Weishan Zhang
Biographic Data
| ID | 8826720 |
|---|---|
| NAME | Weishan Zhang |
| GIVEN NAMES | Weishan |
| FAMILY NAME | Zhang |
| SIGNATURE | ZHANG W |
| AFFILIATIONS | China University of Petroleum, East China |
| ORCID | 0000-0001-9800-1068 |
| VERIFIED | Yes |
| TOTAL WORKS | 11 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 11 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 0 |
Diffusion Generation-Based Federated Learning for Non-IID Defect Recognition
Effective defect recognition is essential for improving quality and stability in smart manufacturing, often necessitating collaborative learning across multiple organizations. Federated learning (FL) is promising in this regard. However, FL struggles with client-drift problem in nonindependent and identically distributed (non-IID) data. To this end, this article introduces a novel federated learning with diffusion generation (FL-DiG), which tackl…
Opposing Stance in Topic Evolution
In February 2024, Lionel Messi's absence from a Hong Kong exhibition match ignited extensive debate across social media platforms, capturing the attention of the public and sparking controversies that extended into realms such as business partnerships and diplomatic implications. This incident not only reflects the public's reaction and pattern of stance changes toward such a complex Incident but also significantly demonstrates the close connecti…
Consistency and Controversy Analysis in the Hype of Room-Temperature Superconductivity
Room-temperature superconductors (esp. LK-99 in the recent) have attracted extensive academic attention in recent years, both in academic circles and among the general public. This topic has spread through a number of social media channels, a plethora of contradiction in information has emerged within social networks. There arises the question on how to analyze the consistency and controversy of such scientific knowledge in the dissemination proc…
SLoB
Large language models (LLMs) are becoming powerful engines for social productivity in the manufacturing lifecycle. Existing application-level LLMs inference services focus on large datacenter and small edge intelligence (EI) scenarios, adopting iteration-level batch schedulers to solve resource utilization and inference speed problems. However, these services are incompatible with the scene of medium-sized local heterogeneous graphics processing …
Spy Balloon or Sputnik Moment
Examining the perceptual differences between China and the United States can facilitate a better understanding of their opinions and perspectives, helping to promote peaceful interactions among the two nations as well as the world. This study presents a data-driven approach to measure cognitive differences, investigating these differences from topical and sentimental angles regarding the unmanned balloon event that had been shot down by U.S. warp…
Public Opinion Evolution in Cyberspace
The dynamics of public opinion on social media affects people’s feeling and minds about international affairs and leads to the reconstruction of societal states for international conflicts. In this article, we analyze the topics’ evolution on social media during the Pelosi visit. Such kind of analysis should help the related departments sense and beware the situation effectively and efficiently, and may provide technical supports for proper polic…
Decoding Activist Public Opinion in Decentralized Self-Organized Protests Using LLM
Based on an investigation of online public opinion on the Nahel Merzouk protests in France, an approach for analyzing and predicting public opinion on protests based on large language model (LLM) is proposed, revealing the impact of emerging social media on the protests. We demonstrate that protests generate public opinion on social media with some lag, but that comment sentiment and expression are consistent with protest trends. As the protests …
Community Awareness Personalized Federated Learning for Defect Detection
Multiple organizations in social manufacturing can collaborate on high-quality product defect detection with social networks. Federated learning (FL) is an emerging paradigm where multiple clients can collaboratively train a defect detection model in a privacy-preserving manner. A prevalent issue in FL, concept drift, is discussed in this article. Feature representations of the same label may vary at different clients which affects the performanc…
Knowledge Graph-Based Reinforcement Federated Learning for Chinese Question and Answering
Knowledge question and answering (Q&A) is widely used. However, most existing semantic parsing methods in Q&A usually use cascading, which can incur error accumulation. In addition, using only one institution’s Q&A data definitely will limit the Q&A performance, while data privacy prevents sharing between institutions. This article proposes a knowledge graph-based reinforcement federated learning (KGRFL)-based Q&A approach to address these challe…
Public Opinion Dynamics in Cyberspace on Russia–Ukraine War
The intensity and scale of the opinion fightings in cyberspace on the Russia–Ukraine war (RUW) have opened a new chapter in the history of world warfare. This is a magnificent demonstration of social cognitive war fighting with cyber-physical-social systems (CPSS) that would impact our humankind significantly now and for a long time to come, not just on our understanding of wars, but every aspect of our life. Therefore, it is worth of studying th…
Federated Data
Federated ecology can provide an effective solution forthe serious isolated data island issues caused by data privacy protection and information security requirements in the era of artificial intelligence (AI). As the data foundation of federated ecology, federated data include the data of all the nodes in the federation, as wellas their storage, computation, and communication resources. For privacy-preserving, federated data are divided into pri…
No prominent works on this page.
Federated Data
Federated ecology can provide an effective solution forthe serious isolated data island issues caused by data privacy protection and information security requirements in the era of artificial intelligence (AI). As the data foundation of federated ecology, federated data include the data of all the nodes in the federation, as wellas their storage, computation, and communication resources. For privacy-preserving, federated data are divided into pri…
Public Opinion Dynamics in Cyberspace on Russia–Ukraine War
The intensity and scale of the opinion fightings in cyberspace on the Russia–Ukraine war (RUW) have opened a new chapter in the history of world warfare. This is a magnificent demonstration of social cognitive war fighting with cyber-physical-social systems (CPSS) that would impact our humankind significantly now and for a long time to come, not just on our understanding of wars, but every aspect of our life. Therefore, it is worth of studying th…
SLoB
Large language models (LLMs) are becoming powerful engines for social productivity in the manufacturing lifecycle. Existing application-level LLMs inference services focus on large datacenter and small edge intelligence (EI) scenarios, adopting iteration-level batch schedulers to solve resource utilization and inference speed problems. However, these services are incompatible with the scene of medium-sized local heterogeneous graphics processing …
Spy Balloon or Sputnik Moment
Examining the perceptual differences between China and the United States can facilitate a better understanding of their opinions and perspectives, helping to promote peaceful interactions among the two nations as well as the world. This study presents a data-driven approach to measure cognitive differences, investigating these differences from topical and sentimental angles regarding the unmanned balloon event that had been shot down by U.S. warp…
Public Opinion Evolution in Cyberspace
The dynamics of public opinion on social media affects people’s feeling and minds about international affairs and leads to the reconstruction of societal states for international conflicts. In this article, we analyze the topics’ evolution on social media during the Pelosi visit. Such kind of analysis should help the related departments sense and beware the situation effectively and efficiently, and may provide technical supports for proper polic…
Decoding Activist Public Opinion in Decentralized Self-Organized Protests Using LLM
Based on an investigation of online public opinion on the Nahel Merzouk protests in France, an approach for analyzing and predicting public opinion on protests based on large language model (LLM) is proposed, revealing the impact of emerging social media on the protests. We demonstrate that protests generate public opinion on social media with some lag, but that comment sentiment and expression are consistent with protest trends. As the protests …
Community Awareness Personalized Federated Learning for Defect Detection
Multiple organizations in social manufacturing can collaborate on high-quality product defect detection with social networks. Federated learning (FL) is an emerging paradigm where multiple clients can collaboratively train a defect detection model in a privacy-preserving manner. A prevalent issue in FL, concept drift, is discussed in this article. Feature representations of the same label may vary at different clients which affects the performanc…
Knowledge Graph-Based Reinforcement Federated Learning for Chinese Question and Answering
Knowledge question and answering (Q&A) is widely used. However, most existing semantic parsing methods in Q&A usually use cascading, which can incur error accumulation. In addition, using only one institution’s Q&A data definitely will limit the Q&A performance, while data privacy prevents sharing between institutions. This article proposes a knowledge graph-based reinforcement federated learning (KGRFL)-based Q&A approach to address these challe…
Diffusion Generation-Based Federated Learning for Non-IID Defect Recognition
Effective defect recognition is essential for improving quality and stability in smart manufacturing, often necessitating collaborative learning across multiple organizations. Federated learning (FL) is promising in this regard. However, FL struggles with client-drift problem in nonindependent and identically distributed (non-IID) data. To this end, this article introduces a novel federated learning with diffusion generation (FL-DiG), which tackl…
Opposing Stance in Topic Evolution
In February 2024, Lionel Messi's absence from a Hong Kong exhibition match ignited extensive debate across social media platforms, capturing the attention of the public and sparking controversies that extended into realms such as business partnerships and diplomatic implications. This incident not only reflects the public's reaction and pattern of stance changes toward such a complex Incident but also significantly demonstrates the close connecti…
Consistency and Controversy Analysis in the Hype of Room-Temperature Superconductivity
Room-temperature superconductors (esp. LK-99 in the recent) have attracted extensive academic attention in recent years, both in academic circles and among the general public. This topic has spread through a number of social media channels, a plethora of contradiction in information has emerged within social networks. There arises the question on how to analyze the consistency and controversy of such scientific knowledge in the dissemination proc…
Computer Science (9 works) · Artificial Intelligence (5 works) · Computer security (4 works) · Political science (4 works) · Public opinion (4 works) · Data science (3 works) · Law (3 works) · Physics (3 works) · World Wide Web (3 works) · Complex Network Analysis Techniques (2 works)