Selected work

Representative Papers

Domain Adaptation of Carotid Ultrasound Images using Generative Adversarial Network

Jan 04, 2026arXiv.org

This work addresses the challenge of domain distribution discrepancies in carotid ultrasound images arising from different imaging devices. To mitigate this issue, the authors propose a novel generative adversarial network (GAN) architecture that formulates domain adaptation as an image-to-image translation task. The method simultaneously achieves texture transfer and reverberation noise suppression while preserving anatomical structures. Evaluated on two three-domain carotid ultrasound datasets, the approach substantially outperforms existing techniques such as CycleGAN, significantly enhancing cross-domain consistency. Quantitative results demonstrate high histogram correlation coefficients of 0.960 and 0.920, along with reduced Bhattacharyya distances of 0.040 and 0.085, thereby eliminating performance degradation on new devices and avoiding the need for costly retraining.

1 citationsRead paper

The Emptiness Problem for Quantum Finite Automata with Classical States

Aug 29, 2026

研究了量子有限自动机与经典状态(QFAC)的表达能力和空集问题，提出了一种验证单循环QFAC非空性的方法。

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Pseudonym Scheme Based on Hybrid Certificates for Security Credential Management System in Vehicular Communications

Jun 11, 2026

This study addresses the vulnerability of existing vehicular communication security standards to quantum attacks and the privacy risks arising from inferable linkages between pseudonym certificates and registration certificates. To mitigate these issues, the authors propose a novel hybrid certificate mechanism that integrates elliptic curve cryptography (ECC) with post-quantum cryptography (PQC), marking the first application of hybrid cryptographic techniques in vehicular credential management. They further design a unified pseudonym generation framework compatible with ECC, PQC, and RSA algorithms, effectively decoupling pseudonyms from registered public keys to enhance privacy. Certificate issuance and management are implemented based on IEEE/ETSI SCMS and Butterfly Key Expansion (BKE) mechanisms. Through evaluation of message size and computational overhead, the work benchmarks NIST-standardized PQC candidates and recommends an efficient, quantum-resistant, and privacy-preserving hybrid pseudonym scheme tailored for vehicular networks.

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NGram-MoSE: Efficient Remote Sensing Super-Resolution via N-Gram Context and Mixture-of-Experts

Jun 07, 2026

This work addresses the challenge in remote sensing image super-resolution of simultaneously achieving computational efficiency and robust out-of-distribution generalization, where performance typically degrades significantly on unseen geographic regions. The authors propose a lightweight Transformer architecture that innovatively incorporates N-Gram context injection to enhance local texture continuity and mitigate window boundary artifacts. This design is further augmented with a sparsely activated Mixture-of-Experts (MoE) feed-forward network, which increases model capacity with negligible additional inference cost. Evaluated on out-of-distribution test sets, the method achieves a PSNR of 31.68 dB while reducing FLOPs by 14× compared to existing approaches. When applied to a downstream landslide segmentation task, it improves mAP@50 by 4.47%, substantially outperforming the bicubic interpolation baseline.

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ErgoGlide: A Wearable Trackball Device for Ergonomic Text Entry in Virtual Reality

May 30, 2026

This work addresses the longstanding challenge in virtual reality (VR) text input of simultaneously achieving high speed, accuracy, and ergonomic comfort. To this end, the authors propose ErgoGlide, a lightweight ring-mounted wearable trackball device paired with a hexagonal-layout virtual keyboard. Users precisely select keys by rotating the integrated miniature trackball, substantially minimizing thumb movement. The design pioneers the integration of a micro trackball into a finger-ring form factor and incorporates a multimodal confirmation mechanism alongside an interactive training strategy. Experimental results demonstrate that ErgoGlide maintains high typing accuracy and usability while significantly improving input speed after user training, thereby offering an effective optimization of human–computer interaction for VR text entry.

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Recent publications

Latest Papers

The Emptiness Problem for Quantum Finite Automata with Classical States

Aug 29, 2026

研究了量子有限自动机与经典状态(QFAC)的表达能力和空集问题，提出了一种验证单循环QFAC非空性的方法。

0 citationsRead paper

Pseudonym Scheme Based on Hybrid Certificates for Security Credential Management System in Vehicular Communications

Jun 11, 2026

This study addresses the vulnerability of existing vehicular communication security standards to quantum attacks and the privacy risks arising from inferable linkages between pseudonym certificates and registration certificates. To mitigate these issues, the authors propose a novel hybrid certificate mechanism that integrates elliptic curve cryptography (ECC) with post-quantum cryptography (PQC), marking the first application of hybrid cryptographic techniques in vehicular credential management. They further design a unified pseudonym generation framework compatible with ECC, PQC, and RSA algorithms, effectively decoupling pseudonyms from registered public keys to enhance privacy. Certificate issuance and management are implemented based on IEEE/ETSI SCMS and Butterfly Key Expansion (BKE) mechanisms. Through evaluation of message size and computational overhead, the work benchmarks NIST-standardized PQC candidates and recommends an efficient, quantum-resistant, and privacy-preserving hybrid pseudonym scheme tailored for vehicular networks.

0 citationsRead paper

NGram-MoSE: Efficient Remote Sensing Super-Resolution via N-Gram Context and Mixture-of-Experts

Jun 07, 2026

This work addresses the challenge in remote sensing image super-resolution of simultaneously achieving computational efficiency and robust out-of-distribution generalization, where performance typically degrades significantly on unseen geographic regions. The authors propose a lightweight Transformer architecture that innovatively incorporates N-Gram context injection to enhance local texture continuity and mitigate window boundary artifacts. This design is further augmented with a sparsely activated Mixture-of-Experts (MoE) feed-forward network, which increases model capacity with negligible additional inference cost. Evaluated on out-of-distribution test sets, the method achieves a PSNR of 31.68 dB while reducing FLOPs by 14× compared to existing approaches. When applied to a downstream landslide segmentation task, it improves mAP@50 by 4.47%, substantially outperforming the bicubic interpolation baseline.

0 citationsRead paper

ErgoGlide: A Wearable Trackball Device for Ergonomic Text Entry in Virtual Reality

May 30, 2026

This work addresses the longstanding challenge in virtual reality (VR) text input of simultaneously achieving high speed, accuracy, and ergonomic comfort. To this end, the authors propose ErgoGlide, a lightweight ring-mounted wearable trackball device paired with a hexagonal-layout virtual keyboard. Users precisely select keys by rotating the integrated miniature trackball, substantially minimizing thumb movement. The design pioneers the integration of a micro trackball into a finger-ring form factor and incorporates a multimodal confirmation mechanism alongside an interactive training strategy. Experimental results demonstrate that ErgoGlide maintains high typing accuracy and usability while significantly improving input speed after user training, thereby offering an effective optimization of human–computer interaction for VR text entry.

0 citationsRead paper

Exploring Agent Interactions in MoltBook through Social Network Analysis

May 26, 2026

This study addresses a critical gap in multi-agent systems research by moving beyond conventional analyses of network topology to incorporate the semantic and affective dimensions of agent interactions. The authors propose an integrative multidimensional framework that combines social network analysis, sentiment analysis, and topic visualization, thereby transcending prior paradigms anchored in human-centric social benchmarks. Leveraging Hermes agents powered by the Minimax 2.7 large language model, the study collects and preprocesses communication data from the MoltBook platform, followed by a holistic evaluation integrating structural metrics with qualitative diagnostics. For the first time, this work uncovers distinctive quality characteristics of agent-to-agent interactions within this ecosystem, establishing both a novel analytical paradigm and empirical foundation for semantically rich investigations of decentralized autonomous digital networks.

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