ScholarWorks@Korea University: Baek, Jun Geol

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Baek, Jun Geol (백준걸)

College of Engineering

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Tel 02-3290-3396
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Scheduling:5||Dispatching:4||Rework:4||Fault detection:3||BiDirectional Kohonen Network:3||Anomaly Detection:3||Feature extraction:3||Feature Extraction:3||Anomaly detection:3||Artificial Neural Network:2||Minimum Slack:2||classification:2||Reactive Kanban System:2||Manufacturing:2||Quality Prediction:2||Neural network:2||Time series analysis:2||Fault Detection:2||Data augmentation:2||Imbalanced Data:2||NonStationary Demand:2||Dispatching Rules:2||Demand Clustering:2||Automated Guided Vehicles:2||주기 신호:2||Quality:2||Class imbalance:2||Runtorun:2||ActionReward Learning:2||Inventory Cost:2||ensemble learning:2||EWMA:2||Process control:2||Semiconductor fabrication process:2||Control Chart:2||Semiconductor manufacturing process:2||Control Chart Pattern Recognition:2||MPBC:2||Realtime contrasts (RTC):2||Clustering:2||Time series data:1||Class imbalance problem:1||Generative adversarial network:1||continuous wavelet transform:1||nonreferential method:1||NonParametric Test:1||KS Test:1||Multiple Hypothesis Testing:1||Wafer map image:1||kNearest neighbor approach:1||SOM(SelfOrganaizing Map):1||semiconductor process:1||decision tree(C4.5):1||semiconductor manufacturing:1||Music emotion classification:1||모델모수기반 관리도:1||Timeseries:1||Quality assurance:1||Length adjustment:1||Rotated defects (RoD) transform:1||oneclass classification (OCC):1||Multimode Data:1||Time series forecasting:1||Masked Autoregressive Flow:1||Long Short Term Memory:1||Automation:1||automated manufacturing execution:1||Semiconductor Package Test:1||fault pattern learning:1||kernel density estimation:1||semiconductor manufacturing process:1||Random Forest:1||Root Cause Analysis:1||Wafer Test:1||Failbit:1||kernel fisher discriminant analysis:1||Correspondence Analysis:1||Semiconductor:1||Oneclass classification (OCC):1||Semiconductor Manufacturing Process:1||Statistical Process Control:1||Extreme learning machine:1||NonNormal Data:1||cyclic signal:1||Activated sludge:1||Deadband:1||Parameter monitoring:1||modelbased:1||Bootstrap:1||길이 보정:1||다중목적 유전 알고리즘:1||Incremental learning:1||Stochastic dynamic programming:1||fault detection and classification (FDC):1||automated visual inspection:1||Multivariate to Multivariate Time Series Forecasting:1||LSTM Autoencoder:1||Timeseries Anomaly Detection:1||computerized numerical control (CNC) machines:1||Maximum overlap discrete wavelet transform:1||Indexes:1||production system balance index:1||Data models:1||Faces:1||semiconductor fabrication:1||Semiconductor Manufacturing:1||control chart:1||novelty detection:1||fault detection:1||profile integrated measure:1||feature extraction:1||Spare Parts(수리부속):1||Forecasting Method:1||Failure Period:1||MCSVM:1||Control Limit:1||Algorithm learning based neural network (ALBNN):1||Time Series Analysis:1||Photolithography:1||Spline regression:1||관리도 패턴 인식:1||회귀모델:1||Variable selection:1||Genetic algorithm:1||Automatic defect classification (ADC):1||isolation forest (iF):1||signal segmentation:1||Multiple Discriminator:1||reinforcement learning (RL):1||deep Qnetwork (DQN):1||Attention mechanism:1||Variational LSTM:1||longterm cloud workload forecasting:1||Production system maturity model:1||Maximal overlap discrete wavelet transform (MODWT):1||realtime contrasts (RTC):1||variable importance:1||System Log File:1||Word2Vec:1||convolutional neural network:1||decision trees:1||Statistical process control:1||weapon systems:1||Fail bit:1||Wafer test process:1||Delivery Time:1||OPTICS:1||Classification:1||AutoRegressive Model:1||특징 신호 추출:1||oneclass classification:1||Ammoniaoxidizing bacteria:1||feature selection:1||neural network:1||Kernel density estimation:1||TIFEM(Time Invariant Feature point Extraction and Matching):1||유전 알고리즘:1||Catastrophic forgetting:1||Modified median filtering:1||Reinforcement learning:1||Soft Decision:1||internet of things:1||InterRelationship:1||Bagging:1||Production facilities:1||deep clustering:1||regression ensemble network:1||Control chart:1||Process monitoring:1||kmeans:1||Chemical vapor deposition (CVD) process:1||multivariate exponentially weighted moving average (MEWMA):1||prediction model:1||particle map:1||Multivariate Statistical Process Control Chart:1||Outlier:1||Majority Voting(다수결 투표):1||Demand Forecast Accuracy(수요예측 정확도):1||Low Consumption with Unclear Pattern(적은 소모량과 불분명한 소모패턴):1||Plasma Display Panel:1||CCA:1||Package test:1||Count Data Model:1||Feature selection:1||Maximum Likelihood Estimation:1||Dual filter EWMA:1||Cyclic Signal:1||불균형 데이터:1||Dynamics:1||특질 추출:1||Multivariate control charts:1||Quality index:1||Cyclic Signals:1||support vector machine:1||semiconductor yield classification:1||변수선택:1||Machine Learning:1||SelfAttention Convolutional Autoencoder:1||Temporal Convolutional Network:1||Automated surface inspection:1||Normalizing Flow:1||RealValues NonVolume Preserving:1||Companies:1||Semiconductor device manufacture:1||Cycle time prediction:1||Adaptive breakpointsSAX (ABPSAX):1||Shape segment dynamic time warping (SSDTW):1||Alignment path:1||Predictive Model Update:1||Outlier detection:1||MES:1||Variational Autoencoder:1||remaining useful lifetime:1||weighted kernel density estimation (WKDE):1||ensemble classifier:1||rotation forest:1||Big Data Analysis:1||PostLogistics Support:1||Weighted Decision Tree:1||Wafer test:1||Cox PH Model:1||Cell Level:1||Pearson Distribution System:1||Feature Signal Extraction:1||Unbalanced Data:1||SOM(SelfOrganizing Map):1||DRAM module:1||Highlight detection:1||모델모수:1||K^2관리도:1||KBANN:1||Cyclebased Signal:1||Support Vector MachineRegression:1||시불변 특징점 추출 및 정합:1||Convolutional neural network (CNN):1||Revenue management:1||generative adversarial networks:1||Cause Analysis:1||IntraRelationship:1||Automated guided vehicle (AGV):1||production system maturity index:1||manufacturing digital transformation:1||Noise:1||Training:1||Representation learning:1||Semiconductor device modeling:1||Symbolic aggregate approximation (SAX):1||Oversampling:1||Predictive maintenance:1||multiprofile:1||manufacturing process simulation:1||prognostics and health management:1||health indicator:1||image inspection:1||particle defect management:1||RealTime Contrast:1||MultiClass Classifier:1||Abnormality Detection:1||DBNs:1||Multicollinearity:1||Voltage:1||Support vector data description (SVDD):1||Density weighted SVDD (DWSVDD):1||Survival Analysis:1||Cell Defect:1||UnderSampling:1||Semiconductor Process:1||multiclass classification:1||Support vector machine:1||Semiconductor manufacturing:1||Music video browsing:1||Themebased music classification:1||Flow Time:1||공정이상탐지:1||K^2control chart:1||data mining:1||multivariate analysis:1||Hotelling's T2 chart:1||Average run length:1||Dispatching algorithm:1||Regression:1||Generative adversarial networks:1||Pseudorehearsal strategy:1||local outlier factor (LOF):1||anomaly detection:1||Sensing Level Prediction:1||latent mapping adversarial networks:1||Fault diagnosis:1||Multivariate time series:1||Production systems:1||Smart manufacturing:1||Lifetime estimation:1||Adaptation models:1||temporal convolutional network (TCN):1||Accuracy:1||Predictive models:1||Dynamic time warping (DTW):1||Importance of Variables:1||SOM:1||Health condition monitoring:1||bearings:1||Hybrid Method(하이브리드 방법):1||Principal curvebased monitoring chart:1||Nonlinear process signal:1||Fault isolation:1||Random forests:1||Weighted voting:1||ARIMA:1||TimeSeries:1||Wavelet Transforms:1||Exploratory Data Analysis:1||Canonical Correlation Analysis:1||Fail bit pattern:1||Accelerated Failure Time Model:1||Support Vectors:1||fault classification:1||Wastewater treatment:1||Shot classification:1||Nonidentical Parallel Machine:1||인공신경망:1||시계열:1||Parallel machines:1||Wavelet Transform:1||Cyclic signal:1||semiconductor manufacturing
process:1||Multiobjective GA:1||Liner shipping:1||Distribution of Cell Threshold Voltage:1||NAND Flash:1||Adversarial Autoencoder:1||Manufacturing Process:1||defect synthesis:1||dispatching algorithm:1||Ensemble method:1||Electrolytic copper manufacturing:1||multivariate time series analysis:1||resource management:1||Surveys:1||Contrastive learning:1||multiview augmentation:1||timeseries domain generalization:1||Production:1||Fabrication:1||

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