A5066652469- Anomaly Detection Techniques and Applications
- Network Security and Intrusion Detection
- Software System Performance and Reliability
- Artificial Immune Systems Applications
- Data Mining Algorithms and Applications
- COVID-19 diagnosis using AI
- Mechanical Failure Analysis and Simulation
- Machine Fault Diagnosis Techniques
- Data Stream Mining Techniques
- Transportation Planning and Optimization
- melanin and skin pigmentation
- Atherosclerosis and Cardiovascular Diseases
- Software Engineering Research
- Railway Systems and Energy Efficiency
- Biochemical Analysis and Sensing Techniques
- Probabilistic and Robust Engineering Design
Air Force Medical University
2025
PLA Information Engineering University
2023-2024
Sun Yat-sen University
2022-2024
Northeastern University
2022
Southwest Jiaotong University
2011
Vitiligo is a challenging chronic condition with unpredictable disease course and high propensity for relapse post-treatment. Recent studies have reported the biomarkers activity, severity, therapeutic response of vitiligo, yet very few investigated cytokines as predictive recurrence in vitiligo. This study aims to explore that serve extend research on factors related disease's activity. 92 patients 40 healthy controls were recruited at Air Force Medical Center from September 20, 2023,...
The goal of anomaly detection is to identify anomalous samples from normal ones. In this paper, a small number anomalies are assumed be available at the training stage, but they collected only several types, leaving majority types not represented in dataset all. To effectively leverage kind incomplete knowledge by anomalies, we propose learn probability distribution that can model samples, also guarantee assign low density values for anomalies. end, an anomaly-aware generative adversarial...
Anomaly detection aims to detect instances that deviate significantly from the majority. Due difficulties of collecting a large amount anomalies in practice, existing methods generally assume availability clean normal dataset and leverage it by characterizing normality samples. However, for many application scenarios, is sufficiently not easy. What often observed small are falsely mixed into dataset, resulting contaminated dataset. Obviously, contamination could compromise model's ability...
According to the demand of management and features EMU routing scheme for passenger dedicated line, puts forward necessity urgency developing it, carries on analysis data flow it. In paper, total function structure design system are also investigated .And related problems discussed, such as design. On this basis, a corresponding using VC is developed.
The diversity of logs leads to difficulties in log anomaly detection. Identifying the source can provide guidelines for subsequent To this end, paper proposes a method recognition based on similarity determination, called ReLog. ReLog first takes feature codes target and matches them with baseline. Then uses cosine function calculate similarity. Finally selects item highest meets minimum threshold as matching item, so identify log. In order verify effectiveness ReLog, we tested it datasets...
Abnormal features and normal are the key to log anomaly detection. There various features, but software workflow undoubtedly most fundamental ones. So, this paper presents a novel method restore construct invariants, which we call it as MvLog. MvLog first uses modified Drain obtain events corresponding parameters, then improved Apriori find related event sequences, finally analyses relationship between sequences recover fragment considered invariants for We had developed prototype system...