Research Accomplishments of Prof. Chin-Teng Lin |

Since 1991, Prof. Lin proposed
the world first fuzzy neural network (FNN) at the most authoritative journal
in the area of computer science;
Prof. Lin was one prominent pioneer to introduce the human-like reasoning mechanism to incorporate adaptive learning ability. The resultant novel model, FNN, had become one major research domain in Computational Intelligence since his invention 20 years ago. More than 1 million items can be found when we search "FNN" in Google. The FNN has very high impact to the intelligent systems and machine learning societies nowadays. This work resulted in the following publications: 1. (Textbook) C. T. Lin and C. S. G. Lee,
Neural Fuzzy Systems: A Neuro-Fuzzy Synergism to
Intelligent Systems (with disk), Prentice Hall, 1996, 797 pages (ISBN
0-13-261413-8). 2. (Textbook) C. T. Lin, Neural Fuzzy
Control Systems with Structure and Parameter Learning, World Scientific,
1994, 127 pages (ISBN 981-02-1613-0). 3. C. T. Lin and C. S. G. Lee, “Neural-Network-Based Fuzzy Logic
Control and Decision System,” (IF:
1.822, 55/245 or 22.24% of ENGINEERING, ELECTRICAL & ELECTRONIC) 4. C. T. Lin and C. S. G. Lee, “Reinforcement Structure/Parameter
Learning for Neural-Network-Based Fuzzy Logic Control Systems,” (IF: 3.343, 10/245
or 4% of ENGINEERING, ELECTRICAL & ELECTRONIC 5. C. T. Lin, C. J. Lin, and C. S. G. Lee, “Fuzzy Adaptive Learning Control
Network with On-line Neural Learning,” (IF: 2.138, 8/202
or 3.9% of MATHEMATICS, APPLIED) 6. C. T. Lin and Y. C. Lu, “A Neural Fuzzy System with
Linguistic Teaching Signals,” (IF: 3.343, 10/245
or 4% of ENGINEERING, ELECTRICAL & ELECTRONIC) 7. C. J. Lin and C. T. Lin, “Reinforcement Learning for an
ART-based Fuzzy Adaptive Learning Control Network,” (IF: 2.889, 17/245
or 6.9% of ENGINEERING, ELECTRICAL & ELECTRONIC) 8. C. T. Lin and Y. C. Lu, “A Neural Fuzzy System with Fuzzy
Supervised Learning,” (IF: 3.007, 11/102
or 10.7% of COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE) 9. C. F. Juang and
C. T. Lin, “An On-line
Self-constructing Neural Fuzzy Inference Network and Its Applications,”
(IF: 3.343, 10/245
or 4% of ENGINEERING, ELECTRICAL & ELECTRONIC) 10. C. F. Juang and
C. T. Lin, “A
Recurrent Self-Organizing Neural Fuzzy Inference Network,” IEEE Transactions on Neural Networks, Vol. 10, No. 4, pp.
828-845, July 1999. (IF: 2.889, 17/245
or 6.9% of ENGINEERING, ELECTRICAL & ELECTRONIC) 11. C. T. Lin and I. F. Chung, “A Reinforcement Neuro-fuzzy Combiner for Multiobjective
Control,” (IF: 3.007, 11/102
or 10.7% of COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE) 12. C. F. Juang, J.
Y. Lin, and C. T. Lin, “Genetic Reinforcement Learning Through Symbiotic Evolution for
Fuzzy Controller Design,” (IF: 3.007, 11/102
or 10.7% of COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE) 13. I. F. Chung, C. J. Lin, and C. T. Lin, “A GA-based Fuzzy Adaptive Learning
Control Network,” (IF: 2.138, 8/202
or 3.9% of MATHEMATICS, APPLIED) 14. C. T. Lin, W. C. Cheng, and S. F. Liang, “An On-line ICA-mixture-model-based
Self-constructing Fuzzy Neural Network,” (IF: 1.420, 80/245
or 32.6% of ENGINEERING, ELECTRICAL & ELECTRONIC) 15. C. T. Lin, C. M. Yeh,
S. F. Liang, J. F. Chung, and Nimit Kumar, “Support-vector-based Fuzzy Neural
Network for Pattern Classification,” (IF: 3.343, 10/245
or 4% of ENGINEERING, ELECTRICAL & ELECTRONIC) 16. C. H. Chen, C. J. Lin, and C. T. Lin, “A Functional-link-based NeuroFuzzy Network for Nonlinear System Control,” (IF: 3.343, 10/245
or 4% of ENGINEERING, ELECTRICAL & ELECTRONIC) 17. C. J. Lin, C. H. Chen, and C. T. Lin, “A Hybrid of Cooperative Particle
Swarm Optimization and Cultural Algorithm for Neural Fuzzy Networks and Its
Prediction Applications,” (IF: 2.016, 22/95
or 23.1% of COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE) 18. C. H. Chen, C. J. Lin, and C. T. Lin, “Using an Efficient Immune
Symbiotic Evolution Learning for Compensatory Neuro-fuzzy
Controller,” (IF: 3.343, 10/245
or 4% of ENGINEERING, ELECTRICAL & ELECTRONIC) 19. Y. Y. Lin, J. Y. Chang, and C. T. Lin*, “Identification and Prediction of
Dynamic Systems Using an Interactively Recurrent Self-evolving Fuzzy Neural
Network (IRSFNN)”, (IF: 2.952, 1/50
or 2% of COMPUTER SCIENCE, HARDWARE & ARCHITECTURE) 20. M. F. Han, C. T. Lin, and J. Y. Chang, “Efficient
Differential Evolution Algorithm based Optimization of Fuzzy Prediction Model
for Time Series Forecasting,”
Our fundamental contributions add to the key foundation of
Prof. Lin's contributions on the
This work resulted in the following publications: 1. C. T. Lin, “A Neural Fuzzy Control System with Structure and
Parameter Learning,” (IF:
2.138, 8/202 or 3.9% of MATHEMATICS, APPLIED) 2. C. T. Lin and C. S. G. Lee, “A Multi-valued Boltzmann Machine,” IEEE Transactions on Systems, Man, and Cybernetics, Vol. 25, No.
4, pp. 660-669, April 1995. (IF:
3.007, 11/102 or 10.7% of COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE) 3. C. J. Lin and C. T. Lin, “An ART-based Fuzzy Adaptive
Learning Control Network,” (IF:
3.343, 10/245 or 4% of ENGINEERING, ELECTRICAL & ELECTRONIC) 4. Y. J. Wang and C. T. Lin, “Runge Kutta Neural Network for Identification
of Dynamical Systems in High Accuracy,” (IF:
2.889, 17/245 or 6.9% of ENGINEERING, ELECTRICAL & ELECTRONIC) 5. Y. J. Wang and C. T. Lin, “A Second-order Learning Algorithm
for Multilayer Networks Based on Block Hessian Matrix,” (IF:
2.656, 15/94 or 16% of COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE) 6. C. T. Lin, H. W. Nein, and W. C. Lin, “A Space-time Delay Neural Network
for Motion Recognition and Its Application to Lipreading,” (IF:
2.988, 12/102 or 11.7% of COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE) 7. Y. J. Wang and C. T. Lin, “Recurrent Learning Algorithms for
Designing Optimal Controllers of Continuous Systems,” (IF:
2.033, 16/91 or 17.5% of COMPUTER SCIENCE, THEORY & METHODS) 8. C. S. Shieh and
C. T. Lin, “A Vector
Neural Network for Emitter Identification,” (IF:
2.011, 10/76 or 13.1% of TELECOMMUNICATIONS) 9. C. T. Lin, C. L. Chang, and W. C. Cheng, “A Recurrent Fuzzy Cellular Neural
Network System with Automatic Structure and Template Learning,” (IF:
1.420, 80/245 or 32.6% of ENGINEERING, ELECTRICAL & ELECTRONIC) 10. C. L. Chang, K. W. Fan, I. F. Chung, and
C. T. Lin, “A
Recurrent Fuzzy Coupled Cellular Neural Network System with Automatic
Structure and Template Learning,” (IF:
1.320, 85/245 or 34.1% of ENGINEERING, ELECTRICAL & ELECTRONIC) 11. C. H. Huang and C. T. Lin, “Bio-inspired Computer Fovea Model
Based on Hexagonal-type Cellular Neural Network,” (IF:
1.420, 80/245 or 32.6% of ENGINEERING, ELECTRICAL & ELECTRONIC) 12. C.H. Li, B.C. Kuo,
and C.T. Lin, “LDA-Based
Clustering Algorithm And Its Application To An
Unsupervised Feature Extraction,” (IF:
2.695, 17/247 or 6.9% of ENGINEERING, ELECTRICAL & ELECTRONIC) 13. M. T. Su, C. H. Chen, C. J. Lin and C. T.
Lin, “A Rule-based
Symbiotic Modified Differential Evolution for Self-Organizing Neuro-Fuzzy Systems,” (IF:
2.097, 19/97 or 19.59% of COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS) 14. M. F. Han, S. H. Liao, J. Y. Chang, and C.
T. Lin, “Dynamic Group-Based Differential Evolution Using a Self-Adaptive
Strategy for Global Optimization Problems,”
Although fuzzy logic control has been applied
to many real-life systems and products, the evidence of its theoretic
soundness was usually a pushing issue to pursue. Especially, people were
usually questioning the stability, robustness, and optimality of a fuzzy
control system embedded with expert knowledge. To attack this problem, Prof.
Lin presented
This work uniquely proposed the design
method to This work resulted in the following publications: 1. S. J. Wu and C. T. Lin, “Optimal Fuzzy Controller Design:
Local Concept Approach,” (IF: 3.343, 10/245
or 4% of ENGINEERING, ELECTRICAL & ELECTRONIC) 2. S. J. Wu and C. T. Lin, “Optimal Fuzzy Controller Design in
Continuous Fuzzy System: Global Concept Approach,” (IF: 3.343, 10/245
or 4% of ENGINEERING, ELECTRICAL & ELECTRONIC) 3. S. J. Wu and C. T. Lin, “Discrete-time Optimal Fuzzy
Controller Design: Global Concept Approach,” (IF: 3.343, 10/245
or 4% of ENGINEERING, ELECTRICAL & ELECTRONIC) 4. C. H. Wang, H. L. Liu, and C. T. Lin, “Dynamic Optimal Learning Rates of
a Certain Class of Fuzzy Neural Networks and its Applications with Genetic
Algorithm,” (IF: 3.007, 11/102
or 10.7% of COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE) 5. M. F. Han, C. T. Lin, and J. Y. Chang,
" Group-Based Differential Evolution for Numerical Optimization
Problems," (IF: 1.667, 12/60 or 20% of AUTOMATION
& CONTROL SYSTEMS) 6. S. Y. Li, C. H. Yang, S. A. Chen, L. W. Ko, and C. T. Lin*, “Fuzzy Adaptive Synchronization of Time-Reversed Chaotic Systems
via a New Adaptive Control Strategy,” (IF= 2.833, 9/133
or 6.76% of COMPUTER SCIENCE, INFORMATION SYSTEMS) 7. S. Y. Li, C. H. Yang, C. T. Lin, L. W. Ko, and T. T. Chiu, ”Adaptive Synchronization of Chaotic Systems with Unknown
Parameters via New Backstepping Strategy”, (IF: 1.741, 17/116
or 14.65% of ENGINEERING, MECHANICAL)
Prof. Lin and his team had contributed widely in applying the
aforementioned computational intelligence technology to real-world systems,
covering the domains of robotics, automation, and control. The main challenges in these
real-world applications
Prof. Lin advanced the applications of computational intelligence technology to solve the real-world human-in-loop problems efficiently. Many of these techniques have been successfully transferred to the industry. For example, His work to predict the emissivity changes for compensating the temperature reading of the pyrometer in rapid thermal processing has been transferred to nanometer silicon semiconductor foundries including Taiwan Semiconductor Manufacturing Company (TSMC). These achievements directly impact the development of human-centered intelligent systems. This work resulted in the following publications: 1. C. T. Lin and C. S. G. Lee, “Fault-Tolerant Reconfigurable
Architecture for Robot Kinematics and Dynamics Computations,” (IF:
3.007, 11/102 or 10.7% of COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE) 2. C. H. Hsiao, C. T. Lin, and M. Cassidy, “Application of Fuzzy Logic and
Neural Networks to Automatically Detect Freeway Traffic Incidents,” Journal of Transportation Engineering, American Society of Civil
Engineers (ASCE), Vol. 120, No. 5, pp. 753-772, Sep./Oct. 1994. 3. C. J. Lin and C. T. Lin, “Adaptive Fuzzy Control of Unstable
Nonlinear Systems,” International Journal of Neural
Systems, Vol. 6, No. 3, pp. 283-298, 1995. (IF:
2.988, 12/102 or 11.7% of COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE) 4. P. H. Chen, J. H. Lai, and C. T. Lin, “Application of Fuzzy Control to a
Road Tunnel Ventilation System,” (IF:
2.138, 8/202 or 3.9% of MATHEMATICS, APPLIED) 5. C. F. Juang, C.
T. Lin, and J. C. Huang, “Temperature Control of Rapid Thermal Process Using Neural Fuzzy
Network,” (IF:
2.138, 8/202 or 3.9% of MATHEMATICS, APPLIED) 6. J. H. Lai and C. T. Lin, “Application of Neural Fuzzy
Network to Pyrometer Correction and Temperature Control in Rapid Thermal
Processing,” (IF:
3.343, 10/245 or 4% of ENGINEERING, ELECTRICAL & ELECTRONIC) 7. C. T. Lin and C. P. Jou,
“Controlling Chaos by
GA-based Reinforcement Learning Neural Network,” (IF:
2.889, 17/245 or 6.9% of ENGINEERING, ELECTRICAL & ELECTRONIC) 8. C. T. Lin, C. F. Juang,
and C. P. Li, “Temperature
Control with a Neural Fuzzy Inference Network,” (IF:
2.016, 22/95 or 23.1% of COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS) 9. M. S. Bai, I L.
Hsiao, H. M. Tsai, and C. T. Lin, “Development of an On-line Diagnosis System for Rotor Vibration via
Model-based Intelligent Inference,” (IF:
1.717, 7/26 or 26.92% of ACOUSTICS) 10. C. T. Lin and C. P. Jou,
“GA-based Fuzzy
Reinforcement Learning for Control of a Magnetic Bearing System,” (IF:
3.007, 11/102 or 10.7% of COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE) 11. C. T. Lin, C. F. Juang,
and C. P. Li, “Water
Bath Temperature Control with a Neural Fuzzy Inference Network,” (IF:
2.138, 8/202 or 3.9% of MATHEMATICS, APPLIED) 12. C. T. Lin, I F. Chung, and S. Y. Huang, “Improvement of Machining Accuracy at Corner Parts
for Wire-EDM,” Fuzzy Sets and Systems,
Vol. 122, No. 3, pp. 499-511, Sep. 2001. 13. C. T. Lin, I. F. Chung, H. C. Pu, T. H. Lee, and J. Y. Chang, “Genetic Algorithm-Based Neural Fuzzy Decision Tree
for Mixed Scheduling in ATM Networks,”
IEEE Transactions on Systems Man and Cybernetics Part B-Cybernetics, Vol. 32,
No. 6, pp. 832-845, Dec. 2002. 14. F. B. Duh and C. T. Lin, “Tracking a Maneuvering Target
Using Neural Fuzzy Network,” (IF: 3.007, 11/102
or 10.7% of COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE) 15. M. T. Su, C. T. Lin and K. W. Hsu, “A Novel Method for Locating Solder
Joints Based on Modified Binary Potential Function,” (IF: 1.667, 12/60
or 22.95% of AUTOMATION & CONTROL SYSTEMS)
Multimedia information technology (IT)
is the kernel in this 3C (Computer, Communications, and Consumer) electronics
era. Its main challenge is to meet the increasing high demanding of acute
human perceptual systems in real time. Prof. Lin's major contributions in
this area is to adopt the biological models and features of human perceptual
systems into the multimedia information processing techniques to process the
multimedia signals in the way of well fitting human
perceptual characteristics in reasonable time and space bandwidth. This
so-called
The This work resulted in the following publications:
1. C. T. Lin and C. F. Juang,
“An Adaptive Neural
Fuzzy Filter and Its Applications,” (IF:
3.007, 11/102 or 10.7% of COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 2. C. T. Lin and M. C. Kan,
“Adaptive Fuzzy
Command Acquisition with Reinforcement Learning,” 3. S. F. Liang, W. Y. Su, and C. T. Lin, “Model-based Synthesis of Plucked
String Instruments by Using a Class of Scattering Recurrent Networks,”
(IF:
2.889, 17/245 or 6.9% of ENGINEERING, ELECTRICAL & ELECTRONIC) 4. C. S. Shieh and
C. T. Lin, “Direction
of Arrival Estimation Based on Phase Difference Using Neural Fuzzy Network,”
(IF:
2.011, 10/76 or 13.1% of TELECOMMUNICATIONS) 5. G. D. Wu and C. T. Lin, “Word Boundary Detection with
Mel-scale Frequency Bank in Noisy Environment,” (IF:
1.668, 5/30 or 16.7% of ACOUSTICS) 6. C. T. Lin, H. W. Nein, and J. Y. Hwu, “GA-based Noisy Speech Recognition Using Two-Dimensional Cepstrum,” (IF:
1.668, 5/30 or 16.7% of ACOUSTICS) 7. C. F. Juang and
C. T. Lin, “Noisy
Speech Processing by Recurrently Adaptive Fuzzy Filters,” (IF:
3.343, 10/245 or 4% of ENGINEERING, ELECTRICAL & ELECTRONIC) 8. H. W. Nein and C. T. Lin, “Incorporating Error Shaping
Techniques into LSF Vector Quantization,” (IF:
1.668, 5/30 or 16.7% of ACOUSTICS) 9. G. D. Wu and C. T. Lin, “A Recurrent Neural Fuzzy Network
for Word Boundary Detection in Variable Noise-level Environments,” (IF:
3.007, 11/102 or 10.7% of COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE) 10. D. J. Liu and C. T. Lin, “Fundamental Frequency Estimation
Based on the Joint Time-frequency Analysis of Harmonic Spectral Structure,”
(IF:
1.668, 5/30 or 16.7% of ACOUSTICS) 11. C. T. Lin, J. Y. Lin, and G. D. Wu, “A Robust Word Boundary Detection
Algorithm for Variable Noise-level Environment in Cars,” (IF:
2.092, 7/106 or 6.6% of ENGINEERING, CIVIL) 12. G. D. Wu and C. T. Lin, “Single-channel Speech Enhancement
in Variable Noise-level Environment,” (IF:
3.007, 11/102 or 10.7% of COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE) 13. F. B. Duh, C. F. Juang,
and C. T. Lin, “A
Neural Fuzzy Network Approach to Radar Pulse Compression,” (IF:
2.234, 34/245 or 13.8% of ENGINEERING, ELECTRICAL & ELECTRONIC) 14. C. T. Lin, R. C. Wu, J. Y. Chang, and S.
F. Liang, “A Novel
Prosodic-information Synthesizer Based on Recurrent Fuzzy Neural Network for
the Chinese TTS System,” (IF:
3.007, 11/102 or 10.7% of COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE) 15. S. F. Liang, S. M. Lu, J. Y. Chang and C.
T. Lin, “A Novel
Two-stage Impulse Noise Removal Technique Based on Neural Networks and Fuzzy
Decision,” (IF:
3.343, 10/245 or 4% of ENGINEERING, ELECTRICAL & ELECTRONIC)
1. C. T. Lin, S. C. Hsiao, and G. D. Wu, “New Techniques on Deformed Image
Motion Estimation and Compensation,” (IF:
3.007, 11/102 or 10.7% of COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE) 2. C. T. Lin, Y. C. Lee, and H. C. Pu, “Satellite Sensor Image Classification Using Cascaded Architecture
of Neural Fuzzy Network,” (IF:
2.234, 34/245 or 13.8% of ENGINEERING, ELECTRICAL & ELECTRONIC) 3. C. T. Lin, I. F. Chung, and L. K. Sheu, “A Neural Fuzzy System for Image Motion Estimation,” (IF:
2.138, 8/202 or 3.9% of MATHEMATICS, APPLIED) 4. Y. W. Shou and
C. T. Lin, “Image Descreening by GA-CNN-based Texture Classification,”
(IF:
1.420, 80/245 or 32.6% of ENGINEERING, ELECTRICAL & ELECTRONIC) 5. S. C. Hsu, S. F. Liang, and C. T. Lin, “A Robust Digital Image
Stabilization Technique Based on Inverse Triangle Method and Background
Detection,” (IF:
0.942, 121/229 or 44.7% of TELECOMMUNICATIONS) 6. C. T. Lin, W. C. Cheng, and S. F. Liang, “A 3-D Surface Reconstruction
Approach Based on Postnonlinear ICA Model,” (IF:
2.889, 17/245 or 6.9% of ENGINEERING, ELECTRICAL & ELECTRONIC) 7. C. T. Lin, W. C. Cheng, and S. F. Liang, “Neural-network-based Adaptive
Hybrid-reflectance Model for 3-D Surface Reconstruction,” (IF:
2.889, 17/245 or 6.9% of ENGINEERING, ELECTRICAL & ELECTRONIC) 8. C. T. Lin, H. C. Pu,
K. W. Fan, S. M. Lu, and S. F. Liang, “An HVS-directed Neural-network-based Image Resolution Enhancement
Scheme for Image Resizing,” (IF:
3.343, 10/245 or 4% of ENGINEERING, ELECTRICAL & ELECTRONIC) 9. S. C. Hsu, S. F. Liang, K. W. Fan, and C.
T. Lin, “A Robust
In-car Digital Image Stabilization Technique,” (IF:
2.016, 22/95 or 23.1% of COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS) 10. C. T. Lin, C. H. Huang, and S. A. Chen, “CNN-based Hybrid-order Texture
Segregation as Early Vision Processing and its Implementation on CNN-UM,”
(IF:
1.420, 80/245 or 32.6% of ENGINEERING, ELECTRICAL & ELECTRONIC) 11. C. T. Lin, Y. C. Yu, and L. D. Van, “Cost-effective Triple-mode
Reconfigurable Pipeline FFT/IFFT/2-D DCT Processor,” (IF:1.010,
121/245 or 49.3% of ENGINEERING, ELECTRICAL & ELECTRONIC) 12. C. T. Lin, C. T. Hong, and C. T. Yang, “Real-time Digital Image
Stabilization System Using Modified Proportional Integrated Controller,”
(IF:
2.548, 24/245 or 9.7% of ENGINEERING, ELECTRICAL & ELECTRONIC) 13. P. Y. Chen, L. D. Van, I. H. Khoo, H.C. Reddy, and C. T. Lin, “Power-efficient and Cost-effective
2-D Symmetry Filter Architectures,” (IF:
1.580, 64/247 or 25.9% of ENGINEERING, ELECTRICAL & ELECTRONIC) 14. C. H. Li, B.C. Kuo,
C.-T. Lin, and C.-S. Huang, “A Spatial-Contextual Support
Vector Machine For Remotely Sensed Image Classification,” (IF:
2.485, 27/247 or 10.93% of ENGINEERING) 15. C. Y. Lee, C. T. Lin, C. T. Hong, and M.
T. Su, “Smoke
Detection Using Spatial and Temporal Analyses,” (IF:
1.667, 12/60 or 20% of AUTOMATION & CONTROL SYSTEMS)
The present era is an era of
biological science and engineering which has been generating a huge amount of
data. Those data usually requires specialized modeling and analysis tools. Furthermore, for such biological/medical data there are always too
many indifferent and derogatory features which may lead to enhanced data
acquisition time and cost, more design time, more decision making time, and
other increased expenditures in cost, time and effort. Hence reducing the
dimensionality, if possible, is always desirable through feature selection.
The structure classification of
proteins plays a very important role in bioinformatics, since the
relationships and characteristics among those known proteins can be exploited
to predict the structure of new proteins. Prof. Lin's invented HLA with
automatic feature selection had provided a general tool in bioinformatics to
effectively predicts protein structures in high
accuracy. It had also been adopted to do biomarker discovery and cancer
diagnostic system construction. Such a technique may be further applied to drug discovery. In bioengineering, Prof. Lin had
designed a micro syringe device with tonometer chamber based on a model-based
HLA for noninvasively
continuous blood pressure waveform detection accurately without distortion. This was the
first of such devices in the world. This technology was transferred to Microlife Co., which is an international
well known healthcare-devices company located in over 50 countries in the
world. This work resulted in the following publications:
1. C. D. Huang,
C. T. Lin, and N. R. Pal, “Hierarchical
Learning Architecture with Automatic Feature Selection for MultiClass Protein Fold Classification,” (IF: 1.705, 31/59 or 52.5% of NANOSCIENCE &
NANOTECHNOLOGY) 2. C. T. Lin, K.
L. Lin, C. H. Yang, I F. Chung, C. D. Huang, and Y. S. Yang, “Protein Metal Binding Residue Prediction Based
on Neural Networks,” (IF: 2.988, 12/102 or 11.7% of COMPUTER SCIENCE,
ARTIFICIAL INTELLIGENCE) 3. K. L. Lin, C.
Y. Lin, C. D. Huang, H. M. Chang, C. Y. Yang, C. T. Lin, C. Y. Tang, and D.
F. Hsu, “Feature Selection and Combination
Criteria for Improving Accuracy in Protein Structure Prediction,” (IF: 1.705, 31/59 or 52.5% of NANOSCIENCE &
NANOTECHNOLOGY) 4. Y. S. Tsai, I.
F. Chung, J. C. Simpson, M. I. Lee, C. C. Hsiung,
T. Y. Chiu, L. S. Kao, T. C. Chiu, C. T. Lin, W. C. Lin, S. F. Liang, and C.
C. Lin, “Automated Recognition System to Classify
Subcellular Protein Localizations in Images of Different Cell Lines Acquired by
Different Imaging Systems,” (IF: 1.850, 6/16 or 37.5% of ANATOMY &
MORPHOLOGY) 5. Y. S. Tsai,
C. T. Lin, G. C. Tseng, I. F. Chung, and N. R. Pal "Discovery of
Dominant and Dormant Genes from Expression Data Using a Novel Generalization
of SNR for Multi-class Problems,” (IF: 3.428, 4/29 or 13.7% of MATHEMATICAL &
COMPUTATIONAL BIOLOGY ) 6. K. L. Lin, C.
T. Lin, N. R. Pal, and S. Ojha, "Structural
Building Blocks: Construction of Protein 3-D Structures Using a Structural
Variant of Mountain Clustering Method,” (IF: 1.081, 16/23 or 69.5% of MEDICAL
INFORMATICS) 7. K. L. Lin, C.
T. Lin and N. R. Pal, “Incremental
Mountain Clustering Method to Find Building Blocks For Constructing
Structures of Proteins,” (IF: 1.712, 39/64 or 60.9% of NANOSCIENCE &
NANOTECHNOLOGY)
1. S. H. Liu and
C. T. Lin, “A Model-based Fuzzy Logic Controller with
Kalman Filtering for Tracking Mean Arterial
Pressure,” (IF: 2.033, 16/91 or 17.5% of COMPUTER SCIENCE,
THEORY & METHODS) 2. J. J. Wang,
C. T. Lin, S. H. Liu, and Z. C. Wen, “Model-based
Synthetic Fuzzy Logic Controller for Indirect Blood Pressure Measurement,” (IF: 3.007, 11/102 or 10.7% of COMPUTER SCIENCE,
ARTIFICIAL INTELLIGENCE) 3. B. C. P. Hu,
Y. C. Shih, Y. S. Yang, C. Y. Wu, C. J. Yuan, M. D. Ker, T. K. Wu, Y. K. Li,
Y. Z. Hsieh, W. S. Hsu, and C. T. Lin, “CMOS Chip As
Luminescent Sensor For Biochemical Reactions,” (IF: 1.581, 67/229 or 29.3% of ENGINEERING,
ELECTRICAL & ELECTRONIC) 4. C. T. Lin, S.
H. Liu, J. J. Wang, and Z. C. Wen, “Reduction of
Interference in Oscillometric Arterial Blood
Pressure Measurement Using Fuzzy Logic,’’ (IF: 2.154, 22/59 or 37.2% of ENGINEERING,
BIOMEDICAL)
The growing number of traffic accidents in recent years has become a serious concern to
society. Accidents caused by driver’s inattention such as fatigue, drowsiness or distraction behind
the steering wheel have a high fatality rate because of the marked decline in
the driver’s abilities of
perception, recognition, and vehicle control abilities while being sleepy.
Prof. Lin's work demonstrated the feasibility of online assessment
and rectification of brain networks exhibiting characteristic dynamic
patterns in response to momentary cognitive challenges. This work resulted in the following publications: 1. C. T. Lin, S. A. Chen, T. T. Chiu, H. Z. Lin,
and L. W. Ko, “Spatial and Temporal EEG Dynamics of Dual-Task Driving
Performance,” (IF: 2.638, 4/44 or 9.09% of Rehabilitation) 2.
C.
T. Lin, K. C. Huang, C. F. Chao, J. A. Chen, T. W. Chiu, L. W. Ko, and T. P. Jung, “Tonic and Phasic EEG and Behavioral Changes Induced by Arousing
Feedback,” (IF: 5.937,
3/113 or 2.7% of RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING) 3. C. T. Lin, L. W. Ko,
and T. K. Shen, “Computational Intelligent Brain Computer Interaction and Its
Applications on Driving Cognition,” (IF: 2.622,
19/102 or 18.6% of COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE) 4. C. T. Lin, T. T. Chiu, T. Y. Huang, C. F.
Chao, W. C. Liang, S. H. Hsu, and L. W. Ko, “Assessing Effectiveness of Various
Auditory Warning Signals in Maintaining Drivers”
Attention in Virtual Reality-based Driving Environments,” (IF: 0.492,
77/81, Top 95.06%) 5. C. T. Lin, Y. C. Chen, T. Y. Huang, T. T.
Chiu, L. W. Ko, S. F. Liang, H. Y. Hsieh, S. H.
Hsu, and J. R. Duann, “Development of Wireless Brain
Computer Interface with Embedded Multi-task Scheduling and its Application on
Real-time Driver’s Drowsiness Detection and Warning,”
(IF: 2.154, 22/59
or 37.2% of ENGINEERING, BIOMEDICAL) 6. C. T. Lin, K. L. Lin, L. W. Ko, S. F. Liang, B. C. Kuo, and
I. F. Chung, “Nonparametric
Single-trial EEG Feature Extraction and Classification of Driver's Cognitive
Responses,” (IF: 0.885, 132/245 or 53.8% of ENGINEERING, ELECTRICAL &
ELECTRONIC) 7. C. T. Lin, I. F. Chung, L. W. Ko, Y. C. Chen, S. F. Liang, and J. R. Duann, “EEG-based Assessment of Driver Cognitive Responses in a Dynamic
Virtual-Reality Driving Environment,” (IF: 2.154,
22/59 or 37.2% of ENGINEERING, BIOMEDICAL) 8. C. T. Lin, L. W. Ko,
I. F. Chung, T. Y. Huang, Y. C. Chen, T. P. Jung, and S. F. Liang, “Adaptive EEG-based Alertness
Estimation System by Using ICA-based Fuzzy Neural Networks,” (IF: 1.420,
80/245 or 32.6% of ENGINEERING, ELECTRICAL & ELECTRONIC) 9. C. T. Lin, R. C. Wu, S. F. Liang, W. H.
Chao, Y. J. Chen, and T. P. Jung, "EEG-based Drowsiness Estimation For
Safety Driving Using Independent Component Analysis," (IF: 1.420, 80/245 or 32.6% of ENGINEERING, ELECTRICAL &
ELECTRONIC) 10. Y. K. Wang, S. A. Chen, and C. T. Lin*, “An
EEG-Based Brain-Computer Interface for Dual Task Driving Detection,” (IF: 1.580, 39/11 or 35.1% of COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE)
Motion sickness (MS) and spatial navigation are the common
experience of numerous people and has motivated extensive physiological,
neurophysiological and psychophysiological research. The main challenge to
study such driving related cognitive tasks in the real operational environment
is to develop an easy-to-operate online rating mechanism sought to record
continuously the level of motion sickness in subjects. Prof. Lin's work
demonstrates a VR-based driving environment that comprises a 32-channel EEG
system and a joystick with a continuous scale, by which subjects can
continuously report their behavior responses such as level of motion sickness
and spatial navigation performance during experiments.
This work resulted in the following publications: 1. Y. C. Chen, J. R. Duann,
S. W. Chuang, C. L. Lin, L. W. Ko, T. P. Jung, and
C. T. Lin, “Spatial
and Temporal EEG Dynamics of Motion Sickness,” (IF: 5.937, 3/113 or 2.7%
of RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING) 2. S. W. Chuang, L. W. Ko,
Y. P. Lin, R. S. Huang, T. P. Jung, and C. T. Lin, "Co-modulatory
Spectral Changes in Independent Brain Processes Are Correlated with Task
Performance," accepted by (IF: 5.937, 3/113 or 2.7% of RADIOLOGY, NUCLEAR MEDICINE &
MEDICAL IMAGING) 3. T. C. Chiu, K. Gramann,
L. W. Ko, J. R. Duann, T.
P. Jung, and C. T. Lin, “Alpha Modulation in Parietal and Retrosplenial
Cortex correlates with Navigation Performance,” (IF: 3.263,
14/73, 19.18% of Psychology) 4. C. T. Lin, T. Y. Huang, W. J. Lin, S. Y.
Chang, Y. H. Lin, L. W. Ko, D. L. Hung, and E. C.
Chang, “Gender
Differences in Wayfinding in Virtual Environments
with Global or Local Landmarks”, accepted by Journal
of Environmental Psychology, 2012. (SSCI) (IF:
1.449, 39/120 or 32.5% of PSYCHOLOGY, MULTIDISCIPLINARY) 5. K. Gramann, J.
T. Gwin, D. P. Ferris, K. Oie,
T. P. Jung, C. T. Lin, L. D. Liao, and S. Makeig, “Cognition in Action: Imaging
Brain/Body Dynamics in Mobile Humans”, (IF: 0.102, 182/185 or 98.37% of Clinical
Neurology) 6. C. S.
Wei, L. W. Ko, S. W. Chuang, T. P.
Jung, and C. T. Lin, “EEG-based
Evaluation System for Motion Sickness Estimation,” 7. L. W. Ko, C. S. Wei, S. W. Chuang, T. P. Jung, and C. T. Lin, “Development
of A Motion Sickness Evaluation System Based on EEG Spectrum Analysis,” 8. L.
W. Ko, C. S. Wei, T. P. Jung, and C. T. Lin,
“Estimating
The Level of Motion Sickness Based on EEG Spectra,” 9. C. T. Lin, F. S. Yang, T. C. Chiou, L. W. Ko, J. R. Duann, and K. Gramann, “EEG-Based Spatial Navigation
Estimation in a Virtual Reality Driving Environment,” 10. C. L. Lin, T. P. Jung, S. W. Chuang, J.
R. Duann, C. T. Lin*, and T. W. Chiu*, “Self-adjustments
May Account for the Contradictory Correlations between HRV and
Motion-sickness Severity,”
Learning a new movement or rehabilitation engineering often guided
by external stimuli and feedback. In recent years, EEGs have increasingly
been utilized as a means to study the neuronal mechanisms underlying
behavioral changes associated with the acquisition of motor skills. Haptic
feedback is now receiving increasing attention related to motor-skill
learning due to its novelty and potential for real world applications.
Prof. Lin's work demonstrates that haptic feedback improves the
behavioral performance and associates haptic feedback with behavioral
improvement by describing a variety of spectral changes in different brain
processes and the interactions between them. This is This work resulted in the following publications: 1. C. L. Lin, F. Z. Shaw, K. Y. Young, C. T.
Lin, and, T. P. Jung, “EEG Correlates of Haptic Feedback in A Visuomotor
Tracking Task,” (IF: 5.937, 3/113 or 2.7% of RADIOLOGY, NUCLEAR
MEDICINE & MEDICAL IMAGING) 2. L. D. Liao, C. Y. Chen, I. J. Wang, S. F.
Chen, S. Y. Li, B. W. Chen, J. Y. Chang, and C. T. Lin, “Gaming Control Using A Wearable
and Wireless EEG-Based Brain-Computer Interface Device with Novel Dry
Foam-Based Sensors,” (IF: 2.638, 4/44 or 9.09% of REHABILITATION)
(IF: 0.492, 77/81 or 95% of PSYCHOLOGY,
EXPERIMENTAL) 4. C. T. Lin, C. L. Lin, K. C. Huang, S. A.
Chen, and J. H. Tung, “The
Performance of Visuo-Motor Coordination Changes
Under Force Feedback Assistance System,” 5. S. L. Wu, L. D. Liao, S. W. Lu, W. L.
Jiang, S. A. Chen, and C. T. Lin* “Controlling a Human-Computer Interface
System with a Novel Classification Method that uses Electrooculography
Signals,” IEEE Transactions on Biomedical Engineering (TBME) , Vol. 60, No.
8, Aug. 2013.
EEG is the only brain imaging modality with high temporal and fine
(potentially cm2-scale) spatial resolution that is lightweight enough to be
worn in operational settings. The lack of availability of EEG monitoring
system capable of high-definition recording, online signal processing and
artifact cancellation, without use of conductive gels applied to the scalp,
has long thwarted the applications of EEG monitoring in the workplace.
Because of current limitations in size, weight, and cost of available EEG
systems, early brain-computer interface (BCI) systems have been designed to
use a minimal number of recording channels. To attacked this problem,
Data collection in most EEG studies requires skin preparation and
gel application to ensure good electrical conductivity between sensor and
skin. These procedures are time
consuming, uncomfortable, and even painful for participants since skin
preparation usually involves abrasion of the outer skin layer. Further, the signal quality may
degrade over time as the skin regenerates and the conductive gel becomes
dry. This work resulted in the following publications: 1. L.
D. Liao, C. T. Lin, K. McDowell, A. Wickenden, K. Gramann, T. P. Jung, L.W. Ko,
and J. Y. Chang, “Biosensor Technologies for the Augmented
Brain-Computer Interface in the Next Decades," (IF:
5.151, 4/247, Top 1.6% of Engineering,
Electrical & Electronic) 2. C. T. Lin, L. D. Liao, Y. H.
Liu, I. J. Wang, B. S. Lin, and J. Y. Chang, “Novel Dry Polymer Foam Electrodes for
Long-Term EEG Measurement,” (IF:
1.790, 32/70 of Engineering, Biomedical)
(IF:
1.774, 14/61 or 22.95% of
Instruments & Instrumentation) 4. C. T. Lin, C. J. Chang, B. S. Lin, S. H.
Hung, C. F. Chao, and I. J. Wang, “A Real-time Wireless Brain Computer Interface System for Drowsiness
Detection,” (IF: 1.689,61/247 or 24.7% of
ENGINEERING, ELECTRICAL & ELECTRONIC) 5. C. T. Lin, L. W. Ko,
M. H. Chang, J. R. Duann, J. Y. Chen, T. P. Su, and
T. P. Jung, “Review of
Wireless and Wearable Electroencephalogram Systems and Brain-Computer
Interfaces - A Mini-Review,” (IF: 1.661,
20/44 or 45.4% of GERIATRICS & GERONTOLOGY) 6. C. T. Lin, L. W. Ko,
J. C. Chiou, J. R. Duann,
R. S. Huang, T. W. Chiu, S. F. Liang, and T. P. Jung, “Noninvasive Neural Prostheses
Using Mobile & Wireless EEG,” (IF: 4.878, 2/245 or 0.8% of ENGINEERING,
ELECTRICAL & ELECTRONIC) 7. C. T. Lin, Y. C. Chen, T. Y. Huang, T. T.
Chiu, L. W. Ko, S. F. Liang, H. Y. Hsieh, S. H.
Hsu, and J. R. Duann, “Development of Wireless Brain
Computer Interface with Embedded Multitask Scheduling and its Application on
Real-time Driver’s Drowsiness Detection and Warning,”
(IF: 2.154,
22/59 or 37.2% of ENGINEERING, BIOMEDICAL) 8. C. T. Lin, W. R. Wang, I. J. Wang, L. D.
Liao, S. F. Chen, K. C. Tseng, and L. W. Ko, “A New Design of the Multi-channels
Mobile and Wireless EEG System,” 9.
C. T. Lin, L. W. Ko,
C. J. Chang, Y. T. Wang, C. H. Chung, F. S. Yang, J. R. Duann,
T. P. Jung, and J. C. Chiou, “Wearable and
Wireless Brain-Computer Interface and Its Applications,” 10. L. D. Liao, H. Y. Lai, C. T. Lin, and Y. Y. Chen, “Design and Experimental Verification of a Novel
Light-addressable Multi-electrode Arrays Chip for Multi-channel Neural Signal
Recording,” 11. L. D. Liao and C. T. Lin*, “Development Trends of the Biosensors for Electroencephalography
Measurements in Cognitive Neuroscience Applications,” 12. K. Mcdowell, C. T. Lin, K. S. Oie, T. P. Jung, S. Gordon, K. W. Whitaker, S. Y. Li, S. W.
Lu, W. D. Hairston, "Real-World Neuroimaging Technologies," Access, IEEE , vol.1, no., pp.131,149, 2013.
Physiological signals (like EEG and ECG) detection is the powerful
non-invasive tool widely used for both medical diagnosis and neurobiological
research because it can provide high temporal resolution in milliseconds
which directly reflects the dynamics of the generating cell assemblies. EEG
is also the only brain imaging modality that can be performed without fixing
the head/body. Heart rate variability (HRV) through common ECG signal process
can reflect the sympathetic and parasympathetic changes. Both physiological
signals can be easily applied to daily life healthcare applications. After
understanding the brain dynamic changes on several cognitive studies and
clinical research,
Prof. Lin developed EEG and ECG-based expert systems imbedded with
doctors' knowledge and self-learning ability had demonstrated their high
accuracy and reliability in clinics applications. The developed expert
systems were also integrated with his invented mobile wireless EEG and ECG
systems mentioned in the above for daily homecare applications. This work resulted in the following publications:
(IF:
1.580, Top 25.91%, 64/247 of Engineering, Electrical & Electronic)
(IF:
1.707, 37/128, Top 28.9% of Computer Science, Information Systems)
(IF: 0.420, 63/70 or 90% of ENGINEERING,
BIOMEDICAL) 4.
C. T. Lin, Y. C. Chen, T. Y.
Huang, T. T. Chiu, L. W. Ko, S. F. Liang, H. Y.
Hsieh, S. H. Hsu, and J. R. Duann, “Development of Wireless Brain
Computer Interface with Embedded Multi-task Scheduling and its Application on
Real-time Driver’s Drowsiness Detection and Warning,” (IF:
1.790, 32/70 of Engineering, Biomedical) 5.
N.
R. Pal, C. Y. Chuang, L. W. Ko, C. F. Chao, T. P.
Jung, S. F. Liang, and C. T. Lin, “EEG-based Subject- and Session-independent Drowsiness Detection:
An Unsupervised Approach,” (IF: 0.885,
132/245 or 53.8% of ENGINEERING, ELECTRICAL & ELECTRONIC) 6. C. T. Lin, S. W. Lu, S. A. Chen, H. S.
Pan, C. L. Lin, T. C. Chiu, Y. H. Yu, and L. W. Ko,
“A Novel Telehealthcare Service System with Personal Health Record
Management,”
8. Y. Y. Lin, J. Y. Chang, and C. T. Lin, “A
TSK-type-based Self-Evolving Compensatory Interval Type-2 Fuzzy Neural Network
(TSCIT2FNN) and Its Applications,”
Speeding up the functional brain
imaging is the ‘holy
technology’ of cognitive neurosciences because of its
compelling potential to localize and investigate functional or cognitive
brain responses to realistic, rapidly presented stimuli. Advances in
functional magnetic resonance imaging continue to result in improved spatial
resolution, but
Prof. Lin's innovative work serves two
purposes. First, it establishes the capabilities and utilities of the
noninvasive photoacoustic microscopy system for
brain function studies. Second, it contributes to the understanding of vascular
response to functional stimuli. The technology shows compelling applications
that evidently complements the other methodologies ranging from optical
intrinsic signal imaging to blood oxygen level dependent functional magnetic
resonance imaging. It can boost our understanding on the relationship between
cognitive reactions and brain neuro-dynamics for
solving related clinics as well as daily-life problems. This work resulted in the following publications: 1. L. D. Liao,
Paul C. P. Chao, J. T. Chen, W. D. Chen, W. H. Hsu, C. W. Chiu, and C. T.
Lin, “A Miniaturized Electromagnetic Generator
With Planar Coils and Its Energy Harvest Circuit,” (IF: 1.061, 115/245 or 46.9% of ENGINEERING,
ELECTRICAL & ELECTRONIC) 2. C. H. Tsai,
L. D. Liao, Y. S. Luoa, Paul C.-P. Chao, E. C.
Chen, H. F. Meng, W. D. Chen, S. K. Lin, and C. T.
Lin, “Optimal Design and Fabrication of
ITO/Organic Photonic Crystals in Polymer Light Emitting Diodes using a
Focused Ion Beam,” (IF: 1.575, 66/247 or 26.7% of ENGINEERING,
ELECTRICAL & ELECTRONIC) 3. L. D. Liao, M.
L. Li, H. Y. Lai, Y. Y. Shih, Y. C. Lo, S. Tsang, Paul C.-P. Chao, C. T. Lin,
F. S. Jaw, and Y. Y. Chen, “Imaging Brain
Hemodynamic Changes During Rat Forepaw Electrical
Stimulation Using Functional Photoacoustic
Microscopy,” (IF: 5.937, 3/113 or 2.7% of RADIOLOGY, NUCLEAR
MEDICINE & MEDICAL IMAGING) 4. H. Y. Lai, L.
D. Liao, C. T. Lin, Y.Y. I. Shih, Y. Y. Chen, J. H. Hsu, H. F. Chen, S.
Tsang, and J. Y. Chang, "Design, Simulation and Experimental Validations
of a Novel Flexible Neural Probe for Deep Brain Stimulation and Multichannel
Recording," (IF: 2.628, 16/70 of Engineering, Biomedical) 5. L. D. Liao,
C. T. Lin, Y. Y. I. Shih, Timothy Q, Duong, M. L. Li, and Y. Y. Chen, “Transcranial Imaging of
Functional Cerebral Hemodynamic Changes in Single Blood Vessels Using In Vivo
Photoacoustic Microscopy,” accepted by (IF: 4.522, 27/116 or 16.27% of ENDOCRINOLOGY
& METABOLISM)
6. L. D. Liao,
C. T. Lin, Y. Y. I. Shih, H. Y. Lai, W. T. Zhao, T. Q. Duong, J. Y. Chang, Y.
Y. Chen, and M. L. Li, "Investigation of the Cerebral Hemodynamic
Response Function in Single Blood Vessels by Functional Photoacoustic
Microscopy," Vol. 17(6), Journal of Biomedical Optics, June 2012. (SCI ) (IF: 3.188, 8/78 or 10.27% of OPTICS) 7. T. Y. Tu, Paul C. P. Chao, and C. T. Lin, "A New Liquid
Crystal Lens with Axis-Tunability via Three Sector
Electrodes," accepted by (IF: 1.071, 115/247 or 46.6% of ENGINEERING,
ELECTRICAL & ELECTRONIC) |

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