A5072696348- Advancements in Battery Materials
- Advanced Battery Materials and Technologies
- Meteorological Phenomena and Simulations
- Machine Learning in Healthcare
- Bayesian Modeling and Causal Inference
- Formal Methods in Verification
- Artificial Intelligence in Healthcare
- Recommender Systems and Techniques
- Supercapacitor Materials and Fabrication
- Machine Learning and Data Classification
- Model-Driven Software Engineering Techniques
- Climate variability and models
- Extraction and Separation Processes
- Advanced Battery Technologies Research
- Domain Adaptation and Few-Shot Learning
- Gene Regulatory Network Analysis
- Data Quality and Management
- Advanced Graph Neural Networks
- Software Testing and Debugging Techniques
- Video Analysis and Summarization
- Imbalanced Data Classification Techniques
- Advanced MIMO Systems Optimization
- Bioinformatics and Genomic Networks
- Big Data and Business Intelligence
- Gene expression and cancer classification
Northeastern University
2023
Harbin Engineering University
2009-2023
Guangzhou University
2022
Harbin University
2022
Wuhan University of Science and Technology
2021
Yunnan University
2021
Sun Yat-sen University
2017-2020
LinkedIn (United States)
2019-2020
National Yunlin University of Science and Technology
2020
Wuhan No.1 Hospital
2019
Ti and Mg codoped Li3V2–2xTixMgx(PO4)3 (x = 0, 0.05, 0.10, 0.20, 0.25) samples were prepared by a sol–gel method. The effects of codoping on the physical electrochemical characteristics Li3V2(PO4)3 investigated. Compared with XRD pattern undoped sample, those have no extra reflections, which indicates that enter structure Li3V2(PO4)3. According to results charge–discharge measurements, initial capacity at low current density (0.2 C) decreases increasing x. However, discharge capacities...
Small and Medium-sized Enterprises (SMEs) are playing a vital role in the modern economy. Recent years, financial risk analysis for SMEs attracts lots of attentions from institutions. However, usually suffers data deficiency problem, especially mobile institutions which seldom collect credit-related directly SMEs. Fortunately, although information is hard to be acquired sufficiently, interactive relationships between SMEs, may contain valuable risk, available Finding out relationship SME...
Diffusion Transformers (DiTs) dominate video generation but their high computational cost severely limits real-world applicability, usually requiring tens of minutes to generate a few seconds even on high-performance GPUs. This inefficiency primarily arises from the quadratic complexity 3D Full Attention with respect context length. In this paper, we propose training-free framework termed Sparse VideoGen (SVG) that leverages inherent sparsity in boost inference efficiency. We reveal...
Abstract Summary Imputation of dropout events that may mislead downstream analyses is a key step in analyzing single-cell RNA-sequencing (scRNA-seq) data. We develop EnImpute, an R package introduces ensemble learning method for imputing scRNA-seq EnImpute combines the results obtained from multiple imputation methods to generate more accurate result. A Shiny application developed provide easier implementation and visualization. Experiment show outperforms individual state-of-the-art almost...
Traditional content marketing methods resort grossly to market requirements but barely obtain relatively accurate prediction under loads of requirements. Machine learning‐based approaches nowadays are widely used in multiple fields as they involve a training process deal with big data problems. In this paper, decision tree‐based introduced the field marketing, and intrinsically follow human making. Specifically, paper considers well‐known method, called C4.5, which can well continuous...
Rare diseases are hard to identify and diagnose. Our goal is use self-reported behavioural data distinguish people with rare from more common chronic illnesses. To this effect, we adapt a state of the art machine learning algorithm make classification. We find that using method, an appropriate set questions, can accurately diseases.
Organizational citizenship behavior is the key factor to promote sustainable development of an organization, and it great significance explore research status, hotspots, trends organizational organization. Therefore, purpose this study knowledge structure dynamic evolution trend more comprehensively objectively by using bibliometrics, in order theoretical on This found following: Scholars have studied factors individual group from three aspects: factors, leadership styles, factors. The...
We consider the problem of learning probabilistic models from relational data. One key issues with data is class imbalance where number negative examples far outnumbers positive examples. The common approach for dealing this use sub-sampling We, on other hand, a soft margin that explicitly trades off between false positives and negatives. apply to recently successful formalism functional gradient boosting. Specifically, we modify objective function include trade-off show empirically more in...
Simulation-based verification is still one of the most important methods to validate correctness System-on-Chips. Here, explicitly specified stimuli need be generated which trigger certain scenarios design. However, so far generation mainly performed independently desired coverage. In this work, we propose approaches for coverage-driven generation. Despite a naive method, introduce and discuss automatic interactive an improved We show that considering coverage metrics leads smaller complete...
To identify biological network rewiring under different conditions, we develop a user-friendly R package, named DiffNetFDR, to implement two methods developed for testing the difference in Gaussian graphical models. Compared existing tools, our have following features: (i) they are based on models which can capture changes of conditional dependencies; (ii) determine tuning parameters data-driven manner; (iii) take multiple procedure control overall false discovery rate; and (iv) approach...
Abstract Summary We develop DiffGraph, an R package that integrates four influential differential graphical models for identifying gene network rewiring under two different conditions from expression data. The input and output of are packaged in the same format, making it convenient users to compare using a wide range datasets carry out follow-up analysis. Furthermore, inferred networks can be visualized both non-interactively interactively. is useful datasets, comparing predictions methods...
Many real world applications in medicine, biology, communication networks, web mining, and economics, among others, involve modeling learning structured stochastic processes that evolve over continuous time. Existing approaches, however, have focused on propositional domains only. Without extensive feature engineering, it is difficult-if not impossible-to apply them within relational where we may varying number of objects relations them. We therefore develop the first representation called...
Incorporating richer human inputs including qualitative constraints such as monotonic and synergistic influences has long been adapted inside AI. Inspired by this, we consider the problem of using influence statements in successful gradient-boosting framework. We develop a unified framework for both classification regression settings that can effectively efficiently incorporate to accelerate learning better model. Our results large number standard domains two particularly novel real-world...
Compared with serial robots, because of some advantages, e.g. higher stiffness, errors will not accumulated, parallel robot has much potential use. To 3-RPS robot, there are 3 controllable degrees freedom (axis x, axis y, z, or angle z). It may be called position kinematics posture kinematics. According to structural characteristics the mathematical model inverse is established. The simulation set up using SimMechanics and Simulink module. validity proved by comparing two models. And during...