Jinhuan Wang
Biographic Data
| ID | 3928093 |
|---|---|
| NAME | Jinhuan Wang |
| GIVEN NAMES | Jinhuan |
| FAMILY NAME | Wang |
| SIGNATURE | WANG J |
| AFFILIATIONS | Zhejiang University of Technology |
| ORCID | 0000-0001-9348-3424 |
| VERIFIED | Yes |
| TOTAL WORKS | 14 |
| TOTAL CITATIONS | 35 |
| WORKS AS AUTHOR | 14 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2006 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 4 |
Hierarchical machine learning model integrating clinical history and nursing observations for predicting violent behavior in hospitalized schizophrenia patients
The hierarchical machine learning model integrating clinical history and dynamic nursing observations significantly enhances predictive accuracy for violent behavior in schizophrenia inpatients, providing clinicians with valuable tools for timely risk assessment and personalized preventive interventions
Associations among mental well-being, marital quality, and maternal depressive symptoms in China
PPD is a significant postpartum issue that is influenced by numerous factors. Early screening of parturients, accurate diagnosis of PPD, and timely intervention are crucial. Targeted interventions addressing risk factors may help to mitigate the incidence of PPD
DeepInsight
With the rapid development of artificial intelligence, a number of machine learning algorithms, such as graph neural networks (GNNs), have been proposed to facilitate network analysis or graph data mining. Although effective, recent studies show that these advanced methods may suffer from adversarial attacks, i.e., they may lose effectiveness when only a small fraction of links are unexpectedly changed. This article investigates three well-known …
Node Injection Attack Based on Label Propagation Against Graph Neural Network
Graph neural network (GNN) has achieved remarkable success in various graph learning tasks, such as node classification, link prediction, and graph classification. The key to the success of GNN lies in its effective structure information representation through neighboring aggregation. However, the attacker can easily perturb the aggregation process through injecting fake nodes, which reveals that GNN is vulnerable to the graph injection attack (G…
GA-Based Multipopulation Synergistic Gene Screening Strategy on Critical Nodes Detection
Critical node detection (CND) is commonly used to detect nodes with a high impact on network robustness. It has been widely used in disease propagation, social networks, communications, and other fields. As a nondeterministic polynomial-time (NP)-complete problem, the efficiency of solving CND severely limits the scale of the available network. Fortunately, the evolutionary algorithm (EA) is an effective method to solve this problem. However, alt…
Single-Node Injection Label Specificity Attack on Graph Neural Networks via Reinforcement Learning
Graph neural networks (GNNs) have achieved remarkable success in various real-world applications. However, recent studies highlight the vulnerability of GNNs to malicious perturbations. Previous adversaries primarily focus on graph modifications or node injections to existing graphs, yielding promising results but with notable limitations. Graph modification attack (GMA) requires manipulation of the original graph, which is often impractical, whi…
Attacking the Core Structure of Complex Network
The concept of $k$ -core in complex networks plays a key role in many applications, e.g., understanding the global structure or identifying central/critical nodes, of a network. A malicious attacker with a jamming ability can exploit the vulnerability of the $k$ -core structure to attack the network and invalidate the network analysis methods, e.g., reducing the $k$ -shell values of nodes can deceive graph algorithms, leading to the wrong decisio…
Can urban agglomeration bring “1 + 1 > 2Effect”? A perspective of land resource carrying capacity
How to address properly the scale of urban infrastructures? –An empirical study of 35 large Chinese cities
An integrative method for analyzing spatial accessibility in the hierarchical diagnosis and treatment system in China
A novel evaluation method for urban infrastructures carrying capacity
Economic perspective-based analysis on urban infrastructures carrying capacity — A China study
An alternative model for evaluating the balance of carrying capacity between functional urban infrastructures
Chromosome painting between human and lorisiform prosimians
Multidirectional chromosome painting with probes derived from flow‐sorted chromosomes of humans ( Homo sapiens , HSA, 2n = 46) and galagos ( Galago moholi , GMO, 2n = 38) allowed us to map evolutionarily conserved chromosomal segments among humans, galagos, and slow lorises ( Nycticebus coucang , NCO, 2n = 50). In total, the 22 human autosomal painting probes detected 40 homologous chromosomal segments in the slow loris genome. The genome of the …
Can urban agglomeration bring “1 + 1 > 2Effect”? A perspective of land resource carrying capacity
An alternative model for evaluating the balance of carrying capacity between functional urban infrastructures
A novel evaluation method for urban infrastructures carrying capacity
Economic perspective-based analysis on urban infrastructures carrying capacity — A China study
How to address properly the scale of urban infrastructures? –An empirical study of 35 large Chinese cities
An integrative method for analyzing spatial accessibility in the hierarchical diagnosis and treatment system in China
Chromosome painting between human and lorisiform prosimians
Multidirectional chromosome painting with probes derived from flow‐sorted chromosomes of humans ( Homo sapiens , HSA, 2n = 46) and galagos ( Galago moholi , GMO, 2n = 38) allowed us to map evolutionarily conserved chromosomal segments among humans, galagos, and slow lorises ( Nycticebus coucang , NCO, 2n = 50). In total, the 22 human autosomal painting probes detected 40 homologous chromosomal segments in the slow loris genome. The genome of the …
An alternative model for evaluating the balance of carrying capacity between functional urban infrastructures
A novel evaluation method for urban infrastructures carrying capacity
Economic perspective-based analysis on urban infrastructures carrying capacity — A China study
How to address properly the scale of urban infrastructures? –An empirical study of 35 large Chinese cities
An integrative method for analyzing spatial accessibility in the hierarchical diagnosis and treatment system in China
Can urban agglomeration bring “1 + 1 > 2Effect”? A perspective of land resource carrying capacity
Attacking the Core Structure of Complex Network
The concept of $k$ -core in complex networks plays a key role in many applications, e.g., understanding the global structure or identifying central/critical nodes, of a network. A malicious attacker with a jamming ability can exploit the vulnerability of the $k$ -core structure to attack the network and invalidate the network analysis methods, e.g., reducing the $k$ -shell values of nodes can deceive graph algorithms, leading to the wrong decisio…
DeepInsight
With the rapid development of artificial intelligence, a number of machine learning algorithms, such as graph neural networks (GNNs), have been proposed to facilitate network analysis or graph data mining. Although effective, recent studies show that these advanced methods may suffer from adversarial attacks, i.e., they may lose effectiveness when only a small fraction of links are unexpectedly changed. This article investigates three well-known …
Node Injection Attack Based on Label Propagation Against Graph Neural Network
Graph neural network (GNN) has achieved remarkable success in various graph learning tasks, such as node classification, link prediction, and graph classification. The key to the success of GNN lies in its effective structure information representation through neighboring aggregation. However, the attacker can easily perturb the aggregation process through injecting fake nodes, which reveals that GNN is vulnerable to the graph injection attack (G…
GA-Based Multipopulation Synergistic Gene Screening Strategy on Critical Nodes Detection
Critical node detection (CND) is commonly used to detect nodes with a high impact on network robustness. It has been widely used in disease propagation, social networks, communications, and other fields. As a nondeterministic polynomial-time (NP)-complete problem, the efficiency of solving CND severely limits the scale of the available network. Fortunately, the evolutionary algorithm (EA) is an effective method to solve this problem. However, alt…
Single-Node Injection Label Specificity Attack on Graph Neural Networks via Reinforcement Learning
Graph neural networks (GNNs) have achieved remarkable success in various real-world applications. However, recent studies highlight the vulnerability of GNNs to malicious perturbations. Previous adversaries primarily focus on graph modifications or node injections to existing graphs, yielding promising results but with notable limitations. Graph modification attack (GMA) requires manipulation of the original graph, which is often impractical, whi…
Hierarchical machine learning model integrating clinical history and nursing observations for predicting violent behavior in hospitalized schizophrenia patients
The hierarchical machine learning model integrating clinical history and dynamic nursing observations significantly enhances predictive accuracy for violent behavior in schizophrenia inpatients, providing clinicians with valuable tools for timely risk assessment and personalized preventive interventions
Associations among mental well-being, marital quality, and maternal depressive symptoms in China
PPD is a significant postpartum issue that is influenced by numerous factors. Early screening of parturients, accurate diagnosis of PPD, and timely intervention are crucial. Targeted interventions addressing risk factors may help to mitigate the incidence of PPD
Computer Science (9 works) · Engineering (6 works) · Urban Transport and Accessibility (6 works) · Business (5 works) · Economics (5 works) · Environmental planning (5 works) · Geography (5 works) · Water Resources and Sustainability (5 works) · Advanced Graph Neural Networks (4 works) · Carrying capacity (4 works)