Printmaking Mini-Residency at SOL PRINT STUDIOS

Sol Print Studios

New paper: Zareen Syed, Tim Finin, Muhammad Rahman, James Kukla and Jeehye Yun, Discovering and Querying Hybrid Linked Data, Third Workshop on Knowledge Discovery and Data Mining Meets Linked Open Data, held in conjunction with the 12th Extended Semantic Web Conference, Portoroz Slovenia, June 2015.

In this paper, we present a unified framework for discovering and querying hybrid linked data. We describe our approach to developing a natural language query interface for a hybrid knowledge base Wikitology, and present that as a case study for accessing hybrid information sources with structured and unstructured data through natural language queries. We evaluate our system on a publicly available dataset and demonstrate improvements over a baseline system. We describe limitations of our approach and also discuss cases where our system can complement other structured data querying systems by retrieving additional answers not available in structured sources.

Ph.D. Dissertation Proposal

Real-time Spectral Rendering of Atmospheric Optical Phenomena

Ari Blenkhorn

2:00pm Wednesday, 10 June 2015, ITE 352

Glories, rainbows, and coronas are colorful atmospheric effects which occur when sunlight interacts with cloud droplets. Adding these effects to digital cloud environments will provide increased realism and a greater sense of immersion. Furthermore, these phenomena are the subject of active scientific research.  In both communities, high-resolution real-time rendering is desirable.

The color distribution of these phenomena is typically calculated using the Mie scattering theory, Debye series, or Airy theory. The calculations give the intensity of a single wavelength of light at a single scattering angle. They must be repeated for all desired wavelengths at all desired pixels of the final image.

I propose accelerating the calculations by using general-purpose GPU computing to transform a single-threaded, CPU-based Mie scattering application into a collection of highly-parallel GPU calculations.  I also propose to reduce the number of wavelengths required by using importance sampling, a monte-carlo selection method which concentrates the computing resources on the wavelengths belonging to the most important regions of the visible spectrum.

Planned work includes development of both numerical and perceptually-based image quality metrics, of interest to optical physicists and interactive application developers, respectively. These metrics will guide development of the GPU kernel parallel structure and the selection of a suitable estimator for importance sampling.

Committee: Drs. Marc Olano, Penny Rheingans, Curtis Menyuk, Matthias Gobbert (Mathematics), Raymond Lee (USNA)

Walk In Advising Hours June 8th-12th

Monday, June 8th
10am-11:30am

Tuesday, June 9th
1:30pm-3pm

Wednesday, June 10th
None

Thursday, June 11th
10am-11:30am

Friday, June 12th
None

Advisors are also available by appointment. Our advising offices are located in ITE 202-206. Email and telephone contact information is available here.

Here at UMBC, we take pride in what our alums accomplish after graduation. Take a moment to see which Retrievers have been on the move and making news!

Damon Tweedy (M4) ’96, biological science, explains the need for more black doctors, saying that a lack of black doctors contributes to racial health disparities. Tweedy writes for The New York Times and states that as a “general rule” most black patients feel more comfortable being treated by a doctor of the same ethnicity. The article examines statistical evidence provided by the latest medical journals that illustrate the deficiency in black doctors in the medical field.

Click here to read the full article.

Ian Ralby ’02, modern languages and linguistics, M.A., intercultural communication, writes about the struggles President Obama faces in establishing a Trans-Pacific Partnership Free Trade Agreement. Ralby writes about the President’s own personal investment in seeing the Trans-Pacific Partnership proceed and how he has made efforts in getting both democrats and republicans to agree on the trade pact.

Read the full article here.

Tigue Tozer ’08, interdisciplinary studies, shares his passion for learning through international travel and his career as a medical officer in Australia and medical correspondent for Newsfirst Sri Lanka. Tozer provides an in depth analysis surrounding the Ebola crisis and explains why the disease should be considered a global problem. He also talks about working as a foreign correspondent and his opportunity to work with another one of his passions.

Click here to read the full article.

Michael Moubarek ’15, biochemistry and molecular biology, shares how a rock-climbing accident inspired him to finish high school and graduate as UMBC’s valedictorian. In an article from The Huffington Post, Moubarek talks about his battle with low self-esteem and depression and explains how his near death experience put his life into perspective and inspired him to change his path and get back on the road to success.

Read more here.

Have a story of your own to share? Tell us about it in a class note.

Computers can crunch mind-boggling arrays of data. They can even win quiz shows. But are there more powerful applications of this analytical power yet to come? Claudia Pearce ’89 M.S., ’94 Ph.D., computer science, is the Senior Computer Science Authority at the National Security Agency (NSA). The winner of UMBC’s Alumna of the Year Award in Engineering and Information Technology in 2014, Pearce is diligently seeking the answer to that question.

Watson is IBM’s Deep Question Answering system. You might recall that when Watson was put to the test against human contestants on the television quiz show,Jeopardy!, the system successfully bested its competitors in providing questions to answers whose associated question was already known. (And won $1,000,000.)

But like any game, Jeopardy! has its rules – and its limits. Along with my colleagues and others in the field who study big data and predictive analytics, I’ve been wondering whether the techniques implemented in Watson could be used as a powerful knowledge discovery tool to find the questions to answers whose associated questions are unknown.

Subspecialties in the fields of computer science and statistics such as knowledge discovery, machine learning, data mining, and information retrieval are commonly applied in medicine and in the natural and physical sciences – and increasingly in the social sciences, advertising, and cybersecurity, too. (It’s often called “computational biology” or “computational advertising.”)

And as the scope of computational practices has increased, the resources needed to perform it have shrunken tremendously. Ten years ago, massive computation was primarily in the areas of physics, astronomy, and biology, where petabytes of data were collected and analyzed using massive high performance computing systems. The advent of Cloud computing technologies –and their increasing public availability – now allows institutions, companies, and users to rent time for large-scale computation without the enormous costs of creating and maintaining supercomputers.

Additionally, programming and data storage paradigms have evolved to make use of the inherent parallelism in many domain applications. This trend has created new applications for computer science that provide individuals and organizations access to a plethora of online information in real time.

Real-time data sources spur not only social media, but online commerce, video streaming, and geolocation. Wireless technologies and smartphones put that information in the palm of our hands.

The power and speed of these technologies have aided the machine learning and data mining techniques at the heart of analytics, from retrieval of simple facts to trends and predictions. Advertising applications, for instance, analyze your click stream and cookies so that ads tailored to your interests appear as you browse in real time.

Yet the process of developing and maintaining analytics has its costs. First, there is labor. It usually requires teams of people to identify and solve problems in various domains. Analysts (who are usually experts in their subject) develop a collection of research questions in their discipline. They are teamed with statisticians, computer scientists, and others to develop and write programs to put the data in a usable form and create machine learning applications, tools, and algorithms. This combination of data and programming combines into analytics designed to answer a question in a given line of inquiry.

Labor isn’t the only cost. Depending on the application, analytics can be reused – but eventually need to be refreshed with new data. This is particularly true when the analytic is designed to be predictive. Real-time financial industry data, for example, requires that credit card fraud models must be recreated at least annually. Computational advertising models must be refreshed weekly.

Outdated analytics become an artifact of the maintenance cycle. Reuse requires knowledge specific to the analytic, data, and inherent question, and is most likely unknown outside of a small development team. So how can we get beyond these limitations and make a simple easy-to-use system that helps people get answers to questions beyond Googling them?

Part of the answer may be found in a series of Beyond Watson workshops and other activities involving university, government, and industry partners, including one held at UMBC in February.

We’re looking at things like natural language, which is at the core of the ultimate computer human interface. Think back to Star Trek, when Spock would say something like: “Computer, what is the probability the Klingons will attack the Enterprise in this sector of the galaxy?” The computer would often engage in a back and forth interaction with Spock, asking for more information or clarification before offering one or more scenarios (and probabilities supporting those scenarios) to aid the crew of the Enterprise in their next move. When we can ask a computer a question and then engage in a dialogue with it in this way, we can freely use computers to their best advantage. This sort of exchange allows us to hone in on an answer (or answers) to our question, supported by knowing both how the information was derived and what level of confidence to place in it.

Envisioning such a model opens up new vistas. We may not be limited to retrieving existing answers from Wikipedia-like text, but use all available data to elicit answers to non-obvious questions, or to queries that have never been asked. We might also dispense with arcane interfaces that are poorly matched to both the task at hand and the needs of users and consumers. Database management systems, for instance, have historically been developed to ask a few specific questions of data, but imposing such a structure on the data makes it very difficult to anticipate (or answer) questions we weren’t thinking of when we built the system.

Pushing our thinking – and technology – to generalize on the automation of building big data analytics could permit us to leverage existing tools and build on them instead of shelving them. And pulling these tools together in yet another set of big data analytics may even allow for the entire enterprise of analytics (newly created systems as well as existing ones) to help us advance particular knowledge.

Your cell phone has a plethora of apps (collected in an “app store”) to help you make the best use of it. Creating a similar “analytics store” for our Question Answering systems will accelerate automation of these processes and encourage crowd sourcing in analytics development. It’s a vision of the future for which technology already exists. By specifying and clarifying what we want big data analytics to accomplish, we can start to build that future now.

Read more from the latest issue of UMBC Magazine.

Note: The views and opinions expressed are those of Claudia Pearce and do not reflect those of NSA/CSS.

JOB SUMMARY

As the BSO celebrates its 100th anniversary in 2016, this exciting new position reinforces the orchestra’s commitment to building future audiences for the BSO’s second century as a top priority. Our initiatives have been boosted by a recent multi-year grant from the Wallace Foundation for audience-building, and the board has created a task force, ‘Reimagining the BSO Experience’ to help identify ways to heighten engagement with new and existing patrons.

AAAS Science and Technology Policy Fellows invite you to register for the upcoming symposium “Making Changes: Learning from Social Science Research to Drive Behavior Change”.

When: June 18, 8:30 am – 5 pm with reception to follow

Where: AAAS Headquarters, 1200 New York Avenue NW, Washington, DC

RSVP here: http://aaaspolicyfellowships.org/event/making-changes

Organized by the AAAS Science and Technology Policy Fellowship’s Social Science Affinity Group in collaboration with the Affinity Groups on Energy/Climate, Health Policy, Global Health, Biodiversity, STEM Diversity and Women of Color in STEM.

Government agencies and contractors, non-governmental organizations, and private sector firms enact numerous policies and programs to achieve behavioral change in target populations, but often with mixed results. Promoting large-scale behavior change requires more than personal insights, “common sense”, and untested assumptions. Social scientists have spent decades learning what does and does not work to incite change, but there is often a gap when applying this to practice. Come join us on June 18th at the American Association for the Advancement of Science (AAAS) to learn what insights social science research can provide for better understanding human behavior and improving behavior change efforts!

The full-day symposium brings together different actors, including policymakers, public- and private-sector organizations, civil society, academics, and activists, who want to promote behavior change in individuals and organizations for the common good. The symposium will provide an opportunity to discuss both theory and examples, success stories and continued challenges, and what can be done to improve programs and policies. It will showcase academic research and practical experiences and will highlight common themes across sectors and fields, including health, environment, human rights, and countering extremism.

The symposium is free and open to the public. Breakfast and lunch will be provided.

Please RSVP here: http://aaaspolicyfellowships.org/event/making-changes