Jongtae Rhee
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View article: Development and Evaluation of an Immersive Metaverse-Based Meditation System for Psychological Well-Being Using LLM-Driven Scenario Generation
Development and Evaluation of an Immersive Metaverse-Based Meditation System for Psychological Well-Being Using LLM-Driven Scenario Generation Open
The increasing prevalence of mental health disorders highlights the need for innovative and accessible interventions. Although existing digital meditation applications offer valuable basic guidance, they often lack interactivity, real-time…
View article: EmoBERTa–CNN: Hybrid Deep Learning Approach Capturing Global Semantics and Local Features for Enhanced Emotion Recognition in Conversational Settings
EmoBERTa–CNN: Hybrid Deep Learning Approach Capturing Global Semantics and Local Features for Enhanced Emotion Recognition in Conversational Settings Open
Emotion recognition in conversations is a key task in natural language processing that enhances the quality of human–computer interactions. Although existing deep learning and Transformer-based pretrained language models have shown remarka…
View article: Margin and Shared Proxies: Advanced Proxy Anchor Loss for Out-of-Domain Intent Classification
Margin and Shared Proxies: Advanced Proxy Anchor Loss for Out-of-Domain Intent Classification Open
Out-of-Domain (OOD) intent classification is an important task for a dialog system, as it allows for appropriate responses to be generated. Previous studies aiming to solve the OOD intent classification task have generally adopted metric l…
View article: Multi-View Masked Autoencoder for General Image Representation
Multi-View Masked Autoencoder for General Image Representation Open
Self-supervised learning is a method that learns general representation from unlabeled data. Masked image modeling (MIM), one of the generative self-supervised learning methods, has drawn attention for showing state-of-the-art performance …
View article: Diffusion-Denoising Process with Gated U-Net for High-Quality Document Binarization
Diffusion-Denoising Process with Gated U-Net for High-Quality Document Binarization Open
The binarization of degraded documents represents a crucial preprocessing task for various document analyses, including optical character recognition and historical document analysis. Various convolutional neural network models and generat…
View article: Multi-view Masked Autoencoder for General Image Representation
Multi-view Masked Autoencoder for General Image Representation Open
Self-supervised learning is a method that learns general representation from unlabeled data. Masked image modeling (MIM), one of the generative self-supervised learning methods, has drawn attention showing state-of-the-art performance on v…
View article: 3D Position Estimation of Objects for Inventory Management Automation Using Drones
3D Position Estimation of Objects for Inventory Management Automation Using Drones Open
With the recent development of drone technology, drones are being used in various fields. Drones have the advantage of being equipped with various devices to move freely and perform various tasks. In the field of inventory management, many…
View article: Diffusion Denoising Process with Gated U-Net for High-Quality Document Binarization
Diffusion Denoising Process with Gated U-Net for High-Quality Document Binarization Open
Binarization of degraded documents is an important preprocessing task for various document analysis such as OCR and historical document analysis. Existing studies have applied various convolutional neural network (CNN) models and generativ…
View article: Performance Analysis and Assessment of Type 2 Diabetes Screening Scores in Patients with Non-Alcoholic Fatty Liver Disease
Performance Analysis and Assessment of Type 2 Diabetes Screening Scores in Patients with Non-Alcoholic Fatty Liver Disease Open
Type 2 diabetes (T2D) and non-alcoholic fatty liver disease (NAFLD) are worldwide chronic diseases that have strong relationships with one another and commonly exist together. Type 2 diabetes is considered one of the risk factors for NAFLD…
View article: Utilizing deep neural network for web-based blood glucose level prediction system
Utilizing deep neural network for web-based blood glucose level prediction system Open
Machine learning algorithms can be used to forecast future blood glucose (BG) levels for diabetes patients, according to recent studies. In this study, dataset from continuous glucose monitoring (CGM) system was used as the sole input for …
View article: A Study on Model of Psychotherapy Narration Focused on Mental Well-Being for Stress Management in the Elderly
A Study on Model of Psychotherapy Narration Focused on Mental Well-Being for Stress Management in the Elderly Open
Psychological well-being is vitally important for the quality of life of the elderly and is only increasing in importance with the rapidly increasing elderly population worldwide. Emerging elderly problems include a deterioration in physic…
View article: A Study on Emotions to Improve the Quality of Life of South Korean Senior Patients Residing in Convalescent Hospitals
A Study on Emotions to Improve the Quality of Life of South Korean Senior Patients Residing in Convalescent Hospitals Open
This study examined the occurrence of emotion types and the contents and meanings of individual emotion types to improve the quality of life of South Korean senior patients in convalescent hospitals. This research is a sequential mixed stu…
View article: Mixup Based Cross-Consistency Training for Named Entity Recognition
Mixup Based Cross-Consistency Training for Named Entity Recognition Open
Named Entity Recognition (NER) is at the core of natural language understanding. The quality and amount of datasets determine the performance of deep-learning-based NER models. As datasets for NER require token-level or word-level labels t…
View article: Predicting Breast Cancer from Risk Factors Using SVM and Extra-Trees-Based Feature Selection Method
Predicting Breast Cancer from Risk Factors Using SVM and Extra-Trees-Based Feature Selection Method Open
Developing a prediction model from risk factors can provide an efficient method to recognize breast cancer. Machine learning (ML) algorithms have been applied to increase the efficiency of diagnosis at the early stage. This paper studies a…
View article: Investigation of UHF Signal Strength Propagation at Warehouse Management Applications Based on Drones and RFID Technology Utilization
Investigation of UHF Signal Strength Propagation at Warehouse Management Applications Based on Drones and RFID Technology Utilization Open
As a part of the supply chain, inventory management includes, among other things, maintaining the storage of stock, controlling the amount of product for sale and order fulfilment. In business terms, inventory management means the right st…
View article: A Methodology for Utilizing Vector Space to Improve the Performance of a Dog Face Identification Model
A Methodology for Utilizing Vector Space to Improve the Performance of a Dog Face Identification Model Open
Recent improvements in the performance of the human face recognition model have led to the development of relevant products and services. However, research in the similar field of animal face identification has remained relatively limited …
View article: Pesticides in Drinking Water—A Review
Pesticides in Drinking Water—A Review Open
The ubiquitous problem of pesticide in aquatic environment are receiving worldwide concern as pesticide tends to accumulate in the body of the aquatic organism and sediment soil, posing health risks to the human. Many pesticide formulation…
View article: Deep Neural Network for Predicting Diabetic Retinopathy from Risk Factors
Deep Neural Network for Predicting Diabetic Retinopathy from Risk Factors Open
Extracting information from individual risk factors provides an effective way to identify diabetes risk and associated complications, such as retinopathy, at an early stage. Deep learning and machine learning algorithms are being utilized …
View article: A Self-Care Prediction Model for Children with Disability Based on Genetic Algorithm and Extreme Gradient Boosting
A Self-Care Prediction Model for Children with Disability Based on Genetic Algorithm and Extreme Gradient Boosting Open
Detecting self-care problems is one of important and challenging issues for occupational therapists, since it requires a complex and time-consuming process. Machine learning algorithms have been recently applied to overcome this issue. In …
View article: In-store Customer Shopping Behavior Analysis by Utilizing RFID-enabled Shelf and Multilayer Perceptron Model
In-store Customer Shopping Behavior Analysis by Utilizing RFID-enabled Shelf and Multilayer Perceptron Model Open
Understanding customer shopping behavior in retail store is important to improve the customers’ relationship with the retailer, which can help to lift the revenue of the business. However, compared to online store, the customer browsing ac…
View article: Blood Glucose Prediction Model for Type 1 Diabetes based on Extreme Gradient Boosting
Blood Glucose Prediction Model for Type 1 Diabetes based on Extreme Gradient Boosting Open
Predicting future blood glucose (BG) level for diabetic patients will help them to avoid critical conditions in the future. This study proposed Extreme Gradient Boosting (XGBoost), an ensemble learning model to predict the future blood glu…
View article: HDPM: An Effective Heart Disease Prediction Model for a Clinical Decision Support System
HDPM: An Effective Heart Disease Prediction Model for a Clinical Decision Support System Open
Heart disease, one of the major causes of mortality worldwide, can be mitigated by early heart disease diagnosis. A clinical decision support system (CDSS) can be used to diagnose the subjects' heart disease status earlier. This study prop…
View article: False Positive RFID Detection Using Classification Models
False Positive RFID Detection Using Classification Models Open
Radio frequency identification (RFID) is an automated identification technology that can be utilized to monitor product movements within a supply chain in real-time. However, one problem that occurs during RFID data capturing is false posi…
View article: Development of Disease Prediction Model Based on Ensemble Learning Approach for Diabetes and Hypertension
Development of Disease Prediction Model Based on Ensemble Learning Approach for Diabetes and Hypertension Open
Early diseases prediction plays an important role for improving healthcare quality and can help individuals avoid dangerous health situations before it is too late. This paper proposes a disease prediction model (DPM) to provide an early p…
View article: An Affordable Fast Early Warning System for Edge Computing in Assembly Line
An Affordable Fast Early Warning System for Edge Computing in Assembly Line Open
Maintaining product quality is essential for smart factories, hence detecting abnormal events in assembly line is important for timely decision-making. This study proposes an affordable fast early warning system based on edge computing to …
View article: Constituents and Consequences of Online-Shopping in Sustainable E-Business: An Experimental Study of Online-Shopping Malls
Constituents and Consequences of Online-Shopping in Sustainable E-Business: An Experimental Study of Online-Shopping Malls Open
With the growth of the internet, electronic (online) business has become an important trend in the economy. This study investigates how retailers could enhance their shopping processes and hence help sustain their e-business development. T…
View article: Performance Analysis of IoT-Based Sensor, Big Data Processing, and Machine Learning Model for Real-Time Monitoring System in Automotive Manufacturing
Performance Analysis of IoT-Based Sensor, Big Data Processing, and Machine Learning Model for Real-Time Monitoring System in Automotive Manufacturing Open
With the increase in the amount of data captured during the manufacturing process, monitoring systems are becoming important factors in decision making for management. Current technologies such as Internet of Things (IoT)-based sensors can…
View article: Hybrid Prediction Model for Type 2 Diabetes and Hypertension Using DBSCAN-Based Outlier Detection, Synthetic Minority Over Sampling Technique (SMOTE), and Random Forest
Hybrid Prediction Model for Type 2 Diabetes and Hypertension Using DBSCAN-Based Outlier Detection, Synthetic Minority Over Sampling Technique (SMOTE), and Random Forest Open
As the risk of diseases diabetes and hypertension increases, machine learning algorithms are being utilized to improve early stage diagnosis. This study proposes a Hybrid Prediction Model (HPM), which can provide early prediction of type 2…
View article: A Personalized Healthcare Monitoring System for Diabetic Patients by Utilizing BLE-Based Sensors and Real-Time Data Processing
A Personalized Healthcare Monitoring System for Diabetic Patients by Utilizing BLE-Based Sensors and Real-Time Data Processing Open
Current technology provides an efficient way of monitoring the personal health of individuals. Bluetooth Low Energy (BLE)-based sensors can be considered as a solution for monitoring personal vital signs data. In this study, we propose a p…