Selected work

Representative Papers

Small Object Detection in Industrial Recycling: A New Dataset and YOLO Performance Evaluation

May 26, 2026

This study addresses the challenge of detecting small, densely packed, and overlapping objects in industrial recycling scenarios by introducing the first dedicated small-object detection dataset, comprising over 10,000 images and 120,000 annotated instances. The authors systematically evaluate the performance of YOLO-family models across three tasks: small object detection, length measurement, and anomaly detection. To enhance robustness to scale variations, they propose an anomaly detection method leveraging high-resolution inputs, scale-robust data augmentation, and synthetic image generation. Experimental results demonstrate that the selected optimal YOLO variant achieves superior accuracy, efficiency, and stability, offering a reliable solution for automating industrial recycling processes and establishing a benchmark for future research in this domain.

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Residue Number System Comparison revisited, a software perspective

May 18, 2026

This work addresses the long-standing challenge of general integer comparison in residue number systems (RNS) by proposing an efficient method based on the introduction of an auxiliary modulus and a single mixed-radix conversion. The approach is applicable to arbitrary RNS moduli sets without imposing restrictions on the input range, thereby overcoming limitations inherent in existing techniques that require specific modulus forms or bounded dynamic ranges. The algorithm achieves a time complexity of O(n²), which can be parallelized to O(log n), significantly outperforming both classical and recent state-of-the-art methods constrained by such assumptions. This advancement provides a novel and practical solution to a critical bottleneck in RNS-based applications, including division, scaling, and cryptographic operations.

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Bijections Between Smirnov Words and Hamiltonian Cycles in Complete Multipartite Graphs

Oct 30, 2025

This paper addresses the exact enumeration of Hamiltonian cycles in complete multipartite graphs. Methodologically, it constructs an explicit bijection between Hamiltonian cycles and Smirnov words—sequences over a finite alphabet with no adjacent identical letters—under a letter-frequency balance condition; this bijection is then generalized to non-uniform multipartite graphs, and combined with the inclusion–exclusion principle to derive a closed-form formula for the number of Hamiltonian cycles. Using Stirling’s approximation and asymptotic analysis, the work further obtains a precise logarithmic asymptotic expansion, revealing factorial-order growth. The contributions unify combinatorial enumeration of constrained words and graph-theoretic cycle counting, establishing a cross-domain analytical framework that bridges adjacency-constrained structures and Hamiltonicity problems.

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The Parity-Constrained Four-Peg Tower of Hanoi Problem and Its Associated Graph

Oct 25, 2025

This paper investigates the parity-constrained Tower of Hanoi problem on four pegs: two pegs are designated—exclusively for even- or odd-numbered disks—while the remaining two are neutral. For this novel variant, we establish exact recurrence relations and derive closed-form optimal move counts for four distinct target configurations, revealing a semi-exponential growth rate—strictly between linear and classical exponential—and slower than that of the standard four-peg Tower of Hanoi. We further construct the constrained Hanoi graph and systematically characterize its fundamental graph-theoretic properties: order, diameter, connectivity, planarity, Hamiltonicity, clique number, and chromatic number—proving its structural position is strictly intermediate between the classical three- and four-peg Hanoi graphs. Most notably, we discover that all optimal disk-movement sequences exhibit a periodic growth pattern—a first such result for structurally constrained combinatorial optimization problems—thereby establishing a new analytically tractable modeling paradigm.

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Recent publications

Latest Papers

Small Object Detection in Industrial Recycling: A New Dataset and YOLO Performance Evaluation

May 26, 2026

This study addresses the challenge of detecting small, densely packed, and overlapping objects in industrial recycling scenarios by introducing the first dedicated small-object detection dataset, comprising over 10,000 images and 120,000 annotated instances. The authors systematically evaluate the performance of YOLO-family models across three tasks: small object detection, length measurement, and anomaly detection. To enhance robustness to scale variations, they propose an anomaly detection method leveraging high-resolution inputs, scale-robust data augmentation, and synthetic image generation. Experimental results demonstrate that the selected optimal YOLO variant achieves superior accuracy, efficiency, and stability, offering a reliable solution for automating industrial recycling processes and establishing a benchmark for future research in this domain.

0 citationsRead paper

Residue Number System Comparison revisited, a software perspective

May 18, 2026

This work addresses the long-standing challenge of general integer comparison in residue number systems (RNS) by proposing an efficient method based on the introduction of an auxiliary modulus and a single mixed-radix conversion. The approach is applicable to arbitrary RNS moduli sets without imposing restrictions on the input range, thereby overcoming limitations inherent in existing techniques that require specific modulus forms or bounded dynamic ranges. The algorithm achieves a time complexity of O(n²), which can be parallelized to O(log n), significantly outperforming both classical and recent state-of-the-art methods constrained by such assumptions. This advancement provides a novel and practical solution to a critical bottleneck in RNS-based applications, including division, scaling, and cryptographic operations.

0 citationsRead paper

Bijections Between Smirnov Words and Hamiltonian Cycles in Complete Multipartite Graphs

Oct 30, 2025

This paper addresses the exact enumeration of Hamiltonian cycles in complete multipartite graphs. Methodologically, it constructs an explicit bijection between Hamiltonian cycles and Smirnov words—sequences over a finite alphabet with no adjacent identical letters—under a letter-frequency balance condition; this bijection is then generalized to non-uniform multipartite graphs, and combined with the inclusion–exclusion principle to derive a closed-form formula for the number of Hamiltonian cycles. Using Stirling’s approximation and asymptotic analysis, the work further obtains a precise logarithmic asymptotic expansion, revealing factorial-order growth. The contributions unify combinatorial enumeration of constrained words and graph-theoretic cycle counting, establishing a cross-domain analytical framework that bridges adjacency-constrained structures and Hamiltonicity problems.

0 citationsRead paper

The Parity-Constrained Four-Peg Tower of Hanoi Problem and Its Associated Graph

Oct 25, 2025

This paper investigates the parity-constrained Tower of Hanoi problem on four pegs: two pegs are designated—exclusively for even- or odd-numbered disks—while the remaining two are neutral. For this novel variant, we establish exact recurrence relations and derive closed-form optimal move counts for four distinct target configurations, revealing a semi-exponential growth rate—strictly between linear and classical exponential—and slower than that of the standard four-peg Tower of Hanoi. We further construct the constrained Hanoi graph and systematically characterize its fundamental graph-theoretic properties: order, diameter, connectivity, planarity, Hamiltonicity, clique number, and chromatic number—proving its structural position is strictly intermediate between the classical three- and four-peg Hanoi graphs. Most notably, we discover that all optimal disk-movement sequences exhibit a periodic growth pattern—a first such result for structurally constrained combinatorial optimization problems—thereby establishing a new analytically tractable modeling paradigm.

0 citationsRead paper