International Journal of Computational Science and Engineering

This journal also publishes Open Access articles

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Editor in Chief: Prof. Kuan-Ching Li
ISSN online: 1742-7193
ISSN print: 1742-7185
8 issues per year
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Computational science and engineering is an emerging and promising discipline in shaping future research and development activities in academia and industry, in fields ranging from engineering, science, finance, and economics, to arts and humanities. New challenges arise in the modelling of complex systems, sophisticated algorithms, advanced scientific and engineering computing and associated (multidisciplinary) problem-solving environments. IJCSE addresses the state of the art of all aspects of computational science and engineering, highlighting computational methods and techniques for science and engineering applications.

 



 Topics covered include

  • Scientific and engineering computing, related/interdisciplinary applications
  • Problem-solving environments, complex systems
  • Advanced numerical computation and optimisation
  • Parallel and distributed computing
  • Programming models in GPU, multi/m any-core and cloud
  • Quantum computing technologies and applications
  • Distributed/federated information; knowledge management/discovery
  • Blockchain
  • Cyber security and cryptography
  • Origami engineering
  • Performance modelling, evaluation and optimisation
  • Modelling/simulation, visualisation
  • Remote sensing and multi/hyperspectral imaging
  • Big data mining/applications, data analytics algorithms/applications
  • Machine learning, statistics, deep learning and artificial intelligence

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Objectives

The objective of IJCSE is to provide an outstanding channel for researchers and scientists from mathematics and computer science as basic computing disciplines, researchers from various application areas who are pioneering advanced application of computational methods to sciences, engineering, arts and humanities fields, along with software developers and vendors, to contribute and to disseminate innovative and important new work, and to shape future directions for research, as well as to help industrial professionals apply various advanced computational techniques.


Readership

Scientists, engineers, researchers, graduate students, educators, programmers, industrial professionals and managers.


Contents

IJCSE is a refereed international journal providing an international forum to report, discuss and exchange experimental results, novel designs, work-in-progress, experience, case studies, and trend-setting ideas in the area of computational science and engineering. Papers should be of a quality that represents the state of the art in the field, bringing together the latest computing advances for scientific and engineering research, applications, and education, and stimulating future trends.


 

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Browse issues

Vol. 17
Vol. 16
Vol. 15
Vol. 14
Vol. 13
Vol. 12

 

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 IJCSE is indexed in:

 

 IJCSE is listed in:

 

    Editor in Chief

  • Li, Kuan-Ching, Providence University, Taiwan
    (journaleditorialmanager@outlook.com)

Executive Editors

  • Pan, Yi, Georgia State University, USA
  • Yang, Laurence T., St Francis Xavier University, Canada

Associate Editors

  • Bhalla, Subhash, University of Aizu, Japan
  • Chen, Jinjun, Swinburne University of Technology, Australia
  • Cheung, Yiu-Ming, Hong Kong Baptist University, Hong Kong SAR, China
  • Choo, Kim-Kwang Raymond, University of Texas at San Antonio, USA
  • De Mello, Rodrigo Fernandes, University of Sao Paulo, Brazil
  • Di Martino, Beniamino, Seconda Universitá di Napoli, Italy
  • Huang, Xinyi, Fujian Normal University, China
  • Juckeland, Guido, Helmholtz-Zentrum Dresden-Rossendorf e.V., Germany
  • Lu, Huimin, Kyushu Institute of Technology, Japan
  • Pathan, Al-Sakib Khan, Southeast University, Bangladesh
  • Wang, Guojun, Guangzhou University, China

Advisory Board

  • Bader, David A., Georgia Institute of Technology, USA
  • Bailey, David H., Lawrence Berkeley National Laboratory, USA
  • Bertino, Elisa, Purdue University, USA
  • Cao, Jiannong, Hong Kong Polytechnic University, Hong Kong SAR, China
  • Chang, Chein-I, University of Maryland, Baltimore County, USA
  • Chapman, Barbara, Stony Brook University, USA
  • Dongarra, Jack, University of Tennessee Knoxville, USA
  • Gaudiot, Jean-Luc, University of California – Irvine, USA
  • Gropp, William D., University of Illinois Urbana-Champaign, USA
  • Guo, Minyi, Shanghai Jiao Tong University, China
  • Hu, Bin, Lanzhou University, China
  • Jin, Hai, Huazhong University of Science and Technology, China
  • Keyes, David, Columbia University, USA
  • Li, Keqin, State University of New York at New Paltz, USA
  • Ling, Nam, Santa Clara University, USA
  • Pardalos, Panos M., University of Florida, USA
  • Pedrycz, Witold, University of Alberta, Canada
  • Xiang, Yang, Deakin University, Australia
  • Zomaya, Albert, University of Sydney, Australia

Editorial Board Members

  • Benkner, Siegfried, University of Vienna, Austria
  • Bhuiyan, Md Zakirul Alam, Fordham University, USA
  • Castiglione, Aniello, University of Salerno, Italy
  • Chandrasekaran, Sunita, University of Delaware, USA
  • De Sousa, Fabricio Simeoni, University of Sao Paulo (USP), Brazil
  • Dong, Mianxiong, Muroran Institute of Technology, Japan
  • Faragó, István, Eötvös Loránd University, Hungary
  • Gavrilova, Marina L., University of Calgary, Canada
  • Gorlatch, Sergei, Universität Münster, Germany
  • Kacsuk, Peter, Hungarian Academy of Sciences, Hungary
  • Katz, Daniel S., University of Illinois, USA
  • Kolodziej, Joanna, Cracow University of Technology, Poland
  • Liu, Yan, Concordia University, Canada
  • Lopez, Matthew Graham, Oak Ridge National Laboratory, USA
  • Luo, Xiangfeng, Shanghai University, China
  • Malyshkin, Victor, Russian Academy of Sciences, Russian Federation
  • Massetto, Francisco Isidro, Federal University of ABC, Brazil
  • Mehofer, Eduard, University of Vienna, Austria
  • Navaux, Philippe O. A., Federal University of Rio Grande do Sul (UFRGS), Brazil
  • Pop, Florin, University Politehnica of Bucharest, Romania
  • Ruede, Ulrich, University of Erlangen-Nürnberg, Germany
  • See, Simon, Nvidia, Singapore, Singapore
  • Shen, Jun, University of Wollongong, Australia
  • Strazdins, Peter, Australian National University, Australia
  • Susilo, Willy, University of Wollongong, Australia
  • Thulasiram, Ruppa K., University of Manitoba, Canada
  • Turek, Stefan, University of Dortmund, Germany
  • Wang, Bei, Princeton University, USA
  • Ylianttila, Mika, University of Oulu, Finland
  • Yuan, Juan-Ming, Providence University, Taiwan
  • Zhang, Shunxiang, Anhui University of Science and Technology, China
  • Zlatev, Zahari, Aarhus University, Denmark

 

A few essentials for publishing in this journal

 

  • Submitted articles should not have been previously published or be currently under consideration for publication elsewhere.
  • Conference papers may only be submitted if the paper has been completely re-written (more details available here) and the author has cleared any necessary permissions with the copyright owner if it has been previously copyrighted.
  • All our articles go through a double-blind review process.
  • All authors must declare they have read and agreed to the content of the submitted article. A full statement of our Ethical Guidelines for Authors (PDF) is available.
  • There are no charges for publishing with Inderscience, unless you require your article to be Open Access (OA). You can find more information on OA here.

 

Submission process

 

All articles for this journal must be submitted using our online submissions system.

Submit here.

 

 

Journal news

  • Forthcoming paper

     

    Title: A semantic recommender algorithm for 3D model retrieval based on deep belief networks
    Authors: Li Chen, Hong Liu, Philip Moore
    Abstract: Interest in 3D modelling is growing; however, the retrieval results achieved for semantic-based 3D model retrieval systems have been disappointing. In this paper we propose a novel semantic recommendation algorithm based on a Deep Belief Network (DBN-SRA) to implement semantic retrieval with potential semantic correlations [between models] being achieved using deep learning form known model samples. The algorithm uses the feature correlation [between the models] as the conditions to enable semantic matching of 3D models to obtain the final recommended retrieval result. Our proposed approach has been shown to improve the effectiveness of 3D model retrieval, in terms of both retrieval time and, importantly, accuracy. Additionally, our study and our reported results suggest that our posited approach will generalise to recommender systems in other domains that are characterised by multiple feature relationships.

    More details...

  • International Journal of Computational Science and Engineering increases issues

     

    The International Journal of Computational Science and Engineering has announced that it will be increasing issues from eight to twelve from 2019 onwards.