Research Frontier

 

 

 

The International Journal of Modelling and Simulation (IJMS) is a peer-reviewed research journal in the field of modelling and simulations. It welcomes technical papers on new developments and their implications, papers on applications of existing techniques in science and engineering, survey papers on the state-of-the art, as well as short communications on current events.

This journal is indexed in EI and offers both print and online publication. The topics published in IJMS include, but are not limited to, the following:


conceptual modelling


Agent-based modelling


Mathematical modelling (stochastic and probabilistic modelling, continuum and discrete modelling, graph theory, algebraic coding, behavioural language)


Complex system modelling


Neural and fuzzy modelling


Simulation tools and platforms


formal methods of simulation (Monte Carlo method, planning and scheduling, ontologies, real-time systems, stochastic method, dynamic method, nonlinear method, optimization, distributed and parallel computing, mathematical method, decision support, risk analysis, verification and validation, multi-scale analysis)


Simulation applications in different disciplines


Editor-in-Chief

Professor Jie Shen

Department of Computer and Information Science, University of Michigan-Dearborn

U.S.A.

shen@umich.edu

 

Call for Special Issues

Proposals for special issues in cutting-edge and newly-developing areas are welcome, and should be discussed with the Editors-in-Chief.

 

How to submit

IJMS is always open for new submissions and is now using the Editorial Manager submission system. You can find it at the following address: www.editorialmanager.com/tjms

 

Subscription

For information on how to subscribe, simply contact Taylor & Francis at subscriptions@tandf.co.uk

 

 

Call for a Special Issue: Data Processing, Mining, and Fusion via Modelling and Simulation


International Journal of Modelling and Simulation



Editor: Jie Shen, Ph.D., Professor

Email: shen@umich.edu



This special issue will provide a forum for scientists and engineers alike to present their latest findings on the subject of data processing, mining, and fusion. Specific topics of interest include, but are not limited to:


Sequential or parallel data processing


Big data modelling and simulation


Sequential or parallel data mining


Sequential or parallel data fusion


Data science via modelling and simulation

 

Paper Submission

Submission Website:www.tandfonline.com/loi/tjms20 (The prefix of your manuscript should be SI-DPMFMS:)

Deadline for Full Paper Submission: February 1, 2018

Author Paper Review Acceptance or Revision Notification to Author: May 1, 2018

Submission of Final Paper: June 1, 2018

Journal Publication (online first): June 15, 2018

Journal Publication (print): 3 to 6 months later

 

Call for a Special Issue: Optimization and Machine Learning via Modelling and Simulation


International Journal of Modelling and Simulation



Editor: Jie Shen, Ph.D., Professor

Email: shen@umich.edu


 

This special issue will provide a forum for scientists and engineers alike to present their latest findings on the subject of optimization and machine learning. Specific topics of interest include, but are not limited to:


Evolutionary optimization


Neural network-based optimization and forecasting


Optimization applications of big data


Novel machine learning schemes


Deep learning via modelling and simulation

 

Paper Submission

Submission Website: www.tandfonline.com/loi/tjms20 (The prefix of your manuscript should be SI-OMLMS:)

Deadline for Full Paper Submission: February 1, 2018

Author Paper Review Acceptance or Revision Notification to Author: May 1, 2018

Submission of Final Paper: June 1, 2018

Journal Publication (online first): June 15, 2018

Journal Publication (print): 3 to 6 months later

 

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Advances in Our Research

 

Computational Material Science

Three-dimensional voids, cracks, and inclusions in materials may have a random and heterogeneous distribution within a material specimen or an engineering structure under service conditions. How to measure, model, and analyze those material defects, which could amount to millions of entities, is a challenging, yet fascinating, task. A group of researchers at the University of Michigan – Dearborn (Prof. Shen : computer & information science; Prof. Chow : damage mechanics; Prof. Reyes : material science) has been devoting their efforts jointly in tackling this important problem. The potential research results could provide an effective means to explore material damage mechanisms and establish digital signatures for material or structure degradation. So far, we have developed a novel digital interrogation method for evaluating material damage. Numerical calculation and material tests indicate that our method is significantly superior to traditional damage mechanics and models in micromechanics.

MaterialDamage.jpg

 


Computational Laser Sensing

Our past contributions include

(1) We were among the first in coining the terminology of “non-isolated outlier clusters.”

(2) We developed the first algorithm for removing non-isolated outlier clusters, which was cited and followed by others.

(3) Denoising of 2D geometric discontinuities was developed.

(4) A fast voxel-based method was designed to preprocess discrete point cloud data.

(5) Technology has been licensed in industry with10x speed improvement, which is applicable to the LIDAR data of most cars.

Below is an interesting demo of our novel method.

 

 

Computational Autonomous Driving

Currently, we are conducting a series of studies under an umbrella of Intelligent Driving System with particular focuses on (1) Agent-based Virtual Testing of Autonomous Driving, (2) Novel Brain-Human Interface for Autonomous Driving, and (3) Perception and Pose Analysis of Pedestrians. Our solution to autonomous driving won a semi-finalist of Next Challenge --- Smart Cities 2017.