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Advanced Technologies and Applications in Computer Science and Engineering: 2nd...
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Advanced Technologies and Applications in Computer Science and Engineering: 2nd Edition

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

Deadline for manuscript submissions: 31 December 2025 | Viewed by 3246

Special Issue Editors

Dr. Nikolay Hinov

E-Mail Website
Guest Editor
Faculty of Computer Systems and Technologies, Department of Computer Systems, Technical University in Sofia, 8 Ohridski Blvd., 1000 Sofia, Bulgaria
Interests: artificial intelligence; mathematical modeling; control theory and applications; smart cities and smart grids
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Ognyan Nakov

E-Mail Website
Guest Editor
Faculty of Computer Systems and Technologies, Technical University of Sofia, 1000 Sofia, Bulgaria
Interests: software engineering; software technologies and application systems; cloud technologies; internet of things; smart cities; cybersecurity; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Milena Lazarova

E-Mail Website
Guest Editor
Depаrtment “Computer systems”, Faculty of Computer Systems and Technologies, Technical Unversity of Sofia, Kliment Ohridski Blvd. 8, 1000 Sofia, Bulgaria
Interests: artificial intelligence; machine learning and deep learning; neural networks; pattern recognition; image analysis; optimization algorithms; metaheuristics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Computer science is one of the fastest-growing branches of engineering. This is due both to the increased capabilities and accessibility of the hardware, and to the successful implementation of modern information and communication technologies. Achievements in the fields of artificial intelligence, big data, cloud technologies, modeling, and computational mathematics are notable. In this respect, there is no other field of science that contributes so directly to improving the quality of life of modern society. Intelligent medicine, virtual and augmented reality, smart networks and cities, autonomous cars, digital factories and production, and many other achievements of modern civilization are the product of progress in the field of computer science.

The 2024 12th International Scientific Conference COMPUTER SCIENCE (COMSCI 2024) organized by the Faculty of Computer Systems and Technologies continues the tradition of a series of eleven conferences organized between 2004 and 2023 as a scientific forum to present a discussion of innovative ideas, concepts, and technologies in the field of computer science, computer and software engineering, information technology, and their application. Participation in the conference by researchers from different countries stimulates the building of a scientific community and encourages interaction and international cooperation.

This Special Issue primarily represents a collection of extended versions of selected papers presented at the 2024 12th International Scientific Conference COMPUTER SCIENCE (COMSCI 2024). However, papers not presented at the COMSCI 2024 are also welcome. We invite you to contribute original research articles or comprehensive review papers to this Special Issue. The topics of interest include, but are not limited to, the following:

  • Artificial intelligence, robotics, and control;
  • Cyber security and cyber protection;
  • Data structures and storage;
  • Cloud and blockchain technologies;
  • Electric and autonomous vehicles;
  • High technology management;
  • Human-centered computing;
  • Renewable and green energy;
  • Smart cities and smart society;
  • Software engineering;
  • Software technologies and applications systems;
  • Telecommunications engineering.

Dr. Nikolay Hinov
Prof. Dr. Ognyan Nakov
Prof. Dr. Milena Lazarova
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

  • artificial intelligence, robotics and control
  • cyber security and cyber protection
  • data structures and storage
  • cloud and blockchain technologies
  • electric and autonomous vehicles
  • smart cities and smart society
  • software engineering
  • software technologies and applications systems
  • human-centered computing
  • renewable and green energy
  • telecommunications engineering

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

Related Special Issue

Published Papers (2 papers)

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Research

20 pages, 26851 KiB  
Article
Precise Position Estimation of Road Users by Extracting Object-Specific Key Points for Embedded Edge Cameras
by Gahyun Kim, Ju Hee Yoo, Ho Gi Jung and Jae Kyu Suhr
Electronics 2025, 14(7), 1291; https://doi.org/10.3390/electronics14071291 - 25 Mar 2025
Viewed by 247
Abstract
Detecting road users and estimating accurate positions are significant in intelligent transportation systems (ITS). Most monocular camera-based systems for this purpose use 2D bounding box detectors to obtain real-time operability. However, this approach has the drawback of causing large positioning errors due to [...] Read more.
Detecting road users and estimating accurate positions are significant in intelligent transportation systems (ITS). Most monocular camera-based systems for this purpose use 2D bounding box detectors to obtain real-time operability. However, this approach has the drawback of causing large positioning errors due to the use of upright rectangles for every type of object. To overcome this shortcoming, this paper proposes a method that improves the positioning accuracy of road users by modifying a conventional 2D bounding box detector to extract one or two additional object-specific key points. Since these key points are where the road users contact the ground plane, their accurate positions can be estimated based on the relation between the ground plane on the image and that on the map. The proposed method handles four types of road users: cars, pedestrians, cyclists (including motorcyclists), and e-scooter riders. This method is easy to implement by only adding extra heads to the conventional object detector and improves the positioning accuracy with a negligible amount of additional computational cost. In experiments, the proposed method was evaluated under various practical situations and showed a 66.5% improvement in road user position estimation. Furthermore, this method was simplified based on channel pruning and embedded on the edge camera with a Qualcomm QCS 610 System on Chip (SoC) to show its real-time capability. Full article
(This article belongs to the Special Issue Advanced Technologies and Applications in Computer Science and Engineering: 2nd Edition)
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24 pages, 2751 KiB  
Article
Course Success Prediction and Early Identification of At-Risk Students Using Explainable Artificial Intelligence
by Berat Ujkani, Daniela Minkovska and Nikolay Hinov
Electronics 2024, 13(21), 4157; https://doi.org/10.3390/electronics13214157 - 23 Oct 2024
Cited by 2 | Viewed by 2342
Abstract
Artificial Intelligence (AI) is increasingly used in online education platforms to provide valuable insights into students’ performance and success. However, the complexity of AI models makes it challenging for educators to interpret the specific factors that influence whether a student is going to [...] Read more.
Artificial Intelligence (AI) is increasingly used in online education platforms to provide valuable insights into students’ performance and success. However, the complexity of AI models makes it challenging for educators to interpret the specific factors that influence whether a student is going to pass or fail. Utilizing the Open University Learning Analytics Dataset (OULAD), this study employs various machine learning and deep learning techniques for predicting students’ success, along with SHapley Additive exPlanations (SHAP) as an Explainable Artificial Intelligence (XAI) technique, to understand the key factors behind success or failure. Unlike traditional statistical methods that explore variable relationships, this AI-driven approach uses advanced deep learning techniques to identify patterns and insights, allowing for a better understanding of the factors influencing student success. Additionally, this study focuses on identifying students at risk of failure using XAI techniques, specifically SHAP, to interpret model outputs by breaking down how specific factors contribute to a student’s success. This method enables targeted interventions to support their success. Results reveal that student engagement and registration timelines are critical factors affecting performance. The customized models achieve up to 94% accuracy for the designed tasks, outperforming traditional approaches. This study contributes to the use of AI in education and offers practical insights not only for educators but also for administrators and policymakers to enhance the quality and effectiveness of online learning. Full article
(This article belongs to the Special Issue Advanced Technologies and Applications in Computer Science and Engineering: 2nd Edition)
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