Research Analysis

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1. Introduction Share with us the kind of research experience you have had and the research goals you have for COLL300. In addition, please take a look at the course objectives in the COLL300 syllabus and discuss the relevance to your career goals.

2. Lynch and the 5 Paragraph Essay Please use the link below to read “The Sixth Paragraph: A Re-Vision of the Essay” by Paul Lynch. In this essay, the author examines the traditional five paragraph format and introduces an alternative strategy for writing essays. Does Lynch make his case for an alternative format? How? Is there a place in academia for the more personal type of essay writing Lynch describes? Would you take his class? Please explain why you would or would not.

“The Sixth Paragraph: A Re-Vision of the Essay”

3. Possible Research Topics You will be working on one topic for the entire course, so it should be one you like. Papers written on a topic that is interesting to the author tend to be stronger and the best papers are often written by those who are passionate about their topics.

For this part of the forum, explore five (5) areas of interest that intrigue you. Think outside the box. Go where you have wanted to go, but haven’t yet. Because the research paper assignment in this class asks for a paper on a topic in your field or major, this requirement could form the outer perimeter of your interests. But inside, there are many variations that could intrigue you. For example, if you are majoring in homeland security but have a love for the visual arts, you may want to explore how messages about homeland security have been conveyed, including what visual techniques have been used. If you are majoring in history and love exploring science, you may look at the roles of specific scientific advances in a particular era. If you are majoring in psychology and love building furniture, you may want to look at how humans think about creating things and how they feel about polishing specific skills.

For this part of the forum, share these thoughts:

A. Briefly describe your major or field of study.

B. Explore topics that intrigue you that may or may not be in this field of study. These may be reflected in the kind of leisure reading you do, the movies or TV shows you choose to watch, the places you tend to go to relax, and the topics you really like to talk about with friends and family. List five (5) of these topics.

C. Try making connections between items 1 and 2 above. How might the five (5) interests listed in item 2 connect with your major or field of study?

In your response to others, try to help them see other connections between their interests and major or field of study.

*Program Description*

The online BA in Supply Chain Management program at American Military University (AMU) exercises your ability to solve supply chain management challenges.

Many students are practicing military and civilian logisticians and supply chain practitioners. AMU’s supply chain major focuses on:

Capacity planning
Demand management
Order management
Warehouse management
Reverse logistics
Transportation
Acquisitions management

Sample Solution

Visual descriptors
To match the available dataset, visual descriptions from the FC7 layer of the AlexNet convolutional neural network will be used. These represent abstract, top-level features that are discovered in each key frame, and are descriptors of color and texture.

3.3 Training process
The datasets that will be used for the training of the recommendation system are called MMTF-14K (Deldjoo), MovieLens 20M (reference), and UC Irvine Machine Learning Lab’s Movie Data Set, which has data on the cast of over 10,000 movies.

3.4 Summarization
During the summarization process, video segments are ranked based on computed similarity measures between the user profile and the movie features. Personalized movie summarization can be seen as “the process of measuring the similarity score of each video segment for the given user preferences and selecting those top ranked segments that will increase the cumulative similarity score of the summary” (Kannan et al., 2015).
First, the similarity between each shot and the user preferences on actor appearance, genre, and visual descriptors is calculated using cosine similarity measures. Each shot is stored as a vector of its features in a high-dimensional space, after which the angles between the vectors are calculated as the cosine similarity between the vectors. After this, user profiles are created based on their ratings on the same features on movies and the similarity between a shot and a user is computed similarly. This should return a ranked list of shots to select for that specific user.

3.5 Evaluation
In accordance with previous studies on automatically generated movie trailers, a qualitative user study will be performed to evaluate the summarization system. This presents the “cold-start” problem of recommendation, as there will be no data on the users in question. To alleviate this problem, the most direct way is to make a rapid profile of a new user by asking for explicit ratings after presenting a number of movies to the user.
In an online questionnaire format, 20-50 users will first be given 20 movies to rate, afte

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