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Tsinghua Science and Technology
Scopus
ISSN 1007-0214 · Tsinghua University Press · 1.318 artikel di indeks
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Artikel Jurnal
DualPathTST: A Dual-Pathway PatchTST Utilizing Cross-Variable Dependency and De-Stationary for Time Series Forecasting
In recent years, Transformer-like models have increasingly underscored their importance in Time Series Forecasting (TSF), playing a pivotal role across various fields. However, their attention mechanisms never consider the dependencies across variables, which can diminish the predictive…
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Predicting Production Capacity in Multiplex Networked Industrial Chains Based on Multi-Scale Dynamic Aggregation Network
With the high degree of integration of production capacity in the industrial field, the original form of single, linear, and vertical cooperation between different industrial chains has been broken, and a multiplex networked industrial chain has been formed. Traditional time series forecasting…
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LTKT: Knowledge Tracing Based on Positive and Negative Learning Transfers
As an essential part of educational psychology, the propagated influence among pedagogical concepts (i.e., learning transfer) is important for optimizing Knowledge Tracing (KT) tasks. However, existing KT methods only consider the positive learning transfer and disregard the negative learning…
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Dynamic Constraint Control for Rehabilitation Robot with Event-Triggered Parameters and Actuation Adjustments
In rehabilitation robot systems, communication and computational resources are often limited. Therefore, conserving either of these resources can significantly contribute to cost reduction, longer service life, and improved system reliability. Meanwhile, time-varying asymmetric constraints on the…
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Efficient Log Parsing Method Based on Log Locality Features
Log parsing is indispensable for system maintenance, converting unstructured log data into structured formats (log templates) for further log compression and anomaly detection. The effectiveness of log parsing relies on the efficiency of two key processes: template extraction and log matching…
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Artikel Jurnal
Multi-Affection Prompt Learning for Sentiment, Emotion, and Sarcasm Joint Detection in Conversations
As a new trend in Natural Language Processing (NLP), prompt tuning has been explored to provide a reliable answer without requiring massive labeled samples and training learning in sentiment and emotion detection tasks. However, how to effectively encode the commonness and uniquesness across…
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Uniform Exploration of Dynamic Attributed Graph via Embedded Community Comparison
Though dynamic graph exploration is common in visualization research, few works explore Dynamic Attributed Graphs (DAG). The main reason is that introducing node attributes leads to diverse exploration tasks and rich graph patterns, making it challenging to propose an approach that supports them…
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A Multi-View Hierarchical Intrusion Detection Model with Integrating Spatiotemporal Feature for Industrial Control System
Current intrusion detection in industrial control system (ICS) typically relies on network flows or traffic packets, often neglecting differences in payloads of functional fields and their heterogeneous responses under attacks. Moreover, most methods depend on manually crafted features, limiting…
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Artikel Jurnal
Edge-Cloud Collaborative Video Analytics System for Crowd Gathering Detection in Metro Stations
The safe operation of metro systems, particularly in densely populated cities, relies on the effective management of crowd gatherings within stations. Existing research primarily focuses on camera-based crowd counting but fails to consider crowd movement across multiple interconnected spaces…
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Privacy-Preserving Unobtrusive Fall Detection for Older Adults: A Highly Generalized Deep Anomaly Detection Model
Detecting and treating older adults who fall in an environment without others is essential. Millimeter-wave radar sensors do not have the disadvantage of invading user privacy like cameras, nor do they require users to wear them in real-time like wearable devices. Actual samples of older adults…
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Improving Sequential Service Recommendation via a Novel Neighborhood-Augmented Graph Collaborative Attention Network
As an effective tool to alleviate information overload on the service platform, sequential recommender systems aim to predict the service in which users are interested by analyzing their historical behaviors. To leverage transition patterns among services, some solutions apply the graph attention…
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Artikel Jurnal
3GPP-Like GBSM THz Channel Characterization, Modeling, and Simulation Based on Experimental Observations
To evaluate the performance of terahertz (THz) communication for the sixth-generation (6G) communication system, it is essential to propose THz channel models within the common framework of the geometry-based stochastic model (GBSM) in the 3rd generation partnership project (3GPP). This paper…
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A Blockchain-Enabled Lightweight Boolean Multi-Keyword Search Scheme for Encrypted EHRs in Medical Cloud Environments
To tackle the growing need for efficient and fine-grained ciphertext access control and search capabilities in managing large-scale electronic health records (EHRs) within medical cloud environments, we propose a novel blockchain-enabled lightweight boolean multi-keyword search scheme. This…
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Realistic Corner Case Generation for Autonomous Vehicles with Multimodal Large Language Model
To guarantee the safety and reliability of Autonomous Vehicle (AV) systems, corner cases play a crucial role in exploring the system’s behavior under rare and challenging conditions within simulation environments. However, current approaches often fall short in meeting diverse testing needs and…
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PSTGCN: A Taxi Flow Prediction Model Period-Based Spatial-Temporal Graph Convolution Network
Efficient urban traffic management and intelligent urban planning are pivotal drivers for the development of modern cities. Among them, accurate prediction of taxi flow, as a core component of the urban transportation system, has significant implications for traffic management, resource allocation…
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Artikel Jurnal
Algorithmic Perspectives on Active Object Recognition Systems: A Survey
With the continuous advancement of artificial intelligence technology, traditional passive sensing methods have encountered certain limitations. Some downstream tasks require sensors to acquire information actively. Against this backdrop, active perception technology has made significant progress…
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Artikel Jurnal
Intelligent Decision-Making for Field Crop Production
To address the dynamic and uncertain challenges posed by climate variability, soil heterogeneity, water distribution, and other key factors in crop field production, intelligent decision support systems (IDSS) that integrate domain knowledge and multi-source data for irrigation, fertilization, pest…
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Artikel Jurnal
Efficient Privacy-Preserving Streaming Histogram Publication via Sampling-Based Shuffled Method
The rapid growth of web technologies and the industrial Internet has resulted in massive data streams that are essential for real time decision-making applications. A critical challenge lies in dynamically publishing histograms for the most recent w elements within sliding windows while ensuring…
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Artikel Jurnal
Regularized Semi-Supervised Subspace Clustering with Local-Structure-Preservation-Based Soft-MFA
Semi-supervised subspace clustering (SSC) algorithms utilize partially labeled data to improve clustering performance. However, existing SSC methods often focus on the global similarity structure of data and neglect the local structure to some extent. To address this limitation, we propose a soft…
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Artikel Jurnal
Fast Shortest Distance Estimation via Lighthouse-Based Label on Graph
Shortest distances estimation plays a crucial role in fields such as social network analysis, bioinformatics, and navigation systems. While the traditional breadth first search (BFS) algorithm is effective, it often incurs high computational costs when handling large datasets. Therefore, researches…
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