A5043370961- Lattice Boltzmann Simulation Studies
- Aerosol Filtration and Electrostatic Precipitation
- Distributed and Parallel Computing Systems
- Cloud Computing and Resource Management
- Generative Adversarial Networks and Image Synthesis
- Computational Fluid Dynamics and Aerodynamics
- Advanced Numerical Methods in Computational Mathematics
- Matrix Theory and Algorithms
- Numerical methods in engineering
- Maritime Navigation and Safety
- Fluid Dynamics and Turbulent Flows
- Scientific Computing and Data Management
- Electromagnetic Simulation and Numerical Methods
- Data Mining Algorithms and Applications
- Polynomial and algebraic computation
- Online and Blended Learning
- Online Learning and Analytics
- Advanced Data Storage Technologies
- IoT and Edge/Fog Computing
- Geotechnical Engineering and Underground Structures
- Bioinformatics and Genomic Networks
- Fungal and yeast genetics research
- Advanced MRI Techniques and Applications
- Cyberloafing and Workplace Behavior
- Perfectionism, Procrastination, Anxiety Studies
Shanghai University
2012-2022
Shanghai University of Engineering Science
2007-2022
Dalian Maritime University
2017
Zhejiang University
2013
Zaozhuang University
2008
Shihezi University
2008
Central Institute for Art History
2000
Several challenges are associated with e-learning systems, the most significant of which is lack student motivation in various course activities and for materials. In this study, we used machine learning (ML) algorithms to identify low-engagement students a social science at Open University (OU) assess effect engagement on performance. The input variables study included highest education level , final results score assessment number clicks virtual environment (VLE) activities, dataplus...
Abstract Background Increasing evidence indicates that deregulation of microRNAs (miRNAs) is involved in tumorigenesis. Downregulation microRNA-503 has been observed various types diseases, including cancer. However, the biological function miR-503 hepatocellular carcinoma (HCC) still largely unknown. In this study we aimed to elucidate prognostic implications HCC and its pathophysiologic role. Methods Quantitative reverse transcriptase polymerase chain reaction was used evaluate expression...
The interpolating moving least-squares (IMLS) method is discussed first in this paper. And the formulae of IMLS obtained by Lancaster are revised. Then on basis boundary element-free (BEFM), combining integral equation (BIE) with method, improved (IBEFM) for two-dimensional potential problems presented, and corresponding IBEFM obtained. In BEFM, conditions applied directly, but shape function MLS does not satisfy property Kronecker δ function. This a problem must be solved theoretically....
In contrast with public clouds, private clouds have some unique features, especially when related to workflow scheduling. Of course, the tradeoff problem between power and performance remains be one of key concerns. Based on our previous research, in this paper, we propose a hybrid energy-efficient scheduling algorithm using dynamic migration. The experiments show that it can not only reduce response time, conserve more energy, but also achieve higher level load balancing.
Abstract Parkinson’s disease (PD) is a movement disorder due to the loss of dopaminergic (DA) neurons in substantia nigra. Alpha-synuclein phosphorylation and α-synuclein inclusion (Lewy body) become main contributor, but little known about their formation mechanism. Here we used protein expression profiling PD construct model signalling network from drsophila human nominate major nodes that regulate development. We found this LK6, serine/threonine kinase, plays key role promoting Ser129 by...
Ubiquitous online learning is continuing to expand, and the factors affecting success educational sustainability need be quantified. Procrastination one of compelling characteristics that students observe as a failure achieve weaker outcomes. Past studies have mainly assessed behaviors procrastination by describing explanatory work. Throughout this research, we concentrate on predictive measures identify forecast procrastinator using ensemble machine models (i.e., Logistic Regression,...
Text sentiment classification can be extensively applied to information retrieval, text filtering, online tracking evaluation, the diagnoses of public opinions and chat systems. In this paper, a kinds hybrid methods, based on category distinguishing ability words gain, is adopted feature selection. For examining impact varying dimension results, using corpus car reviews, dimensions, 1000, 2000 3000 are in our experiments. The experiments results indicate that methods best with equal 3000,...
Cloud computing is the next generation of paradigm. Along with cloud computing, many related problems come up. And these in turn slow speed development down. Among problems, e.g. interoperability and privacy, identity management security are strong concerned. Many researchers enterprises have already done a lot to optimize strengthen computing. Most studies focus on usability various kinds method help improve security. But this paper, we do some research from new angle. While federated...
The application of machine learning (ML)-based methods to the study thermoelectric (TE) materials is promising. Although conventional ML algorithms can achieve high prediction performance, their lack interpretability severely obstructs researchers from extracting material-oriented insights models. In this work, ML-based performance was achieved with respect TE power factors (PFs), and results were well understood by SHapley Additive exPlanations (SHAP), a method identify correlations between...
The discrete unified gas kinetic scheme (DUGKS) is a recently devised approach to simulate multiscale flows based on the models, which also shows distinct features for continuum flows. Most of existing DUGKS are sequential or structured grids, thus limiting their scope application in engineering. In this paper, parallel inviscid high-speed compressible unstructured grids proposed. framework DUGKS, gradients distribution functions calculated by least-square method. To parallelize method,...
Growth estimate of positive solution for a quasilinear parabolic equation subject to Robin boundary condition is presented by the maximum principles. The growth then used study blow-up problem. bounds ‘blow-up time’ and rate are obtained.
The lattice Boltzmann method (LBM) has become an attractive and promising approach in computational fluid dynamics (CFD). In this paper, parallel algorithm of D3Q19 multi-relaxation-time LBM with large eddy simulation (LES) is presented to simulate 3D flow past a sphere using multi-GPUs (graphic processing units). order deal complex boundary, the judgement boundary for devised. domain decomposition applied improve scalability cluster, overlapping mode introduced hide communication time by...
The lattice Boltzmann method (LBM) is a potent numerical technique based on kinetic theory. It can effectively simulate the steady-state and unsteady-state flow problems. A multi-domain decomposition strategy developed for LBM in order to accelerate rate of convergence different domains by relative error regions flow. In addition, proposed reduce amount calculations required improve stability. Numerical experiments involving both two- three-dimensional flows demonstrate drastically improved...
The lattice Boltzmann method (LBM) is a computational based on kinetic description of fluid mechanics. Intel Many Integrated Core (MIC) architecture designed for highly parallel computing has not been fully evaluated LBM. This paper proposes hybrid MPI/OpenMP model LBM CPU+MIC heterogeneous architecture, using the two-dimensional partitioning data division and offload, MPI, OpenMP. Furthermore, we use various methods to optimize algorithm. By numerical experiments in cluster Shanghai...
Help-seeking students are those who seek academic help during the assignment or course. Classifying help-seeking in a virtual learning environment (VLE) is challenging task for instructor because student not physically present. In this study, machine techniques and statistical methods were used to detect by analyzing logs data an e-learning system. We determined that which factors associated with behavior of students. found late submitted, low assessment score need more solving course...
A parallel algorithm, namely block diagonal dominant (PBDD) is proposed to solve tridiagonal linear systems on multi-computers. This algorithm based divided-and-conquer idea of the PDD method. When strictly dominant, PBDD highly and provides approximate solutions that equals exact within machine accuracy. The method has been implemented a 64-node multi-computer. analytic results match closely with measured from numerical experiments.