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Kil To Chong 0001
Person information
- affiliation: Jeonbuk National University, Department of Electronics and Information Engineering, Korea
- affiliation: Chonbuk National University, Advanced Electronics and Information Research Center, Jeonju, Korea
- affiliation (PhD 1995): Texas A&M University, TX, USA
Other persons with the same name
- Kil To Chong — disambiguation page
- Kil To Chong 0002 — Mongolian University of Science and Technology, Ulaanbaatar, Mongolia
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2020 – today
- 2024
- [j84]Mir Tanveerul Hassan
, Hilal Tayara, Kil To Chong:
An integrative machine learning model for the identification of tumor T-cell antigens. Biosyst. 237: 105177 (2024) - [j83]Bilal Ahmad Mir
SB-Net: Synergizing CNN and LSTM networks for uncovering retrosynthetic pathways in organic synthesis. Comput. Biol. Chem. 112: 108130 (2024) - [j82]Saima Gaffar, Mir Tanveerul Hassan
IF-AIP: A machine learning method for the identification of anti-inflammatory peptides using multi-feature fusion strategy. Comput. Biol. Medicine 168: 107724 (2024) - [j81]Palistha Shrestha
DL-SPhos: Prediction of serine phosphorylation sites using transformer language model. Comput. Biol. Medicine 169: 107925 (2024) - [j80]Waleed Alam
Unlocking the therapeutic potential of drug combinations through synergy prediction using graph transformer networks. Comput. Biol. Medicine 170: 108007 (2024) - [j79]Saima Gaffar, Hilal Tayara
Stack-AAgP: Computational prediction and interpretation of anti-angiogenic peptides using a meta-learning framework. Comput. Biol. Medicine 174: 108438 (2024) - [j78]Thi Tuyet Van Tran
AMPred-CNN: Ames mutagenicity prediction model based on convolutional neural networks. Comput. Biol. Medicine 176: 108560 (2024) - [j77]Mir Tanveerul Hassan
NaII-Pred: An ensemble-learning framework for the identification and interpretation of sodium ion inhibitors by fusing multiple feature representation. Comput. Biol. Medicine 178: 108737 (2024) - [j76]Maryam
A graph neural network approach for predicting drug susceptibility in the human microbiome. Comput. Biol. Medicine 179: 108729 (2024) - [j75]Zeeshan Abbas
m5C-Seq: Machine learning-enhanced profiling of RNA 5-methylcytosine modifications. Comput. Biol. Medicine 182: 109087 (2024) - [j74]Pasang Sherpa
FvFold: A model to predict antibody Fv structure using protein language model with residual network and Rosetta minimization. Comput. Biol. Medicine 182: 109128 (2024) - [j73]Aiman Parvez, Syed Danish Ali, Hilal Tayara, Kil To Chong:
Stacking based ensemble learning framework for identification of nitrotyrosine sites. Comput. Biol. Medicine 183: 109200 (2024) - [j72]Jeevan Kandel, Palistha Shrestha, Hilal Tayara, Kil To Chong:
PUResNetV2.0: a deep learning model leveraging sparse representation for improved ligand binding site prediction. J. Cheminformatics 16(1): 66 (2024) - [j71]Sadik Bhattarai
Advancing Peptide-Based Cancer Therapy with AI: In-Depth Analysis of State-of-the-Art AI Models. J. Chem. Inf. Model. 64(13): 4941-4957 (2024) - [j70]Waqar Ahmad, Kil To Chong, Hilal Tayara
GGAS2SN: Gated Graph and SmilesToSeq Network for Solubility Prediction. J. Chem. Inf. Model. 64(20): 7833-7843 (2024) - [j69]Mobeen Ur Rehman
Advanced drone-based weed detection using feature-enriched deep learning approach. Knowl. Based Syst. 305: 112655 (2024) - [j68]Prem Singh Bist
Generative AI in the Advancement of Viral Therapeutics for Predicting and Targeting Immune-Evasive SARS-CoV-2 Mutations. IEEE J. Biomed. Health Informatics 28(11): 6974-6982 (2024) - 2023
- [j67]Ali Raza, Waleed Alam
iPro-TCN: Prediction of DNA Promoters Recognition and Their Strength Using Temporal Convolutional Network. IEEE Access 11: 66113-66121 (2023) - [j66]Prem Singh Bist
Sars-escape network for escape prediction of SARS-COV-2. Briefings Bioinform. 24(3) (2023) - [j65]Sehi Park, Mobeen Ur Rehman
iCpG-Pos: an accurate computational approach for identification of CpG sites using positional features on single-cell whole genome sequence data. Bioinform. 39(8) (2023) - [j64]Zeeshan Abbas
ORI-Explorer: a unified cell-specific tool for origin of replication sites prediction by feature fusion. Bioinform. 39(10) (2023) - [j63]Mobeen Ur Rehman
RAAGR2-Net: A brain tumor segmentation network using parallel processing of multiple spatial frames. Comput. Biol. Medicine 152: 106426 (2023) - [j62]Ali Mustafa, Farman Ullah
Non-intrusive RF sensing for early diagnosis of spinal curvature syndrome disorders. Comput. Biol. Medicine 155: 106614 (2023) - [j61]Jihyoung Ryu, Mobeen Ur Rehman
SegR-Net: A deep learning framework with multi-scale feature fusion for robust retinal vessel segmentation. Comput. Biol. Medicine 163: 107132 (2023) - [j60]Priyash Dhakal, Hilal Tayara
An ensemble of stacking classifiers for improved prediction of miRNA-mRNA interactions. Comput. Biol. Medicine 164: 107242 (2023) - [j59]Thi Tuyet Van Tran
Artificial Intelligence in Drug Toxicity Prediction: Recent Advances, Challenges, and Future Perspectives. J. Chem. Inf. Model. 63(9): 2628-2643 (2023) - [j58]Thi Tuyet Van Tran, Hilal Tayara
Recent Studies of Artificial Intelligence on In Silico Drug Absorption. J. Chem. Inf. Model. 63(20): 6198-6211 (2023) - [j57]Mobeen Ur Rehman
DL-m6A: Identification of N6-Methyladenosine Sites in Mammals Using Deep Learning Based on Different Encoding Schemes. IEEE ACM Trans. Comput. Biol. Bioinform. 20(2): 904-911 (2023) - [j56]Bo Long
Enhancement of Power Decoupling for Virtual Synchronous Generator: A Virtual Inductor and Virtual Capacitor Approach. IEEE Trans. Ind. Electron. 70(7): 6830-6843 (2023) - [c28]Mobeen Ur Rehman, Imran Fareed Nizami, Ali Ahsan, Kil To Chong:
Machine Learning Based Image Forgery Detection Using Natural Scene Statistics. eIT 2023: 304-308 - [c27]Zeeshan Abbas, Kil To Chong:
A Novel Approach Towards Fusion of Steganography and Cryptography for Enhanced Data Security using RGB Image. eIT 2023: 309-313 - 2022
- [j55]Jhabindra Khanal
DeepCap-Kcr: accurate identification and investigation of protein lysine crotonylation sites based on capsule network. Briefings Bioinform. 23(1) (2022) - [j54]Mobeen Ur Rehman
i6mA-Caps: a CapsuleNet-based framework for identifying DNA N6-methyladenine sites. Bioinform. 38(16): 3885-3891 (2022) - [j53]Syed Danish Ali
Interpretable machine learning identification of arginine methylation sites. Comput. Biol. Medicine 147: 105767 (2022) - [j52]Syed Danish Ali
Identification of Functional piRNAs Using a Convolutional Neural Network. IEEE ACM Trans. Comput. Biol. Bioinform. 19(3): 1661-1669 (2022) - [j51]Zeeshan Abbas
ZayyuNet - A Unified Deep Learning Model for the Identification of Epigenetic Modifications Using Raw Genomic Sequences. IEEE ACM Trans. Comput. Biol. Bioinform. 19(4): 2533-2544 (2022) - [j50]Bo Long
Gradient Descent Optimization Based Parameter Identification for FCS-MPC Control of LCL-Type Grid Connected Converter. IEEE Trans. Ind. Electron. 69(3): 2631-2643 (2022) - [j49]Bo Long
Robust Fuzzy-Fractional-Order Nonsingular Terminal Sliding-Mode Control of LCL-Type Grid-Connected Converters. IEEE Trans. Ind. Electron. 69(6): 5854-5866 (2022) - [j48]Bo Long
Sequential Model Predictive Fault-Tolerance Control for T-Type Three-Level Grid-Connected Converters With LCL Filters. IEEE Trans. Ind. Electron. 69(9): 9039-9051 (2022) - [j47]Bo Long
Voltage Regulation Enhancement of DC-MG Based on Power Accumulator Battery Test System: MPC-Controlled Virtual Inertia Approach. IEEE Trans. Smart Grid 13(1): 71-81 (2022) - [j46]Bo Long
Stability Enhancement of Battery-Testing DC Microgrid: An ADRC-Based Virtual Inertia Control Approach. IEEE Trans. Smart Grid 13(6): 4256-4268 (2022) - [c26]Zeeshan Abbas, Mobeen Ur Rehman, Kil To Chong:
TC-6mA-Pred: Prediction of DNA N6-Methyladenine Sites Using CNN with Transformer. BIBM 2022: 2506-2510 - [c25]Mobeen Ur Rehman, Zeeshan Abbas, Kil To Chong:
Identification of Human RNA m5C sites using CapsuleNet Architecture. BIBM 2022: 2536-2541 - [c24]Prem Singh Bist
Identification Of Sars-cov-2 Viral Escape Sequences Using Escapetrans Network. ICTC 2022: 664-667 - 2021
- [j45]Arslan Siraj, Tuvshinbayar Chantsalnyam
RecSNO: Prediction of Protein S-Nitrosylation Sites Using a Recurrent Neural Network. IEEE Access 9: 6674-6682 (2021) - [j44]Syed Danish Ali
Prediction of RNA 5-Hydroxymethylcytosine Modifications Using Deep Learning. IEEE Access 9: 8491-8496 (2021) - [j43]Mobeen Ur Rehman
m6A-NeuralTool: Convolution Neural Tool for RNA N6-Methyladenosine Site Identification in Different Species. IEEE Access 9: 17779-17786 (2021) - [j42]Muhammad Tahir
Prediction of Piwi-Interacting RNAs and Their Functions via Convolutional Neural Network. IEEE Access 9: 54233-54240 (2021) - [j41]Muhammad Shujaat
Cr-Prom: A Convolutional Neural Network-Based Model for the Prediction of Rice Promoters. IEEE Access 9: 81485-81491 (2021) - [j40]Hilal Tayara
Recent omics-based computational methods for COVID-19 drug discovery and repurposing. Briefings Bioinform. 22(6) (2021) - [j39]Jeevan Kandel
PUResNet: prediction of protein-ligand binding sites using deep residual neural network. J. Cheminformatics 13(1): 65 (2021) - [j38]Dae Yeong Lim
iRG-4mC: Neural Network Based Tool for Identification of DNA 4mC Sites in Rosaceae Genome. Symmetry 13(5): 899 (2021) - [j37]Hilal Tayara
Improved Predicting of The Sequence Specificities of RNA Binding Proteins by Deep Learning. IEEE ACM Trans. Comput. Biol. Bioinform. 18(6): 2526-2534 (2021) - [j36]Bo Long
MPC-Controlled Virtual Synchronous Generator to Enhance Frequency and Voltage Dynamic Performance in Islanded Microgrids. IEEE Trans. Smart Grid 12(2): 953-964 (2021) - [j35]Bo Long
Enhancement of Frequency Regulation in AC Microgrid: A Fuzzy-MPC Controlled Virtual Synchronous Generator. IEEE Trans. Smart Grid 12(4): 3138-3149 (2021) - [j34]Jinde Cao
Extended Dissipativity Performance of High-Speed Train Including Actuator Faults and Probabilistic Time-Delays Under Resilient Reliable Control. IEEE Trans. Syst. Man Cybern. Syst. 51(6): 3808-3819 (2021) - 2020
- [j33]Jhabindra Khanal
Identifying Enhancers and Their Strength by the Integration of Word Embedding and Convolution Neural Network. IEEE Access 8: 58369-58376 (2020) - [j32]Shahid Akbar, Maqsood Hayat
cACP-2LFS: Classification of Anticancer Peptides Using Sequential Discriminative Model of KSAAP and Two-Level Feature Selection Approach. IEEE Access 8: 131939-131948 (2020) - [j31]Waleed Alam
A CNN-Based RNA N6-Methyladenosine Site Predictor for Multiple Species Using Heterogeneous Features Representation. IEEE Access 8: 138203-138209 (2020) - [j30]Zeeshan Abbas
SpineNet-6mA: A Novel Deep Learning Tool for Predicting DNA N6-Methyladenine Sites in Genomes. IEEE Access 8: 201450-201457 (2020) - [j29]Tuvshinbayar Chantsalnyam, Dae Yeong Lim, Hilal Tayara
ncRDeep: Non-coding RNA classification with convolutional neural network. Comput. Biol. Chem. 88: 107364 (2020) - [j28]Raman Manivannan
Generalized dissipativity state estimation for genetic regulatory networks with interval time-delay signals and leakage delays. Commun. Nonlinear Sci. Numer. Simul. 89: 105326 (2020) - [j27]Muhammad Tahir, Maqsood Hayat, Kil To Chong:
Prediction of N6-methyladenosine sites using convolution neural network model based on distributed feature representations. Neural Networks 129: 385-391 (2020)
2010 – 2019
- 2019
- [j26]Iman Nazari
Branch Point Selection in RNA Splicing Using Deep Learning. IEEE Access 7: 1800-1807 (2019) - [j25]Bo Long
An Overview of DC Component Generation, Detection and Suppression for Grid-Connected Converter Systems. IEEE Access 7: 110426-110438 (2019) - [j24]Jhabindra Khanal
4mCCNN: Identification of N4-Methylcytosine Sites in Prokaryotes Using Convolutional Neural Network. IEEE Access 7: 145455-145461 (2019) - [j23]Abdul Wahab
iIM-CNN: Intelligent Identifier of 6mA Sites on Different Species by Using Convolution Neural Network. IEEE Access 7: 178577-178583 (2019) - [j22]Jinde Cao
Enhanced L2-L∞ state estimation design for delayed neural networks including leakage term via quadratic-type generalized free-matrix-based integral inequality. J. Frankl. Inst. 356(13): 7371-7392 (2019) - [j21]Felipe P. Vista IV
Design and Real-Time Implementation of a 3-Stage CnW Heading System on an Ubuntu Linux-Embedded Board. J. Sensors 2019: 1345202:1-1345202:13 (2019) - [j20]Panati Subbash, Kil To Chong
Adaptive network fuzzy inference system based navigation controller for mobile robot. Frontiers Inf. Technol. Electron. Eng. 20(2): 141-151 (2019) - 2018
- [j19]Hilal Tayara
Vehicle Detection and Counting in High-Resolution Aerial Images Using Convolutional Regression Neural Network. IEEE Access 6: 2220-2230 (2018) - [j18]Mhaned Oubounyt
Deep Learning Models Based on Distributed Feature Representations for Alternative Splicing Prediction. IEEE Access 6: 58826-58834 (2018) - [j17]Felipe P. Vista IV
Design, Development, and Deployment of Real-Time Sensor Fusion (CnW + EKF) for a Linux-Based Embedded System Using Qt-Anywhere. J. Sensors 2018: 8695397:1-8695397:14 (2018) - [j16]Raman Manivannan
An Arcak-type state estimation design for time-delayed static neural networks with leakage term based on unified criteria. Neural Networks 106: 110-126 (2018) - [j15]Hilal Tayara
Object Detection in Very High-Resolution Aerial Images Using One-Stage Densely Connected Feature Pyramid Network. Sensors 18(10): 3341 (2018) - 2016
- [j14]Ji-Hyoung Ryu
Navigation System Heading and Position Accuracy Improvement through GPS and INS Data Fusion. J. Sensors 2016: 7942963:1-7942963:6 (2016) - [j13]Hilal Tayara
A Real-Time Marker-Based Visual Sensor Based on a FPGA and a Soft Core Processor. Sensors 16(12): 2139 (2016) - 2014
- [j12]Xian Zang, Felipe P. Vista IV
Fast global kernel fuzzy c-means clustering algorithm for consonant/vowel segmentation of speech signal. J. Zhejiang Univ. Sci. C 15(7): 551-563 (2014) - [j11]Xian Zang, Felipe P. Vista IV, Kil To Chong:
Erratum to: Fast global kernel fuzzy c-means clustering algorithm for consonant/vowel segmentation of speech signal. J. Zhejiang Univ. Sci. C 15(11): 1086 (2014) - [j10]Sung Goo Yoo, Kil To Chong:
Adaptive wave variables for bilateral teleoperation using neural networks. Neural Comput. Appl. 25(6): 1249-1262 (2014) - 2013
- [j9]Xian Zang, Kil To Chong:
Homomorphic Filtered Spectral Peaks Energy for Automatic Detection of Vowel Onset Point in Continuous Speech. IEICE Trans. Inf. Syst. 96-D(4): 949-956 (2013) - [c23]Zhang Zheng, Seung Jun Baek, Dong Hyun Yu, Kil To Chong:
Comparison study of the Taylor series based discretization method for nonlinear input-delay systems. AuCC 2013: 397-402 - [c22]Hag-Tae Kim, Ganduulga, Dong Pyo Hong, Kil To Chong:
A Numerical Approach to Solve Point Kinetic Equations Using Taylor-Lie Series and the Adomian Decomposition Method. MUE 2013: 1031-1038 - [c21]Zheng Zhang, Seung Jun Baek, Duck Jin Lee, Kil To Chong:
Study of Reinforcement Learning Based Dynamic Traffic Control Mechanism. MUE 2013: 1047-1056 - [c20]Seongkeun Kwak, Ji-Hyoung Ryu
Smart device interface for intelligent control of pipeline type UV Sterilizer. RO-MAN 2013: 352-353 - 2012
- [j8]Yu Gao, Kil To Chong:
The Explicit Constrained Min-Max Model Predictive Control of a Discrete-Time Linear System With Uncertain Disturbances. IEEE Trans. Autom. Control. 57(9): 2373-2378 (2012) - 2011
- [j7]Yuanliang Zhang, Olga I. Kostyukova
A new time-discretization for delay multiple-input nonlinear systems using the Taylor method and first order hold. Discret. Appl. Math. 159(9): 924-938 (2011) - [j6]Yu Gao, Kil To Chong:
Min-Max Model Predictive Controller for Trajectory Tracking of a Wheeled Mobile Robot with Slipping Effects. IEICE Trans. Fundam. Electron. Commun. Comput. Sci. 94-A(2): 680-687 (2011) - [j5]Hua Su, Kil To Chong, R. Ravi Kumar:
Vibration signal analysis for electrical fault detection of induction machine using neural networks. Neural Comput. Appl. 20(2): 183-194 (2011)
2000 – 2009
- 2009
- [j4]Zheng Zhang, Dong Un An, Hyongsuk Kim
Comparative study of Matrix exponential and Taylor series discretization methods for nonlinear ODEs. Simul. Model. Pract. Theory 17(2): 471-484 (2009) - [j3]Yuanliang Zhang, Jae Byung Park, Kil To Chong:
Controller design for nonlinear systems with time delay using model algorithm control (MAC). Simul. Model. Pract. Theory 17(10): 1723-1733 (2009) - [c19]Jingkun Wang, Yuanliang Zhang, Kil To Chong:
GPS/DR Navigation Data Fusion Research Using Neural Network. ICNC (2) 2009: 58-61 - [c18]Felipe P. Vista IV, Kil To Chong, Chang-Goo Lee:
An Experience Report on Systems Development and Design Using a Rapid, Non-Formal and By-Customer-Demand Approach. Software Engineering Research and Practice 2009: 192-194 - 2008
- [c17]Xi Wang, D. W. Kim, Kil To Chong:
Evaluation Of The Deformity Of Cleft Nose Based On Statistical And Neural Network. BIOCOMP 2008: 389-395 - [c16]Yuanliang Zhang, Sung Goo Yoo, Kil To Chong:
Approximation of MIMO Nonlinear Time Delay Problem. CSC 2008: 105-110 - [c15]Yu Gao, Chang Goo Lee, Kil To Chong:
Tracking Control of Wheeled Mobile Robots Using a Receding Horizon Controller with Time-Delay. CSC 2008: 118-124 - [c14]Yuanliang Zhang, Kil To Chong:
A Neural Network Controller for Nonlinear Time Delay Systems. IC-AI 2008: 39-44 - [i1]George S. Eskander, Amir F. Atiya, Kil To Chong, Hyongsuk Kim, Sung Goo Yoo:
Round Trip Time Prediction Using the Symbolic Function Network Approach. CoRR abs/0806.3646 (2008) - 2007
- [j2]Hua Su, Kil To Chong:
Induction Machine Condition Monitoring Using Neural Network Modeling. IEEE Trans. Ind. Electron. 54(1): 241-249 (2007) - [j1]Amir F. Atiya
Packet Loss Rate Prediction Using the Sparse Basis Prediction Model. IEEE Trans. Neural Networks 18(3): 950-954 (2007) - [c13]Yu Gao, Olga I. Kostyukova, Kil To Chong:
Optimal Control for Electrical Drive System with Time-Delay and Uncertainties. CSC 2007: 289-293 - [c12]Yuanliang Zhang, Chang Goo Lee, Kil To Chong:
Approximation Of State-Delay Problem. CSC 2007: 294-299 - [c11]Zheng Zhang, Kil To Chong:
Taylor Series Time-Discretization Method with First Order Hold for Input Delay Nonlinear Systems. CSC 2007: 300-303 - [c10]Kil To Chong, Eun-Ho Son, Jong Ho Park, Young-Chul Kim:
A Path Finding Via VRML and VISION Overlay for Autonomous Robot. ICANNGA (2) 2007: 676-684 - 2005
- [c9]Jong Ho Park, Kil To Chong:
An Implementation of the Client-Based Distributed Web Caching System. APWeb 2005: 759-770 - [c8]Jong Ho Park, Sung Chil Jung, Changlei Zhang, Kil To Chong:
Neural Network Hot Spot Prediction Algorithm for Shared Web Caching System. APWeb 2005: 795-806 - [c7]Sung Goo Yoo, Kil To Chong, Soo Yeong Yi:
Neural Network Modeling of Transmission Rate Control Factor for Multimedia Transmission Using the Internet. APWeb 2005: 851-862 - [c6]Yong-Seok Kim, Kil To Chong:
A Real-Time Multimedia Data Transmission Rate Control Using a Neural Network Prediction Algorithm. APWeb 2005: 1021-1026 - [c5]Yuanliang Zhang, Hyung Jo Choi, Kil To Chong:
Discretization of Delayed Multi-input Nonlinear System via Taylor Series and Scaling and Squaring Technique. ICCSA (2) 2005: 1207-1216 - [c4]Hua Su, Kil To Chong, Alexander G. Parlos:
A Neural Network Method for Induction Machine Fault Detection with Vibration Signal. ICCSA (2) 2005: 1293-1302 - [c3]Sung Goo Yoo, Kil To Chong, Hyongsuk Kim
Development of Predictive TFRC with Neural Network. PaCT 2005: 193-205 - 2004
- [c2]Jong Ho Park, Kil To Chong:
A Simple Client-Based Hybrid Robust Hash Routing Web Caching System (2HRCS). APWeb 2004: 467-472 - 2003
- [c1]Nikolaos Kazantzis, Kil To Chong, Jong Ho Park, Alexander G. Parlos:
Control-relevant discretization of nonlinear systems with time-delay using Taylor-Lie series. ACC 2003: 149-154
Coauthor Index
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