Kil To Chong at Jeonbuk National University - Research Interests, Publications & Academic Profile - ApplyKite

Kil To Chong

Jeju National University

South Korea

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Research Interests

Cell Biology

30%

Biochemistry

30%

Bioinformatic

40%

Resonant Converters

40%

Sliding Mode Control

30%

Power Electronic

30%

Hysteresis Modeling

30%

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Articles21

FvFold: A model to predict antibody Fv structure using protein language model with residual network and Rosetta minimization

Year:

2024

m5C-Seq: Machine learning-enhanced profiling of RNA 5-methylcytosine modifications

Year:

2024

A graph neural network approach for predicting drug susceptibility in the human microbiome

Year:

2024

Low-Complexity and Less-Conservativeness Ostrowski Stability Criterion for Parallel Fractional Grid-Connected Converters Under Unbalanced Grid

Year:

2024

In Silico Exploration of Novel EGFR Kinase Mutant-Selective Inhibitors Using a Hybrid Computational Approach

Year:

2024

Post-translational modification prediction via prompt-based fine-tuning of a GPT-2 model

Year:

2024

A Model-Data Hybrid Driven Diagnosis Method for Open-Switch Faults in Three-Phase T-Type Grid-Connected Converters

Year:

2024

NaII-Pred: An ensemble-learning framework for the identification and interpretation of sodium ion inhibitors by fusing multiple feature representation

Year:

2024

Power Quality Enhancement of Unbalanced Vehicle Microgrids by T-Type Converters Using Dual-Flexible Model Predictive Control

Year:

2024

Pseudo-Three-Layer Sequential Model-Free Predictive Control With Neural-Network Observer for Parallel T-Type Three-Level Converters

Year:

2024

iCpG-Pos: an accurate computational approach for identification of CpG sites using positional features on single-cell whole genome sequence data

Year:

2023

ORI-Explorer: a unified cell-specific tool for origin of replication sites prediction by feature fusion

Year:

2023

Power Sharing and ZSCC Elimination for Parallel T-Type Three-Level Rectifiers Based on Model-Free Predictive Control

Year:

2023

SegR-Net: A deep learning framework with multi-scale feature fusion for robust retinal vessel segmentation

Year:

2023

XGBoost framework with feature selection for the prediction of RNA N5-methylcytosine sites

Year:

2023

Enhancement of Power Decoupling for Virtual Synchronous Generator: A Virtual Inductor and Virtual Capacitor Approach

Year:

2023

Passivity-Based Partial Sequential Model Predictive Control of T-Type Grid-Connected Converters With Dynamic Damping Injection

Year:

2023

Passivity-Based Partial Sequential Model Predictive Control of T-Type Grid-Connected Converters With Dynamic Damping Injection

Year:

2023

XGB5hmC: Identifier based on XGB model for RNA 5-hydroxymethylcytosine detection

Year:

2023

Passivity Fractional-Order Sliding-Mode Control of Grid-Connected Converter With LCL Filter

Year:

2023

Sars-escape network for escape prediction of SARS-COV-2

Year:

2023

Collaborators1

Hilal Tayara

Assistant Professor

Jeju National University

SOUTH KOREA

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