A zero-suppressed binary decision diagram (ZDD) is a graph representation suitable for handling sparse set families. Given a ZDD representing a set family, we present an efficient algorithm to discover a hidden structure, called a co-occurrence relat...
Zero-suppressed Binary Decision Diagrams (ZDDs) are data structures for representing set families in a compressed form. With ZDDs, many valuable operations on set families can be done in time polynomial in ZDD size. In some cases, however, the size o...
In the Internet of Vehicles (IoV), zero-day attacks pose a significant security threat. These attacks are characterized by unknown patterns and limited sample availability. Traditional anomaly detection methods often fail because they rely on oversim...
In this article, we propose a succinct data structure of zero-suppressed binary decision diagrams (ZDDs). A ZDD represents sets of combinations efficiently and we can perform various set operations on the ZDD without explicitly extracting combination...
Link puzzles involve finding paths or a cycle in a grid that satisfy given local and global properties. This paper proposes algorithms that enumerate solutions and instances of two link puzzles, Slitherlink and Numberlink, by zero-suppressed binary d...
In order to ensure an ongoing and long-term breeding progress of soybean, stable sources of major quality traits across multi-environments need to be identified. Here, a panel of 135 soybean genotypes was tested in three different Chinese environment...
This Special Issue of Algorithms is focused on the design, formal analysis, implementation, and experimental evaluation of efficient data structures for various computational problems.