The document summarizes the results of a questionnaire about preferences for short films. It found that the target audience was teens and young adults. Most respondents were female, so the film will include more female themes but also some male aspects. While most people don't like short films due to boring storylines, the film will try to have a unique storyline. The most popular genres were drama, comedy, romance, action and fantasy, so the film will be a hybrid of genres. It will last around 6 minutes to keep the audience intrigued.
This questionnaire was constructed to allow me to gain a better understanding of the demographics of my target audience. I was able to identify the audiences expectations for thriller films and psychological thriller films through the use of qualitative and quantitative data responses which will influence the way that my media product will be constructed because I am aware of my target audiences needs.
This questionnaire was constructed to allow me to gain a better understanding of the demographics of my target audience. I was able to identify the audiences expectations for thriller films and psychological thriller films through the use of qualitative and quantitative data responses which will influence the way that my media product will be constructed because I am aware of my target audiences needs.
Creating a professional online journalism portfolioDamian Radcliffe
Slides from a class given at the University of Oregon School of Journalism and Communication on 26th October 2015, covering portfolio websites, their role in job hunting and defining your personal brand, as well as a review of examples of sites managed by current journalists.
Social Media in the Middle East: The story of 2015Damian Radcliffe
Fourth annual report on the state of social media in the Middle East and North Africa. The report looks at data from a wide variety of public sources to identify trends in usage, controversies and wider developments across Facebook, WhatsApp, Instagram, Twitter, Snapchat and other networks.
These are the results and analysis from my main task audience survey. They have helped me discover things about my target audience and also given me confidence in some of the decisions I have made about the film.
This analysis is based on the drama movie that I'll be making. It includes references of how the people responded and how ill refer these in the movie.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
2. WHAT IS YOUR AGE
GROUP?
I will be aiming my short
film towards teens and
young adults. So I will
consider including
appropriate themes to
create relationships.
3. WHAT IS YOUR
GENDER?
The majority of the
people who answered
my questionnaire were
female so I could include
more female themes
within my short film. I
could also include some
male aspects to draw
them in.
4. HAVE YOU EVER
WATCHED A SHORT
FILM?
Everyone who answered my
questionnaire had watched a
short film so this was helpful
for the rest of my
questionnaire.
5. DO YOU LIKE SHORT
FILMS?
As the majority of
people don’t like short
films due to boring
storylines, I will try to
produce a unique
storyline to intrigue
my audience.
6. WHAT GENRES DO
YOU PREFER?
The most popular genres
were Drama, Comedy,
Romance, Action and
Fantasy.
I will produce a hybrid of
genres to attract a larger
audience.
7. HOW LONG DO YOU
THINK SHORT FILMS
SHOULD LAST?
I will make my short
film last around 6
minutes so this isn’t too
long or short to keep
the audience intrigued.
