Zhidong Cao
Biographic Data
| ID | 3863344 |
|---|---|
| NAME | Zhidong Cao |
| GIVEN NAMES | Zhidong |
| FAMILY NAME | Cao |
| SIGNATURE | CAO Z |
| AFFILIATIONS | Chinese Academy of Sciences |
| ORCID | 0000-0001-5936-6822 |
| VERIFIED | Yes |
| TOTAL WORKS | 10 |
| TOTAL CITATIONS | 1 |
| AUTHOR COUNT | 10 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2012 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
Enhancing Knowledge Graph Completion With Structural-Semantic Integration and Contrastive Learning
Knowledge graph completion (KGC) addresses the issue of incomplete knowledge graphs by inferring missing triples, which is crucial for information retrieval, question answering, and recommender systems. Existing KGC methods generally focus on either exploiting the graph’s structural topology or leveraging the semantic information from entity descriptions. However, existing approaches often overlook the synergy between structure information and se…
Modeling the Coupling Propagation of Information, Behavior, and Disease in Multilayer Heterogeneous Networks
With the development of internet, transportation network, and other technologies, the transmission of information and disease presents complex and diverse new modes, which are mainly manifested as the coupling transmission of information and disease in the cyber–physical–social space. Inspired by this phenomenon, this article proposes a multilayer network-based information–behavior–disease coupling (IBDN) transmission model for the process of inf…
Energy-Social Manufacturing for Social Computing
This article explores social manufacturing (SM) within cyber–physical–social systems (CPSSs), leveraging artificial intelligence (AI) to revolutionize energy prosumer networks. We introduce a blockchain-enabled operation and management mechanism for energy systems, incorporating energy aggregators for efficient transaction audits and employing consortium blockchain and proof-of-work for enhanced security. Guided by social governance principles an…
Socially Governed Energy Hub Trading Enabled by Blockchain-Based Transactions
Decentralized trading schemes involving energy prosumers have prevailed in recent years. Such schemes provide a pathway for increased energy efficiency and can be enhanced by the use of blockchain technology to address security concerns in decentralized trading. To improve transaction security and privacy protection while ensuring desirable social governance, this article proposes a novel two-stage blockchain-based operation and trading mechanism…
A Deep Learning Approach for Semantic Analysis of Covid-19-Related Stigma on Social Media
The rapid spread of the pandemic of coronavirus disease of 2019 (COVID-19) has created an unprecedented, global health disaster. During the outburst period, the paucity of knowledge and research aggravated devastating panic and fears that lead to social stigma and created serious obstacles to contain the disastrous epidemic. We propose a deep learning-based method to detect stigmatized contents on online social network (OSN) platforms in the earl…
Two-Stage Co-Optimization for Utility-Social Systems With Social-Aware P2P Trading
Effective utility system management is fundamental and critical for ensuring the normal activities, operations, and services in cities and urban areas. In that regard, the advanced information and communication technologies underpinning smart cities enable close linkages and coordination of different subutility systems, which is now attracting research attention. To increase operational efficiency, we propose a two-stage optimal co-management mod…
Equitable access to Covid-19 vaccines makes a life-saving difference to all countries
Despite broad agreement on the negative consequences of vaccine inequity, the distribution of COVID-19 vaccines is imbalanced. Access to vaccines in high-income countries (HICs) is far greater than in low- and middle-income countries (LMICs). As a result, there continue to be high rates of COVID-19 infections and deaths in LMICs. In addition, recent mutant COVID-19 outbreaks may counteract advances in epidemic control and economic recovery in HIC…
Covid-19
The outbreak of the 2019 novel coronavirus disease (COVID-19) has caused more than 100,000 people infected and thousands of deaths. Currently, the number of infections and deaths is still increasing rapidly. COVID-19 seriously threatens human health, production, life, social functioning and international relations. In the fight against COVID-19, Geographic Information Systems (GIS) and big data technologies have played an important role in many a…
Modeling Heterogeneity in Direct Infectious Disease Transmission in a Compartmental Model
Mathematical models have been used to understand the transmission dynamics of infectious diseases and to assess the impact of intervention strategies. Traditional mathematical models usually assume a homogeneous mixing in the population, which is rarely the case in reality. Here, we construct a new transmission function by using as the probability density function a negative binomial distribution, and we develop a compartmental model using it to …
Adaptive modeling of the human-environment relationship applied to estimation of the population carrying capacity in an earthquake zone
Equitable access to Covid-19 vaccines makes a life-saving difference to all countries
Despite broad agreement on the negative consequences of vaccine inequity, the distribution of COVID-19 vaccines is imbalanced. Access to vaccines in high-income countries (HICs) is far greater than in low- and middle-income countries (LMICs). As a result, there continue to be high rates of COVID-19 infections and deaths in LMICs. In addition, recent mutant COVID-19 outbreaks may counteract advances in epidemic control and economic recovery in HIC…
Adaptive modeling of the human-environment relationship applied to estimation of the population carrying capacity in an earthquake zone
Modeling Heterogeneity in Direct Infectious Disease Transmission in a Compartmental Model
Mathematical models have been used to understand the transmission dynamics of infectious diseases and to assess the impact of intervention strategies. Traditional mathematical models usually assume a homogeneous mixing in the population, which is rarely the case in reality. Here, we construct a new transmission function by using as the probability density function a negative binomial distribution, and we develop a compartmental model using it to …
Covid-19
The outbreak of the 2019 novel coronavirus disease (COVID-19) has caused more than 100,000 people infected and thousands of deaths. Currently, the number of infections and deaths is still increasing rapidly. COVID-19 seriously threatens human health, production, life, social functioning and international relations. In the fight against COVID-19, Geographic Information Systems (GIS) and big data technologies have played an important role in many a…
Equitable access to Covid-19 vaccines makes a life-saving difference to all countries
Despite broad agreement on the negative consequences of vaccine inequity, the distribution of COVID-19 vaccines is imbalanced. Access to vaccines in high-income countries (HICs) is far greater than in low- and middle-income countries (LMICs). As a result, there continue to be high rates of COVID-19 infections and deaths in LMICs. In addition, recent mutant COVID-19 outbreaks may counteract advances in epidemic control and economic recovery in HIC…
A Deep Learning Approach for Semantic Analysis of Covid-19-Related Stigma on Social Media
The rapid spread of the pandemic of coronavirus disease of 2019 (COVID-19) has created an unprecedented, global health disaster. During the outburst period, the paucity of knowledge and research aggravated devastating panic and fears that lead to social stigma and created serious obstacles to contain the disastrous epidemic. We propose a deep learning-based method to detect stigmatized contents on online social network (OSN) platforms in the earl…
Two-Stage Co-Optimization for Utility-Social Systems With Social-Aware P2P Trading
Effective utility system management is fundamental and critical for ensuring the normal activities, operations, and services in cities and urban areas. In that regard, the advanced information and communication technologies underpinning smart cities enable close linkages and coordination of different subutility systems, which is now attracting research attention. To increase operational efficiency, we propose a two-stage optimal co-management mod…
Modeling the Coupling Propagation of Information, Behavior, and Disease in Multilayer Heterogeneous Networks
With the development of internet, transportation network, and other technologies, the transmission of information and disease presents complex and diverse new modes, which are mainly manifested as the coupling transmission of information and disease in the cyber–physical–social space. Inspired by this phenomenon, this article proposes a multilayer network-based information–behavior–disease coupling (IBDN) transmission model for the process of inf…
Energy-Social Manufacturing for Social Computing
This article explores social manufacturing (SM) within cyber–physical–social systems (CPSSs), leveraging artificial intelligence (AI) to revolutionize energy prosumer networks. We introduce a blockchain-enabled operation and management mechanism for energy systems, incorporating energy aggregators for efficient transaction audits and employing consortium blockchain and proof-of-work for enhanced security. Guided by social governance principles an…
Socially Governed Energy Hub Trading Enabled by Blockchain-Based Transactions
Decentralized trading schemes involving energy prosumers have prevailed in recent years. Such schemes provide a pathway for increased energy efficiency and can be enhanced by the use of blockchain technology to address security concerns in decentralized trading. To improve transaction security and privacy protection while ensuring desirable social governance, this article proposes a novel two-stage blockchain-based operation and trading mechanism…
Enhancing Knowledge Graph Completion With Structural-Semantic Integration and Contrastive Learning
Knowledge graph completion (KGC) addresses the issue of incomplete knowledge graphs by inferring missing triples, which is crucial for information retrieval, question answering, and recommender systems. Existing KGC methods generally focus on either exploiting the graph’s structural topology or leveraging the semantic information from entity descriptions. However, existing approaches often overlook the synergy between structure information and se…
Computer Science (8 works) · Business (4 works) · Medicine (4 works) · Computer security (3 works) · COVID-19 epidemiological studies (3 works) · Economics (3 works) · Engineering (3 works) · Geography (3 works) · Pandemic (3 works) · Disease (2 works)