Controllability of nonlinear fractional delay dynamical systems with prescribed controls

In this paper, we consider controllability of nonlinear fractional delay dynamical systems with prescribed controls. We firstly give the solution representation of the fractional delay dynamical systems using Laplace transform and Mittag–Leffler functions. Then we give necessary and sufficient conditions for the controllability criteria of linear fractional delay dynamical systems with prescribed controls. Further, we use a fixed point theorem to establish the sufficient condition for the controllability of nonlinear fractional delay dynamical systems with prescribed controls. In particular, we determine several sufficient conditions on the nonlinear function term so that if the linear system is controllable, then the nonlinear system is controllable. Finally, we give two examples to demonstrate the applicability of our obtained results

Dibromido{2-morpholino-N-[1-(2-pyrid­yl)ethyl­idene]ethanamine-κ3 N,N′,N′′}zinc(II)

In the title complex, [ZnBr2(C13H19N3O)], the ZnII atom is five-coordinated by the three N-donor atoms of the Schiff base ligand and by two Br atoms in a distorted square-pyramidal geometry. The morpholine ring adopts a chair conformation

Querying Streaming System Monitoring Data for Enterprise System Anomaly Detection

The need for countering Advanced Persistent Threat (APT) attacks has led to the solutions that ubiquitously monitor system activities in each enterprise host, and perform timely abnormal system behavior detection over the stream of monitoring data. However, existing stream-based solutions lack explicit language constructs for expressing anomaly models that capture abnormal system behaviors, thus facing challenges in incorporating expert knowledge to perform timely anomaly detection over the large-scale monitoring data. To address these limitations, we build SAQL, a novel stream-based query system that takes as input, a real-time event feed aggregated from multiple hosts in an enterprise, and provides an anomaly query engine that queries the event feed to identify abnormal behaviors based on the specified anomaly models. SAQL provides a domain-specific query language, Stream-based Anomaly Query Language (SAQL), that uniquely integrates critical primitives for expressing major types of anomaly models. In the demo, we aim to show the complete usage scenario of SAQL by (1) performing an APT attack in a controlled environment, and (2) using SAQL to detect the abnormal behaviors in real time by querying the collected stream of system monitoring data that contains the attack traces. The audience will have the option to interact with the system and detect the attack footprints in real time via issuing queries and checking the query results through a command-line UI.Comment: Accepted paper at ICDE 2020 demonstrations track. arXiv admin note: text overlap with arXiv:1806.0933