A5090038362- Rough Sets and Fuzzy Logic
- Privacy-Preserving Technologies in Data
- Seismic Imaging and Inversion Techniques
- Extenics and Innovation Methods
- Simulation and Modeling Applications
- Advanced Vision and Imaging
- 3D Surveying and Cultural Heritage
- Aerospace and Aviation Technology
- Multi-Criteria Decision Making
- Artificial Intelligence in Healthcare and Education
- Advanced Decision-Making Techniques
- Elevator Systems and Control
- Transportation and Mobility Innovations
- Slime Mold and Myxomycetes Research
- Multi-Agent Systems and Negotiation
- Vibration Control and Rheological Fluids
- Remote Sensing and LiDAR Applications
- Explainable Artificial Intelligence (XAI)
- Adversarial Robustness in Machine Learning
- Face and Expression Recognition
- Machine Learning and Data Classification
- Geophysics and Gravity Measurements
- Vibration and Dynamic Analysis
- 3D Shape Modeling and Analysis
- Network Security and Intrusion Detection
Xiamen University
2005-2025
Delft University of Technology
2024
Pomfret School
2024
China Construction Eighth Engineering Division (China)
2024
Nanjing University
2023
Nanjing University of Aeronautics and Astronautics
2006
National University of Singapore
2006
Large language models (LLMs), exemplified by ChatGPT, have gained considerable attention for their excellent natural processing capabilities. Nonetheless, these LLMs present many challenges, particularly in the realm of trustworthiness. Therefore, ensuring trustworthiness emerges as an important topic. This paper introduces TrustLLM, a comprehensive study LLMs, including principles different dimensions trustworthiness, established benchmark, evaluation, and analysis mainstream discussion...
Generative Foundation Models (GenFMs) have emerged as transformative tools. However, their widespread adoption raises critical concerns regarding trustworthiness across dimensions. This paper presents a comprehensive framework to address these challenges through three key contributions. First, we systematically review global AI governance laws and policies from governments regulatory bodies, well industry practices standards. Based on this analysis, propose set of guiding principles for...
To mitigate the metro-induced vertical vibration of indoor substation structure, this study proposes a gas-spring quasi-zero stiffness air damping isolator (AD-QZSI) with excellent low dynamic and high-static characteristics. The working principle mechanical properties AD-QZSI are introduced studied through theoretical numerical methods. A model for considering soil–structure–equipment interaction is established using software ABAQUS, its accuracy validated based on series measured data from...
Microarray technology is a powerful tool for human genetic research and other biomedical applications.Numerous improvements to the standard K-means algorithm have been carried out complete image segmentation step.However, most of previous studies classify into two clusters.In this paper, we propose novel algorithm, which first classifies three clusters, then one clusters divided as background region foreground region.The proposed method was evaluated on six different data sets.The analyses...
This paper summarizes the characters of some theories which deal with uncertain information including probability and mathematical statistics, fuzzy mathematics, rough sets, nonclassical logic grey systems, as well compares analyses similarities differences among them. Moreover, in this paper, we discuss feasibility combining respective advantages dealing others' so to process more effectively.
Abstract The advent of federated learning (FL) has presented a viable solution for distributed training in edge environment, while simultaneously ensuring the preservation privacy. In real‐world scenarios, devices may be subject to label noise caused by environmental differences, automated weakly supervised annotation, malicious tampering, or even human error. However, potential noisy samples have not been fully leveraged prior studies on FL aimed at addressing noise. Rather, they primarily...
This paper analyses several extended rough set models in incomplete information systems and proposes a tolerance relation based model of processing grey systems, which is an extension to models. The method the is: firstly partitioning original system by introduced threshold value, then establishing classes through obtaining upper lower approximations these classes. Moreover, whitening numbers on given. shows that accords with practice according examples algorithm also comparatively ideal....
Dynamic obstacle avoidance is a popular research topic for autonomous systems, such as micro aerial vehicles and service robots. Accurately evaluating the performance of dynamic methods necessitates establishment metric to quantify environment's difficulty, crucial aspect that remains unexplored. In this paper, we propose four metrics measure difficulty environments. These aim comprehensively capture influence obstacles' number, size, velocity, other factors on difficulty. We compare...
Due to the exponential growth of cars in urban areas, parking problems have become a significant concern. Addressing this issue requires efficient methods for locating available spaces, enhancing overall experience drivers. This paper introduces lot recommendation model leveraging meta-heuristic algorithms generate list potential locations based on users travel destinations. The primary objectives these include minimizing distance, reducing total fees, and selecting lots with ample spaces....
This technical report outlines our submission system for the CHiME-8 NOTSOFAR-1 Challenge. The primary difficulty of this challenge is dataset recorded across various conference rooms, which captures real-world complexities such as high overlap rates, background noises, a variable number speakers, and natural conversation styles. To address these issues, we optimized in several aspects: For front-end speech signal processing, introduced data-driven joint training method diarization...
Machine learning (ML), driven by prominent paradigms such as centralized and federated learning, has made significant progress in various critical applications ranging from autonomous driving to face recognition. However, its remarkable success been accompanied attacks. Recently, the model hijacking attack shown that ML models can be hijacked execute tasks different their original tasks, which increases both accountability parasitic computational risks. Nevertheless, thus far, this only...
In this paper, a method of data pre-processing in grey information systems was proposed to deal with information. The binning technique introduced smooth noisy used for relative analysis. It constructed the function coefficient each null value and filled up solution function. also can be detect data. This is an application system theory pre-processing. has great significance filling values detecting "poor" database
This paper introduces the background of rough set theory, and then brought forward a new algorithm for finding optimal reduct make comparison between original improved one via experiment about nine standard datasets in UL database to explain validity heuristic algorithm.