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Electronics
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Advanced Research in Technology and Information Systems, 2nd Edition
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Advanced Research in Technology and Information Systems, 2nd Edition

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 30 September 2025 | Viewed by 4084

Special Issue Editors

Prof. Dr. Vasile-Daniel Pavaloaia

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Guest Editor
Department of Accounting, Business Information Systems and Statistics, Alexandru Ioan Cuza University of Iasi, 700506 Iași, Romania
Interests: neural networks; machine learning; deep learning; sentiment analysis; IoT systems; information systems for management; enterprise resource planning
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Rodrigo Martin-Rojas

E-Mail Website
Guest Editor
Department of Management, Faculty of Education, Economics and Technology, University of Granada, 51001 Ceuta, Spain
Interests: IoT; information systems; innovation; quantitative research
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Piotr Sulikowski

E-Mail Website
Guest Editor
Customer Intelligence Research Group，West Pomeranian University of Technology, 70-311 Szczecin, Poland
Interests: IT in business; AI; R&D; human-computer interaction; management; e-commerce; marketing; R&D tax incentives; new business consulting; leadership; private and public funding
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The domains of Information Systems and Technology are constantly growing, providing a plethora of research topics as well as multiple career opportunities. Information Systems serve as the nexus of technology, processes, and people, and foster innovations in various domains throughout a wide variety of subjects for research such as Databases, Artificial Intelligence (NLP, Deep Learning, Machine Learning) Programming, and Information Systems Analysis and Design. The recent technological advancements and Internet infrastructure bring benefits to worldwide communities through smart cities, smart governance, and smart education, and increase the emergence of IoT and “smart” capabilities of electronic sensors.

This Special Issue of the Electronics journal, entitled Advanced Research in Technology and Information Systems, aims to unite in a single volume the most recent discoveries in the form of original research manuscripts and reviews on relevant subjects for this collection. The implications related to technology and Information Systems in higher education curricula are also welcome in this SI. Therefore, the topics of interest for this Special Issue can include, but are not limited to:

  • Information Systems: analysis, design, and developments;
  • Information Systems—as a study discipline—higher education curricula challenges;
  • Artificial Intelligence Applications;
  • Natural Language Processing;
  • Human–computer interaction;
  • Electronic commerce;
  • Machine learning techniques for intelligent software development;
  • Artificial Neural Networks applications;
  • Big Data applications;
  • Intelligent electronic solutions for future applications;
  • IoT implementations;
  • Smart government, smart education, smart cities, smart electronics, and smart offices;
  • Advanced features of power systems.

Prof. Dr. Vasile-Daniel Pavaloaia
Prof. Dr. Rodrigo Martin-Rojas
Prof. Dr. Piotr Sulikowski
Guest Editors

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. Electronics is an international peer-reviewed open access semimonthly 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 2400 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

  • IoT
  • information systems
  • human–computer interaction
  • big data applications
  • artificial intelligence applications

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

Related Special Issue

Published Papers (6 papers)

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Research

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12 pages, 842 KB  
Article
Preliminary Study on Heart Rate Response to Physical Activity Using a Wearable ECG and 3-Axis Accelerometer Under Free-Living Conditions
by Emi Yuda and Junichiro Hayano
Electronics 2025, 14(18), 3688; https://doi.org/10.3390/electronics14183688 (registering DOI) - 18 Sep 2025
Abstract
Recent advances in wearable sensing technology have enabled simultaneous measurement of heart activity and body movement using devices equipped with both ECG recording and 3-axis accelerometers. This study examined whether transient heart rate (HR) responses to physical activity can be accurately characterized under [...] Read more.
Recent advances in wearable sensing technology have enabled simultaneous measurement of heart activity and body movement using devices equipped with both ECG recording and 3-axis accelerometers. This study examined whether transient heart rate (HR) responses to physical activity can be accurately characterized under free-living conditions. Continuous RR interval data and activity levels derived from accelerometer signals were analyzed using a multivariate autoregressive (MVAR) model. Results from 12 male participants showed a strong correlation between predicted and observed HR responses (r2 = 0.93, r = 0.96, p < 0.001). These findings indicate that up to 93% of transient HR dynamics associated with daily physical activity can be explained by the model. While these results are preliminary due to the limited sample size, the approach provides a promising framework for the noninvasive, continuous monitoring of cardiovascular responses in everyday health and wellness applications. Full article
(This article belongs to the Special Issue Advanced Research in Technology and Information Systems, 2nd Edition)
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23 pages, 2044 KB  
Article
PAGURI: A User Experience Study of Creative Interaction with Text-to-Music Models
by Francesca Ronchini, Luca Comanducci, Gabriele Perego and Fabio Antonacci
Electronics 2025, 14(17), 3379; https://doi.org/10.3390/electronics14173379 - 25 Aug 2025
Viewed by 469
Abstract
In recent years, text-to-music models have been the biggest breakthrough in automatic music generation. While they are unquestionably a showcase of technological progress, it is not clear yet how they can be realistically integrated into the artistic practice of musicians and music practitioners. [...] Read more.
In recent years, text-to-music models have been the biggest breakthrough in automatic music generation. While they are unquestionably a showcase of technological progress, it is not clear yet how they can be realistically integrated into the artistic practice of musicians and music practitioners. This paper aims to address this question via Prompt Audio Generation User Research Investigation (PAGURI), a user experience study where we leverage recent text-to-music developments to study how musicians and practitioners interact with these systems, evaluating their satisfaction levels. We developed an online tool through which users can generate music samples and/or apply recently proposed personalization techniques based on fine-tuning to allow the text-to-music model to generate sounds closer to their needs and preferences. Using semi-structured interviews, we analyzed different aspects related to how participants interacted with the proposed tool to understand the current effectiveness and limitations of text-to-music models in enhancing users’ creativity. Our research centers on user experiences to uncover insights that can guide the future development of TTM models and their role in AI-driven music creation. Additionally, they offered insightful perspectives on potential system improvements and their integration into their music practices. The results obtained through the study reveal the pros and cons of the use of TTMs for creative endeavors. Participants recognized the system’s creative potential and appreciated the usefulness of its personalization features. However, they also identified several challenges that must be addressed before TTMs are ready for real-world music creation, particularly issues of prompt ambiguity, limited controllability, and integration into existing workflows. Full article
(This article belongs to the Special Issue Advanced Research in Technology and Information Systems, 2nd Edition)
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28 pages, 781 KB  
Article
Unlinkable Revocation Lists for Qualified Electronic Attestations: A Blockchain-Based Framework
by Emil Bureacă, Răzvan-Andrei Leancă, Ionuț Ciobanu, Andrei Brînzea and Iulian Aciobăniței
Electronics 2025, 14(14), 2795; https://doi.org/10.3390/electronics14142795 - 11 Jul 2025
Viewed by 1227
Abstract
The use of Verifiable Credentials under the new eIDAS Regulation introduces privacy concerns, particularly during revocation status checks. This paper proposes a privacy-preserving revocation mechanism tailored to the European Digital Identity Wallet and its Architecture and Reference Framework. Our method publishes a daily [...] Read more.
The use of Verifiable Credentials under the new eIDAS Regulation introduces privacy concerns, particularly during revocation status checks. This paper proposes a privacy-preserving revocation mechanism tailored to the European Digital Identity Wallet and its Architecture and Reference Framework. Our method publishes a daily randomized revocation list as a cascaded Bloom filter, enhancing unlinkability by randomizing revocation indexes derived from ARF guidelines. The implementation extends open-source components developed by the European Committee. This work demonstrates a practical, privacy-centric approach to revocation in digital identity systems, supporting the advancement of privacy-preserving technologies. Full article
(This article belongs to the Special Issue Advanced Research in Technology and Information Systems, 2nd Edition)
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21 pages, 2734 KB  
Article
Quantifying Cyber Resilience: A Framework Based on Availability Metrics and AUC-Based Normalization
by Harksu Cho, Ji-Hyun Sung, Hye-Jin Kang, Jisoo Jang and Dongkyoo Shin
Electronics 2025, 14(12), 2465; https://doi.org/10.3390/electronics14122465 - 17 Jun 2025
Viewed by 1008
Abstract
This study presents a metric selection framework and a normalization method for the quantitative assessment of cyber resilience, with a specific focus on availability as a core dimension. To develop a generalizable evaluation model, service types from 1124 organizations were categorized, and candidate [...] Read more.
This study presents a metric selection framework and a normalization method for the quantitative assessment of cyber resilience, with a specific focus on availability as a core dimension. To develop a generalizable evaluation model, service types from 1124 organizations were categorized, and candidate metrics applicable across diverse operational environments were identified. Ten quantitative metrics were derived based on five core selection criteria—objectivity, reproducibility, scalability, practicality, and relevance to resilience—while adhering to the principles of mutual exclusivity and collective exhaustiveness. To validate the framework, two availability-oriented metrics—Transactions per Second (TPS) and Connections per Second (CPS)—were empirically evaluated in a simulated denial-of-service environment using a TCP SYN flood attack scenario. The experiment included three phases: normal operation, attack, and recovery. An Area Under the Curve (AUC)-based Normalized Resilience Index (NRI) was introduced to quantify performance degradation and recovery, using each organization’s Recovery Time Objective (RTO) as a reference baseline. This approach facilitates objective, interpretable comparisons of resilience performance across systems with varying service conditions. The findings demonstrate the practical applicability of the proposed metrics and normalization technique for evaluating cyber resilience and underscore their potential in informing resilience policy development, operational benchmarking, and technical decision-making. Full article
(This article belongs to the Special Issue Advanced Research in Technology and Information Systems, 2nd Edition)
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25 pages, 2726 KB  
Article
Requirements Engineering Approach for Data Ownership Concepts
by Jad Asswad, Viktor Dmitriyev, Maria Edith Elizondo Guerrero, Cedrik Theesen and Julia Köhlke
Electronics 2025, 14(7), 1288; https://doi.org/10.3390/electronics14071288 - 25 Mar 2025
Viewed by 618
Abstract
In recent years, the growing importance of data ownership has attracted significant attention, reflecting not only its pivotal role in the evolving data-driven environment but also the complexity of addressing it across diverse contexts. The necessity of developing effective data ownership concepts for [...] Read more.
In recent years, the growing importance of data ownership has attracted significant attention, reflecting not only its pivotal role in the evolving data-driven environment but also the complexity of addressing it across diverse contexts. The necessity of developing effective data ownership concepts for data platforms is indisputable; nevertheless, the process is inherently complex and demands a comprehensive examination of the requirements surrounding this multifaceted issue. This paper puts forward a novel approach to the development of data ownership concepts, which draws on principles from requirements engineering (RE). The efficacy of this approach is evaluated through in-depth case-studies focusing on three distinct contexts: the development of a data ownership concept within the realm of smart meters, smart livestock farming, and data spaces for energy. Through the application of RE principles, this work strives to provide a structured and effective approach for addressing the nuanced challenges associated with data ownership in the process of developing data ownership concepts for data-driven platforms and applications. Full article
(This article belongs to the Special Issue Advanced Research in Technology and Information Systems, 2nd Edition)
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Review

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13 pages, 333 KB  
Review
Scaling Entity Resolution with K-Means: A Review of Partitioning Techniques
by Dimitrios Karapiperis and Vassilios S. Verykios
Electronics 2025, 14(18), 3605; https://doi.org/10.3390/electronics14183605 - 11 Sep 2025
Viewed by 183
Abstract
Entity resolution (ER) is a fundamental data integration process hindered by its quadratic computational complexity, making naive comparisons infeasible for large datasets. Blocking (or partitioning) is the foundational strategy to overcome this, traditionally using methods like K-Means clustering to group similar records. However, [...] Read more.
Entity resolution (ER) is a fundamental data integration process hindered by its quadratic computational complexity, making naive comparisons infeasible for large datasets. Blocking (or partitioning) is the foundational strategy to overcome this, traditionally using methods like K-Means clustering to group similar records. However, with the rise of deep learning and high-dimensional vector embeddings, the ER task has evolved into a vector similarity search problem. This review traces the evolution of K-Means from a direct, standalone blocking algorithm into a core partitioning engine within modern Approximate Nearest Neighbor (ANN) indexes. We analyze how its role has been adapted and optimized in partition-based systems like the Inverted File (IVF) system and Google’s SCANN, which are now central to scalable, embedding-based ER. By examining the architectural principles and trade-offs of these methods and contrasting them with non-partitioning alternatives like HNSW, this paper provides a coherent narrative on the journey of K-Means from a simple clustering tool to a critical component for scaling modern ER workflows. Full article
(This article belongs to the Special Issue Advanced Research in Technology and Information Systems, 2nd Edition)
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