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Konnakol is a South Indian, Carnatic musical practice involving the vocal recitation of algorithmic, geometric rhythmic patterns of non-lexical syllables. I reflect on the experience of learning konnakol rhythms, and of adapting the TidalCycles and ...

Tessellations of a plane surface by means of unit-sided regular polygons is a classical subject both in art, with examples dating back to the earliest human civilisations, and mathematics, where the complex patterns generated by a very simple set of ...

The compilation of feature models into binary decision diagrams (BDDs) is a major challenge in the area of configurable systems analysis. Many large-scale feature models have been reported to exceed state-of-the-art compilation capabilities, e.g., for ...

Bayesian inference is a probabilistic approach to the problem of drawing conclusions from observed data. Its main challenge is computational, which the Bayesian community tends to address through approximation techniques. However, these techniques come ...

Large space high-precision attitude dynamic measurement technology has urgent application needs in aerospace, rail transit, automobile and ship, wind power and other large equipment manufacturing fields. In this paper, a dynamic attitude angle ...

Many research results in nonlinear science indicate that many nonlinear systems exhibit long-range correlation characteristics. The Hurst exponent can effectively measure the long-range correlations and predictability of time series. Existing research ...

Against the background of the Chinese government's emphasis on energy conservation and emission reduction, this study explores the methane emission problem in the petrochemical industry. By analyzing the challenges and limitations of traditional methods ...

Ultrasound neurostimulation, a technique that modulates the brain's electrical activity, has emerged as a significant secondary treatment option for cases resistant to pharmacological interventions. The therapy is achievable through the application of a ...

Today's scientific applications running on supercomputers produce large volumes of data, leading to critical data storage and communication challenges. To tackle the challenges, error-bounded lossy compression is commonly adopted since it can reduce data ...

Graphic Processing Units (GPUs) have become a key component of high-end computing infrastructures due to their massively parallel architecture, which delivers large floating-point operations per cycle rates. Many scientific workloads benefit from GPUs ...

Lossy compression can be an effective tool in AI training and inference to reduce memory requirements, storage footprint, and in some cases, execution time. With the rise of novel architectures designed to accelerate AI workloads, compression can ...

Numerical programs that generate floating-point exceptions, such as NaNs, are inherently unreliable, as these programs can produce meaningless outputs or affect control flow. When these programs run on GPUs, one cannot rely on hardware traps to handle ...

Counting and enumerating all occurrences of k-cliques, i.e., complete subgraphs with k vertices, in a large graph G is a fundamental problem with many applications. However, exact solutions are often infeasible due to the exponential growth in the number ...

Index Advisor tools settle for sub-optimal index configurations based on greedy heuristics, owing to the computational hardness of index selection. We investigate here how this limitation can be addressed by leveraging the computing power offered by ...

Betweenness centrality (BC), a classic measure which quantifies the importance of a vertex to act as a communication "bridge" between other vertices in the network, is widely used in many practical applications. With the advent of large heterogeneous ...

Hypothesis testing is a statistical method used to draw conclusions about populations from sample data, typically represented in tables. With the prevalence of graph representations in real-life applications, hypothesis testing on graphs is gaining ...

We present a system for Complex Event Recognition (CER) based on automata. While multiple such systems have been described in the literature, they typically suffer from a lack of clear and denotational semantics, a limitation which often leads to ...

This paper addresses the challenge of identifying super spreaders within large, high-speed data streams. In these streams, data is segmented into flows, with each flow's spread defined as the number of distinct items it contains. A super spreader is ...

In the heterogeneous information network (HIN), a motif-clique is a "complete graph" for a given motif (or a small connected graph) that could capture the desired relationship in the motif. The maximal motif-cliques of HINs have found various ...

Locally-densest subgraph (LDS) decomposition is a fundamental decomposition in graph analysis that finds numerous applications in various domains, including community detection, fraud detection, graph querying, and graph visualization. However, the LDS ...