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MMSE-Based Power Control for Amplify-and-Forward Relay Systems in Time-Varying Channels
This study proposes a novel power control method for amplify-and-forward (AF) relay systems operating in time-varying channels. Transmit power control between the source and relay nodes significantly enhances the performance of the AF relay system, and the improvements are proportional to the number of antennas. However, these enhancements are restricted by the presence of time-varying channels, and this limitation increases in severity with increasing number of antennas. To address the challenges posed by these channel variations, the proposed method adaptively optimizes the power-scaling fac...
Journal of information and communication convergence engineering 2024; 22(4): 267-272
Mid-span Spectral Inversion System with Random Triangular Dispersion Maps
In dispersion-managed links with mid-span spectral inversion (MSSI) systems, the symmetry of the cumulative dispersion profile is important for compensating the distorted wavelength division multiplexing (WDM) signals. The triangular dispersion map has antipodal symmetry with respect to the midway optical phase conjugator (OPC). A triangular dispersion map is proposed in this paper that has a singularity in which the lengths of the optical fibers that contribute to forming the cumulative dispersion profile are determined randomly. We analyzed three types for randomly determining and deploying ...
Journal of information and communication convergence engineering 2024; 22(4): 273-279
Automatic Classification of Scientific and Technical Papers Using Large Language Models and Retrieval-Augmented Generation
This study proposes artificial intelligence (AI) technology for the automatic classification of Korean scientific and technical papers, aiming to achieve high accuracy even with a small amount of labeled data. Unlike existing BERT-based Korean document classification models that perform supervised learning based on a large amount of accurately labeled data, this study proposes a structure that utilize large language models (LLMs) and retrieval-augmented generation (RAG) technology. The proposed method experimentally demonstrates that it can achieve higher accuracy than existing technologies ac...
Journal of information and communication convergence engineering 2024; 22(4): 280-287
Enhancing Transformer-based Cooking Recipe Generation Models from Text Ingredients
Recipe generation is an important task in both research and real life. In this study, we explore several pretrained language models that generate recipes from a list of text-based ingredients. Our recipe-generation models use a standard self-attention mechanism in Transformer and integrate a re-attention mechanism in Vision Transformer. The models were trained using a common paradigm based on cross-entropy loss and the BRIO paradigm combining contrastive and cross-entropy losses to achieve the best performance faster and eliminate exposure bias. Specifically, we utilize a generation model to p...
Journal of information and communication convergence engineering 2024; 22(4): 288-295
Blockchain and IPFS-based IoT Massive Data-Management Model
The exponential growth of the Internet of Things has resulted in a substantial surge in the volume of data produced by numerous sensors and microcontroller devices. The objective of this study is to create a comprehensive data-management framework using blockchain and InterPlanetary File System with the aim of enhancing the security, dependability, and decentralized processing of large-scale data storage. This study utilizes a hyperledger blockchain and an interstellar file system to transmit data via ZigBee and Wi-Fi networks. In addition, edge devices are employed for pre-processing to guara...
Journal of information and communication convergence engineering 2024; 22(4): 296-302
Simple 1D CNN Model for Accurate Classification of Gait Patterns Using GRF Data
Gait analysis plays a pivotal role in clinical diagnostics and aids in the detection and evaluation of various disorders and disabilities. Traditional methods often rely on intricate video systems or pressure mats to assess gait. Previous studies have demonstrated the potential of artificial intelligence (AI) in gait analysis using techniques, such as convolutional neural networks (CNN) and long short-term memory (LSTM) networks. However, these methods often encounter challenges related to high dimensionality, temporal dependencies, and variability in gait patterns, making accurate and efficie...
Journal of information and communication convergence engineering 2024; 22(4): 303-309
Utilization of XGBoost for Behavior Analysis of Lottery Purchasers
In this study, we conducted a data-driven analysis of lottery purchase behavior by using the XGBoost algorithm to predict future lottery purchase amounts based on purchase patterns of the previous four weeks. We began by judiciously defining key features including the weekly average purchase amount and variance in purchase amount. Subsequently, we evaluated the proposed method’s performance, finding the predicted future purchase amounts to match the actual purchase amounts. A key strength of this study was the interpretability of feature variables. Through the feature importance score fr...
Journal of information and communication convergence engineering 2024; 22(4): 310-315
Mode Decomposition and Long-Term Solution Prediction for the Vlasov-Poisson Equation
The Vlasov-Poisson (VP) equation plays an important role in plasma physics. Most numerical methods for the VP equation are based on the finite difference method (FDM) or finite element method (FEM), where the computational costs are high. However, this study focuses on the efficient reconstruction of solutions to the VP equation. We begin by generating short-term solutions to the VP equation using an FDM-type algorithm. Among various versions of FDM schemes, we employ backward semi-Lagrangian-based methods with weighted, essentially non-oscillatory schemes for interpolation. Subsequently, a st...
Journal of information and communication convergence engineering 2024; 22(4): 316-321
The Impact of Backchannel in Medical-Questionnaire Robot on User Perception
Robot backchanneling is implemented using verbal expressions, such as reiterating after remembering the response of the user or chiming in with the user. We performed experiments to investigate how the backchannel behavior of the robot affects the user's perception of the robot's empathy and attentiveness toward their reported pain and sleep concerns. The results indicate that users prefer the robot that provides backchannel and perceive it as more intelligent. Where the robot backchanneled, the number of conversational turns between the user and the robot decreased compared to situations wher...
Journal of information and communication convergence engineering 2024; 22(4): 322-329
Development of a HUD-based Integrated Navigation Information System User Interface for Effective Autonomous Ship Navigation
Various AI-based digital navigation technologies, such as autonomous navigation, are being developed in the maritime shipping industry. It is necessary to effectively integrate the information provided individually by various navigation information systems installed on a ship and efficiently deliver it to navigators to realize the first stage of autonomous navigation, known as an onboard decision support ship. In this study, we developed a user interface for an HUD-based integrated navigation information system that supports navigators in performing navigation tasks safely and efficiently. Thr...
Journal of information and communication convergence engineering 2024; 22(4): 330-335
Computer-Vision-Based Mobile Application for Translating Sundanese Scripts to Modern Indonesian Language With Gamification Strategies
In the digital era, teaching endangered local languages and scripts to children has become challenging owing to the scarcity of learning media and materials. The present study addresses this problem through the development of a mobile application that classifies and automatically converts Sundanese scripts into Latin using computer vision algorithms. The proposed method represents an innovative solution for capturing children's interest using gamification strategies. We discuss the development, implementation, and evaluation of YOLOv8, a deep learning technology for computer vision in mobile a...
Journal of information and communication convergence engineering 2024; 22(4): 336-343

Current Issue Volume 22, Number 4, December 2024

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About JICCE

Background

It has been published since 2003 with a title of International Journal of Maritime Information and Communication Sciences. In 2012, this journal was greatly reformed to further improve the quality of journal, for example, title, research areas and policy of journal etc. The title was changed from the year of 2012 as Journal of Information and Communication Convergence Engineering.

Aims and Scope

Journal of Information and Communication Convergence Engineering (J. Inf. Commun. Converg. Eng., JICCE) is an official English journal of the Korea Institute of Information and Communication Engineering (KIICE). It is an international, peer reviewed, and open access journal that is published quarterly in March, June, September, and December. Its objective is to provide rapid publications of original and significant contributions and it covers all areas related to information and communication convergence engineering including the following areas: communication system and applications, networking and services, intelligent information system, multimedia and digital convergence, semiconductors and communication devices, imaging and biomedical engineering, and computer vision and autonomous vehicles.

Journal of Information and Communication Convergence Engineering Jouranl of information and
communication convergence engineering
(J. Inf. Commun. Converg. Eng.)

eISSN 2234-8883
pISSN 2234-8255