Implementation Research: Concepts and Scope

Related lectures (28)

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Delves into the complexity and interdependencies of transitioning to smart cities, emphasizing the importance of a holistic approach.

Explores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.

Explores algorithm correctness, worst-case complexity analysis, and efficiency comparison based on input size.

Covers the theory and applications of graph coloring, focusing on disassortative stochastic block models and planted coloring.

Explores linear systems, convergence, and solving methods with a focus on CPU time and memory requirements.

Discusses a systematic approach for specifying and operationalizing implementation strategies.

Explores ethical analysis, 'goods at stake', and the impact on human good, emphasizing equality, empowerment, and responsible decision-making.

Discusses challenges in scalable analytics over heterogeneous Big Data and introduces SmartDataLake for efficient handling of raw data.

Covers algorithmic complexity and travel time analysis, focusing on measuring the time taken by algorithms and evaluating their performance.