The F-Area Seepage Basins at the U.S. Department of Energy (DOE)’s Savannah River Site (SRS) have been a long-standing source of groundwater contamination due to the disposal of low-level radioactive waste during the Cold War. To mitigate further contamination, the basins were dewatered and sealed with low-permeability caps designed to prevent rainwater infiltration and minimize migration of contaminants into the groundwater. Monitoring the structural integrity of these caps is crucial to maintaining the effectiveness of remediation efforts. Electrical Resistivity Tomography (ERT) has been deployed to detect water seepage through the cap by measuring changes in electrical conductivity beneath the cap. However, although ERT data collection and processing can be automated, analysis of the resultant images requires human effort, which is time-consuming and resource-intensive over the timescales required for long-term monitoring. An AI-based automated system was developed to process and analyze ERT images in real time. This system identifies anomalies in conductivity values, locates potential seepage areas, and evaluates their severity. The results are automatically visualized in an interactive 3D model, enabling stakeholders to efficiently assess cap integrity and determine whether further investigation is warranted. By eliminating the need for daily manual data analysis, this approach significantly reduces monitoring costs and enhances early detection capabilities. The AI system is adaptable to any ERT-based monitoring application beyond the F-Area Seepage Basin caps, enabling the detection, localization, and assessment of anomalies across a wide range of domains, both within and beyond the DOE complex.

We introduce two new metrics of “simplicity” for knight's tours: the number of turns and the number of crossings. We give a novel algorithm that produces tours with 9.25n+O(1) turns and 12n+O(1) crossings on an n×n board, and we show lower bounds of (6−ϵ)n and 4n−O(1) on the respective problems of minimizing these metrics. Hence, our algorithm achieves approximation ratios of 9.25/6+o(1) and 3+o(1). Our algorithm takes linear time and is fully parallelizable, i.e., the tour can be computed in O(n2/p) time using p processors in the CREW PRAM model. We generalize our techniques to rectangular boards, high-dimensional boards, symmetric tours, odd boards with a missing corner, and tours for (1,4)-leapers. In doing so, we show that these extensions also admit a constant approximation ratio on the minimum number of turns, and on the number of crossings in most cases.

We empirically study sorting in the evolving data model. In this model, a sorting algorithm maintains an approximation to the sorted order of a list of data items while simultaneously, with each comparison made by the algorithm, an adversary randomly swaps the order of adjacent items in the true sorted order. Previous work studies only two versions of quicksort, and has a gap between the lower bound of Ω(n) and the best upper bound of O(n log log n). The experiments we perform in this paper provide empirical evidence that some quadratic-time algorithms such as insertion sort and bubble sort are asymptotically optimal for any constant rate of random swaps. In fact, these algorithms perform as well as or better than algorithms such as quicksort that are more efficient in the traditional algorithm analysis model.

We give optimal sorting algorithms in the evolving data framework, where an algorithm's input data is changing while the algorithm is executing. In this framework, instead of producing a final output, an algorithm attempts to maintain an output close to the correct output for the current state of the data, repeatedly updating its best estimate of a correct output over time. We show that a simple repeated insertion-sort algorithm can maintain an O(n) Kendall tau distance, with high probability, between a maintained list and an underlying total order of n items in an evolving data model where each comparison is followed by a swap between a random consecutive pair of items in the underlying total order. This result is asymptotically optimal, since there is an Omega(n) lower bound for Kendall tau distance for this problem. Our result closes the gap between this lower bound and the previous best algorithm for this problem, which maintains a Kendall tau distance of O(n log log n) with high probability. It also confirms previous experimental results that suggested that insertion sort tends to perform better than quicksort in practice.

A square-contact representation of a planar graph $G=(V,E)$ maps vertices in $V$ to interior-disjoint axis-aligned squares in the plane and edges in $E$ to adjacencies between the sides of the corresponding squares. In this paper, we study proper square-contact representations of planar graphs, in which any two squares are either disjoint or share infinitely many points. We characterize the partial $2$-trees and the triconnected cycle-trees allowing for such representations. For partial $2$-trees our characterization uses a simple forbidden subgraph whose structure forces a separating triangle in any embedding. For the triconnected cycle-trees, a subclass of the triconnected simply-nested graphs, we use a new structural decomposition for the graphs in this family, which may be of independent interest. Finally, we study square-contact representations of general triconnected simply-nested graphs with respect to their outerplanarity index.

We describe a security visualization tool for finding algorithmic complexity attacks in Java bytecode. Our tool, which we call J-Viz, visualizes connected directed graphs derived from Java bytecode according to a canonical node ordering, which we call the sibling-first recursive (SFR) numbering. The particular graphs we consider are derived from applying Shiver's k-CFA framework to Java bytecode, and our visualizer includes helpful links between the nodes of an input graph and the Java bytecode that produced it, as well as a decompiled version of that Java bytecode. We show through experiments involving test cases provided by DARPA that the canonical drawing paradigm used in J-Viz is effective for identifying potential security vulnerabilities for algorithmic complexity attacks.

This talk will provide an overview of the Niagara 2 architecture, its physical implementation, and the challenges faced with designing a 65nm SoC microprocessor. Details will also be shared with respect to Niagara 2's clocking scheme and unique design for power and power management schemes.