Lectures related to Expert Systems: Backward Chaining

Information Extraction & Knowledge Inference

Explores information extraction, knowledge inference, taxonomy induction, and entity disambiguation.

Knowledge Representation: Introduction

Covers knowledge representation in AI, logical inference, and applications in various domains.

Knowledge Inference

Explores knowledge inference, embedding techniques, and schema matching in data integration.

Knowledge Inference: Entity Disambiguation and Graph Embeddings

Explores entity disambiguation, graph embeddings, scoring functions, and learning methods.

Inference Engines: Resolution and Horn Clauses

Covers inference engines based on resolution, Horn clauses, filtering, and unification in artificial intelligence.

Inference of Reaction Kinetics

Focuses on the inference of reaction kinetics in combustion, covering rules inference, sensitivity analysis, and Bayesian inference.

Neuro-symbolic Representations: Commonsense Knowledge & Reasoning

Explores neuro-symbolic representations for understanding commonsense knowledge and reasoning, emphasizing the challenges and limitations of deep learning in natural language processing.

Sets and Operations: Introduction to Mathematics

Covers the basics of sets and operations in mathematics, from set properties to advanced operations.

Mechanical and Biological Treatments

Explores water and waste treatment through mechanical and biological methods, focusing on composting and anaerobic digestion processes.

Bayesian Extremes: MCMC Analysis

Explores Bayesian techniques for extreme value problems, focusing on MCMC analysis and the importance of proper prior information.

Water and Wastewater Treatment: Introduction

Covers the basics of water and wastewater treatment, including the history of wastewater treatment, undesirable pollutants, and treatment performance.

Water Treatment: Lutry Production Plant

Explores the water treatment process at the Lutry production plant in ensuring high-quality water supply.

Bayesian Inference: Error Minimization

Discusses error minimization in Bayesian inference and the importance of prior knowledge in the inference process.

Landfills and Waste Management

Explores landfills, waste management, and environmental protection, emphasizing sustainable waste disposal.

Organic Micropollutant Treatment: Plants in Operation and Pilot Studies

Explores the operation of plants for organic micropollutant treatment, including PAC dosage and pilot study results.

Knowledge Inference for Graphs

Explores knowledge inference for graphs, discussing label propagation, optimization objectives, and probabilistic behavior.

Wastewater Treatment I

Explores wastewater treatment principles, BOD removal efficiency, and typical pollutant concentrations.

Waste Management: Challenges and Solutions

Explores the historical evolution and challenges of waste management, emphasizing the need for a multidisciplinary approach.

Wastewater Treatment and Recovery

Explores wastewater treatment, resource recovery, and the history of water systems.

Advanced OMP Removal: Oxidation and Adsorption Processes

Explores advanced OMP removal through oxidation and adsorption processes for effective wastewater treatment.