Attached are the final versions of my paper and poster
This week, I spent time figuring out how to make the software publication ready, and discussed with Craig on whereabouts of the server and database
This week, I finalized my poster and prepared my paper for the evaluation draft submission. I also met with Craig to discuss taking the application live.
This week, I started working on my poster, and revised my paper based on the feedback I received from Dave and Ajit
This week I tested out the reader with student interface, and checked if self-check in and check-out worked properly. I also met with Craig and discussed plan to migrate the application to the server and perhaps have it ready for the EPIC expo.
This week I spent most of my time working on the paper, and finished the implementation and design sections. I also started working on the administrator interface and got a good portion of it done.
This week I finished implementing a rough version of the student user interface. I spent a considerable time discussing the logic behind to student check out and check and what measures were necessarily to put in. I received feedback from Ajit on the design, and modified my approach based on that.
This week I discussed the structure of my paper with Ajit, and received feedback on how to explain the design and implementation sections. I also started working on implementing the student user interface.
This week I finalized the schema for the database with Ajit, and familiarized myself with the PostgreSQL commands after receiving the log in information from Craig. I faced an unexpected challenge with the ordering of the RFID device from Ebay. Instead I researched for two days and found a few other cost friendly options in the US, and have proposed to the department to purchase one of them.
I am planning to finish all the software end of the project by the time I get my hands on the device!
This week I met with Ajit and discussed some of the necessary features for the user interface that the administrator will be using. This involved seeing a list of recently checked out items, adding new objects, and adding new users. I also met with Craig and discussed the back-end work. We decided to use Django and PostgreSQL.
This is my first post for CS488.
- Met with Ajit to plan the next few weeks, and decided to start the data collection this week.
- Edited the timeline a little bit to include implementation of the project.
- I’ve shared my box folder with Dave and Charlie and will soon be contacting Andy Moore for access to volumetric data collected by the Geology students across campus.
My first idea is for a application that allows the computer to be navigated with gesture control, initial thought is to use the camera that is on almost every laptop to map the mouse pointer between say the thumb and the forefinger, and when the thumb and forefinger touch emulate a the click of the mouse. Further interface could also be implemented such as a virtual keyboard or talk to text features, basically attempting to replace a mouse and keyboard, further research needed.
My second idea is either a stand alone software or a Photoshop add on for real time pixel art animation editors. Given a sequence of images with a specified distance apart, color pallet and speed at which to move through the images, one could make a change and the animation would update real time, also allowing the change of color pallets.
My third idea is a personal budget planning and expense tracking app. I person can track what they buy by inputting the cost of an item and categorize that item falls into (possibly further subcategories for more in depth statistics) ie $16.69 on groceries on 1/21/19, $32.55 on cloths on 1/22/19 etc. One can input there salary and how much they want to not spend and the app could keep track and suggest a budget for you, give statistics about your spending patterns etc.
This week I met with Ajit for an hour. We went over timeline and design of my project. I also met with Craig and ordered the RFID reader and tags after approving them.
This week, I was focused on making the poster and including the final results of my research.
Submitted the CS second draft on Wednesday and waiting for Xunfei’s Feedback. The demo presentation went well without much questions from the audience. On working on making the poster for the presentation on Dec 5.
- Met with Ajit to talk about the follow up steps on Monday.
- Based on the feedback, we decided to focus efforts on the following:
- Updating the design framework/diagram,
- Writing and explaining the design of the project,
- Read other published papers to get an idea of the structure of the paper,
- Add transition paragraphs in the paper.
Worked on the demo presentation. Experimented with 2 datasets each taking 4 hours of run time. One observation I found is that changing the labels of the fake news changes the accuracy. It was found that detecting reliable news rather than fake news was statistically better in performance.
- Did second pass for more papers for this week, focusing on the design, and processes used,
- Met with Ajit on Monday to discuss the project and plan rest of the semester,
- Took Quiz 5 for Project update.
The front end development part for my project is almost complete. The database setup and connection is completed. The integration of backend machine learning model with flask has worked. The flask prediction model has also been linked with the frontend. There are some issues with websites that are not blog and I am fixing the issue. Next step is to make a retrainable model.
- Did second pass for three papers for this week,
- Worked on First draft for proposal.
Worked on the front end component of the project. With the sys admin telling me that they cannot host flask for my project. I started to look for alternatives. Heroku could not be used as it did not provide support for sci-kit the way I needed. Worked with Ajit to edit my first draft paper. Mades some figures of the architectures.
- Did second pass for three papers, posted on the box,
- Took Quiz 4 for CS388,
- Chose 3 papers for next week.
Finished the machine learning pipeline with actual experimentation. Having issues getting Flask setup and have been in touch with the SysAdmins. Halfway through the first draft of the paper. Made new design for the system architecture.
- Finished literature review.
- Selected 1 topic from the remaining two for Quiz 3 (proposal)
I did an experimentation with Sci-kit Learn. The run-time for the program was more than 2 hours. Testing the multiple dataset has been an issue lately.
Progress on the draft of the paper. Related works is almost completed.
- Started 2nd pass for the papers.
- Continued work on literature review.
Worked on the first draft of the paper. Focusing on the related works and findings currently.
- Finished bibliography.
- Selected two topics and prepared topics presentation.
- Started literature review.
In the past week, I have been working on the related for my three project ideas. I wrote an annotated bibliography for each topic with five different sources. This week got rid of one of the ideas and decided to work on these two:
- Sleep Pattern Classification
- Modified method for HDI calculation
Build a rough machine learning pipeline for testing. Worked with Ajit to update timeline. Started with the first draft of paper.
- Continued working on Annotated Bibliography:
- Found more papers on the topics,
- Did the first pass reading for all of them.
Created a smaller dataset using pySpark for training and testing the fake news model.
- Met with Andy Moore and talked about projects regarding natural disasters.
- Realized that many of the ideas were too big for a semester, and started researching in Earthquake Early Warning systems
- Worked on Quiz 2, and collected papers for each topic.
- Worked on Annotated bibliography.
Worked with setting up sci-kit learn and testing environment. Got Craig to give me access to Pollock and Bronte.
- Read the papers about how to read a paper.
- Met with Michael Lerner regarding one of the strategies talked about in his research last year.
- Found 5-7 papers related to each of the three topic areas.
- Attempted the Quiz 1 for CS388.
Met with my advisor twice, worked on an updated timeline. Worked out a design framework and prepared the presentation slides.
- Met with Ajit to filter ideas regarding parallel computing, and machine learning.
- Emailed Andy Moore in Geology to talk about Earthquake and Tsunami predictions.
- Emailed Charlie for suggestions regarding my Structure From Motion idea.
- Searched for more specific details on work done in similar areas.
Started the project pipeline for Fake News Detection.
- Looked for three general areas that I want to do my research in, namely:
- Structure from Motion
- Disaster prep and management
- Parallel Computing
- Searched for some related work that has happened in these areas.
- Pillow AI: I am thinking of having Arduino device built-in the pillow, which can be charged and have heart-rate sensors to receive heart-rate while the person is sleeping. Having this data, I could determine sleeping patterns and find the Light Sleep phase. After having a light sleep phase, I can send the alarm signal to the phone to wake up a person closest to the time when they set the alarm.
- Signature Recognition: I can use some deep learning algorithms, create a testing dataset and collect signatures of a lot of people. After that, I want to determine if the given signature is fake or a person’s real one.
- Human Development Index: I’ve been working on this project with my Econ professor this summer on the research, but the project turned out to be so exciting I might use it for my senior research project. So the basic idea is that have a platform(website) where people can go and choose their indicators(whatever they think are essential for country’s development) for the Human Development Index and get a new ranking of those countries. Keeping track of all given inputs from users, I can make some cool data analysis with it. Back-end will be python with pandas library, and dataset will be streaming live Restful API from Worldbank database.
A Data Science and Machine Learning Project to explore the stock data of a particular stock exchange. The exploration will be focused on observing the repetitive trend in stock markets and relating it to the business cycles. Some questions that can be asked in this project is as follows:
- Is there any particular pattern that stocks market follow in between the end of December and start of January. This time period is said to be a speculative time for investors and trader. Particularly, it is observed that traders can benefit by buying in December and selling in January because of the closure of accounting books of firms.
- Another interesting phenomenon would be to ask if there is a trend in between bull market and bear market. That does a bull market always have to be followed by a bear market and vice versa.
The main resource for this project would be “Python for Finance” Analyze Big Financial Data by O’Reilly Media. Some other resources are as follows:
A portfolio tracker that keep tracks of investments in stocks in a particular market. Keeping in mind the time limitation, it would be better to focus on small markets for this project. The web-based application will provide different portfolios to users to keep track of their investments and to easily look at their best and worst investment.
In this project, the major component of research would be figuring about how to structure the database design for such a system as well as enforcing multiple levels of database transactions logging. A further investigation might be in mirroring the data for backup. Along with this, the project can have a data analysis research segment for any market that might suffice the need of this project.
The research component of this project will also lie in using Model View Controller design pattern to develop such a system. This project essentially has two part, the software design, and the data analysis research. If this project is taken, serious amount of planning has to be done to ensure that all both the component of the project is completed,
The project is about creating a software that can determine an optimal value for a company by looking at their balance sheets records in the past to predict future cash flows. Financial analysis methods such as DCF, DDM and FCE can be implemented in this approach (only one). This system would be automated using machine learning and data analysis.
The main research for this project is coming up with a model that can predict the future cash flows of a company by looking at past trends. Regression will be one of the core Machine Learning Techniques that will be applied in this research. Some resources for this project will be “Python for Finance” Analyze Big Financial Data by O’Reilly Media.
The valuation of the company is doing using what finance people call as the time value of money adjustment. Basically, what this means is that getting $100 today is better than getting in tomorrow or anytime in the future. Thus, all future cash flows that the company generates needs to be discounted at today’s value. In order to do this, we need to figure out the discount rate. There are different approaches we can take for this. For instance, we can use the interest rate provided by the Federal Reserve or we can make our own that can reflect the real financial scenario better. The Capital Asset Pricing Model can be used in this scenario but there are things such are beta and the free interest rate that needs to be estimated. This estimation can be the second part of the research.