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399 results on '"Cao, Jiawei"'

1. Dynamic Decentralized 3D Urban Coverage and Patrol with UAVs

Author

Leong, Wai Lun, Cao, Jiawei, and Teo, Rodney

Subjects
Computer Science - Robotics
Abstract

In the event of natural or man-made disasters in an urban environment, such as fires, floods, and earthquakes, a swarm of unmanned aerial vehicles (UAVs) can rapidly sweep and provide coverage to monitor the area of interest and locate survivors. We propose a modular framework and patrol strategy that enables a swarm of UAVs to perform cooperative and periodic coverage in such scenarios. Our approach first discretizes the area of interest into viewpoints connected via closed paths. UAVs are assigned to teams via task allocation to cooperatively patrol these closed paths. We propose a minimal, scalable, and robust patrol strategy where UAVs within a team move in a random direction along their assigned closed path and "bounce" off each other when they meet. Our simulation results show that such a minimal strategy can exhibit an emergent behaviour that provides periodic and complete coverage in a 3D urban environment., Comment: Accepted for the 2024 International Conference on Unmanned Aircraft Systems (ICUAS 2024) in Chania, Greece

Published
2024

2. Deep Learning based Performance Testing for Analog Integrated Circuits

Author

Cao, Jiawei, Guo, Chongtao, Li, Hao, Wang, Zhigang, Wang, Houjun, and Li, Geoffrey Ye

Subjects
Electrical Engineering and Systems Science - Systems and Control
Abstract

In this paper, we propose a deep learning based performance testing framework to minimize the number of required test modules while guaranteeing the accuracy requirement, where a test module corresponds to a combination of one circuit and one stimulus. First, we apply a deep neural network (DNN) to establish the mapping from the response of the circuit under test (CUT) in each module to all specifications to be tested. Then, the required test modules are selected by solving a 0-1 integer programming problem. Finally, the predictions from the selected test modules are combined by a DNN to form the specification estimations. The simulation results validate the proposed approach in terms of testing accuracy and cost.

Published
2024

3. Don't Ignore Dual Logic Ability of LLMs while Privatizing: A Data-Intensive Analysis in Medical Domain

Author

Du, Yanrui, Zhao, Sendong, Cai, Muzhen, Ma, Ming, Zhao, Danyang, Cao, Jiawei, and Qin, Bing

Subjects
Computer Science - Computation and Language
Abstract

Extensive studies have been devoted to privatizing general-domain Large Language Models (LLMs) as Domain-Specific LLMs via feeding specific-domain data. However, these privatization efforts often ignored a critical aspect: Dual Logic Ability, which is a core reasoning ability for LLMs. The dual logic ability of LLMs ensures that they can maintain a consistent stance when confronted with both positive and negative statements about the same fact. Our study focuses on how the dual logic ability of LLMs is affected during the privatization process in the medical domain. We conduct several experiments to analyze the dual logic ability of LLMs by examining the consistency of the stance in responses to paired questions about the same fact. In our experiments, interestingly, we observed a significant decrease in the dual logic ability of existing LLMs after privatization. Besides, our results indicate that incorporating general domain dual logic data into LLMs not only enhances LLMs' dual logic ability but also further improves their accuracy. These findings underscore the importance of prioritizing LLMs' dual logic ability during the privatization process. Our study establishes a benchmark for future research aimed at exploring LLMs' dual logic ability during the privatization process and offers valuable guidance for privatization efforts in real-world applications.

Published
2023

17. A Fast Stain Normalization Network for Cervical Papanicolaou Images

Author

Cao, Jiawei, Lu, Changsheng, Wu, Kaijie, Gu, Chaochen, Filipe, Joaquim, Editorial Board Member, Ghosh, Ashish, Editorial Board Member, Prates, Raquel Oliveira, Editorial Board Member, Zhou, Lizhu, Editorial Board Member, Tanveer, Mohammad, editor, Agarwal, Sonali, editor, Ozawa, Seiichi, editor, Ekbal, Asif, editor, and Jatowt, Adam, editor

Published
2023
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49. Free‐energy lattice Boltzmann simulations of slicing of rising droplets.

Author

Cao, Jiawei, Liu, Fengjiao, Wang, Shipeng, Li, Xiang, Zhang, Lijuan, Lu, Jie, and Derksen, Jos J.

Subjects
LATTICE Boltzmann methods, SPATIAL resolution, CONTACT angle
Abstract

We performed two‐dimensional simulations of the slicing of a rising droplet by a vertical knife and by two knives. We used a free‐energy lattice Boltzmann method. Most simulations are for an Eötvös number of 3.96 and a Morton number of 1.24 × 10−4. We carefully probed effects of the spatial resolution on the rising speed and slicing process. The effect of wettability of the knife(s) was studied by varying the equilibrium contact angle of the drop on the knife in the range of 45° to 135°. Slicing time as well as fine droplet fragments staying behind on the knife depend on the knife's wettability. [ABSTRACT FROM AUTHOR]

Published
2024
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