40 Result(s)
within
Ziang **e
Artificial Intelligence
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Article
MODE: a multimodal open-domain dialogue dataset with explanation
The need for high-quality data has been a key issue hindering the research of dialogue tasks. Recent studies try to build datasets through manual, web crawling and so on. However, man-made data is expensive an...
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Article
Construction of key parameter change model of human-computer interaction for intelligent decision-making under the condition of long time voyage
Under the long time voyage of the ship, finding out the task time regularity of human operator in the command and control system can help the intelligent system to carry out the task intelligent assignment and...
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Chapter and Conference Paper
Satellite Swarm Orbital Pursuit-Evasion Game Based on Multi-agent Proximal Policy Optimization Algorithm
This paper studies an orbital pursuit-evasion game involving multiple cooperative pursers and a non-cooperative evader, by applying multi-agent reinforcement learning method. In particular, challenges of compl...
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Chapter and Conference Paper
FedTag: Towards Automated Attack Investigation Using Federated Learning
With the popularity of microservice systems in the industry, the security problems faced by microservice systems have received more and more attention, and the security of their systems is usually reflected in...
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Article
Siamese object tracking for unmanned aerial vehicle: a review and comprehensive analysis
Unmanned aerial vehicle (UAV)-based visual object tracking has enabled a wide range of applications and attracted increasing attention in the field of artificial intelligence (AI) because of its versatility an...
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Article
New Riccati Velocity Controller of the Spherical Robot
For the spherical robot, an efficient and precise velocity controller suitable for different terrains is crucial. In this paper, a new Riccati controller with feedforward compensation based on Kalman observer ...
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Article
Data-driven approaches and model-based methods for detecting and locating leaks in water distribution systems: a literature review
Water distribution systems are made up of interconnected components that should allow water systems to meet demand, but leaks can waste enough water to limit supply. To limit financial losses, water utilities ...
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Chapter and Conference Paper
Detecting Escalation Level from Speech with Transfer Learning and Acoustic-Linguistic Information Fusion
Textual escalation detection has been widely applied to e-commerce companies’ customer service systems to pre-alert and prevent potential conflicts. Similarly, acoustic-based escalation detection systems are a...
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Chapter and Conference Paper
Research Trends and Applications of Human-Machine Interface in Air Traffic Control: A Scientometric Analysis
To systematically understand trends and applications of human-machine interface in air traffic control, this study used data from Web of Science Core Collection as a sample, adopted scientific bibliometric met...
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Chapter and Conference Paper
BertHTLG: Graph-Based Microservice Anomaly Detection Through Sentence-Bert Enhancement
Microservice systems in the industry typically comprise a large-scale distributed architecture with numerous services running on different machines. Anomalies caused by cyber attacks or other factors within su...
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Chapter and Conference Paper
Study on the Influence of Environment on Multimodal Interaction
In order to explore the influence of cabin environment on multimodal interaction, 12 adult males were recruited to carry out interaction ergonomics experiments with multimodal input. The experiment is based on...
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Chapter and Conference Paper
Robot Learning from Human Demonstration for Playing Ocarina
Nowadays the field of combining robots with music has received great attention. However, the current work often focuses on how to control the mechanical performance of music with established rules. We hope tha...
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Chapter and Conference Paper
Research on 5G-Based Zero Trust Network Security Platform
The number and types of network access devices and functions in the cloud computing and big data environments are continuously increasing, so the ability to actively expand network services is needed to ensure...
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Chapter and Conference Paper
Fine-Grained Access Control for Power Mobile Service Based on PA Network Under Zero-Trust Framework
In the power mobile interconnection scenario, the traditional role-based access control (RBAC) is no longer applicable due to the large number of mobile terminals and resource services, complex and diverse acc...
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Chapter and Conference Paper
ETH-TT: A Novel Approach for Detecting Ethereum Malicious Accounts
Ethereum, as the second generation of blockchain technology, it not only brings many advantages, but also spawns various malicious incidents. Ethereum’s anonymity makes it a hotbed of cybercrime, causing huge ...
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Chapter and Conference Paper
PEKIN: Prompt-Based External Knowledge Integration Network for Rumor Detection on Social Media
Pretrained language models(PLMs) and additional features have been used in rumor detection with excellent performance. However, on the one hand, some recent studies find one of its critical challenges is the s...
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Chapter and Conference Paper
Optical Design of Human Blood Fluorescence Scanning System
In the human blood fluorescence scanning system, the optical system design involves a fluorescence and a two-part system. Simple structure of concave and convex lens and objective structure with double cylindr...
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Chapter and Conference Paper
Fast Optimal Transport Artistic Style Transfer
Artistic style transfer plays an important role in the culture and entertainment industry. However, contemporary stylization approaches are suffering from two obstacles: 1) the low temporal efficiency and 2) t...
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Chapter and Conference Paper
AABC:ALBERT-BiLSTM-CRF Combining with Adapters
Pre-training models (PTMs) are language models pre-trained on a large corpus, which can learn general language representations through training tasks within the model. PTMs complete various NLP tasks by connec...
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Chapter and Conference Paper
TS-Bert: Time Series Anomaly Detection via Pre-training Model Bert
Anomaly detection of time series is of great importance in data mining research. Current state of the art suffer from scalability, over reliance on labels and high false positives. To this end, a novel framewo...
