Cong Liu

Evaluation of sustainable bilateral tourism relations among the RCEP countries: a network-based quantitative analysis

LIANG Xiaoyao, Lijun Ma, Cong Liu, Min Ouyang et autres

Purpose The regional comprehensive economic partnership (RCEP) provides a new institutional platform for regional tourism cooperation. Bilateral tourism relations (BTR), the basic units of a tourism relations network, remain insufficiently quantified, limiting the accurate identification of the foundations for cooperation. Therefore, this …

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MUTUALISM: Low-Footprint and High-Throughput Software Implementation of HQC for Resource-Constrained Devices

Cong Liu, Akira Maruko, Yasushi Takahashi, Naoto Yanai

Hamming Quasi-Cyclic (HQC) is a code-based key-encapsulation mechanism selected by NIST for post-quantum cryptography standardization, but it is challenging to deploy on resource-constrained devices due to its memory and computational costs. In this paper, we propose a novel software implementation of HQC, …

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Association between Chinese only-child university students’ psychological symptoms and lifestyle behaviors

Cong Liu, Yan Yuan, Juncheng Zhu, Jianping Xiong et autres

BACKGROUND: Only children in China have been reported to experience greater psychological distress and engage in less healthy behaviors compared to their peers with siblings. This study aimed to investigate associations between physical activity, sedentary behaviors, dietary habits, sleep duration, and psychological …

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A QCM gas sensor based on Ce-MOF-808 and graphene oxide nanocomposite for rapid and sensitive detection of trimethylamine

Guolin Cheng, Yunyan Li, Lei Ren, Cong Liu et autres

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Giant Footprint Sharing: A Memory-Efficient Decryption Implementation for Classic McEliece

Cong Liu, Naoto Yanai, Naohisa Nishida, Akira Maruko

Classic McEliece has gathered attention as a candidate in NIST post-quantum cryptography standardization. However, it suffers from high demands on the decryption algorithm, making it unsuitable for resource-constrained devices. In this paper, we propose a novel implementation method, named giant footprint sharing, …

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Deep reinforcement learning for energy-efficient workflow scheduling in edge computing

Xiufeng Liu, Xin Ning, Cong Liu, Xiaomin Chen et autres

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Enhanced Building Extraction via STMC-UNet: Integrating Super Token Transformer and Multi-scale Convolution

Ke Zhou, Cong Liu, Yanna Zhang, Ru Miao et autres

Accurate extraction of buildings from high-resolution remote sensing images is pivotal for urban planning and sustainable development. While existing CNN- and Transformer-based semantic segmentation methods have advanced, they often struggle with long-range dependencies and high computational complexity, respectively. We propose STMC-UNet, a …

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Analysis of Spatiotemporal Characteristics in the Prevalence of Depressive Disorder and Anxiety Disorders Among Adolescents in Asia Before and After the COVID-19 Pandemic

Zhike He, Ting Yuan, Juncheng Zhu, T Yang et autres

Using data from the Global Burden of Disease (GBD) study, this research systematically examines the spatiotemporal trends of depressive disorder and anxiety disorders among adolescents aged 15 to 19 years across 48 Asian countries/regions from 2016 to 2021. Pre-pandemic (2016-2019), South Asia, …

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A QCM gas sensor based on 0.5Co-Mn-BTC MOF nanocomposites for salmon meat freshness detection

Guolin Cheng, Cong Liu, Shihao Chen, Yunyan Li et autres

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Research on Dynamic Task Allocation of UAV Based on Event-Triggered

Yongliang Du, Cong Liu, Di Chen

UAV task allocation still has some challenges in the field of military search, such as the dynamic search environment. Firstly, a task grouping algorithm is proposed, and the search task group allocation is realized by combining the auction algorithm. Secondly, events such …

Enhancing Manufacturing Process Discovery Through Sub-Process Optimization

Cong Liu, Long Cheng, Jiujun Cheng, Weijian Ni et autres

Manufacturing process discovery extracts insights from event logs recorded by Manufacturing Information Systems (MISs) to optimize operational processes. However existing process discovery techniques struggle with complex concurrency relations, resulting in imprecise sub-processes that compromise model accuracy. This paper proposes a novel enhancement …

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EdgeIM: An Efficient Edge-Based Process Model Discovery Technique

Xuan Su, Cong Liu, Faming Lu, Long Cheng et autres

The rapid expansion of Internet of Things (IoT) devices has led to an explosion of event data, posing significant challenges for traditional process model discovery techniques in terms of scalability and discovery accuracy. These techniques rely on centralized storage and processing, which …

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