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2012 national conference on information technology and computer science, citcs 2012

ISBN: (纸本)9789491216381

The proceedings contain 271 papers. The topics discussed include: application of ant colony algorithm in fingerprint identification system based on Internet of things;research on lash-up maintenance technology of engineering equipment;the research of future-market-like supervision of the exchange of cultural products and artworks;applicability evaluation to capital asset pricing model;the innovative study of Jilin province's urban integration development;the research of online transaction risk in service provider to consumer;innovation of emergency management establishment of new mode for holographic command and collaborative work;the market competition, law enforcement, and banking system's efficiency in China;mutual authentication scheme for multi-server environment without using smart cards;and research on data acquisition and signal processing of fault diagnosis system for electromechanical equipment.

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A Compressive Memory-based Retrieval Approach for Event Argument Extraction 31

A Compressive Memory-based Retrieval Approach for Event Argu...

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31st International conference on Computational Linguistics, COLING 2025

作者： Liu, Wanlong Zhang, Enqi Cheng, Shaohuan Zhou, Li Zeng, Dingyi Zhang, Chen Zhang, Malu Chen, Wenyu University of Electronic Science and Technology of China China The Chinese University of Hong Kong Shenzhen China National University of Singapore Singapore

ISBN: (纸本)9798891761964

Recent works have demonstrated the effectiveness of retrieval augmentation in the Event Argument Extraction (EAE) task. However, existing retrieval-based EAE methods have two main limitations: (1) input length constraints and (2) the gap between the retriever and the inference model. These issues limit the diversity and quality of the retrieved information. In this paper, we propose a Compressive Memory-based Retrieval (CMR) mechanism for EAE, which addresses the two limitations mentioned above. Our compressive memory, designed as a dynamic matrix that effectively caches retrieved information and supports continuous updates, overcomes the limitations of the input length. Additionally, after pre-loading all candidate demonstrations into the compressive memory, the model further retrieves and filters relevant information from memory based on the input query, bridging the gap between the retriever and the inference model. Extensive experiments show that our method achieves new state-of-the-art performance on three public datasets (RAMS, WikiEvents, ACE05), significantly outperforming existing retrieval-based EAE methods. © 2025 Association for Computational Linguistics.

关键词： Computational linguistics

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Hybrid Scalable Video Coding with Neural Compression and Enhancement for Streaming Media 31st

Hybrid Scalable Video Coding with Neural Compression and E...

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31st International conference on Multimedia Modeling, MMM 2025

作者： Ye, Yuyao Yang, Jiayu Zhao, Yang Gao, Mengping Cao, Hongbin Wang, Ronggang Guangdong Provincial Key Laboratory of Ultra High Definition Immersive Media Technology School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Shenzhen China School of Computer and Information Hefei University of Technology Hefei China Bytedance Inc. Shenzhen China

ISBN: (纸本)9789819620609

Streaming media is important in modern information consumption industry. However the limited and varied computing resources and bandwidth of client devices pose challenges for video coding. To make a balance between speed and coding efficiency and provide scalability for different devices, we propose a hybrid scalable coding framework (HSVC) which maintains a layered structure including a low resolution basement layer encoded by traditional coding methods and an optional enhancement layer encoded by neural coding methods. The enhancement layer coding is designed with a neural contextual compression module and a neural motion vector-guided enhancement module, which make full use of inter-layer information to boost the performance of enhancement layer and produce better visual quality. Experiments demonstrate that the proposed method outperforms existing scalable coding methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Scalable video coding

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Characterizing the Influence of Topology on Graph Learning Tasks 29th

Characterizing the Influence of Topology on Graph Learning T...

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29th International conference on Database Systems for Advanced Applications (DASFAA)

作者： Wu, Kailong Xie, Yule Ding, Jiaxin Ren, Yuxiang Fu, Luoyi Wang, Xinbing Zhou, Chenghu Shanghai Jiao Tong Univ Shenzhen Shenzhen Guangdong Peoples R China Huawei Technol Shenzhen 2012 Labs Shenzhen Guangdong Peoples R China

ISBN: (纸本)9789819757787;9789819757794

Graph neural networks (GNN) have achieved remarkable success in a wide range of tasks by encoding features combined with topology to create effective representations. However, the fundamental problem of understanding and analyzing how graph topology influences the performance of learning models on downstream tasks has not yet been well understood. In this paper, we propose a metric, TopoInf, which characterizes the influence of graph topology by measuring the level of compatibility between the topological information of graph data and downstream task objectives. We provide analysis based on the decoupled GNNs on the contextual stochastic block model to demonstrate the effectiveness of the metric. Through extensive experiments, we demonstrate that TopoInf is an effective metric for measuring topological influence on corresponding tasks and can be further leveraged to enhance graph learning.

关键词： GNNs graph topology graph rewiring

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Sequential Indifferentiability of 7-Round Misty Structures

Sequential Indifferentiability of 7-Round Misty Structures

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Cryptographers’ Track at the RSA conference, CT-RSA 2025

作者： Ai, Jiayi Guo, Chun School of Cyber Science and Technology Shandong University Qingdao China The State Key Laboratory of Blockchain and Data Security Zhejiang University Hangzhou China Key Laboratory of Cryptologic Technology and Information Security of Ministry of Education Shandong University Shandong Qingdao266237 China Shandong Research Institute of Industrial Technology Shandong Jinan250102 China

ISBN: (纸本)9783031886607

We investigate the Misty structure with respect to the security notion of sequential indifferentiability of Mandal et al. (TCC 2012). As our main result, we prove sequential indifferentiability for 7-round Misty structures using seven independent random permutations in the rounds. We also prove insecurity for 5 rounds by exhibiting an attack. Our main result implies known-key security of 7 rounds in the sense of correlation intractability, providing the first known-key security results on Misty structures to our knowledge. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

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Remote State Estimation and Blum–Shub–Smale Machines—A Computability Analysis With Applications to Virtual Twinning

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IEEE Transactions on Automatic Control 2025年第5期70卷 3165-3180页

作者： Boche, Holger Bock, Yannik Deppe, Christian Fitzek, Frank H. P. Technical University of Munich Chair of Theoretical Information Technology MunichD-80290 Germany BMBF Research Hub 6G-Life D-80333 Munich Germany MunichD-80799 Germany MunichD-80807 Germany Technische Universität Braunschweig Institute for Communications Technology BraunschweigD-38106 Germany 5G Lab Germany DresdenD-01062 Germany

This article analyzes aspects of the problem of remote state estimation (RSE) via noisy communication channels for their Blum–Shub–Smale (BSS) computability, motivated by an exemplary application to a formal model of virtual twinning subject to stringent integrity requirements. Computability theory provides a unique framework for the formal and mathematically rigorous analysis of algorithms and computing machines. Therefore, computability theory is essential in the domain of safety- and life-critical technology, where the formal verification of automated systems is necessary. Based on the RSE problem, we establish a simple mathematical model of virtual-twin systems that entails a formal notion of integrity (i.e., a state where the virtual entity accurately mirrors its physical counterpart). The model's notion of integrity is related to the question of whether the system under consideration is capable of computing the communication channel's zero-error capacity and corresponding zero-error codes. While this task is known to exceed the theoretical capabilities of Turing computers, we prove its formal feasibility within the model BSS machines. As different authors have proposed BSS machines as potential model of some forms of analog computing, this article serves as a proof-of-concept for a theoretical analog supremacy of unconventional information-processing hardware. Considering recent advances in the development of such hardware, forms of analog supremacy will likely become relevant in the future of cyber-physical systems and information technology. © 1963-2012 IEEE.

关键词： Computability and decidability

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Insights into the High-Quality Development of Agriculture under the Wave of Digital Economy 20th

Insights into the High-Quality Development of Agriculture un...

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20th International conference on Metaverse, METAVERSE 2024, Held as Part of the Services conference Federation, SCF 2024

作者： ChaoYu, Liang XiangQiong, Wu Hui, Ou Shengping, Liang College of Information Engineering Capital Normal University Beijing100048 China College of Mathematics and Statistics Hunan Normal University Changsha410081 China China Forestry Group Corporation Beijing100026 China

ISBN: (纸本)9783031769764

Based on panel data from 30 provinces, autonomous regions, and municipalities in China from 2012 to 2021, this study conducted a quantitative analysis of the high-quality development of agriculture amidst the wave of the digital economy. The research revealed that the digital economy plays a significant role in promoting the high-quality development of agriculture. It not only directly enhances the high-quality development of agriculture in various provinces, autonomous regions, and municipalities but also indirectly provides a material foundation for such development by elevating the level of agricultural talent cultivation. However, the impact of the digital economy on the high-quality development of agriculture exhibits regional heterogeneity, with notable effects in the northern region and less significant impacts in the southern region. Consequently, this study’s analysis points out that strengthening strategies to empower agriculture with the digital economy, optimizing talent attraction and cultivation mechanisms, and enhancing differentiated policy support are crucial strategies for promoting the high-quality development of agriculture. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Agricultural economics

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TBA-GNN: A Traffic Behavior Analysis Model with Graph Neural Networks for Malicious Traffic Detection 18th

TBA-GNN: A Traffic Behavior Analysis Model with Graph Neura...

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18th International conference on Wireless Artificial Intelligent Computing Systems and Applications, WASA 2024

作者： Han, Xinbo Zhang, Meng Yang, Zheng Institute of Information Engineering Chinese Academy of Sciences Beijing China School of Cyber Security University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9783031714634

Given the surge in network attack behavior, detecting malicious traffic has become a pivotal cybersecurity task. Many existing methods for malicious traffic detection rely on machine learning and deep learning, but they exhibit certain shortcomings: A considerable number of these methods rely on statistical features, which may lose their relevance as networks evolve and lead to the loss of important information. Additionally, Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN) face limitations in extracting features from network traffic, specifically, their inability to capture traffic interaction behavior information within a network flow. In this paper, we propose a Traffic Behavior Analysis model with Graph Neural Networks (TBA-GNN), which works directly with raw bytes and leverages the hierarchy structure of traffic (byte-packet-flow) to delve into valuable information. Firstly, we devise the PacketCNN to extract packet-level features from raw bytes. Subsequently, we construct a network flow as a Traffic Interaction Graph, containing both the traffic interaction behavior information and packet-level traffic information, and utilize the GNN to extract flow-level features. Finally, we perform a classification task to detect malicious traffic. We conduct extensive experiments on the ISCXIDS2012 and CICIDS2017 datasets, and the experimental results demonstrate that our model effectively identifies malicious traffic, outperforming baselines significantly. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Graph neural networks

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Remote Sensing Based Crop Monitoring Techniques: A Case Study for the Navajo Nation

Remote Sensing Based Crop Monitoring Techniques: A Case Stud...

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2024 Annual conference, ASPRS 2024

作者： Thangavel, Varatharajaperumal Nagarajan, Sudhagar Arockiasamy, Madasamy Khan, Md. Tarique Sklivanitis, George Department of Civil Environmental and Geomatics Engineering Florida Atlantic University FL United States School of Engineering Math & Technology Faculty Navajo Technical University CrownpointNM United States Department of Electrical Engineering and Computer Science Florida Atlantic University FL United States

Agriculture plays a major role in eradicating poverty, promoting prosperity, and nourishing a projected 10 billion people by 2050 globally. In a changing climate, achieving optimal agricultural yields requires a deeper understanding of available natural resources and crops. This is especially important for places like the Navajo Nation, which faces significant challenges in food supply chain management due to various factors such as water demand, water quality, and insufficient information about land fertility and crops timings/seasons. Additionally, it is the largest Native American reservation in the U.S. It covers 27,425 square miles across Arizona, Utah, and New Mexico and has a population of 165,158 people, according to the 2020 census. Agriculture has been a key part of life in the Navajo Nation since the late 19th and early 20th centuries, playing a big role in the region’s development and stability. However, the lack of knowledge about decisions and actions during the crop growing season has resulted in lower crop productivity, as evidenced by the USDA statistical report for the Navajo Nation in 2012 and 2017. To support farmers by providing better decision-making and actionable insights, high-resolution, open-source Sentinel-2 satellite images are being used to develop advanced crop mapping techniques for identifying the spatial extent of various agricultural crops in the Navajo Nation. To address this, a collection of research papers was reviewed, leading to the development of a new methodology for analysing Sentinel-2 data from the 2017 and 2023 growing seasons within the Navajo Nation. The collected data was pre-processed by creating monthly median composites of surface reflectance to remove noise and enhance the results more accurately. After preprocessing, spectral indices were calculated from the spectral bands, including NDVI (Normalized Difference Vegetation Index), EVI (Enhanced Vegetation Index), GCVI (Green Chlorophyll Vegetation Index), and LSWI

关键词： Surface waters

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Predicting Forex Trends: A Comprehensive Analysis of Supervised learning in Exchange Rate Prediction 1st

Predicting Forex Trends: A Comprehensive Analysis of Supervi...

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1st International conference on Machine Learning Algorithms, ICMLA 2024

作者： Nayak, Rudra Kalyan Sodha, Manan Mishra, Nilamadhab Tripathy, Santosh Kumar Tripathy, Ramamani Pradhan, Ashwini Kumar School of Computing Science and Engineering VIT Bhopal University Bhopal-Indore Highway Kothrikalan Madhya Pradesh Sehore466114 India Department of Computer Science and Engineering National Institute of Technology Patna Bihar Patna India Chitkara University School of Engineering & Technology Chitkara University Himachal Pradesh India Department of Computer Science Engineering Galgotias University U.P. Greater Noida India

ISBN: (纸本)9783031758607

This research examines the coherence between regression models and forex trading concentrating on the currency pairs EUR/INR, GBP/INR, and USD/INR. Investigating the ability to dissect and forecast data using machine learning techniques exchange rates on a daily, weekly, and monthly basis using datasets collected over 11 years (January 01, 2012, to January 01, 2023) for the three distinct time frames. The research tested six supervised learning models including regression with a single independent variable (linear regression), regression using multiple independent variables (multiple regression), k-nearest neighbor, regression with decision trees, regression using random forests, and support vector regression. In certain scenarios, models provide significant accuracy for specific currency pairs and time frames. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Multiple linear regression

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