1-Read the attached Notes on Film, which describes a number of common filmmaking techniques, then read the attached Characteristics of Alfred Hitchcock’s Style in filmmaking. Then view the classic film North by Northwest, directed by Alfred Hitchcock. It is available on HBO (you can get a free 10-day subscription), Netflix and several other streaming services. It is also available free on Youtube scene by scene, but not as a continuous film.
2-Provide an analysis of North by Northwest in which you identify and describe five examples of filmmaking techniques utilized in the film, and also identify and describe examples of all of the characteristics of Alfred Hitchcock’s style.
3-This may be in either a narrative or bullet point format.
See Characteristics of Alfred Hitchcock’s Style.docx (11.651 KB)
Types of films:
Narrative – tells a story (many sub-genres such as Western, detective story, science fiction, horror, romantic comedy, etc.) which may be fictional or true
Documentary – sociological or journalistic approach; based on reality
raveling Salesman Problem – Genetic Algorithm The Traveling Salesman Problem is a famous NP-complete problem involving the generation of the shortest route connecting nodes within a graph, with the condition of starting and stopping at the same node. Given the problem’s classification as NP-complete, there is no polynomial algorithm which can perfectly solve this problem. However, randomized optimization can be utilized to calculate approximate solutions. We will apply our collection of optimization algorithms – Randomized Hill Climbing, Simulated Annealing, Genetic Algorithms, and a newcomer, MIMIC – in order to determine the best-performing optimization algorithm for this specific problem. In order to determine the optimal algorithm, we designed two experiments; one to see how each algorithm’s accuracy scales to increased problem complexity, and another to observe each algorithm’s optimization efficiency (by determining how accuracy converges over a fixed amount of iterations). We used the default testing hyperparameters provided by our ABAGAIL implementation, which are listed in Table 4. SA Starting Temp Cooling Factor 1E12 0.95 GA Pop. Size # to Mate # to Mutate 200 150 20 MIMIC Sample Count # to Keep 200 100 Table 4. Optimization algorithm hyperparameters, pulled from ABAGAIL’s Traveling Salesman testing implementation. Randomized Hill Climbing not listed, as no hyperparameters are applicable. We ran our complexity experiment over Traveling Salesman problems with size from 50 to 250 (with steps of 50), where the size N represents the number of nodes in the graph (Figure 5). It’s evident that for all algorithms, increased graph nodes result in poorer fitness. This i>GET ANSWER