Development of a subject-centered social media

Developing subject-based social media requires proper interaction with the users by learning and analyzing their profile and dynamically incorporating their opinion. In this project, a crowd-based profiling of users with respect to their peers will be developed and confidence factor calculated based on the collective opinion of the crowd will be assigned to the individuals’ opinion. There is a prototype system already developed as a proof of idea. The intern will enhance the prototype by adding new functions and modules to it.

Wireless Overhead Line Temperature Sensor Based on RF Cavity Resonance, Design Improvement and Measurement

A wireless sensor has been designed to monitor overhead line temperature. The economic importance of this issue is to maximize the power transfer capacity of the lines. The sensor has two main parts, a local interrogator and a passive battery-less sensor. The power to turn on sensor comes from interrogator. The sensor measures the temperature, and transfers the data to interrogator for signal processing. The measurement accuracy of the sensor is reported to be about 0.07°C. There are some sources of error in sensor measurements.

Subsea Pipeline Risk-based Integrity Assessment

The first objective of this internship is testing and validation of recently customised RISKWISE software for subsea pipeline application using a case study. Second objective is to develop a user manual for the software for future reference. Testing and validation of the software would help provide reliability and confidence in the tool usage that will help in decision making regarding optimal inspection and maintenance planning for risk mitigation.

Inversion of geophysical data

When using geophysical methods to gain insight into the structure of the earth, large geophysical data sets are collected. Since the earth is a 3D structure, the data must be interpreted and processed in 3D to be of the most value in the exploration process. This research will develop the capability to invert large gravity, magnetics, and airborne EM datasets accurately and in a reasonable timeframe. This requires the research and development of inversion software, data visualization and QC software, and inversion setup scripts.

Cloud-based Reengineering and Interoperability of a Primary Care EMR

Computer-supported Electronic Medical Record (EMR) systems are increasingly replacing conventional paper-based information management in primary health care clinics. Recently, there has been a trend to make these EMR systems available in a Cloud-based, interoperable and network-centric architecture. The internship will research ways to increase the interoperability of an existing EMR product, with respect to emerging health information interchange standards and protocols.

Investigating Open Scholarship and Inclusive Practices in Higher Education

The objective of this project is to create a set of innovative business intelligence tools to enhance advanced data mining and data visualization capabilities of the Perspective PPM 2000 software system. The Perspective software is an incident management system that facilitates corporate incident data collection, reporting, analysis and management. Incident data is a post-event record of accidents, thefts, hazards, or other unusual events related to an organization’s infrastructure.

Performance Evaluation for the Infer Engine–Optimization on Dynamic Advertising

Different from traditional online advertising, dynamic media campaigns show different impressions (visitors to a web page) with different advertisement based on the characteristics of the impression. Infer Engine is a system that optimizes bidding for media campaigns by maximizing total profit for every impression. The theoretical foundation of the Engine is a by statistics based learning theory for predictive models and mathematics analysis for optimization. The proposed project is on performance valuation of the Infer Engine with different learning algorithms.

Advanced Network Intrusion Detection Using Automated Algorithms and Threat Models

Computer attacks such as viruses, Trojans, etc. are a continuous problem for governments, companies, and individuals. The most common methods of detecting these computer problems like anti-virus systems rely on an attack being known and described before it can be detected. This opens a hole in computer security systems for new attacks that have not yet been detected. This project focuses on the use of mathematics and advanced anomaly detection algorithms to determine 'normal' and 'abnormal' behavior on computer networks, and attempts to detect attacks by detecting 'abnormal' behavior.

Book Recommendation: Improving Collaborative Filtering with Content Information

Collaborative filtering is a product recommendation technique for making automated product suggestions to a user based on the preference information from similar users. Traditional recommendation algorithms drive personalized recommendations using the data from user purchases and ratings. For e-book retailers, besides user purchases and ratings, product features such as book content and metadata also provide valuable information that can be used 'to improve the recommendation precision and recall.

Predicting for Targeted Advertising by Maximum Information Coefficient

Predictive modeling is a statistical data mining approach that builds a prediction function from the observed data. The function is then used to estimate a value of a dependent variable for new data. Then objective of the project is to develop predictive models by machine learning approach and data mining techniques from the large volum of data collected at the partner site. The intension is to study applications of some most recent adademic reserach restuls to an industry product, a real-time analytics and data-intensive platfome.