1,184 technical terms and definitions
e-waste recycling and material recovery, e-waste recycling material, recycling material recovery, e-waste recycling, recycling material, material recovery
E-Waste Recycling and Material Recovery Introduction & Motivation E-Waste Recycling and Material Recovery addresses a central problem in sustainability process control…
e-waste recycling and material recovery, e-waste recycling material, recycling material recovery, e-waste recycling, recycling material, material recovery
E-Waste Recycling and Material Recovery Introduction & Motivation E-Waste Recycling and Material Recovery addresses a central problem in sustainability process control…
e-waste recycling
E-Waste Recycling Introduction & Motivation E-Waste Recycling addresses a central problem in sustainability process control and recovery prediction: how to Predict recovery…
Elastic Weight Consolidation for Catastrophic Forgetting Introduction & Motivation Elastic Weight Consolidation for Catastrophic Forgetting addresses a central problem…
ewma, spc
EWMA chart is the exponentially weighted moving average control chart that emphasizes recent data while retaining memory of prior observations - it is highly effective…
Exponentially Weighted Moving Average EWMA Charts Introduction & Motivation Exponentially Weighted Moving Average EWMA Charts addresses a central problem in anomaly detection…
data quality
Exact deduplication is the removal of records that are byte-identical or normalized-text identical within a dataset - it is the fastest first-pass step in data cleaning pipelines.…
evaluation
Exact Match is a strict metric that awards full credit only when prediction text exactly matches the reference answer - It is a core method in modern AI evaluation and governance…
extended x-ray absorption fine structure, exafs spectroscopy, exafs analysis, exafs semiconductor, exafs metrology
Once an absorbed X-ray launches a photoelectron above an element-specific edge, the electron does not simply leave the atom. Its wave scatters from nearby atoms and returns with…
interpretability
Example-Based Explanation is an explanation style that justifies predictions using influential examples or prototypes - It makes decisions easier to understand through concrete…
Example-Based Explanations Introduction & Motivation Example-Based Explanations addresses a central problem in explainability interpretation and model understanding: how…
prompt engineering
Example ordering (also called demonstration ordering) is the arrangement of in-context learning examples within a prompt to maximize model performance — because the order in which…
training
Example ordering is the arrangement of individual samples within training streams or prompt demonstrations - Ordering changes local context and gradient interactions, which can…
prompting techniques
Example Ordering is the arrangement of in-context demonstrations in a specific sequence to influence model behavior - It is a core method in modern LLM execution workflows. What…
Selective Example Explanation Introduction & Motivation Selective Example Explanation addresses a central problem in explainability interpretation and model understanding: how…
sample code, template, boilerplate
Code Examples and Templates LLM API Quick Start Templates OpenAI Chat Completion Anthropic Claude Streaming Response Hugging Face Transformers (Local) RAG Template Project…
computing, architecture, software, performance
Exascale Computing Architecture and Software is a comprehensive framework for designing and implementing computing systems capable of executing quintillion (10^18) floating-point…
exaflop performance system, exascale memory bandwidth, exascale power consumption, hpe cray ex exascale
Exascale Computing Architecture: 1.1 ExaFLOPS Frontier System — massive parallel supercomputer achieving one billion-billion floating-point operations per second with extreme…
mpi openmp hybrid programming, chapel pgas language, upc++ partitioned global address, exascale computing project ecp
Exascale Programming Models are the software abstractions and runtime systems that enable scientists to express parallelism across the millions of heterogeneous processing units…
exception handling mechanism, exception handling, handling mechanism
Exception Handling Mechanism Introduction & Motivation Exception Handling Mechanism addresses a central problem in programming process control and performance-exception-overhead…
quality, solder bridge, too much solder, stencil aperture oversized, component float, SPI feedback, print process root cause, fillet distortion, closed-loop print control
Excess solder is the condition where the solder paste actually deposited at a joint exceeds its target volume, and that extra material doesn't just sit harmlessly in place — it…
production
An excursion is an unexpected deviation from normal process behavior or specifications that may affect product quality, requiring investigation and corrective action. Detection…
excursion alarm threshold tuning prediction machine learning, excursion alarm, threshold tuning prediction, spc, excursion alarm threshold tuning prediction, alarm threshold
Excursion Alarm Threshold Tuning Prediction with Machine Learning Introduction & Motivation Excursion Alarm Threshold Tuning Prediction with Machine Learning addresses a central…
production
Excursion Detection is the automated, real-time identification that a semiconductor process has deviated beyond its qualified operating envelope — the triggering event that…
yield enhancement
Excursion Detection is identification of abnormal process or yield behavior that deviates from expected control limits - It provides early warning for events that can rapidly…
production
Excursion Management is the operational framework encompassing the detection, containment, root cause analysis, corrective action, and release protocols for process excursions…
production
Excursion Response (OCAP — Out of Control Action Plan) is the pre-documented, step-by-step response procedure that operators and engineers execute immediately upon receiving…
nlp
Executable semantic parsing is the NLP task of converting natural language utterances into executable formal representations — such as SQL queries, API calls, Python code…
code ai
Execution feedback is a code AI paradigm where generated code is actually executed, and any resulting errors, outputs, or test results are fed back to the model to iteratively…
ai agents
Execution Trace is a step-by-step causal record of how an agent progressed from initial state to final output - It is a core method in modern semiconductor AI-agent engineering…
biden, safety
The Biden Executive Order on AI (October 2023) is the first major binding U.S. federal directive on artificial intelligence safety, security, and trust — establishing reporting…
content creation
Executive summary generation is the use of AI to automatically create concise, high-level overviews of longer documents — distilling reports, proposals, research papers…
self-supervised learning
Exemplar learning is a self-supervised learning approach that trains models to distinguish between different transformed versions of the same image treating each image as its own…
self-supervised learning
Exemplar learning is the early self-supervised approach that groups multiple augmentations of the same image into one pseudo-class to learn invariant features - it predated…
continual learning
Exemplar selection is the process of choosing which specific examples to store in a limited memory buffer for continual learning. Since buffer space is constrained, selecting…
substrate
Exfoliation is the process of peeling or splitting thin layers from a bulk crystalline material using mechanical stress, chemical etching, or ion implantation — ranging from…
exhaust abatement efficiency prediction, exhaust abatement efficiency, abatement efficiency prediction, exhaust abatement, abatement efficiency, efficiency prediction
Exhaust Abatement Efficiency Prediction with Machine Learning Introduction & Motivation Exhaust Abatement Efficiency Prediction with Machine Learning addresses a central problem…
exhaust abatement scrubber efficiency prediction, exhaust abatement scrubber, abatement scrubber efficiency, scrubber efficiency prediction, exhaust abatement
Exhaust Abatement Scrubber Efficiency Prediction with Machine Learning Introduction & Motivation Exhaust Abatement Scrubber Efficiency Prediction with Machine Learning addresses…
exhaust duct static pressure drift prediction machine learning, exhaust duct, static pressure drift, exhaust duct static pressure drift prediction, exhaust duct static
Exhaust Duct Static Pressure Drift Prediction with Machine Learning Introduction & Motivation Exhaust Duct Static Pressure Drift Prediction with Machine Learning addresses…
exhaust fan bearing wear prediction machine learning, exhaust fan, bearing wear prediction, exhaust fan bearing wear prediction, exhaust fan bearing, fan bearing wear, fan bearing
Exhaust Fan Bearing Wear Prediction with Machine Learning Introduction & Motivation Exhaust Fan Bearing Wear Prediction with Machine Learning addresses a central problem…
facility
Exhaust scrubbers neutralize toxic and hazardous gases from process tools before releasing air to the environment. Purpose: Remove toxic, corrosive, or otherwise harmful gases…
exhaust scrubber efficiency drift prediction, exhaust scrubber efficiency, scrubber efficiency drift, efficiency drift prediction, exhaust scrubber, scrubber efficiency
Exhaust Scrubber Efficiency Drift Prediction with Machine Learning Introduction & Motivation Exhaust Scrubber Efficiency Drift Prediction with Machine Learning addresses a central…
exhaust scrubber particulate loading backpressure prediction, exhaust scrubber particulate, scrubber particulate loading, particulate loading backpressure
Exhaust Scrubber Particulate Loading Backpressure Prediction with Machine Learning Introduction & Motivation Exhaust Scrubber Particulate Loading Backpressure Prediction…
manufacturing operations
Exhaust System is the facility subsystem that removes and treats process byproducts and airborne contaminants - It is a core method in modern semiconductor facility and process…
exllama, efficient
EXL2 is an advanced quantization format for ExLlamaV2 that uses dynamic per-layer bit allocation to achieve optimal quality-size trade-offs for GPU inference of large language…
quantization, inference, python, fast inference
ExLlama (and its successor ExLlamaV2) is a hyper-optimized Python/C++/CUDA inference engine specifically designed for maximum speed on NVIDIA GPUs — writing custom CUDA kernels…
exoskeleton human augmentation, exoskeleton human, human augmentation
Exoskeleton Human Augmentation Introduction & Motivation Exoskeleton Human Augmentation addresses a central problem in robotics process control…
exoskeleton human interface, exoskeleton human, human interface
Exoskeleton Human Interface Introduction & Motivation Exoskeleton Human Interface addresses a central problem in wearable process control and force-feedback-fidelity prediction…
metrology
Expanded Uncertainty ( ) is the combined standard uncertainty multiplied by a coverage factor to provide a confidence interval — , where is typically 2 (providing approximately…
process
Expanding the Process Window is the deliberate engineering of wider acceptable parameter ranges — achieved through design rule relaxation, process improvements, material changes…