DataCI: A Platform for Data-Centric AI on Streaming Data

We introduce DataCI, a comprehensive open-source platform designed specifically for data-centric AI in dynamic streaming data settings. DataCI provides 1) an infrastructure with rich APIs for seamless streaming dataset management, data-centric pipeline development and evaluation on streaming scenarios, 2) an carefully designed versioning control function to track the pipeline lineage, and 3) an intuitive graphical interface for a better interactive user experience. Preliminary studies and demonstrations attest to the easy-to-use and effectiveness of DataCI, highlighting its potential to revolutionize the practice of data-centric AI in streaming data contexts.Comment: 3 pages, 4 figure

Requirement of dendritic Akt degradation by the ubiquitin–proteasome system for neuronal polarity

Asymmetric distributions of activities of the protein kinases Akt and glycogen synthase kinase 3β (GSK-3β) are critical for the formation of neuronal polarity. However, the mechanisms underlying polarized regulation of this pathway remain unclear. In this study, we report that the instability of Akt regulated by the ubiquitin–proteasome system (UPS) is required for neuron polarity. Preferential distribution in the axons was observed for Akt but not for its target GSK-3β. A photoactivatable GFP fused to Akt revealed the preferential instability of Akt in dendrites. Akt but not p110 or GSK-3β was ubiquitinated. Suppressing the UPS led to the symmetric distribution of Akt and the formation of multiple axons. These results indicate that local protein degradation mediated by the UPS is important in determining neuronal polarity

Lie algebras with differential operators of any weights

In this paper, we define a cohomology theory for differential Lie algebras of any weight. As applications of the cohomology, we study abelian extensions and formal deformations of differential Lie algebras of any weight. Finally, we consider homotopy differential operators on $\mathrm{L}_{\infty}$ algebras and 2-differential operators of any weight on Lie 2-algebras, and we prove that the category of 2-term $\mathrm{L}_{\infty}$ algebras with homotopy differential operators of any weight is same as the category of Lie 2-algebras with 2-differential operators of any weight

Active-Learning-as-a-Service: An Efficient MLOps System for Data-Centric AI

The success of today's AI applications requires not only model training (Model-centric) but also data engineering (Data-centric). In data-centric AI, active learning (AL) plays a vital role, but current AL tools can not perform AL tasks efficiently. To this end, this paper presents an efficient MLOps system for AL, named ALaaS (Active-Learning-as-a-Service). Specifically, ALaaS adopts a server-client architecture to support an AL pipeline and implements stage-level parallelism for high efficiency. Meanwhile, caching and batching techniques are employed to further accelerate the AL process. In addition to efficiency, ALaaS ensures accessibility with the help of the design philosophy of configuration-as-a-service. It also abstracts an AL process to several components and provides rich APIs for advanced users to extend the system to new scenarios. Extensive experiments show that ALaaS outperforms all other baselines in terms of latency and throughput. Further ablation studies demonstrate the effectiveness of our design as well as ALaaS's ease to use. Our code is available at \url{https://github.com/MLSysOps/alaas}.Comment: 8 pages, 7 figure

Practical Attacks Against Graph-based Clustering

Graph modeling allows numerous security problems to be tackled in a general way, however, little work has been done to understand their ability to withstand adversarial attacks. We design and evaluate two novel graph attacks against a state-of-the-art network-level, graph-based detection system. Our work highlights areas in adversarial machine learning that have not yet been addressed, specifically: graph-based clustering techniques, and a global feature space where realistic attackers without perfect knowledge must be accounted for (by the defenders) in order to be practical. Even though less informed attackers can evade graph clustering with low cost, we show that some practical defenses are possible.Comment: ACM CCS 201

Smart Rock Technology for Real-Time Monitoring of Bridge Scour and Riprap Effectiveness -- Design Guidelines and Visualization Tools

This study aims to further develop and demonstrate the recently-proposed smart rock technology for scour depth and protection effectiveness monitoring. A smart rock is one or two stacked magnets encased in a concrete sphere with a specially-designed rotational mechanism. Design guidelines, rotational mechanisms, remote measurement tools and localization algorithms of smart rocks were developed and validated at three bridge sites. The effect of steel reinforcement in bridge piers/deck on the orientation of gravity-controlled magnets was negligible. The localization accuracy with a single smart rock met a general requirement of less than 0.5 m in engineering applications. The spherical smart rock placed directly on the riverbed of the Roubidoux Creek successfully demonstrated its movement to the bottom of scour hole during the December 27, 2015, flood. Those deployed in the Waddell Creek and the Gasconade River were washed away and thus replaced with smart rocks embedded in deposits such that their top is in flush with the riverbed for improved stability under water current. For rip-rap effectiveness monitoring, polyhedral smart rocks are recommended to increase their interlock with other natural rocks