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-====== Proposed Projects for Fall 2014 ======
+====== Proposed Projects for Fall 2015 ======
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+=====Clustering High-Dimensional Data Sets=====
-===Dynamic Interface Detection and Control Project===
+**Supervisor: Suprakash Datta**
+Clustering is a basic technique for analyzing data sets. Clustering is the process of grouping data points in a way that points within a group are
+more similar to each other than points in other clusters. Many clustering algorithms have been developed over the years. However no single algorithm works well for all data sets. Further, most clustering algorithms have running times of the order of n^2 or n^3, so that they are not feasible for data sets with hundreds of thousands of points. In this project we will design good clustering algorithms for large real data sets. In particular we are interested in
+Biological data sets.
+Our data sets will include those obtained from Flow Cytometry data. Flow Cytometry is a common technique in many areas of Biology, particularly Immunology. Typical usage involves testing a blood sample for 25 attributes on a per-cell basis, and thus typical data sets are arrays of 500,000 points in a 25 dimensional space. The aim is to identify clusters that correspond to a biologist's notion of a cell "population". In addition to the size of the data, the factors that make this problem difficult are heterogeneity of population sizes and densities and overlapping populations. With the help of collaborators we proposed an accurate algorithm called SWIFT (Cytometry A. 2014 May;85(5):408-33) that successfully finds small cell populations of interest to Immunologists. This project attempts to design and implement algorithms that are faster than SWIFT but at least as accurate. The supervisor has collaborators in Immunology who are experts in interpreting and analyzing Flow Cytometry data. Their expertise will be used to design and validate effective clustering algorithms that can run on large data sets.
+No Biology knowledge is required. The student should be a strong programmer. Knowledge of C/C++ is desirable but not essential. The work involves reading and understanding existing algorithms and working with the supervisor to design and implement improved algorithms and to measure the performance of the proposed algorithm(s).
+For more information, please send email to datta@cse.yorku.ca.
+Required Background: General CSE408x prerequisites
+\\
+=====Metaheuristic-based Optimization techniques=====
+**Supervisor: Suprakash Datta**
+Optimization is a crucial step in many computational problems. For computational problems that seem (or are known to be) intractable, metaheuristic-based techniques often work well in practice. These are typically randomized algorithms, often inspired by physical or biological systems. Examples of such algorithms include simulated annealing, genetic algorithms and ant colony optimization. In this project we will focus on particle swarm optimization (PSO), a technique inspired by the search for food by flocks of birds or schools of fish. Briefly, a set (or population) of candidate solutions (called particles) are maintained at all times by the algorithm. These particles move in the search-space using simple rules that make use of the best solutions found so far by the particle as well as by the swarm. Movement of particles result in new particles being generated. The process is repeated until some termination criteria are met and the best solution found is output by the algorithm. While there is no guarantee of optimality, PSO has been shown to produce good or very good solutions for many practical problems. Many variants of PSO's have been proposed. In this problem we will study the performance of some PSO variants on both artificial and real optimization problems.
+The student should be a strong programmer. A good grasp of algorithms and knowledge of C/C++ are desirable but not essential. The work involves reading and understanding existing algorithms and working with the supervisor to design and implement improved algorithms and to measure the performance of the proposed algorithm(s).
+For more information, please send email to datta@cse.yorku.ca.
+Required Background: General CSE408x prerequisites
+\\
+=====Data visualization in Skydive=====
+**Supervisor: Jarek Gryz**
+Skydive is a prototype system designed for database visualization using a concept of the so called
+data pyramid. The system is composed of three modules (DB - Database Module, D2I -
+Data-to-Image module, and VC - Visualizaton Client). Each is designed to use a different type
+of computer memory. The DB module uses disk to store and manage the raw data, and materialized
+data pyramids. The D2I module works with a small subset of the aggregated dataset,
+and stores data in main memory (RAM). The VC module uses the graphic card’s capabilities to
+perform more advanced operations – such as zooming, scaling, panning, and rotation – over the
+graphical representation of the data.
+Currently the system support three presentation models implemented within the Visualization
+Component, namely:
+• a 2D heat-map;
+• a 2.5 D heat-map by 3D barchart; and
+• a 2.5 D terrain (by mesh and UV-mapping).
+The goal of the project is to implement two additional ways of data visualization as well as
+extend some of existing ones, that is:
+. Implement and test functions for data pyramid-based visualization of time series.
+. Implement functions for visualization based on cross-product of data pyramids.
+. Add support for specular and normal maps for 2.5 D terrain presentation model.
+Required Background: CSE 3421, Java programming course, (C programming course a plus)
+\\
+=====Genome-wide identification of plant micro RNAs=====
+**Supervisor: Katalin Hudak**
+The Hudak Lab in the Biology Department has an opening for a fourth-year Honours student to assist with a bioinformatics project. We study the pokeweed plant, Phytolacca americana, which displays broad-spectrum virus resistance. To evaluate pokeweed gene expression, we recently sequenced the plant’s mRNA and small RNA transcriptomes under jasmonic acid (JA) treatment. JA is a plant hormone that mediates defence against pathogens and insect herbivores. We are interested in learning how pokeweed gene expression is regulated by miRNAs during biotic stress.  Please note: no previous knowledge of biology is required.
+Working with the support of a PhD student, your project will involve:
+) Prediction of micro RNA (miRNA) targets on the basis of complementary sequence matches
+) Correlation of miRNA and mRNA expression changes to identify genes that are regulated by miRNAs
+) Conducting pathway analysis to determine which biological processes are controlled by miRNAs
+) Construction of a miRNA/target interaction network to visualize predictions
+This work will contribute to a scientific manuscript on miRNA-mediated gene regulation in pokeweed during response to JA.
+Requirements:
+) Pre-requisites as per EECS Calendar
+) Facility with script-writing/modification (in Perl or Python)
+) Preference for students with knowledge of statistics and familiarity with R programming
+) Able to begin in September 2015
+Learning outcomes:
+) Manipulate and analyze quantitative biological data
+) Develop and test hypotheses by modifying existing software and writing new script
+) Manage a CentOS computer server to store and facilitate ongoing research
+No knowledge of biology is required.
+For more information, please see:
+ Hudak Lab website- http://hudak.lab.yorku.ca/
+RNA sequencing- http://www.illumina.com/applications/sequencing/rna.html
+miRNAs- http://en.wikipedia.org/wiki/MicroRNA
+\\
+=====Dynamic Interface Detection and Control Project=====
 **Supervisor: Michael Jenkin**
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-====== Hunting for Bugs in Logging: applying JPF to log4j ======
+====== JPF in a Jar ======
 **Supervisor:** Franck van Breugel
 Description:
-Java PathFinder (JPF) is a tool that can detect bugs in Java code.
+JPF, which is short for Java PathFinder, is an open source
-The Java library Apache log4j allows developers to control which log
+tool that has been developed at NASA's Ames Research Center.
-statements are output.  In the past, Dickey et al. [1] have attempted
+The aim of JPF is to find bugs in Java code.  Instead of
-to detect bugs in log4j by means of JPF with very limited succes.
+using testing to find those bugs, JPF uses model checking.
+The facts that JPF is downloaded hundreds of times per month
+and that some of the key papers on JPF have been cited more
+than a thousand times reflect the popularity of JPF. In
+fact it is the most popular model checker for Java.
-Recently, in collaboration with Shafiei (NASA) we have developed
+A study done by Cambridge University in 2014 found that the
-an extension of JPF called jpf-nhandler.  The aim of this project
+global cost of debugging code has risen to $312 billion annually.
-is to apply this extension to log4j.
+Furthermore, on average software developers spend 50% of their
+programming time with finding and fixing bugs.  As a consequence,
+advocating the use tools, such as JPF, may have significant impact.
-[1] David A. Dickey, B. Sinem Dorter, J. Michael German, Benjamin D. Madore, Mark W. Piper, Gabriel L. Zenarosa. "Evaluating Java PathFinder on Log4J."  2011.
+Installing JPF is far from trivial.  The tool itself has been
+implemented in Java.  Therefore, it should, in theory, be
+feasible to encapsulate JPF in a Java archive (jar) file.
+This would make it significantly simplifying the installation
+process of JPF and, therefore, make the tool more easily
+accessible to its potential users.
-**Required Background:** General CSE408x prerequisites
+The aim of this project is to attempt to put JPF in a jar.
-\\
+Since JPF relies on a number of configuration files, so-called
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+Java properties files, incorporating these properly into the
-\\
+jar is one of the challenges.  Setting JPF's classpath is
+another challenge.  Since JPF changes almost on a daily basis,
+our modifications to JPF should ideally be limited to only a
+few classes, yet another challenge.
+In this project you may collaborate with graduate students
+of the DisCoVeri group (discoveri.eecs.yorku.ca) and
+computer scientists of NASA.  For more information, feel
+free to send email to franck@cse.yorku.ca.
-====== Immersive Virtual Reality Kitchen Planner ======
+**Required Background:** General CSE408x prerequisites
-**Supervisor:** Wolfgang Stuerzlinger
-**Required Background:** General 408X prerequisites, 3D Computer Graphics (3431) completed or equivalent, 4431 desired, Javascript or C# coding experience
-This project implements a kitchen planner application for an immersive virtual reality system. The implementation will be based on Unity 4.
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-======3D Interaction in Immersive Virtual Reality======
-**Supervisor:** Wolfgang Stuerzlinger
-**Required Background:** General 408X prerequisites, 3D Computer Graphics (3431) completed or equivalent, 4431 desired, Javascript or C# coding experience
-This project implements and tests various 3D Navigation and 3D Interaction methods in an immersive virtual reality system. The target is to enable the user to roam freely in a large environment while still being able to interact with the environment. The implementation will be based on Unity 4.
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-======Reliably tracking horizontal eye movements======
-**Supervisor:** Wolfgang Stuerzlinger
-**Required Background:** General 408X prerequisites, C++/C# coding experience. Ideally CSE3451, CSE4422 or CSE4452.
-**Description:** The Intel Perceptual Computing SDK includes support for head tracking and facial analysis. The project will use the Creative Interactive Gesture Camera, a depth camera designed to work with the SDK. Based on these technologies, the project implements an eye tracking system that detects the horizontal eye position and consequently, if the user is looking at the left, center, or right portion of the screen. Based on this, the project will implement a simple media browsing browsing system, e.g., for TV channels, music, or videos.
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 ======Model-based Design and Development of Embedded Systems with Code Generation Tools======