Identifying and Prioritizing Critical to Quality Characteristics

Research In Motion (RIM) is a leading designer, manufacturer and marketer of innovative wireless solutions. High-quality reliable products are critical in today’s competitive manufacturing environment. To help monitor and improve their processes and products, manufacturers collect large amounts of data from a variety of sources including warranty claims, customer surveys, usage data, inspection, reliability testing and the manufacturing process. The goal of this research project is to determine how to model and make sense of these complex data.

Development of Software Algorithms for Efficient Acquisition and Mining of Hyperspectral Imaging Data

For project, the intern will assist with the development of a new software package for a product line of hyperspectral imaging devices for Channel Systems Inc, a developer of technologies for scientific and industrial imaging and measurement. The general purpose of this research is to implement mathematical, statistical, and chemometric tools as software algorithms in order to enhance quality of data and explore both qualitative and quantitative information contained in the hyperspectral data sets. The proposed research is two-fold.

Convex Decomposition of a Triangle Soup

Radical Entertainment is a video game developer which creates and develops games for all current and next generation platforms. Collision detection forms an indispensable part in today’s 3D game engines. Due to increasing size of the 3D objects used in game development, high-performance collision detection running directly on these objects requires a significant amount of work. To allow for real-time collision detection between a 3D object and other objects in the game environment, the typical approach is to first find for each object a set of best-fitting convex hulls.

Access Network Evolution

Considering the introduction of new network services such as high definition television over the internet protocol (IPTV), new technologies should be introduced and planned in the Bell’s access network to improve the access rate. In this project, to maximize the profitability of the network infrastructure, we propose to explore an access network evolution model (a mixed integer mathematical programming model) to help the network engineers to plan Bell’s access network considering the demand over the time and the introduction of new services.

Clustering of Network Data Streams for Alcatel-Lucent

Alcatel-Lucent manufactures telecommunications equipment ranging from telephone handsets to internet routers. The Research & Innovation group within Alcatel-Lucent is mandated with evaluating new technologies and new ideas that may benefit Alcatel products, thereby benefiting Alcatel-Lucent’s customers, and ultimately the end users. One current area of research is the ability to group streams of traffic into clusters, so that similar types of traffic can be treated together, and to allocate resources suitable for the stream.

Application of Data Smoothing Techniques to Trend Analysis of Large-Scale Survey Data

One of the problems in identifying trends in time series or spatial data is that there are usually so many irregularities or random fluctuations that the underlying trend is difficult to discern. Smoothing techniques can be used to reduce local irregularities (local in the sense of being close in time or geography) so that the underlying trend becomes clear. Although these techniques are widely used in the physical sciences, they are seldom used in the social sciences or in spatial (GIS) applications.

User Behavior Modeling and Scalabitliy Analyzing for VoIP Network

Eyeball Networks is a leading developer of software for the VoIP, video telephony and instant messaging industry. In this project, the intern will investigate and model user behavior of VoIP networks developed by the company. Based on a statistical user behavior model, he will then develop a test tool to collect specific Quality-of-Service performance metrics, so as to analyze the scalability of system, and to formulate its relation with the user behavior model.

Transliteration from Arabic to English

Machine translation has been an active field in Natural Language Processing. Although the quality of translation cannot reach that of a human, it is getting closer. One of the major sub-tasks in this field is ‘transliteration’, which is mapping the letters from the source language to the letters of target language. It would be useful for translating the proper names, location names and any out-of-vocabulary word found in the source text.

Fusing Structural, Functional and Diffusion Tensor MR Image for Neurological Disorders

Structural Magnetic Resonance Imaging (sMRI) provides high-quality images of soft tissue through the use external magnetic fields and electromagnetic radio-frequency pulses to excite protons abundant in the human body. Diffusion Tensor MRI (dtMRI) is a unique, non-invasive imaging technique capable of measuring the anisotropic diffusion of water molecules in biological tissues.

Correlating Intrusion Scenarios with an Unsupervised Learning Model

The increasing sophistication of distributed attacks on networked infrastructure has resulted in a requirement for tools capable of abstracting and alerting network managers of network status across multiple data sources. The basic objective of this project is to provide a framework for correlating information from multiple network sources into a cohesive picture of system status. As such, it is necessary to provide a model capable of correlating information from both spatial and temporal information sources.