UMBC CSEE Colloquium

Advanced Computer Systems (ACS)
Machine Learning program

Mark McLean
Senior Researcher, Advanced Computer Systems group

1:00pm Friday, 30 November 2012, ITE 227, UMBC

My talk will discuss the ACS Machine learning program. The ACS ML program's focus is on three main areas; algorithm development, applied research and integration into efficient hardware. Our algorithm development work has created the Concurrent Learning Algorithm and Importance Map technologies. These technologies were developed in-house and have some unique capabilities which make it ideal for our purposes. I'll give some demos of these technologies learning on datasets from the UCI repository. For our current research effort, I will discuss our ideas of using neural networks to process complex digital algorithms, which is not a traditional focus for neural networks. Here, I will discuss our efforts to make a neural network learn the Advanced Encryption Standard encryption functionality and why this could impact the way we design digital systems in the future. For our hardware focus, I'll talk about our efforts to develop a Memristor-based neuromorphic processor and why we hope to succeed where others have failed.

Mark McLean has been a senior researcher in the Advanced Computer Systems group Since 2009. His main area of research is on neural network algorithms, application and neuromorphic processor development. Mr. McLean has done post-graduate work at UMD, Holds a MS degree in Computer Engineering from Loyola College and a BS degree in Computer Science. Previously, he held the position of technical director for the microelectronics and reverse engineering group in the DOD. He has work in industry as lead designer for re-configurable computing at Annapolis Micro-Systems and is a retired officer from the USAF.

– more information and directions –

Information Systems Department Seminar

Subjectivity and Social Role Recognition in Meetings

Theresa A. Wilson
Human Language Technology Center of Excellence
Johns Hopkins University

12 noon-1pm, Tue. 20 Nov. 2012, ITE459

Opinions, sentiments and other types of subjective content are an important part of any meeting. Meeting participants express pros and cons about ideas, they support or oppose decisions, and they make suggestions that may or may not be adopted. In this talk, I will present an annotation scheme for labeling subjective content in meetings, as well as experiments for recognizing subjective utterances and their polarity. Our experiments show that even very shallow linguistic features, such as n-grams of characters, can be effective for this task, and that the combination of classifiers using word, character, and phoneme n-grams yields the best result for subjective utterance recognition. Finally, I will discuss the application of subjectivity recognition to social role recognition in meetings.

Theresa Wilson is a research scientist working on opinion and sentiment analysis at the Johns Hopkins Human Language Technology Center of Excellence (HLTCOE). Before coming to Johns Hopkins, she completed her post-doctoral research as part of the AMIDA Project (www.amiproject.org) at the University of Edinburgh Human Communication Research Centre. She received her Ph.D. in Intelligent Systems from the University of Pittsburgh in 2008.

Information Systems Department Seminar

Subjectivity and Social Role Recognition in Meetings

Theresa A. Wilson
Human Language Technology Center of Excellence
Johns Hopkins University

12 noon-1pm, Tue. 20 Nov. 2012, ITE459

Opinions, sentiments and other types of subjective content are an important part of any meeting. Meeting participants express pros and cons about ideas, they support or oppose decisions, and they make suggestions that may or may not be adopted. In this talk, I will present an annotation scheme for labeling subjective content in meetings, as well as experiments for recognizing subjective utterances and their polarity. Our experiments show that even very shallow linguistic features, such as n-grams of characters, can be effective for this task, and that the combination of classifiers using word, character, and phoneme n-grams yields the best result for subjective utterance recognition. Finally, I will discuss the application of subjectivity recognition to social role recognition in meetings.

Theresa Wilson is a research scientist working on opinion and sentiment analysis at the Johns Hopkins Human Language Technology Center of Excellence (HLTCOE). Before coming to Johns Hopkins, she completed her post-doctoral research as part of the AMIDA Project (www.amiproject.org) at the University of Edinburgh Human Communication Research Centre. She received her Ph.D. in Intelligent Systems from the University of Pittsburgh in 2008.

Ph.D. Thesis Defense Announcement

Data Intensive Scientific Compute Model for Multicore Clusters

Phuong Nguyen

10:00am 21 November 2012, ITE 325B

Data intensive computing holds the promise of major scientific breakthroughs and discoveries from the exploration and mining of the massive data sets becoming available to the science community. This expectation has led to tremendous increases in data intensive scientific applications. However, data intensive scientific applications still face severe challenges in accessing, managing and analyzing petabytes of data. In particular, workflow systems to support such scientific applications are not as efficient when dealing with thousands and even more of complex tasks within jobs that operate across high performance large multicore clusters with very large amounts of streaming data. Scheduling, it turns out, is an integral workflow component in the execution often of thousands or more tasks within a data intensive scientific application as well as in managing  the access and flow of many jobs to the available resource environment. Recently, MapReduce systems such as Hadoop, have proven successful for many business data intensive problems. However, there are still many limitations in the use of MapReduce systems for data-intensive scientific problems mainly because they do not support the characteristics of science such as data formats, specialized data analytic tools (e.g. math libraries), accuracies, and interfaces with non MapReduce components.

This thesis addresses some of these limitations by proposing a MapReduce workflow model and its runtime system using Hadoop for orchestrating MapReduce jobs for data intensive scientific workflows. Novel heuristic based scheduling algorithm is proposed in the workflow system to manage the parallel execution of data intensive scientific applications. This thesis has developed a hybrid MapReduce scheduling algorithm based on dynamic priorities, proportional resource sharing techniques that reduce delays for variable length concurrent tasks, and takes advantage of data locality. As a result, a new scheduling policy, Balanced Closer to Finish First (BCFF), is proposed as solutions for some problems of scheduling in MapReduce environment. The scheduling algorithm is implemented in Hadoop 1.0.1 framework and is available as a new Hadoop plug-in Scheduler. The evaluations of the workflow system on the climate data processing and analysis application (several TB dataset) show that it is feasible and significantly improved compared to traditional parallel processing method. The scientific results of the application provide new source of monitoring global climate changes for the near decade 2002-2011.

Thesis Committee:

• Prof. Milton Halem (Chair)
• Prof. Yelena Yesha (Co-Chair)
• Prof. Tim Finin
• Prof. Yaacov Yesha
• Prof. Tarek El-Ghazawi at George Washington University

Ph.D. Thesis Defense Announcement

A Decadal Gridded Hyperspectral Infrared Record for Climate
Sep 1st 2002 – Aug 31st 2012

David Chapman

2:00pm 20 November 2012, ITE 325B

We present a gridded Fundamental Decadal Data Record (FDDR) of Brightness Temperatures (BT) from the NASA EOS Atmospheric Infrared Sounder (AIRS) from ten years of hyperspectral Infrared Radiances onboard the NASA EOS Aqua satellite. We show that these results are consistent with the expected greenhouse forcings, and also discovered a drift of ~0.13K/decade in spectrum relative to 4 MODIS-Aqua for Global All-sky Brightness Temperatures. AIRS, operational on September 1, 2002 is the first successful hyperspectral satellite weather instrument of more than 1 year, as well as the longest running global IR hyperspectral measurement. Although global surface temperature data records are available for over 130 years, it was not until 1978 when the Microwave Sounding Unit (MSU) was the first instrument series to reliably monitor long-term trends of the upper atmosphere. The Atmospheric Infrared Sounder (AIRS) provides the first continuous global hyperspectral IR radiance data record from a single satellite for a decade. Our contribution, was to prepare a gridded data record from the AIRS Outgoing Longwave Spectrum (OLS). We have shown high correlations with the GISS global surface air temperatures as well as with the NOAA ONI index of El Niño phase. In addition, we have performed inter-annual inter-comparisons with the Moderate Resolution Spectroradiometer (MODIS) on the same satellite to examine the relative consistency of their calibrations. The comparisons of the two instruments for the 4µ spectral channels indicate an inter-annual warming of 0.13K per decade of AIRS more than MODIS. This relative decadal drift is small relative to inter-annual variability but on the order of historic surface temperature trends. In the 12µ window channels we see a relative constant difference of 0.01K over a decade. It is convenient to observe the climate variability by using monthly average lat-lon grid projections. The polar orbiting data projection to a lat-lon grid is a lossy process that invariably introduces aliasing artifacts and noise. We observed an exponential decay between the number of days averaged and the expected noise due to gridding. We have extended the Observation Coverage (Obscov) gridding algorithm, developed for the MODIS instrument that incorporates the Point Spread Function (PSF) and we show the Obscov gridding algorithm reduces the aliasing noise from AIRS grids by nearly 40% by comparing the spatial correlation of gridded MODIS IR data. We also show that the use of a circular approximate PSF is a sufficient representation to obtain the noise reduction of Obscov at the climate resolution 0.5×1 degree monthly average grids. We extended these spatial sampling methods to the AIRS Level 3 retrieval records for which quality filtering due to opaque clouds is an additional spatial sampling challenge. We correct for an observed dry bias in the AIRS Level 3 monthly average gridded moisture retrieval records by means of spatial interpolation with the Nearest Neighbor (NN) strategy.

Thesis Committee:

• Dr. Milton Halem  (Chair)
• Dr. Yelena Yesha
• Dr. Chin-I Chang
• Dr. Shujia Zhou
• Dr. Joel Susskind (NASA Goddard)

Ph.D. Thesis Defense Announcement

Semantically Rich, Policy Based Framework to Automate Lifecycle of Cloud Based Services

Karuna P. Joshi

10:00am 19 November 2012, ITE 325B

Managing virtualized services efficiently over the cloud is an open challenge.  Traditional models of software development are very time consuming and labor intensive for the cloud computing domain, where software (and other) services are acquired on demand. Virtualized services are often composed of pre-existing components that are assembled on an as-needed basis. We have developed a new framework to automate the acquisition, composition and consumption/monitoring of virtualized services delivered on the cloud.  We have divided the service lifecycle into five phases of requirements, discovery, negotiation, composition, and consumption and have developed ontologies to represent the concepts and relationships for each phase. These are represented in Semantic Web languages. We have developed a protocol to automate the negotiation process when acquiring virtualized services. This protocol allows complex relaxation of constraints being negotiated based on user defined policies. We have also developed detailed ontologies to define service level agreements for cloud services. To illustrate and validate how this framework can automate the acquisition of cloud services, we have built two applications from real world scenarios. The Smart cloud services application enables users to determine and procure the cloud storage application that matches most of their constraints and policies. We have also built a VCL broker application that allows users to automatically reserve the VCL Image that will best meet their requirements. We have developed a framework to measure and semi-automatically track quality of a virtualized service delivery system. The framework provides a mechanism to relate hard metrics typically measured at the backstage of the delivery process to quality related hard and soft metrics tracked at the front stage where the consumer interacts with the service. While this framework is general enough to be applied to any type of IT service, in this dissertation we have primarily concentratated on the Helpdesk service and include the performance rules we have created by mining Helpdesk data.

Thesis Committee:

• Dr. Yelena Yesha (chair)
• Dr. Tim Finin (co-chair)
• Dr. Milton Halem
• Dr. Yaacov Yesha
• Dr. Aryya Gangopadhyay

CSEE Colloquium

Active PURLs: An architecture for enterprise information interoperability

Dr. David Wood
Three Round Stones

11:00am Friday, 9 November 2012, ITE 325b, UMBC

The World Wide Web differed from other early hypertext systems in the removal of "back links" (the ability of a hyperlinked object to link back to a referring resource). The removal of back links allowed the scalability inherent in the Web's design, but sacrificed the knowledge necessary to update links when content moved. Persistent URLs (PURLs) have been used on the Web since 1995 to provide an inexpensive and partial solution to link updates via HTTP redirection: PURLs do not change their URL, but they may change the target they redirect to. Various iterations of the PURL concept have allowed Web addresses to be updated, clients notified of permanent changes of address and the provision of directions to metadata about a requested resource.

"Active" PURLs are a relatively new (2007) iteration of the PURL concept that allow PURLs to actively participate in the creation of data returned. The Callimachus Project, an Open Source Linked Data management system, now implements Active PURLs as a means to automate the collection, transformation and provision of information from distributed sources. Active PURLs are implemented in Callimachus by means of a PURL service, a new PURL type and an XML pipeline (XProc) implementation.

This talk will introduce Active PURLs and describe how they may be used to address long standing problems in enterprise architecture, especially those of distributed information interoperability, by facilitating a strong separation of concerns between data producers, publishers, administrators, librarians and consumers.

Dr. David Wood has contributed to the evolution of the World Wide Web since 1999, especially in the formation of standards and technologies for the Semantic Web. He has architected key aspects of the Web to include the Persistent Uniform Resource Locator (PURL) service and several Semantic Web databases and frameworks. David is co-chair of the W3C RDF Working Group, co-chaired the Semantic Web Best Practices and Deployment Working Group and is a member of the Semantic Web Coordination Group. David has represented international organizations in the evolution of Internet standards at the International Standards Organization (ISO), the Internet Engineering Task Force (IETF) and the World Wide Web Consortium. David is a founding and contributing member of many Free/Libre/Open Source Software (FLOSS) projects, including the Mulgara Semantic Store, Persistent URL (PURLs), Freemix and the Callimachus Project. He is the author of Programming Internet Email (O'Reilly, 1999), editor of Linking Enterprise Data (Springer, 2010) and Linking Government Data (Springer, 2011) and lead author of Linked Data (Manning, anticipated 2013).

Host: Tim FInin, Sorry, you need javascript to view this email address.

— more information and directions: http://bit.ly/UMBCtalks —

CSEE Colloquium

Modeling the dynamics of pulsed optical fiber lasers that rely on nonlinear polarization rotation

Brian Marks
Research Scientist
UMBC Computational Photonics Laboratory

1 pm Friday, 2 November 2012, ITE 227, UMBC

Ultrashort pulse lasers are important tools in time and frequency metrology, atomic spectroscopy, and medical applications. Passively modelocked fiber lasers are short pulse lasers that have many advantages over non-fiber alternatives — particularly size, weight, and cost. However, fiber lasers can drift due to environmental changes and changes in fiber properties, making robustness a problem. Although fiber modelocked lasers have been studied for decades, until recently modeling these devices has primarily been phenomenological. In this talk, I will discuss how passively modelocked fiber lasers work, improvements in the modeling effort in recent years, challenges for their robustness, and possible improvements for robustness based on our modeling work.

Brian Marks is a research scientist in the computational photonics laboratory at UMBC. He received his Ph.D. in Engineering Sciences and Applied Mathematics at Northwestern University, and B.S.'s in Math and Physics from N. C. State University. He was at UMBC from 2000–2005 in the computational photonics lab, then taught math and statistics at Indiana University in Bloomington for several years, and is now back at UMBC. His research interests include modeling and simulation of photonics and communications systems.

CSEE Colloquium

Emerging Challenges in High Performance Computing: Resilience and the Science of Embracing Failure

John. T. Daly
Advanced Computing Systems Program at the Department of Defense / Center for Exceptional Computing

1:00 p.m. Friday, 9 November 2012, ITE 227, UMBC

Resilience is about keeping the application workload running to a correct solution in a timely and efficient manner in spite of system failures. Future extreme scale supercomputers are likely to suffer more frequent failures than current systems: As devices scale, they are more susceptible to upsets due to radiation and to errors due to manufacturing variances. The probability of multiple bit upsets is growing, since an event is increasingly likely to impact multiple nearby cells. The use of near-threshold voltage in order to reduce power consumption also increases error rates. Thus, we can expect more frequent hardware failures, and a significant rate of undetected soft errors. While it is desirable to have failure-free system hardware and software, this goal may not be achievable at reasonable cost as both hardened components and methodologies to design and test critical software tend to be extremely expensive. The challenge is to construct a system out of less than perfectly reliable hardware and software that nevertheless behaves as a reliable system from the perspective of the user.

John T. Daly is a computer systems researcher for the Advanced Computing Systems (ACS) Program at the Department of Defense / Center for Exceptional Computing (CEC). He is focused on the problem of keeping supercomputer applications running toward a correct solution in a timely and efficient manner in the presence of system degradations and failures. His research interests include mathematical modeling and analysis of failure, reliability, fault tolerance, calculational correctness, and throughput for applications at extreme scale. Before coming to the CEC, John was a researcher and resilience technical leader in the High Performance Computing (HPC) division at Los Alamos National Laboratory and a software engineer and application analyst for Raytheon Intelligence and Information Systems. He is a nationally recognized expert in resilience with 25 years of experience developing, porting, and running applications as an early adopter of many of the world's fastest supercomputers. He holds degrees in engineering and applied science and aerospace engineering from Caltech and Princeton University.

    — more information and directions: http://bit.ly/UMBCtalks –

Cyber Security Mergers & Acquisitions – Striving for a
Successful Exit: Trends, Preparation, and Lessons Learned

9:00-10:30am, Friday 9 November 2012

RWD Building, UMBC Research Park
5521 Research Park Dr.
Baltimore, MD 21228

The Cyber Incubator at bwtech@UMBC will host a third CYBERInnovation Briefing on Friday 9 November 2012 in the RWD Building of UMBC's Research Park. Registration begins at 8:30am.

Cyber security acquisitions continue to heat up. Join the CyberHive community as we host a distinguished panel of cyber security executives and capital markets experts who will share their recent merger and acquisition experiences in the cyber security industry. Learn from buyers, sellers, and deal flow managers – how to drive a successful deal and be best prepared. Our panel will explore recent trends in activity, acquisition characteristics, attributes that enhance company valuation, lessons learned, process and financial preparation, retention of key employees, and offer words of wisdom.

Acquisition activity involving cyber security companies will continue to influence the economic growth of our region, as innovators from the National Security Agency, US Cyber Command, and the Defense Industrial Base launch creative business opportunities. These sessions are very interactive and we look forward to and welcome your participation.

For more information and to RSVP, contact Alexandra Gold, Sorry, you need javascript to view this email address.