Computational Science and Its Applications 2024 (ICCSA 2024)

A special issue of Computers (ISSN 2073-431X).

Deadline for manuscript submissions: 15 April 2025 | Viewed by 1822

Special Issue Editor


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Guest Editor
Department of Mathematics and Computer Science, University of Perugia, 06123 Perugia, Italy
Interests: parallel and distributed systems; grid computing; cloud computing; virtual reality and scientific visualization; implementation of algorithms for molecular studies; multimedia and internet computing; e-learning
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Special Issue Information

Dear Colleagues,

The 24th International Conference on Computational Science and Its Applications (ICCSA 2023) will be held on July 1–4, 2024, in collaboration with Thuyloi University, Hanoi, Vietnam. Computational science is one of the main pillars of most of the present research, industrial, and commercial activities, and plays a unique role in exploiting information and communication technologies as innovative technologies. The ICCSA Conference offers a real opportunity to discuss new issues, tackle complex problems and find advanced enabling solutions able to shape new trends in computational science. For more information, please visit the following link: http://www.iccsa.org/.

The authors of a number of selected high-quality full papers will be invited after the conference to submit revised and extended versions of their originally accepted conference papers to this Special Issue of Computers, published by MDPI, in open access format. The selection of these papers will be based on their ratings in the conference review process, the quality of the presentation during the conference, and the expected impact on the research community. Each submission to this Special Issue should contain at least 50% new material, e.g., in the form of technical extensions, more in-depth evaluations, or additional use cases and a change in the title, abstract, and keywords. These extended submissions will undergo a peer-review process according to the journal’s rules of action. At least two technical committees will act as reviewers for each extended article submitted to this Special Issue; if needed, additional external reviewers will be invited to guarantee a high-quality reviewing process.

We also encourage original research work related to the topic of computer science. Topics of interest to this Special Issue include, but are not limited to, the following subjects:

  • High-Performance Computing and Networks Parallel and Distributed Computing:
    • Cluster Computing;
    • Supercomputing;
    • Cloud Computing;
    • Autonomic Computing;
    • P2P Computing;
    • Mobile Computing;
    • Grid and Semantic Grid Computing;
    • Workflow Design and Practice;
    • Computer and Network Architecture.
  • Geometric Modelling, Graphics and Visualization:
    • Scientific Visualization;
    • Computer Graphics;
    • Geometric Modelling;
    • Pattern Recognition;
    • Image Processing;
    • CAD/CAM;
    • Web3D, Virtual and Augmented Reality.
  • Information Systems and Technologies:
    • Information Retrieval;
    • Scientific Databases;
    • Security Engineering;
    • Risk Analysis;
    • Reliability Engineering;
    • Software Engineering;
    • Data Mining;
    • Artificial Intelligence;
    • Machine Learning;
    • Learning Technologies;
    • Web-Based Computing;
    • Web 2.0;

Dr. Osvaldo Gervasi
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Computers is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • high-performance computing and networks parallel and distributed computing
  • geometric modelling, graphics and visualization
  • information systems and technologies

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Published Papers (2 papers)

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Research

25 pages, 1610 KiB  
Article
A Novel End-to-End Provenance System for Predictive Maintenance: A Case Study for Industrial Machinery Predictive Maintenance
by Emrullah Gultekin and Mehmet S. Aktas
Computers 2024, 13(12), 325; https://doi.org/10.3390/computers13120325 - 4 Dec 2024
Viewed by 377
Abstract
In this study, we address the critical gap in predictive maintenance systems regarding the absence of a robust provenance system and specification. To tackle this issue, we propose a provenance system based on the PROV-O schema, designed to enhance explainability, accountability, and transparency [...] Read more.
In this study, we address the critical gap in predictive maintenance systems regarding the absence of a robust provenance system and specification. To tackle this issue, we propose a provenance system based on the PROV-O schema, designed to enhance explainability, accountability, and transparency in predictive maintenance processes. Our framework facilitates the collection, processing, recording, and visualization of provenance data, integrating them seamlessly into these systems. We developed a prototype to evaluate the effectiveness of our approach and conducted comprehensive user studies to assess the system’s usability. Participants found the extended PROV-O structure valuable, with improved task completion times. Furthermore, performance tests demonstrated that our system manages high workloads efficiently, with minimal overhead. The contributions of this study include the design of a provenance system tailored for predictive maintenance and a specification that ensures scalability and efficiency. Full article
(This article belongs to the Special Issue Computational Science and Its Applications 2024 (ICCSA 2024))
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28 pages, 44234 KiB  
Article
Exploring Park and Ride: A Spatial Analysis of Transit Catchment in Outer Melbourne
by Yanlin Chen, Kiki Adhinugraha, Shiyang Lyu and David Taniar
Computers 2024, 13(11), 299; https://doi.org/10.3390/computers13110299 - 18 Nov 2024
Viewed by 561
Abstract
Public transportation is essential for improving urban mobility, enhancing travel quality, reducing reliance on private vehicles, and alleviating traffic congestion. However, inadequate public transportation in outer Melbourne is a significant issue limiting urban development. While existing research primarily focuses on walking distance to [...] Read more.
Public transportation is essential for improving urban mobility, enhancing travel quality, reducing reliance on private vehicles, and alleviating traffic congestion. However, inadequate public transportation in outer Melbourne is a significant issue limiting urban development. While existing research primarily focuses on walking distance to define service catchments, commuters in transit-disadvantaged or outlying urban areas often drive to transit, noted as the park-and-ride mode. This research uniquely examines drive-distance catchments for park-and-ride transit accessibility in outer Melbourne, using spatial SQL and GIS techniques to provide a detailed, multi-dimensional analysis of population coverage, parking capacity, and accessibility gaps. This approach fills a gap in the existing literature by offering adaptable insights and approaches to other outer urban areas with transit disadvantages. The findings underscore the necessity for targeted enhancements in public transportation in outer Melbourne: Most of the outer residents concentrate near the train stations, though significant spatial gaps exist; The general accessibility status of residential mesh blocks is found; Parking capacity varies with high tension found at certain stations. This study contributes insights to create more equitable and sustainable transportation systems by providing a detailed spatial analysis of current transit coverage and identifying critical gaps. Full article
(This article belongs to the Special Issue Computational Science and Its Applications 2024 (ICCSA 2024))
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