Project info
- 1—2 students per group (1 preferred)
- At most 1 group from CS, 1 group from CDA, 1 group from 2nd-major
- Design and Development project
- Updated 2019-06-03[Mon]
Natural science projects often involves recording the time and location particular species (e.g., birds, trees) or specimens (rocks) are observed, as well as observation notes such as their behaviour (foraging, resting), measurements (juvenile bird, 5m tall tree) or conditions (weathered rocks). While the traditional way of keeping records on paper or cards is time-honoured and reliable, information such as the exact time location of records are not easy to keep.
This project is about making a system that would help surveyors to keep records in a convenient and reliable way.
Why can you recognize the voice of your girlfriend/boyfriend on the other side of the phone?
Why can you still recognize a person when he or she deliberately makes his or her sound high pitched?
There are acoustic features that can be extracted to identify the speaker.
Given a recorded speech of person A and some reference of speech of person B, the project is about developing software to produce a sound clip of the speech that sounds like it is spoken by person B.
Some resources that may make experimentation and implementation easier
The Best Track Archive of Joint Typhoon Warning Center (JTWC) (link, another link, yet another link; these links don't work all the time) contain decades of data of tracks of tropical cyclones all over the world. The Severe Weather Information Centre, Meteoalarm, and Pacific Disaster Center contain current data for weather warning. These data are publicly available and can be analyzed for applications based on statistics.
The project is to use these data to answer some questions, such as
The student is expected to come up with questions similar to these above that makes sense meteorologically, and answer them by analysing data.
Some resources that may make experimentation and implementation easier
Although some resources here are Python libraries, there is no restriction on the languages and tools you use. Indeed, a good data analysis and machine learning project like this one often requires the use of multiple languages.
scikit-learnStudents intended to take this project should email me one or more outlines of your app design before selection, and "sell" your idea in a meeting. Expect to refine the ideas for a few times before it is finalised.
The open-sourced language Swift has been evolved to version 5, and is gaining popularity among macOS/iOS/watchOS/tvOS developers, as its library integration is getting better. The project is to develop an macOS/iOS/watchOS/tvOS application by looking into the details of the language and taking advantage of its language features.
It is open to the student to design and implement a Swift-based application or application suite to be run on macOS/iOS/watchOS/tvOS. i.e., it is the student who proposes what the app should be like. Your supervisor's job is to make sure its scale is that of a final year project, and oversees its progress.
Some resources that may make experimentation and implementation easier
Given a scanned image of text, identify the list of possible languages the text is in, in order of decreasing confidence.
Also, recognise the text and output it to a file for verification.
The implementation should be as platform-independent as possible so that it can be run standalone on mobile devices or desktop devices.
Some resources that may make experimentation and implementation easier
Though electronic forms are gaining widespread use, paper forms are still used often. For example, the Government's Care and Share Scheme (CSS) require paper form submission, citing latency in tendering and building a new reliable system.
This project is about building a generic system that after a blank form is read by a webcam or mobile device, the same forms with content can be extracted and processed.
While a generic system powerful for processing the CSS forms would involve written character recognition that can be quite involved, we can start with paper survey forms in which the respondent should put a mark on some of the boxes, with minimal optional free-form writing which can be collected as images.
Ideally, the system should recognise the content in a second or two so autofeeding the forms under the camera is feasible.
A more powerful system would have features such as recognition of corrections in the forms, extraction of the out-of-template elements, recognition of written characters,... your milage may vary.
Some resources that may make experimentation and implementation easier
Collect time series of historical financial data (cryptocurrency prices, stock prices, futures prices, market indices) at different points in time, design an algorithm that would predict their values in the future.
Some factors the algorithm can take into the consideration include the day in month, weekday of day, time of day, various financial indicators, correlations between data from different time series.
Time series of non-numerical data such as news articles, Twitter feeds, or Facebook posts can be analysed to improve the accuracy of the prediction. Indeed, this has been proven to be quite effective in prior studies.
Note that the student is expected to build their own collection of training and testing data.
Be very careful about accuracy claims of better than 70% when you do literature research on how good their systems are, especially when the system uses historical numerical data or financial indicators only.
It is not a easy project, or everyone who can program are already billionaires.
Some resources that may make experimentation and implementation easier
Although some resources here are Python libraries, there is no restriction on the languages and tools you use. Indeed, a good data analysis and machine learning project like this one often requires the use of multiple languages.