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Future Information & Communication Engineering 2025

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 2105

Special Issue Editors


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Guest Editor
Department of Electrical, Electronic and Control Engineering, Hankyong National University, Anseong 17579, Republic of Korea
Interests: compact modeling for circuit simulation; device modeling for TCAD simulation; device characterization; steep-switching device; GAA NW-FET; 2D material transistor; neuromorphic device
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
Department of Computer Engineering, Catholic University of Pusan, Busan 46252, Republic of Korea
Interests: security in network; convergence and operating system
Special Issues, Collections and Topics in MDPI journals

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Guest Editor Assistant
School of IT Convergence, University of Ulsan, Ulsan 44610, Republic of Korea
Interests: virtual reality; social presence; user experience; pose estimation; computer vision; deep neural network

Special Issue Information

Dear Colleagues,

This Special Issue will comprise selected papers from The 17th International Conference on Future Information & Communication Engineering (ICFICE 2025), which was held at the Hotel Nikko Guam, USA on 1st–4th July 2025.

Following ICFICE 2025, we will organize a Special Issue, soliciting original research papers on all of the technical aspects of computer science, information, and communication engineering. Potential topics include, but are not limited to, the following:

  • Communication systems and applications;
  • Networking and services;
  • AI and intelligent information systems;
  • Multimedia and digital convergence;
  • Semiconductor and communication services;
  • Biomedical imaging and engineering;
  • Ubiquitous sensor networks;
  • Database and internet applications;
  • IoT and Big Data;
  • IT convergence technology.

Prof. Dr. Yun Seop Yu
Prof. Dr. Daesung Lee
Prof. Dr. Jun-Ho Huh
Guest Editors

Dr. Dae-hwan Kim
Guest Editor Assistant

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 250 words) can be sent to the Editorial Office for assessment.

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. Applied Sciences 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

  • communication systems
  • networking
  • smart security
  • intelligent information systems
  • artificial intelligence
  • machine learning
  • biomedical imaging
  • multimedia and digital convergence
  • semiconductors
  • ubiquitous sensor networks
  • database
  • internet application
  • big data
  • Internet of Things (IoT)
  • Information Technology (IT) convergence
  • Augmented Reality (AR)/Virtual Reality (VR)
  • metaverse

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Published Papers (2 papers)

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Research

17 pages, 2079 KB  
Article
AI-Powered Fertility Insights: An Automated Human Sperm Analysis via Deep Learning
by Son The Trinh, Nhat Ngoc Nguyen, Thanh Quoc Trinh and Viet Trinh
Appl. Sci. 2026, 16(2), 1067; https://doi.org/10.3390/app16021067 - 20 Jan 2026
Viewed by 831
Abstract
This paper presents a semi-autonomous AI-based platform designed for the efficient management and quantitative analysis of human spermatozoa. Addressing the limitations of manual semen analysis, this system integrates advanced image processing and analytical techniques to offer a high-throughput diagnostic solution. During operation, the [...] Read more.
This paper presents a semi-autonomous AI-based platform designed for the efficient management and quantitative analysis of human spermatozoa. Addressing the limitations of manual semen analysis, this system integrates advanced image processing and analytical techniques to offer a high-throughput diagnostic solution. During operation, the proposed system autonomously performs a precise quantitative assessment of sperm concentration, accurately tracks individual sperm motility patterns, and systematically classifies morphological abnormalities. The result is a comprehensive sperm analysis report, meticulously generated according to the latest established World Health Organization (WHO) guidelines for concentration, motility, and morphology. A distinguishing feature of this system is the ability to yield reliable preliminary results even with minimally pre-processed clinical samples, thereby enhancing diagnostic objectivity, efficiency, and reliability in male reproductive health assessments. Full article
(This article belongs to the Special Issue Future Information & Communication Engineering 2025)
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22 pages, 3852 KB  
Article
Improved Attendance Tracking System for Coffee Farm Workers Applying Computer Vision
by Hong-Danh Thai, YuanYuan Liu, Ngoc-Bao-Van Le, Daesung Lee and Jun-Ho Huh
Appl. Sci. 2026, 16(1), 319; https://doi.org/10.3390/app16010319 - 28 Dec 2025
Cited by 1 | Viewed by 747
Abstract
Agricultural mechanization and advanced technology have developed significantly in the coffee industry. However, there are still requirements for human laborers to operate, monitor crop health care, and manage production. The integration of advanced technology can significantly enhance the production efficiency and management practices [...] Read more.
Agricultural mechanization and advanced technology have developed significantly in the coffee industry. However, there are still requirements for human laborers to operate, monitor crop health care, and manage production. The integration of advanced technology can significantly enhance the production efficiency and management practices of agricultural enterprises. This paper aims to address these gaps by proposing and implementing a computer vision-based attendance tracking system on mobile platforms that are suitable for the requirements and limitations of agricultural enterprises. First, the face detection process involves interpreting and locating facial structure. Next, the model transforms a photographic image of a human face into digital data based on the unique features and facial structure. We utilize the InsightFace model with the buffalo_l variant, as well as ArcFace with a ResNet backbone, as a facial recognition algorithm. After capturing a facial image, the system conducts a matching process against the existing database to verify identity. Finally, we implement a mobile application prototype on both iOS and Android platforms, ensuring accessibility for farm workers. As a result, our system achieved 95.2% accuracy on the query set, with an average processing time of <200 ms per image (including face detection, embedding extraction, and database matching). The system performs real-time attendance monitoring, automatically recording the entry and exit times of farm workers using facial recognition technology, and enables quick registration of new workers. Our work is expected to enhance transparency and fairness in the human management process, focusing on the coffee farm use case. Full article
(This article belongs to the Special Issue Future Information & Communication Engineering 2025)
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