch molecular structure is also useful for determining the release of fermentable sugars, an important functional property. This provides brewers with some new methods to choose malting barley

Real-time three-dimensional smooth path planning for unmanned aerial vehicles in completely unknown cluttered environments

This paper presents a real-time three-dimensional path planning algorithm for improving autonomous navigation of Unmanned Aerial Vehicles (UAVs) operating in completely unknown cluttered environments. The algorithm generates smooth paths consisting of continuous piecewise Bézier curves in real time. Specifically, a RRT-based waypoint generation algorithm is firstly proposed for the exploration of collision-free waypoints successively during flight. Besides, a novel real-time path smoothing technique is developed to generate continuous collision-free paths that satisfy the motion constraints of UAVs. This is achieved by fitting Bézier curves between consecutive waypoints based on the particle swarm optimization (PSO) algorithm. Lastly, a path selection strategy is also introduced to seek for an optimum path when multiple solutions are available. The simulation results demonstrate the superiority of the proposed real-time three-dimensional smooth path planning algorithm.NRF (Natl Research Foundation, S’pore