GE3451 Part A Part B Important questions Anna University | Anna University

 

GE3451 Important questions Anna University | Anna University


Part A


Unit 1

1. Endangered & Endemic Species of Indias

2. Eco-system & Energy Flow / Biodiversity

3. Hot-spots of Biodiversity

4. Types of Biodiversity



Unit 2

1. Important Sources of Air Pollution

2. Effects / Causes of Noise Pollution

3. Hazardous & E-Waste Management

4. Environmental Protection / OHASMS/Pollution


Unit 3

1. Tidal Energy Conversion

2. Renewable & Non Renewable Resource

3. Objectives of Energy Conservation

4. Applications of Hydrogen / Ocean Energy Resources


Unit 4

1. GDP/Sustainability

2  Carbon Footprint/ Carbon Credit

3. Development /MDGS

4. Indicators & Intervention areas Climate Changes


Unit 5

1. Zero Waste & R Concepts / Carbon Cycle > Circular Economy /Sustainable Transports.

2. Green Buildings / Sustainable Urbanization

3. Energy Efficiency / Green Materials

4. Material Lifecycle / ISO 14000 /EIA



Part B - Click here

Comments

Post a Comment

Popular posts from this blog

CS3491 artificial intelligence and machine learning important questions | Anna University

 CS3491 artificial intelligence and machine learning important questions PART A UNIT 1 AI Application Artifical intelligence agents and its types ideal rational agent environment and task environmrnt UNIT 2 Approximate inference in BN/Bayes Rule uncertainty and list the cause of uncertainty Bayesian networks Bayesian inference Global and local semantics casual networks UNIT 3 Probabilistic Discriminative Support vector machine Bayesian Linear Regression Single and Multiple Variables Machine learning Regression UNIT 4 Bagging Boosting knn voing unsupervised learning stacking UNIT 5 stochastic gradient descenty Perceptron Regulrization Multilayer perceptron Error Backpropagation PART B UNIT 1 1.search strategies • uninformed search strategies • Heuristic search strategies 2. constraint satisfaction problems 3. Local search 4. adversarial search unit 2 1.Bayesian networks  2.causal networks 3.Bayesian inference 4.naïve bayes models 5.Bayes theorem and baye’s rules unit 3 1.Linear Regres
Read more