Work History Part 7: RIT Electrical Engineering Dept.

Employer: RIT Electrical Engineering Dept.

Location: Rochester, NY

Position: Software / Firmware Engineer

Period: June 2010 - December 2010

Ever since I began my thesis work I've had a growing interest in applying my skills to the field of medicine and medical research. I find devices that interact with the underlying biomechanical processes of the human body fascinating. I enjoy learning about how the human body functions and technological advances ranging from neural modification to gene manipulation and artificial limb development.

Through the recommendation of a certain kindhearted software engineering professor, I was put in contact with the up-and-coming RIT Biomedical Engineering Dept. Within a matter of days I was hired by the RIT Electrical Engineering Dept. (which forms the backbone of the new biomedical engineering dept.) to begin working on the body area sensor network (BASN) project.

The BASN consists of multiple wireless nodes strapped to a user's body. Each node is about the size of a watch and the band is similar to a watchband. Each node collects biometric information, such as body temperature and limb orientation and acceleration, based on where it is positioned on the user's body. Each collector node wirelessly sends data back to a central access point. In turn the access point aggregates all of the data and wirelessly sends it to a USB dongle attached to a host machine where it is processed by a host-side application.

Each node consists of custom-designed PCB architecture and firmware API. A complementary API allows host-side applications to communicate with the nodes using the USB dongle. The centerpiece of each node is the Texas Instruments CC430 microcontroller. Wireless communication leverages the Texas Instruments SimpliciTI protocol.

The goal of the project is to implement a development platform that will allow future developers to create custom applications such as:

• Seizure / muscle tremor detection and patient caretaker alert system.
• Local positioning system using dead reckoning from a known starting location. Can be used to track firefighters as they enter a burning building.
• Wireless electrocardiograph (ECG). Current ECG models use 10 wired electrodes and are cumbersome.
• Soldier injury detection system. In a battle scenario, the command center can track the physical condition and stress levels of soldiers in the field.

Responsibilities and accomplishments:

• Developed 3D proof-of-concept applications demonstrating the ability to capture and process biometric data.
• Leveraged existing firmware to set up a low-power RF communication network between wireless nodes and a host-side USB dongle.
• Implemented a device driver in Linux to provide an API for interacting with the RF network through the host-side USB dongle.

Work History Part 6: RIT Industrial Engineering Dept.

Employer: RIT Industrial Engineering Dept.

Location: Rochester, NY

Position: LabVIEW Specialist

Period: December 2009 - May 2010

The Electrophotographic Development and Transfer Station (EDTS) fixture was a generous donation by Kodak to the Print Research and Image Systems Modeling Laboratory in the Center for Imaging Science at RIT. I briefly mentioned this job in a previous post.

The ultimate goal is to use the fixture as a tool to teach students about the fundamentals of xerography. Additionally, the fixture exposes the internal components of a xerographic printing press, which makes it a desirable candidate for running experiments that require modifying individual components, spaces between components, carriage speeds over specific stations, etc. Xerox expressed an interest in using the fixture to analyze the characteristics of small-particle developer (i.e. toner) and examining its impact on print quality.

I worked directly with the P10503 senior design team and representatives from both Kodak and Xerox. All of the team's documentation can be found on their website. The project poster (PPT) provides a general overview. My primary objective was to modify the existing rudimentary LabVIEW software in order to execute control over all of the various electrical and mechanical components of the fixture. When I began the fixture could not print an image. When I left it could. I call that a success!

Responsibilities and accomplishments:

• Led a 6-person team consisting of mechanical engineers, an industrial engineer, an electrical engineer, and a software engineer.
• Implemented LabVIEW software to control a flat plate xerographic printing fixture through NI DAQ hardware.
• Wired electrical and mechanical components, including stepper motors, DC motors, relays, high voltage power supplies, and electrostatic voltmeters.

Facebook Application: Spot the Fake Smile Quiz

Web development has always been a hobby of mine. I enjoy it because it provides a more artistic outlet than typical programming. That's not to say that designing program architectures and writing code doesn't require creativity; rather, sometimes I like to create something visually appealing. Sometimes I like to dabble in Photoshop as well.

Also, websites and web applications often have a more direct social impact. One day while browsing the BBC website I stumbled across this online quiz where you are asked to spot the difference between fake smiles and real smiles. The theory is based on the work of Guillaume Duchenne who discovered that people who are genuinely smiling have raised cheeks and crow's feet (wrinkles in the outer corner of the eyes).

I thought that it would be interesting to see how well my friends and colleagues could spot the fake smiles, so I decided to create a Spot the Fake Smile Quiz Facebook application where users can post their quiz results to their profile feed. My first task was to find free-to-use photos of smiling people and determine myself if their smiles were real or fake. In order to remove any errors in my classification, I only used photos available under the an appropriate Creative Commons license where the author commented on whether the subject's smile is fake or not.

Some of the technologies I used to develop the application include HTML, CSS, PHP, AJAX, JavaScript, JSON, and mySQL. I slightly modified some jQuery code to create the photo sliding effect. I decided not to use the special FaceBook Markup Language (FBML) tags and instead embed my application in the Facebook webpage as an iframe. I found that this approach provided me with more freedom over the layout of my application and allowed me to use the web technologies that I'm already familiar with. Also, FBML applications require special modification to use jQuery, which was a major turnoff. The differences between the two approaches are explained here.

000webhost.com is an excellent free web hosting service that I'm using to host my application.

Object Tracking using Particle Filters

During my first year as a computer science grad I took a course in advanced computer vision. The class was divided into teams and each team could choose one of two projects to work on. The first project involved identifying students as they walked into a classroom based on their facial features. The second project involved tracking students as they walked into the classroom in-between other students. My team decided to work on the second project because my partner and I were both interested in motion tracking at the time.

We developed 3 systems with various degrees of motion-tracking success:

1. Kalman filter. Actually the particle filter developed by Cuevas, Zaldivar, and Rojas which is based on the Extended Kalman Filter (EKF). Some success.
2. Kalman filter with spring forces. Attempt to use multiple particle systems linked by spring forces to track multiple parts of a subject's body. Limited success.
3. Hierarchical particle filter. Based on the work of Viola and Jones and the work of Yang, et al. Uses rectangular windows for feature extraction. Quite different from the Kalman filter and the 2 systems described above. Most successful.

A lot of time was spent adjusting the particle set properties used by the first 2 systems for each student test video. The third system is more robust and doesn't require as much custom-tailoring to the video to which it is applied.

The particle filter presented by Cuevas, Zaldivar, and Rojas attempts to track a small color distribution within a circular window centered around a target pixel.

Alternatively, the approach presented by Viola and Jones employs a rectangular target window to determine the relative position of average color intensities within an area of the video.

Viola and Jones had great success detecting faces using the target window to capture the average color intensity around a person’s eyes and the average color intensity of that person’s upper cheeks. It's a very simple concept but it works well in practice because of the intensity difference between those two regions of a person's face. In general a person's upper cheeks are much brighter than the inset region around their eyes.

Resources:

• Technical report (PDF)
• Presentation 1 (PPT)
• Presentation 2 (PPT)
• Presentation 3 (PPT)

Mobile Robots Programming: Retriever

During my third quarter as a computer science grad I took a course in mobile robot programming. Students were required to use the Player network server to control a Pioneer 2 DX (differential drive) robot with an 8-point sonar array and bumper array built into the front of the robot.

Using the Player interface, programs can be written on a laptop attached to the robot via an ethernet cable. In such a setup the laptop provides most of the processing power while communicating with the robot's sensors and actuators via an IP connection. Programs can be tested before controlling the hardware using the Stage simulator, which can simulate sensor readings and objects in a 2-D bitmapped environment.

Teams of students were asked to write control software capable of guiding the robot to a number of predetermined locations on the third floor of the GCCIS building, making sure to avoid other robots and innocent human bystanders on the way as well as successfully maneuvering along walls and through door frames when required. The idea was that there were items at each intermediary location that needed to be retrieved before traveling to a final destination.

To accomplish this the robot needed to perform 3 major tasks: localization, path planning, and path execution. The robot was guaranteed to start in one of 8 known poses (location and orientation), however, it did not know which of those locations it started in. We had the robot determine its starting pose by detecting known landmarks in the environment near its starting location, such as pillars and walls, and narrowing down the set of possible locations until it was left with the most probable one.

After localization the robot planned a path to the destinations specified in a user-provided input file. Path planning was aided by the fact that the environment was known a priori. The robot was provided with a black and white raw image file of the layout of the third floor of GCCIS that it converted to a rudimentary obstacle map. A probabilistic road map (PRM) approach was employed to plan a path from one location to another using the obstacle map.

Each path that was planned consisted of a series of waypoints. The entire path itself may have been complex, but the path between any 2 waypoints is nothing more than a straight line. The robot navigated the path between each pair of waypoints by using potential field motion. This addressed the issue of obstacle avoidance because the robot was repulsed by obstacles in its environment while being attracted to its current goal.

Resources:

• Technical paper (PDF)

Handwritten Digit Recognizer

During my first quarter as a computer science grad I took an incredibly enlightening course in pattern recognition. Teams of students were assigned the task of implementing a handwritten digit recognizer. Like humans, computers need to determine the content of handwritten information before it can be used in a meaningful way. This is accomplished through a form of optical character recognition (OCR).

The postal service accepts packages and envelopes with handwritten addresses which must be read and interpreted in order to sort mail and send each item to its intended destination. It's both impractical and expensive to have humans sort large volumes of mail so automated computer systems are often used instead. The systems often consist of cameras which take pictures of the addresses and feed the images into program for processing.

My team decided to implement a convolutional neural network similar to Lecun's LeNet-5.

• The first layer is the input layer and consists of one neuron per pixel in a 29x29 padded version of the sample image.
• The second layer applies 6 feature maps to the input layer. Each feature map is a randomly distributed 5x5 convolutional kernel.
• The third layer applies 50 feature maps to all 6 of the previous feature maps after sub-sampling. Again, each feature map is a randomly distributed 5x5 convolutional kernel. These 2 layers are referred to as a trainable feature extractor.
• The fourth and fifth layers are referred to as a trainable feature classifier. These 2 layers are fully connected and compose a universal classifier.

A convolutional neural network exploits the spatial structure of digits and attempts to train weights to identify spatial differences between digits. We calculated classification error rates using standard backpropagation, which played a major role in training the system.

After running the network with 100 hidden nodes for 5 epochs over 60000 MNIST training samples and 10000 test samples, our network misclassified 851 samples and had a 91.4% success rate. Not bad.

While this project focused on recognizing handwritten digits, the concepts and algorithms covered can be easily extended to apply to all alphanumeric characters.

Resources:

• Technical paper (PDF)

Computer Graphics II Projects

During my last year as a software engineering undergrad I took a graduate-level course in advanced computer graphics using OpenGL. Each student was required to implement a ray tracer from scratch in order to render a scene similar to Turner Whitted's classic example of transmissive and reflective spheres. A record of my progress is posted on the LiveJournal (tag: raytracer) I kept for the class. The image to the right was the final product.

My personal research project during the class was to implement a particle system from scratch to animate realistic looking fire. I applied a texture map to each particle to give it shape and definition detail. Also, the texture map was necessary to provide the alpha channel used for alpha blending. Various system parameters can be modified in real time to give the particle system the appearance of a lava lamp or even multi-colored fireworks.

The project details are posted on my LiveJournal (tag: openfire). I named the project OpenFire because the source code is available free of charge to the open source community. If modified, all I ask is that I be credited in the source code comments.

Resources:

• Research paper on simulating fire in computer graphics (DOC)
• OpenFire top-level report (DOC)
• OpenFire users guide (DOC)
• OpenFire technical document (DOC)
• OpenFire presentation (KEY ZIP)
• OpenFire source code (ZIP)

I also dabbled in a little bit of Pixar's Renderman technology. There was a student competition to see who could create the most interesting image. I won second place for my abstract rendition of a woman's head and brain! Check it out on my LiveJournal (tag: renderman).

Bachelors Senior Design Project: GridShell

My software engineering capstone project at the Rochester Institute of Technology involved developing a command-line shell to allow easy access to distributed computing environments, namely grid resources such as the TeraGrid. The project was part of a development effort put forth by the RIT Center for Advancing the Study of CyberInfrastructure (CASCI).

GridShell was one of many projects spearheaded by Cyberaide, a community of researchers and organizations interested in advancing cyberinfrastructure to promote collaboration between individuals and providing them with the computing power necessary to deploy and execute processor-intensive programs for scientific research.

The GridShell provides uniform syntax and semantics for creating, submitting, managing, and checking the status of tasks deployed to local and remote Unix resources. It simplifies workflow management by allowing users to execute tasks sequentially or in parallel and allowing users to specify dependancies between those tasks, which places a constraint on their order of execution.

Additionally, users can create scripts in Python to specify task order execution, which is useful for more complex jobs. This is because the GridShell front end is implemented in Python and can execute Python code natively in the command-line interpreter (CLI). Specifically, the CLI is based on the IPython environment. In turn JPype is used to establish a functional language binding between the Python front end and Java back end.

Java was chosen as the back end language in order to leverage existing web service technologies written in Java and utilize other Java utilities. Ultimately, our goal was to provide multiple interfaces to the underlying GridShell task management framework, including the traditional terminal interface as well as a web interface, MATLAB interface, Ruby interface, etc. For the web framework we decided to use a deployable Apache Axis2 web server with Rampart security.

Resources:

• Poster
• Technical paper (DOC)
• Demo notes (TXT)
• Demo 1
• Demo 2
• Demo 3

Finite State Process Autocoder

As a software engineering undergrad who was part of the honors program at RIT, I was required to complete an independent study. At the time I was taking a course in concurrent systems and was making extensive use of the Labelled Transition System Analyzer (LTSA), a concurrent system modeling tool which uses Finite State Process (FSP) algebra notation to represent component behavior.

Once a system is specified in FSP notation, the LTSA can parse and compile the FSP notation to generate a graphical Labeled Transition System (LTS) model. The LTSA also provides a means to “animate” the system by performing discrete or shared process behaviors one at a time and stepping through the states of the system. Under the hood, the LTSA generates and stores an internal state machine representation of the system.

One of the major difficulties encountered by software engineers who use the LTSA is deciding how to translate the FSP system representation into an executable implementation. A common practice is to use the LTSA as a system design tool and to deviate from the FSP during the implementation phase in order to create a custom-tailored system from the ground up. The major disadvantage is that the implemented system may no longer exhibit the same behavior as the FSP and therefore will need to undergo an entirely separate, and more complex, verification process.

Clearly, it is advantageous if the system implementation reflects the original FSP design. At the time when I was conducting my independent study there was no widely accepted procedure for converting the FSP into source code. I began developing the an automatic code generation backend called the FSP Autocoder to use the LTSA to parse FSP notation and perform semantic analysis to produce code stubs for primitive concurrent objects.

Before I could begin working on the compiler aspect of the autocoder, I needed to design a “universal” (i.e. widely applicable) concurrent system architecture that could be traced back to the FSP system representation and vice-versa. I considered many approaches, such as employing a state machine architecture, rendezvousing threads in conjunction with a round-robin thread scheduler, and using a Communicating Sequential Processes (CSP) library.

Resources:

• Technical paper (DOC)
• Presentation (PPT)