VerdictDB: Universalizing Approximate Query Processing

Despite 25 years of research in academia, approximate query processing (AQP) has had little industrial adoption. One of the major causes of this slow adoption is the reluctance of traditional vendors to make radical changes to their legacy codebases, and the preoccupation of newer vendors (e.g., SQL-on-Hadoop products) with implementing standard features. Additionally, the few AQP engines that are available are each tied to a specific platform and require users to completely abandon their existing databases---an unrealistic expectation given the infancy of the AQP technology. Therefore, we argue that a universal solution is needed: a database-agnostic approximation engine that will widen the reach of this emerging technology across various platforms. Our proposal, called VerdictDB, uses a middleware architecture that requires no changes to the backend database, and thus, can work with all off-the-shelf engines. Operating at the driver-level, VerdictDB intercepts analytical queries issued to the database and rewrites them into another query that, if executed by any standard relational engine, will yield sufficient information for computing an approximate answer. VerdictDB uses the returned result set to compute an approximate answer and error estimates, which are then passed on to the user or application. However, lack of access to the query execution layer introduces significant challenges in terms of generality, correctness, and efficiency. This paper shows how VerdictDB overcomes these challenges and delivers up to 171$\times$ speedup (18.45$\times$ on average) for a variety of existing engines, such as Impala, Spark SQL, and Amazon Redshift, while incurring less than 2.6% relative error. VerdictDB is open-sourced under Apache License.Comment: Extended technical report of the paper that appeared in Proceedings of the 2018 International Conference on Management of Data, pp. 1461-1476. ACM, 201

Visual Explorations of Dynamics: the Standard Map

The Macintosh application \textit{StdMap} allows easy exploration of many of the phenomena of area-preserving mappings. This tutorial explains some of these phenomena and presents a number of simple experiments centered on the use of this program.Comment: Corrections in a couple of equations, and updated to the latest version of StdMa

Expression of angiogenic and neurotrophic factors in the human amnion and choriodecidua

OBJECTIVE: Our objective was to identify the novel or differential expression of growth or development associated genes in the human gestational membranes that might play roles in pregnancy or in term or preterm parturition. STUDY DESIGN: Complementary DNA arrays were probed with [alpha(33)P]dCTP-labeled-complementary DNA that was prepared from the RNA of reflected amnion and choriodecidua that represent term not-in-labor, term spontaneous labor, and preterm labor with and without chorioamnionitis (n = 4 per group). Differential expression (term not-in-labor vs term spontaneous labor or preterm labor with chorioamnionitis vs preterm labor without chorioamnionitis) was evaluated by Wilcoxon tests. RESULTS: All 16 amnion samples expressed angiogenic factors (endothelin-2 and -3, vascular endothelial growth factor, and vascular endothelial growth factor-B) and neurotrophic factors (ephrin-A2, ephrin receptors-A2, -B1, -B3, -B4, and -B5, neuropilin-2, p75/nerve growth factor receptor and semaphorin-F). In both amnion and choriodecidua, the expression of vascular endothelial growth factor and the angiopoietin receptor, Tie-2, were greater with term spontaneous labor than with term not-in-labor (P <.05); increased VEGF receptor-2 (flk-1) expression was observed in term spontaneous labor choriodecidua (P <.05) but not amnion. Ephrin-A1 expression increased with term spontaneous labor in both tissues (P <.05). Semaphorin-F expression decreased with preterm labor with chorioamnionitis in choriodecidua (P <.05), although the trend was not significant in amnion (P =. 1). CONCLUSION: Neurotrophic and angiogenic factor genes are expressed in amnion and choriodecidual membranes. Several of the genes exhibit differential expression with labor at term or in association with infection preterm, which suggests roles in or associated with these processes

GangSweep: Sweep Out Neural Backdoors by GAN

This work proposes GangSweep, a new backdoor detection framework that leverages the super reconstructive power of Generative Adversarial Networks (GAN) to detect and \u27\u27sweep out\u27\u27 neural backdoors. It is motivated by a series of intriguing empirical investigations, revealing that the perturbation masks generated by GAN are persistent and exhibit interesting statistical properties with low shifting variance and large shifting distance in feature space. Compared with the previous solutions, the proposed approach eliminates the reliance on the access to training data, and shows a high degree of robustness and efficiency for detecting and mitigating a wide range of backdoored models with various settings. Moreover, this is the first work that successfully leverages generative networks to defend against advanced neural backdoors with multiple triggers and their polymorphic forms