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Computers
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Computational Science and Its Applications 2024 (ICCSA 2024)
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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 5000

Special Issue Editor

Dr. Osvaldo Gervasi

E-Mail Website
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
Special Issues, Collections and Topics in MDPI journals

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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Further information on MDPI's Special Issue polices can be found here.

Published Papers (5 papers)

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Research

30 pages, 5494 KiB  
Article
The Right to the Night City: Exploring the Temporal Variability of the 15-min City in Milan and Its Implications for Nocturnal Communities
by Lamia Abdelfattah, Abubakr Albashir, Giulia Ceccarelli, Andrea Gorrini, Federico Messa and Dante Presicce
Computers 2025, 14(1), 22; https://doi.org/10.3390/computers14010022 - 11 Jan 2025
Viewed by 809
Abstract
The needs of night communities and the barriers they face in accessing diverse urban amenities are underexplored in urban planning research. Focus is primarily given to the needs of cultural consumers, frequently overlooking the challenges faced by regular nighttime communities, including night workers. [...] Read more.
The needs of night communities and the barriers they face in accessing diverse urban amenities are underexplored in urban planning research. Focus is primarily given to the needs of cultural consumers, frequently overlooking the challenges faced by regular nighttime communities, including night workers. Through a GIS-based analysis, the aim of this research is to shed light on differences in accessibility to core urban services between day and night in the city of Milan. The spatiotemporal analysis was performed using a customized version of the 15-min City Score Toolkit, an open-source, Python-based proprietary tool developed to automate the 15 min access metric estimation. Proprietary Point-Of-Interest (POI) data that were retrieved, sorted and filtered from the Google Places API are used to simulate time-variant walkability maps based on opening hour information contained in the dataset. The research reveals significant differences in walkability potential, both in spatial and temporal terms, and highlights gaps in nighttime service availability. The work presents an innovation on the 15 min city approach that highlights the impact of 24-h urban rhythms on real walkability outcomes. The quality limitations of the Google data are extensively explored in the article, providing further insight into the replicability and scalability of the methodology for future research. Full article
(This article belongs to the Special Issue Computational Science and Its Applications 2024 (ICCSA 2024))
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27 pages, 2436 KiB  
Article
Seeing the Sound: Multilingual Lip Sync for Real-Time Face-to-Face Translation
by Amirkia Rafiei Oskooei, Mehmet S. Aktaş and Mustafa Keleş
Computers 2025, 14(1), 7; https://doi.org/10.3390/computers14010007 - 28 Dec 2024
Viewed by 815
Abstract
Imagine a future where language is no longer a barrier to real-time conversations, enabling instant and lifelike communication across the globe. As cultural boundaries blur, the demand for seamless multilingual communication has become a critical technological challenge. This paper addresses the lack of [...] Read more.
Imagine a future where language is no longer a barrier to real-time conversations, enabling instant and lifelike communication across the globe. As cultural boundaries blur, the demand for seamless multilingual communication has become a critical technological challenge. This paper addresses the lack of robust solutions for real-time face-to-face translation, particularly for low-resource languages, by introducing a comprehensive framework that not only translates language but also replicates voice nuances and synchronized facial expressions. Our research tackles the primary challenge of achieving accurate lip synchronization across culturally diverse languages, filling a significant gap in the literature by evaluating the generalizability of lip sync models beyond English. Specifically, we develop a novel evaluation framework combining quantitative lip sync error metrics and qualitative assessments by human observers. This framework is applied to assess two state-of-the-art lip sync models with different architectures for Turkish, Persian, and Arabic languages, using a newly collected dataset. Based on these findings, we propose and implement a modular system that integrates language-agnostic lip sync models with neural networks to deliver a fully functional face-to-face translation experience. Inference Time Analysis shows this system achieves highly realistic, face-translated talking heads in real time, with a throughput as low as 0.381 s. This transformative framework is primed for deployment in immersive environments such as VR/AR, Metaverse ecosystems, and advanced video conferencing platforms. It offers substantial benefits to developers and businesses aiming to build next-generation multilingual communication systems for diverse applications. While this work focuses on three languages, its modular design allows scalability to additional languages. However, further testing in broader linguistic and cultural contexts is required to confirm its universal applicability, paving the way for a more interconnected and inclusive world where language ceases to hinder human connection. Full article
(This article belongs to the Special Issue Computational Science and Its Applications 2024 (ICCSA 2024))
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13 pages, 615 KiB  
Article
Wearable Sensor-Based Behavioral User Authentication Using a Hybrid Deep Learning Approach with Squeeze-and-Excitation Mechanism
by Sakorn Mekruksavanich and Anuchit Jitpattanakul
Computers 2024, 13(12), 337; https://doi.org/10.3390/computers13120337 - 14 Dec 2024
Viewed by 671
Abstract
Behavior-based user authentication has arisen as a viable method for strengthening cybersecurity in an age of pervasive wearable and mobile technologies. This research introduces an innovative approach for ongoing user authentication via behavioral biometrics obtained from wearable sensors. We present a hybrid deep [...] Read more.
Behavior-based user authentication has arisen as a viable method for strengthening cybersecurity in an age of pervasive wearable and mobile technologies. This research introduces an innovative approach for ongoing user authentication via behavioral biometrics obtained from wearable sensors. We present a hybrid deep learning network called SE-DeepConvNet, which integrates a squeeze-and-excitation (SE) method to proficiently simulate and authenticate user behavior characteristics. Our methodology utilizes data collected by wearable sensors, such as accelerometers, gyroscopes, and magnetometers, to obtain a thorough behavioral appearance. The suggested network design integrates convolutional neural networks for spatial feature extraction, while the SE blocks improve feature identification by flexibly recalibrating channel-wise feature responses. Experiments performed on two datasets, HMOG and USC-HAD, indicate the efficacy of our technique across different tasks. In the HMOG dataset, SE-DeepConvNet attains a minimal equal error rate (EER) of 0.38% and a maximum accuracy of 99.78% for the Read_Walk activity. Our model presents outstanding authentication (0% EER, 100% accuracy) for various walking activities in the USC-HAD dataset, encompassing intricate situations such as ascending and descending stairs. These findings markedly exceed existing deep learning techniques, demonstrating the promise of our technology for secure and inconspicuous continuous authentication in wearable devices. The suggested approach demonstrates the potential for use in individual device security, access management, and ongoing uniqueness verification in sensitive settings. Full article
(This article belongs to the Special Issue Computational Science and Its Applications 2024 (ICCSA 2024))
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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 696
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 871
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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