A5025224867- Time Series Analysis and Forecasting
- Heat Transfer and Optimization
- Anomaly Detection Techniques and Applications
- Heat Transfer and Boiling Studies
- Mechanical Behavior of Composites
- Mechanical stress and fatigue analysis
- Refrigeration and Air Conditioning Technologies
- Music and Audio Processing
- Engineering Structural Analysis Methods
- Perovskite Materials and Applications
- Conducting polymers and applications
- Advanced Text Analysis Techniques
- Data Management and Algorithms
- Structural Behavior of Reinforced Concrete
- Complex Systems and Time Series Analysis
- Network Security and Intrusion Detection
- Structural Load-Bearing Analysis
- Risk and Safety Analysis
- Advanced Malware Detection Techniques
- Stochastic Gradient Optimization Techniques
- Heat Transfer Mechanisms
- Algorithms and Data Compression
- Privacy-Preserving Technologies in Data
- Transportation Safety and Impact Analysis
- Topic Modeling
The University of Texas Rio Grande Valley
2021-2024
Chongqing Medical University
2024
PLA Army Engineering University
2015-2023
Fujian Institute of Research on the Structure of Matter
2021-2022
Chinese Academy of Sciences
2021-2022
Xiamen Institute of Rare-earth Materials
2021-2022
Chang'an University
2022
George Mason University
2015-2021
Wuhan University of Science and Technology
2021
Institute of Molecular Functional Materials
2021
With the advance of sensor technologies, Multivariate Time Series classification (MTSC) problem, perhaps one most essential problems in time series data mining domain, has continuously received a significant amount attention recent decades. Traditional approaches based on Bag-of-Patterns or Shapelet have difficulty dealing with huge amounts feature candidates generated high-dimensional multivariate but promising performance even when training set is small. In contrast, deep learning methods...
Abstract As game‐changers in the photovoltaic community, perovskite solar cells are making unprecedented progress while still facing grand challenges such as improving lifetime without impairing efficiency. Herein, two structurally alike polyaromatic molecules based on naphthalene‐1,8‐dicarboximide (NMI) and perylene‐3,4‐dicarboximide (PMI) with different molecular dipoles applied to tackle this issue. Contrasting electronically pull–pull cyanide‐substituted PMI (9CN‐PMI) only Lewis‐base...
Efficient electron transport layers (ETLs) not only play a crucial role in promoting carrier separation and extraction perovskite solar cells (PSCs) but also significantly affect the process of nucleation growth layer. Herein, crystalline polymeric carbon nitrides (cPCN) are introduced to regulate electronic properties SnO2 nanocrystals, resulting cPCN-composited (SnO2-cPCN) ETLs with enhanced charge decreased grain boundaries. Firstly, SnO2-cPCN show three times higher mobility than...
Titanium alloys have many advanced applications where they are subject to fatigue. Here, we compare the fatigue crack growth resistance and microstructures of TC4-DT fabricated by wire-arc additive manufacturing (WAAM; sample S1) in-situ rolled WAAM (sample S2) followed quasi-β heat treatment. Sample S2 had superior resistance, which is mainly attributed its finer defects α phase. The critical size related performance was calculated. majority in were smaller than size, while several coarse...
Recently, there has been a significant advancement in designing Self-Supervised Learning (SSL) frameworks for time series data to reduce the dependency on labels. Among these works, hierarchical contrastive learning-based SSL frameworks, which learn representations by contrasting embeddings at multiple resolutions, have gained considerable attention. Due their ability gather more information, they exhibit better generalization various downstream tasks. However, when length is long,...
Multimodal large language models (MLLMs) have shown remarkable performance for cross-modal understanding and generation, yet still suffer from severe inference costs. Recently, abundant works been proposed to solve this problem with token pruning, which identifies the redundant tokens in MLLMs then prunes them reduce computation KV storage costs, leading significant acceleration without training. While these methods claim efficiency gains, critical questions about their fundamental design...
Abstract In recent years, the power conversion efficiency (PCE) of perovskite solar cells (PSCs) has witnessed rapid progress. Nevertheless, pervasive defects prone to non‐radiative recombination and decomposition exist at surface grain boundaries (GBs) polycrystalline films. Herein, we report a comprehensive dual‐passivation (DP) strategy effectively passivate both GBs enhance device performance stability further. Firstly, fluorinated perylene‐tetracarboxylic diimide derivative is permeated...
According to recent security analysis reports, malicious software (a.k.a. malware) is rising at an alarming rate in numbers, complexity, and harmful purposes compromise the of modern computer systems. Recently, malware detection based on low-level hardware features (e.g., Hardware Performance Counters (HPCs) information) has emerged as effective alternative solution address complexity performance overheads traditional software-based methods. Hardware-assisted Malware Detection (HMD)...
Detecting repeated variable-length patterns, also called motifs, has received a great amount of attention in recent years. Current state-of-the-art algorithm utilizes fixed-length motif discovery as subroutine to enumerate motifs. As result, it may take hours or days execute when enumeration range is large. In this work, we introduce an approximate HierarchIcal based Motif Enumeration (HIME) detect motifs with large million-scale time series. We show the experiments that scalability proposed...
High false alarm rates in Intensive Care Unit (ICU) is a common problem that leads to desensitization -- phenomenon called fatigue. Alarm fatigue can cause longer response time or missing of important alarms. In this work, we propose methodology identify alarms generated by ICU bedside monitors. The novelty our approach lies the extraction 216 relevant features capture characteristics all alarms, from both arterial blood pressure (ABP) and electrocardiogram (ECG) signals. Our multivariate...
A unique lightweight string truss deployable bridge assembled by thin-walled fiber reinforced polymer (FRP) and metal profiles was designed for emergency applications. As a new structure, investigations into the static structural performance under serviceability limit state are desired examining integrity of developed when subjected to unsymmetrical loadings characterized combined torsion bending. In this study, full-scale experimental inspection conducted on fabricated bridge,...
We proved that electron-deficient 4-nitrophthalonitrile with σ–π accepting NO<sub>2</sub> and –CN can passivate the charged defects in perovskite solar cells, which achieve a power conversion efficiency (PCE) of 22.1% improved stability.
Perovskite solar cells (PSCs) with LiTFSI-doped Spiro-OMeTAD as the hole transport layer (HTL) generally require aging in air to achieve high efficiency (a.k.a. aging-induced rising), but attention is rarely paid synergistic effects of temperature and humidity during ambient aging. In this work, based on understanding doping mechanism Spiro-OMeTAD, we develop an condition-controlled hot-air treatment (HAT) for such kinds PSCs further improve device relieve photocurrent hysteresis. After...
Hardware-Assisted Malware Detection (HMD) techniques deploy Machine Learning (ML) classifiers to detect patterns of malicious applications based on microarchitectural features captured by modern microprocessors' Hardware Performance Counters (HPCs). Existing HMD methods have limited their analysis detecting that are spawned as a separate thread during application execution, hence embedded malware at run-time still remains an important challenge. Embedded refers harmful stealthy cyber attacks...
To address the high complexity and computational overheads of conventional software-based detection techniques, Hardware Malware Detection (HMD) has shown promising results as an alternative anomaly solution. HMD methods apply Machine Learning (ML) classifiers on microarchitectural events monitored by built-in Performance Counter (HPC) registers available in modern microprocessors to recognize patterns anomalies (e.g., signatures malicious applications). Existing hardware malware solutions...
In recent years, finding repetitive similar patterns in time series has become a popular problem. These are called motifs. Recent studies show that using grammar compression algorithms to find repeating from the symbolized holds promise discovering approximate motifs with variable length. However, traditionally designed for string compression. Therefore, existing work on induction not fully utilized much available information can be used enhance performance of algorithms. this work, an...
In the conventional methods, shear failure load of composite pretightened tooth connections is determined by experiment. To determine connection without performing experiments, a method based on characteristic lengths presented in this paper. This involves three steps: first, are determined; second, stress distribution joint analyzed use finite element method; finally, predicted length and criterion. The loads validated test results for joints with different parameters. comparison...