—Due to the development of intelligent demand-side management with automatic control, distributed populations of large residential loads, such as air conditioners (ACs) and electrical water heaters (EWHs), have the opportunities to provide effective demand-side ancillary services for load serving entities (LSEs) to reduce the emissions and network operating costs. Most present approaches are re...

Learning graph-structured data with graph neural networks (GNNs) has been recently emerging as an important field because of its wide applicability in bioinformatics, chemoinformatics, social network analysis, and mining. Recent GNN algorithms are based on message passing, which enables GNNs to integrate local structures node features recursively. However, past 1-hop neighborhood passing expose...

With the growth in the number of public web archives it is becoming important to provide a means to aggregate them for better coverage and completeness. The Memento protocol [2] provides a uniform API to lookup URIs in web archives. Due to the wide support of the Memento protocol in the archiving ecosystem it is now easy to aggregate their holdings for any URI lookup. However, current applicati...

In this paper, a two-stage optimal charging scheme based on transactive control is proposed for the aggregator to manage day-ahead electricity procurement and real-time EV charging management in order to minimize its total operating cost. The day-ahead electricity procurement considers both the day-ahead energy cost and expected real-time operation cost. In the real-time charging management, th...

Aggregate statistics computed from time-series data contributed by individual mobile nodes can be very useful for many mobile sensing applications. Since the data from individual node may be privacy-sensitive, the aggregator should only learn the desired statistics without compromising the privacy of each node. To provide strong privacy guarantee, existing approaches add noise to each node’s da...