Tsinghua Science and Technology最新文献_第3页

EFSP-TE: End-to-End Frame-Semantic Parsing with Table Encoder 端到端帧语义解析与表编码器

IF 6.6 1区计算机科学

Tsinghua Science and Technology Pub Date : 2025-03-03 DOI: 10.26599/TST.2024.9010036

Xuefeng Su;Ru Li;Xiaoli Li;Zhichao Yan

{"title":"EFSP-TE: End-to-End Frame-Semantic Parsing with Table Encoder","authors":"Xuefeng Su;Ru Li;Xiaoli Li;Zhichao Yan","doi":"10.26599/TST.2024.9010036","DOIUrl":"https://doi.org/10.26599/TST.2024.9010036","url":null,"abstract":"Frame-Semantic Parsing (FSP) aims to extract frame-semantic structures from text. The task usually involves three subtasks sequentially: Target Identification (TI), Frame Identification (Fl), and Frame Semantic Role Labeling (FSRL). The three subtasks are closely related while most previous studies model them individually, encountering error propagation and running efficiency problems. Recently, an end-to-end graph-based model is proposed to jointly process three subtasks in one model. However, it still encounters three problems: insufficient semantic modeling between targets and arguments, span missing, and lacking knowledge incorporation of FrameNet. To address the mentioned problems, this paper presents an End-to-end FSP model with Table Encoder (EFSP-TE), which models FSP as two semantically dependent region classification problems and extracts frame-semantic structures from sentences in a one-step manner. Specifically, EFSP-TE incorporates lexical unit knowledge into context encoder via saliency embedding, and develops an effective table representation learning method based on Biaffine network and multi-layer ResNet-style-CNNs (Convolutional Neural Networks), which can fully exploit word-to-word interactions and capture the information of various levels of semantic relations between targets and arguments. In addition, it adopts two separate region-based modules to obtain potential targets and arguments, followed by two interactive classification modules to predict the frames and roles for the potential targets and arguments. Experiments on two public benchmarks show that the proposed approach achieves state-of-the-art performance in end-to-end setting.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 4","pages":"1474-1495"},"PeriodicalIF":6.6,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10908675","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553337","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Role Identification Based Method for Cyberbullying Analysis in Social Edge Computing 基于角色识别的社会边缘计算网络欺凌分析方法

IF 6.6 1区计算机科学

Tsinghua Science and Technology Pub Date : 2025-03-03 DOI: 10.26599/TST.2024.9010066

Runyu Wang;Tun Lu;Peng Zhang;Ning Gu

{"title":"Role Identification Based Method for Cyberbullying Analysis in Social Edge Computing","authors":"Runyu Wang;Tun Lu;Peng Zhang;Ning Gu","doi":"10.26599/TST.2024.9010066","DOIUrl":"https://doi.org/10.26599/TST.2024.9010066","url":null,"abstract":"Over the past few years, many efforts have been dedicated to studying cyberbullying in social edge computing devices, and most of them focus on three roles: victims, perpetrators, and bystanders. If we want to obtain a deep insight into the formation, evolution, and intervention of cyberbullying in devices at the edge of the Internet, it is necessary to explore more fine-grained roles. This paper presents a multi-level method for role feature modeling and proposes a differential evolution-assisted K-means (DEK) method to identify diverse roles. Our work aims to provide a role identification scheme for cyberbullying scenarios for social edge computing environments to alleviate the general safety issues that cyberbullying brings. The experiments on ten real-world datasets obtained from Weibo and five public datasets show that the proposed DEK outperforms the existing approaches on the method level. After clustering, we obtain nine roles and analyze the characteristics of each role and their evolution trends under different cyberbullying scenarios. Our work in this paper can be placed in devices at the edge of the Internet, leading to better real-time identification performance and adapting to the broad geographic location and high mobility of mobile devices.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 4","pages":"1659-1684"},"PeriodicalIF":6.6,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10908657","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Resource Management and Trajectory Optimization for UAV-IRS Assisted Maritime Edge Computing Networks 无人机- irs辅助海上边缘计算网络的资源管理和轨迹优化

IF 6.6 1区计算机科学

Tsinghua Science and Technology Pub Date : 2025-03-03 DOI: 10.26599/TST.2024.9010074

Chaoyue Zhang;Bin Lin;Xu Hu;Shuang Qi;Liping Qian;Yuan Wu

{"title":"Resource Management and Trajectory Optimization for UAV-IRS Assisted Maritime Edge Computing Networks","authors":"Chaoyue Zhang;Bin Lin;Xu Hu;Shuang Qi;Liping Qian;Yuan Wu","doi":"10.26599/TST.2024.9010074","DOIUrl":"https://doi.org/10.26599/TST.2024.9010074","url":null,"abstract":"With the exponential growth of maritime wireless devices and the rapid development of maritime applications, traditional maritime communication networks encounter communication and computation limitations in supporting computation-intensive and latency-critical tasks. Edge computing and Intelligent Reflecting Surface (IRS) have emerged as promising techniques to improve communication and computation services for maritime devices with limited computation capabilities and battery capacity. This paper studies an IRS Mounted on Unmanned Aerial Vehicle (UIRS) assisted maritime edge computing network, in which the UIRS is deployed to assist the transmission from Unmanned Surface Vehicles (USVs) to the edge server via Non-Orthogonal Multiple Access (NOMA) protocol. We propose a resource management and trajectory optimization scheme by jointly optimizing subslot duration, offloading ratios, transmit power, edge computation capability allocation, UIRS phase shifts and UIRS trajectory, aiming at minimizing the overall energy consumption. Since the non-convex nature of the optimization problem, we propose a two-layered method by decomposing the original problem into two subproblems. The top-layered subproblem is solved by the Semi-Definite Relaxation (SDR) method and the underlying-layered subproblem is solved by the Deep Deterministic Policy Gradient (DDPG) algorithm. Numerical results demonstrate that our proposed scheme can effectively and efficiently reduce overall energy consumption.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 4","pages":"1600-1616"},"PeriodicalIF":6.6,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10908662","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Hyperbolic Graph Wavelet Neural Network 双曲图小波神经网络

IF 6.6 1区计算机科学

Tsinghua Science and Technology Pub Date : 2025-03-03 DOI: 10.26599/TST.2024.9010032

Wenjie Zheng;Guofeng Zhang;Xiaoran Zhao;Zhikang Feng;Lekang Song;Huaizhen Kou

{"title":"Hyperbolic Graph Wavelet Neural Network","authors":"Wenjie Zheng;Guofeng Zhang;Xiaoran Zhao;Zhikang Feng;Lekang Song;Huaizhen Kou","doi":"10.26599/TST.2024.9010032","DOIUrl":"https://doi.org/10.26599/TST.2024.9010032","url":null,"abstract":"Graph neural networks (GNNs), grounded in spatial or spectral domains, have achieved remarkable success in learning graph representations in Euclidean space. Recent advances in spatial GNNs reveal that embedding graph nodes with hierarchical structures into hyperbolic space is more effective, reducing distortion compared to Euclidean embeddings. However, extending spectral GNNs to hyperbolic space remains several challenges, particularly in defining spectral graph convolution and enabling message passing within the hyperbolic geometry. To address these challenges, we propose the hyperbolic graph wavelet neural network (HGWNN), a novel approach for modeling spectral GNNs in hyperbolic space. Specifically, we first define feature transformation and spectral graph wavelet convolution on the hyperboloid manifold using exponential and logarithmic mappings, without increasing model parameter complexity. Moreover, we enable non-linear activation on the Poincaré manifold and efficient message passing via diffeomorphic transformations between the hyperboloid and Poincaré models. Experiments on four benchmark datasets demonstrate the effectiveness of our proposed HGWNN over baseline systems.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 4","pages":"1511-1525"},"PeriodicalIF":6.6,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10908594","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An Efficient Algorithm for Approximate Polyline-Sourced Offset Computation on Triangulated Surfaces 三角曲面上多线源偏移量近似计算的一种高效算法

IF 6.6 1区计算机科学

Tsinghua Science and Technology Pub Date : 2025-03-03 DOI: 10.26599/TST.2024.9010239

Wenlong Meng;Hang Yu;Yixuan Geng;Pengbo Bo

{"title":"An Efficient Algorithm for Approximate Polyline-Sourced Offset Computation on Triangulated Surfaces","authors":"Wenlong Meng;Hang Yu;Yixuan Geng;Pengbo Bo","doi":"10.26599/TST.2024.9010239","DOIUrl":"https://doi.org/10.26599/TST.2024.9010239","url":null,"abstract":"The computation of polyline-sourced geodesic offset holds significant importance in a variety of applications, including but not limited to solid modeling, tool path generation for computer numerical control (CNC) machining, and parametrization. The traditional approaches for geodesic offsets have typically relied on the availability of an exact geodesic metric. Nevertheless, the computation of exact geodesics is characterized by its time-consuming nature and substantial memory usage. To tackle the limitation, our study puts forward a novel approach that seeks to circumvent the reliance on exact geodesic metrics. The proposed method entails a reformulated graph method that incorporates Steiner point insertion, serving as an effective solution for obtaining geodesic distances. By leveraging the aforementioned strategies, we present an efficient and robust algorithm designed for the computation of polyline-sourced geodesic offsets. The experimental evaluation, conducted on a diverse set of three-dimensional models, demonstrates significant improvements in computational speed and memory requirements compared to established state-of-the-art methods.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 4","pages":"1744-1761"},"PeriodicalIF":6.6,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10908677","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143553428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Study on Analyzing the Security and Privacy Implications of Existing and Emerging Sensors in Autonomous Electric Vehicles 自动驾驶电动汽车中现有和新兴传感器的安全和隐私影响分析研究

IF 6.6 1区计算机科学

Tsinghua Science and Technology Pub Date : 2025-03-03 DOI: 10.26599/TST.2023.9010132

Achyut Shankar;Carsten Maple;Gregory Epiphaniou

引用次数: 0

Joint Resource Optimization for Secure Cooperative Perception in Vehicular Networks 面向车辆网络安全协同感知的联合资源优化

IF 6.6 1区计算机科学

Tsinghua Science and Technology Pub Date : 2024-12-30 DOI: 10.26599/TST.2024.9010068

Ya Kang;Qingyang Song;Jing Song;Lei Guo;Abbas Jamalipour

{"title":"Joint Resource Optimization for Secure Cooperative Perception in Vehicular Networks","authors":"Ya Kang;Qingyang Song;Jing Song;Lei Guo;Abbas Jamalipour","doi":"10.26599/TST.2024.9010068","DOIUrl":"https://doi.org/10.26599/TST.2024.9010068","url":null,"abstract":"In the realm of autonomous driving, cooperative perception serves as a crucial technology for mitigating the inherent constraints of individual vehicle's perception. To enable cooperative perception, vehicle-to-vehicle (V2V) communication plays an indispensable role. Unfortunately, owing to weak virus protection in V2V networks, the emergence and widespread adoption of V2V communications have also created fertile soil for the breeding and rapid spreading of worms. To stimulate vehicles to participate in cooperative perception while blocking the spreading of worms through V2V communications, we design an incentive mechanism, in which the utility of each sensory data requester and that of each sensory data provider are defined, respectively, to maximize the total utility of all the vehicles. To deal with the highly non-convex problem, we propose a pairing and resource allocation (PRA) scheme based on the Stackelberg game theory. Specifically, we decompose the problem into two subproblems. The subproblem of maximizing the utility of the requester is solved via a two-stage iterative algorithm, while the subproblem of maximizing the utility of the provider is addressed using the linear search method. The results demonstrate that our proposed PRA approach addresses the challenges of cooperative perception and worm spreading while efficiently converging to the Stackelberg equilibrium point, jointly maximizing the utilities for both the requester and the provider.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 3","pages":"1044-1059"},"PeriodicalIF":6.6,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817771","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905925","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

High-Precision UAV Positioning Method Based on MLP Integrating UWB and IMU 基于集成超宽带和IMU的MLP高精度无人机定位方法

IF 6.6 1区计算机科学

Tsinghua Science and Technology Pub Date : 2024-12-30 DOI: 10.26599/TST.2024.9010106

Binbin Bao;Chuanwen Luo;Yi Hong;Zhibo Chen;Xin Fan

{"title":"High-Precision UAV Positioning Method Based on MLP Integrating UWB and IMU","authors":"Binbin Bao;Chuanwen Luo;Yi Hong;Zhibo Chen;Xin Fan","doi":"10.26599/TST.2024.9010106","DOIUrl":"https://doi.org/10.26599/TST.2024.9010106","url":null,"abstract":"Unmanned Aerial Vehicles (UAVs) are promising for their agile flight capabilities, allowing them to carry out tasks in various complex scenarios. The efficiency and accuracy of UAV operations significantly depend on high-precision positioning technology. However, the existing positioning techniques often struggle to achieve accurate position estimates in conditions of Non-line-Of-Sight (NLOS). To address this challenge, we propose a novel high-precision UAV positioning method based on Multilayer Perceptron (MLP) integrating Ultra-WideBand (UWB) and Inertial Measurement Unit (IMU) technologies, which can acquire centimeter-level high-precision location estimation. In the method, we simultaneously extract key features from channel impulse responses and state space of UAV for training an MLP model, which can not only reduce error of UWB signals from dynamically flying UAV to anchor in NLOS environments, but also adapt to the diverse environment settings. Specifically, we respectively apply the anchor node assisted position calibration method and cooperative positioning techniques to the dynamic flying UAVs for solving the issues of UWB signal being blocked and lost. We conduct extensive real-world experiments to demonstrate the effectiveness of our approach. The results show that the median positioning errors of UAV in hovering and flight are 6.3 cm and within 20 cm, respectively.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 3","pages":"1315-1328"},"PeriodicalIF":6.6,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817766","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Digital Twin and Consensus Empowered Cooperative Control Framework for Platoon-Based Autonomous Driving 基于队列自动驾驶的数字孪生和共识授权协同控制框架

IF 6.6 1区计算机科学

Tsinghua Science and Technology Pub Date : 2024-12-30 DOI: 10.26599/TST.2024.9010076

Jiayu Cao;Supeng Leng;Kai Xiong;Xiaosha Chen

{"title":"A Digital Twin and Consensus Empowered Cooperative Control Framework for Platoon-Based Autonomous Driving","authors":"Jiayu Cao;Supeng Leng;Kai Xiong;Xiaosha Chen","doi":"10.26599/TST.2024.9010076","DOIUrl":"https://doi.org/10.26599/TST.2024.9010076","url":null,"abstract":"Platoon-based autonomous driving is indispensable for traffic automation, but it confronts substantial constraints in rugged terrains with unreliable links and scarce communication resources. This paper proposes a novel hierarchical Digital Twin (DT) and consensus empowered cooperative control framework for safe driving in harsh areas. Specifically, leveraging intra-platoon information exchange, one platoon-level DT is constructed on the leader and multiple vehicle-level DTs are distributed among platoon members. The leader first makes critical platoon-driving decisions based on the platoon-level DT. Then, considering the impact of unreliable links on the platoon-level DT accuracy and the consequent risk of unsafe decision-making, a distributed consensus scheme is proposed to negotiate critical decisions efficiently. Upon successful negotiation, vehicles proceed to execute critical decisions, relying on their vehicle-level DTs. Otherwise, a Space-Air-Ground-Integrated-Network (SAGIN) enabled information exchange is utilized to update the platoon-level DT for subsequent safe decision-making in scenarios with unreliable links, no roadside units, and obstructed platoons. Furthermore, based on this framework, an adaptive platooning scheme is designed to minimize total delay and ensure driving safety. Simulation results indicate that our proposed scheme improves driving safety by 21.1% and reduces total delay by 24.2% in harsh areas compared with existing approaches.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 3","pages":"1096-1111"},"PeriodicalIF":6.6,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817716","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905730","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Context-Aware Edge-Cloud Collaboration Framework for QoS Prediction 面向QoS预测的上下文感知边缘云协作框架

IF 6.6 1区计算机科学

Tsinghua Science and Technology Pub Date : 2024-12-30 DOI: 10.26599/TST.2024.9010027

Yong Cheng;Weihao Cao;Hao Fang;Shaobo Zang

{"title":"A Context-Aware Edge-Cloud Collaboration Framework for QoS Prediction","authors":"Yong Cheng;Weihao Cao;Hao Fang;Shaobo Zang","doi":"10.26599/TST.2024.9010027","DOIUrl":"https://doi.org/10.26599/TST.2024.9010027","url":null,"abstract":"The rapid growth of online services has led to the emergence of many with similar functionalities, making it necessary to predict their non-functional attributes, namely quality of service (QoS). Traditional QoS prediction approaches require users to upload their QoS data to the cloud for centralized training, leading to high user data upload latency. With the help of edge computing, users can upload data to edge servers (ESs) adjacent to them for training, reducing the upload latency. However, shallow models like matrix factorization (MF) are still used, which cannot sufficiently extract context features, resulting in low prediction accuracy. In this paper, we propose a context-aware edge-cloud collaboration framework for QoS prediction, named CQEC. Specially, to reduce the users upload latency, a distributed model training algorithm is designed with the collaboration of ESs and cloud. Furthermore, a context-aware prediction model based on convolutional neural network (CNN) and integrating attention mechanism is proposed to improve the performance. Experiments based on real-world dataset demonstrate that COEC outperforms the baselines.","PeriodicalId":48690,"journal":{"name":"Tsinghua Science and Technology","volume":"30 3","pages":"1201-1214"},"PeriodicalIF":6.6,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10817722","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142905811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0