Department of Computer Science and Electrical Engineering

MS Thesis Defense

Numerical Integration Techniques for Volume Rendering

Preeti Bindu

10:00am Monday, 7 May 2012, ITE 352, UMBC

Medical image visualization often relies on 3D volume rendering. To enable interaction with 3D rendering of medical scans, improvements in the performance of Volume Rendering Algorithms need significant attention. Real-time visualization of 3D image data set is one of the key tasks of Augmented Reality Systems required by many medical imaging applications. Over past five years the development of the Graphics Processing Unit (GPU) has proved beneficial when it comes to Real Time Volume Rendering. We propose a GPU based volume rendering system for medical images using adaptive integration to improve performance. Our system is able to read and render DICOM images, implementing adaptive integration techniques that increase frame rate for volume rendering with the same quality of output images.

Committee: Dr. Marc Olano (advisor), Dr. Penny Rheingans and Dr. Samir Chettri

MS Thesis Defense

A Modular, Power-Intelligent Wireless Sensor Node Architecture

David Riley

10:30am Monday, 7 May 2012, ITE 346

The current state of the art in wireless sensor nodes, both in academia and the commercial world, is a fractured landscape of designs which mostly address individual problems. The most common commercial design derives directly from a mote developed at the University of California, Berkeley around 1999, and presents only moderate, incremental improvements over the original design. No designs yet present a comprehensive, intelligent design befitting a modern system.

By using dynamic power management, deep system configurability, autonomous peripheral modules, and multiple CPU architectures, this thesis presents a flexible and efficient node architecture. Modules in a system communicate between each other to coordinate their activities and power levels. Special attention is given to power sourcing and distribution. Individual peripheral boards supply their own drivers to the CPU using architecture-independent code. The platform may be configured to work with most networks, sensor types and power sources due to its improved connectivity and hierarchical design.

The resulting Configurable Sensor Node (CoSeN) architecture is competitive with existing designs on price, size and power while greatly exceeding most of them on performance, configurability and application potential. The CoSeN architecture is validated through a prototype implementation.

Committee: Professors Mohammed Younis, Tim Oates and Gymama Slaughter

The CSEE Department will hold its annual CSEE Research Review day from 9:30am to 4:00pm on Friday, May 4, 2012. Faculty, research staff and students from the Computer Science, Computer Engineering and Electrical Engineering programs will present and discuss their latest research results via short oral presentations and a poster session.

The event is open to the public and is a good way for prospective collaborators and students to find out about the research our department is doing and meet and network with current faculty and students. See pictures from CRR-06, CRR-08, CRR-09, CRR-10 and CRR-11 to get an idea of what goes on at this event.

The 2012 CSEE Research Review (CRR-12) will take place in the large conference room of the UMBC Technology Center's business Incubator and Accelerator building on South Campus. There is ample free parking and refreshments and a free buffet lunch will be provided.

Schedule
9:30-10:40	Talks
11:00-12:00	Poster Session
12:00-1:00	Lunch (free)
1:00-2:10	Talks
2:30-3:40	Talks

For more information, contact the CRR-11 General Chair, Professor Alan Sherman, .

EE Graduate Seminar

Research vs. Development: Building a
Career in the Modern Tech Industry

Christopher Morris
Fellow Engineer, Northrop Grumman Corp
PhD (CS) Student, CSEE Dept/UMBC

11:30am-12:45pm, Friday, 4 May 2012, ITE 237, UMBC

With the uncertainty present in todays job market, technical college graduates are under increasing pressure to choose a career path that not only fits their personal strengths and interests. but is sustainable. Jobs and employees are becoming more transient and it is seemingly more difficult to establish a career with longevity. In this talk, we will discuss what a recent graduate can look forward to in various technical career paths, specifically a career in research versus a career in development. I will draw upon personal experience to provide an overview of what a student may expect when entering these careers. Lastly, we will discuss how one can prepare to make the most out of their career choice and handle the volatility of the industry.

Christopher (Chris) Morris is currently a Fellow Engineer at the Northrop Grumman Corporation where he is a member of the Teton Project team. The team is charged with research and development of Open Architecture (OA) Processing solutions for distributed, real-time, embedded (DRE) systems. Prior to joining Northrop Grumman in 2009, Chris was an Advisory Staff Engineer in the Visualization Systems Group at IBM Research in Westchester County, New York, where he researched and developed distributed rendering and visualization systems. He holds a BSME from UMBC (`96), a MSME in from Stanford University (`98), and a MSCS from UMBC (`01). Currently, he is a PhD (CS) Candidate at UMBC. His research interests are computer graphics and scientific visualization.

Host: Prof. Joel M. Morris

MS Thesis Defense

An Efficient Network on Chip (NoC) for a Low-Power,
Low-Area Homogeneous Many-Core DSP Platform

James Chandler

10:30am Monday, 30 April 30 2012, ITE 325b

This thesis presents an NoC architecture that is optimized for a course-grained, deterministic many core DSP platform supporting up to 256 cores. The proposed network supports both local and long-distance communication in the event that large applications or multiple smaller applications are mapped onto the platform by means of a hierarchical cluster topology. The NoC is designed to optimize the area- and power-to-performance ratio through implementing the following key characteristics: low hop-count long distance communication, optimized flit buffer size, efficient virtual channel implementation, and a highly restricted virtual channel flow control.

The NoC architecture is implemented in 65 nm CMOS technology with a nominal supply voltage of 1V. Place and Route results show that the proposed architecture saves up to 33% in area and up to 87.6% in energy-per-flit in comparison to some currently-implemented NoCs. Through several traffic pattern tests on a network of 16 cores, the NoC attains a throughput of up to 21.7Gbps. A 256-point FFT mapped onto 16 cores executes in 4.3$us and dissipates 0.649W. This is an improvement of 187% and 508% in latency and power dissipation over a 256-point Xilinx FFT IP Core implemented on a Virtex 6 FPGA.

Committee: Professors Tinoosh Mohsenin (chair), Dr. Chintan Patel and Mohamed Younis

MS Thesis Defense

Situation Aware Intrusion Detection Model

Sumit More

9:00am Friday, 27 April 2012, ITE 346, UMBC

Today, information technology and cyber-services have become the foundation pillars of every business and manufacturing industry. The importance of cyber-services and their extensive use by every section of the society has paved the way for cyber-crimes like espionage, politically motivated attacks, credit card frauds, unauthorized infrastructure access, denial-of-service attacks, and stealing of valuable data. Intrusion Detection Systems (IDS) are applications which monitor cyber-systems to identify any malicious activities, generate an alert when such an activity is detected, and redress the problem if possible. Most of the intrusion detection/prevention systems available today are based on rule-based or signature based activity monitoring which detect threats and vulnerabilities by cross-referencing the threat or vulnerability signatures in their databases. These Intrusion Detection Systems (IDS) face limitations in detecting newly published attacks or variants of existing attacks. They are also point solutions that focus on a single system/component.

We argue that integrating information coming from multiple data channels can lead to a better threat detection model. Data source of web including blogs, chat-rooms, forums etc. can be a good source of information for upcoming attacks or attacks whose signatures have not yet been tracked for the intrusion detection systems to catch. Semantic integration of the data sources from web, information from IDS/IPS modules at the network and host level, and the expert knowledge can be used to create a ‘Situation Aware Intrusion Detection Model’ which can lead to better intrusion detection and prevention results. In this work, we present such a system which makes use of semantic web technologies to find relationships between the information gathered from the web, sensor data coming from IDS/IPS modules and network activity monitors, and reasons over this data and expert provided rules in-order to detect possibility of a cyber attack.

Thesis Committee: Professors Anupam Joshi (chair), Tim Finin and Yelena Yesha

On Measure Transformed Canonical Correlation Analysis

Dr. Koby Todros, University of Michigan

2:00pm Wednesday, 2 May 2012, ITE 325b

In this work linear canonical correlation analysis (LCCA) is generalized by applying a structured transform to the joint probability distribution of the considered pair of random vectors, i.e., a transformation of the joint probability measure defined on their joint observation space. This framework, called measure transformed canonical correlation analysis (MTCCA), applies LCCA to the data after transformation of the joint probability measure. We show that judicious choice of the transform leads to a modified canonical correlation analysis, which, in contrast to LCCA, is capable of detecting non-linear relationships between the considered pair of random vectors. Unlike kernel canonical correlation analysis, where the transformation is applied to the random vectors, in MTCCA the transformation is applied to their joint probability distribution. This results in performance advantages and reduced implementation complexity. The proposed approach is illustrated for graphical model selection in simulated data having non-linear dependencies, and for measuring long-term associations between companies traded in the NASDAQ and NYSE stock markets.

Koby Todros was born in Ashkelon, Israel, in 1974. He received his B.Sc., M.Sc., and Ph.D. degrees in electrical engineering at 2000, 2006, and 2011, respectively, from the Ben-Gurion University of the Negev. He is currently a post-doctoral fellow with the Department of Electrical Engineering and Computer Science, in the University of Michigan. His research interests include statistical signal processing and estimation theory with focus on association analysis, uniformly optimal estimation in the non-Bayesian theory, performance bounds for parameter estimation, blind source separation, and biomedical signal processing.

The Sixth UMBC Digital Entertainment Conference (DEC) will be held this Saturday, April 28 from 10:00am to 4:00pm in LH1 in the Biological Sciences building.

Every year since 2007 the students ofn the UMBC Game Developer's Club has organized the conference and invited speakers from the videogames industry to come in and discuss important topics in the games industry. DEC 2012 is sponsored by Zynga, the studio that developed Farmville and many other Facebook games.  One of the strenghts of the UMBC program in Graphics, Animation and Interactive Media (GAIM) is its strong ties to game development studios in the Maryland, DC and Northern Virginia area.

The 2012 DEC is open to anyone, and features an all-star lineup of speakers from Firaxis Games, Zynga East, Pure Bang, and Mythic Entertainment. Whether you are a high school student, go to UMBC or another university, or are already working in a different industry, you are sure find interesting information about how the games industry works, how some current developers got started, and what they do. If you are a game developer, you are sure to find high school students, UMBC students and students from other universities who are interested in jobs in the games industry.

Here is the schedule.

10:00am – Barry Caudill, Director of Gameplay Development at Firaxis
11:00am – Tim Train, Studio Manager at Zynga East
12:00pm – Lunch Break
1:00pm – Eric Jordan, Programmer at Firaxis
2:00pm – Ben Walsh, CEO of Pure Bang Games
3:00pm – Brian Johnson, Director of Online Operations at Mythic Entertainment

MS Thesis Defense

Distributed Model Consensus for Models of Locally
Biased Measurements in Wireless Sensor Networks

Jacob Thompson

4:00pm Wednesday, 25 April 2012, ITE 325B, UMBC

Wireless sensor networks (WSNs) consist of interconnected microsensors, each of which collects measurements from its local environment, which are often used in monitoring and control applications. These applications make inferences about the global and local states of the deployment environment. However, due to the limited communication and energy resources at the sensors, gathering all the raw data at a central fusion/control point is impractical.

Hence, it is essential to have distributed learning and inference in WSNs, such as learning a consensus model from the locally learned models. Consensus is challenging due to the limited resources of the sensors and the inherent bias of the individual sensor models learned from their local sensing environments. Two leading approaches for this problem are the approach by Zheng et al which uses loopy belief propagation on a certain graphical model based on the WSN topology and the local models, and the approach by Xiao et al which relies on gossip averaging of the parameters of the local models.

We focus on multivariate linear regression models, such as Bayesian, Ridge, and Lasso regression models. We analyze and extend the loopy Gaussian belief propagation (GaBP) approach to model consensus, and compare its performance to the gossip averaging approach. We experimentally find that GaBP tends to converge much faster than gossip averaging, but to a less accurate estimated consensus model (especially in the presence of multiple cycles in its corresponding graphical model). We also find that gossip averaging along paths in the WSN, tends to provide much faster convergence to more accurate estimated consensus models as compared to GaBP.

Committee: Professors Kostas Kalpakis (chair), Tim Oates and Yun Peng

MS Thesis Defense

Towards Implementation of a Pattern Recognition System based on
a Working Theory of the Learning Rule for Dendritic Integration

Shamit Patel

4:00pm Monday 23 April 2012, ITE 346, UMBC

My goal is to develop a working theory of the learning rule for dendritic integration, and to then implement a pattern recognition system based on that learning algorithm so that the algorithm can be evaluated for its generalization ability. In this regard, this thesis presents an implementation of Jeff Hawkins and Dileep George's Hierarchical Temporal Memory (HTM) pattern recognition system that's based on an existing theory of the learning rule for dendritic integration – spike-timing-dependent synaptic plasticity (STDP). The integration of this learning rule is the novel contribution of this thesis. I found that the STDP HTM system achieved much higher probabilistic classification accuracy and better generalization ability than the non-STDP HTM system. Probabilistic classification accuracy is a way of measuring classification accuracy in which a testing pattern is classified correctly if its label appears in the group of labels output by the top-level node of the HTM network.

Committee: Professors Tim Oates (Chair), Yun Peng and Tim Finin