Department of Computer Science and Electrical Engineering

MS Thesis Defense

Semantic Light: Building Blocks

Charles Lohr

2:15pm Thursday, 12 May 2011, ITE 346

The concept of Semantic Light is simply that lighting systems can be aware of what they are lighting. This offers a number of potential advantages over conventional lighting in quality and efficiency. Semantic Light requires fine grained control of the output of many lights and requires sensors to take in information about what is being lit. It uses this information to control the output lighting in great detail. By running various algorithms, Semantic Light can provide information to the user and has a number of applications including augmented reality.

Traditional lighting that is currently in wide use has limited control of quality and quantity of the light produced. Few lights for large-scale use are intended to control their output in any kind of detailed manner. Most area lighting only has a switch that must be manually turned on or off. While there are many commercial systems that allow for more fine grained control, they are typically limited to remote control, motion control and extra manual controls. These systems can be wasteful, or they may provide inappropriate amounts of light, or they may be on when no one is using them.

While other Semantic Lighting systems may focus on "green" or powern saving aspects, we concentrate instead on innovative roles Semantic Light could play as well as on the technology to make it possible to fill those roles. By emphasizing new utility and maximizing our speed to prototype, we have made several tradeoffs that will cause our system to be less efficient than it could be, even less efficient than traditional lighting systems. The ideas and concepts covered, however, could be adapted to different underlying technologies to produce a product that could provide considerable power saving over conventional lighting.

It is important to think of the many concepts covered as primary building blocks, rather than a complete commercial system. A number of refinements and extensions will be needed to produce a commercial viable product. We demonstrate all of the needed building blocks in a concise, prototyped system.

Committee:

• Mark Olano
• Yelena Yesha
• Zary Segall (advisor)

2011 CSEE Research Review

photos · program · posters · location · call for papers

The 2011 research review event was the largest to date, with more than eighty people attending. You can see pictures from the poster session and some of the presentations online.

The CRR-11 program committee selected students for best research based on submitted papers.

• Amy Ciavolino, Eliana Feasley, and Robert Deloatch were selected for best undergraduate research for their work Playing to Program: Towards an Intelligent Programming Tutor for RUR-PLE
• Pramod Jagtap was chosen for best research by a Masters student for his thesis work on Privacy Preservation in Context Aware Geosocial Networking Applications.
• Richard Carback won best research by a PhD student for his research on Scantegrity II Municipal Election at Takoma Park: The First E2E Binding Governmental Election with Ballot Privacy.
• Wenjia Li was selected for honorable mention for his PhD research on A Holistic Framework for Securing Mobile Ad Hoc Networks.

CSEE faculty who attended used range voting to honor three students for best poster presentations.

• First place was awarded to Justin Martineau for his work on Domain Independent Textual Sentiment Analysis.
   
• Second place was given to Charles Lohr for his work on Semantic Light: Building Blocks.
   
• Third place was awarded to Varish Mulwad for his work on Generating Linked Data by Inferring the Semantics of Tables.

MS Thesis Defense

Group Centric Information Sharing
using Hierarchical Models

Amit Mahale

10:00am Tuesday, 10 May 2011, ITE 346, UMBC

Traditional security policies are often based on the concept of “need to know” and are typified by predefined and often rigid specifications of which principals and roles are pre-authorized to access what information. A recommendations of the 9/11 commission was to find ways to move from this traditional perspective toward one that emphasizes the “need to share”. Ravi Sandhu and his colleagues have developed the Group centric secure information sharing model (gSIS) as a new model that is more adaptible to highly dynamic situations requiring information sharing. We present an implementation of gSIS and demonstrate its usefulness to usecases in information sharing in social media. Our contributions include the prototype implementation, extension to the model such as hierarchical groups and necessary and sufficient conditions, and the use of the semantic Web language OWL for representing the central gSIS concepts and associated data. Our framework uses a pragmatic approach of using semantic web technology to represent and reason about the hierarchy and procedural method to compute access decisions relying on the gSIS semantics.

Thesis Committee:

• Dr. Tim Finin (chair)
• Dr. Anupam Joshi
• Dr. Yelena Yesha
• Dr. Laura Zavala

The CSEE department will hold its annual research review this Friday from 9:30am to 4:00pm at the UMBC Technology Center at South Campus. Faculty, research staff and students from all of the department's programs present and discuss their latest research results. The Research Review 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. There is ample free parking and refrehsments and lunch are provided. Directions: Take Gun Road off Rolling Road (Rt. 166) or take the UMBC “Satellite” Shuttle to South Campus.

Twenty CSEE graduate students had oral or poster presentations at the 2011 GRC and CSEE alumnus Dr. Ralph Semmel gave a the keynote address. We have some photographs from the event.

Three of our graduates students were also honored by receiving awards for making outstanding presentations.

• Varish Mulwad received an award for an outstanding oral presentation on his dissertation research on "Generating Knowledge from Tables".

   

  Vast amounts of information are available in structured forms like spreadsheets, database relations, and tables found in documents and on the Web. We describe a framework for automatically understanding and interpreting information encoded in tables and generating knowledge from it. To accurately interpret a table, our framework maps every column header to class (or property wherever appropriate) from appropriate ontologies, link the data values to existing entities from a knowledge base (or map them as values of a property wherever appropriate) and identify and discover relations between various columns. Of the many domains where this work will be useful, we explore the application of this in two important domains — the medical research domain and the open government data. We also present preliminary results evaluating our framework against tables obtained from Google Squared, Wikipedia and a Google dataset.

• Kavita Krishnaswamy received an award for an outstanding oral presentation on her thesis research on "Path planning a roboticarm efficiently".

   

  Individuals with physical disabilities need assistance because of their lack of physical strength. In order to provide a solution, we propose to build an assistive robot to provide physical assistance services for individuals with disabilities in real-time through the Internet. For an assistive robotic arm with a collaborative mode of control, given the initial arm configuration we will attempt to increase the speed of response times for the user requesting physical assistance by calculating the paths of reach to the possible target goals before the time of command. The specific aims of our research project are to a) determine the trajectory path of a human arm to perform tasks; b) identify the paths of frequent use; and c) analyze ways to improve path planning performance. In the first stage, we will investigate the most frequently requested tasks of physical assistance in cases where a robotic arm will be preferred over a personal assistant. For example, if the target task is eating, we may calculate the percentage of volunteering participants picking up a fork, returning the fork, reaching for a cup, and returning the cup. In this study, we utilize the TUM kitchen data set from the Technische Universität München for motion tracking data analysis. With the collected information, we will compute the statistics of the motions to identify paths of frequent use and design the architecture with caching. We anticipate an increase in performance and time will be saved for the computation of path planning. We will begin implementing and testing the new strategies for the proposed architecture.

• Akshya Iyengar received an award for an outstanding poster presentation for her thesis research on "Estimating Temporal Boundaries of Events using Social Media Data".

   

  Social media websites like Twitter, Flickr and YouTube generate a high volume of user generated content as a major event occurs. Our goal is to automatically determine as accurately as possible when the event starts and when it ends by analyzing the volume and content of social media data. We describe a technique that estimates the temporal boundaries of anticipated events like wildfires and hurricanes and helps to monitor changes as events unfold. Estimating these temporal boundaries segments the event"related data into three major phases: the buildup to the event, the event itself, and the post"event effects and repercussions. The technique can also detect the presence and scope of significant sub"events occurring during the course of an event. For events that transpire over time and space, such as the dispersal of an oil spill, a hurricane or a spreading wildfire, we can analyze how event progressed, traveled geographically and major sub"events that occurred within the event. When applied to natural disasters and man-made disturbances, the derived data can help organizations involved in mediation efforts to track and analyze evolving events.

MS defense

Detection of Unsafe Action in Laparoscopic Cholecystectomy Video

Ashwini Lahane

10:00am Thursday, 28 April 2011, ITE 346

Wellness and healthcare are central to the lives of all people. Information technology has already contributed in significant ways towards enhancement of healthcare delivery and to improving the quality of life. And it will continue to do so with the development of “smarter” technologies and environments. Recent years have seen context awareness as one of the most important aspects in the emerging pervasive computing paradigm. We focus our work on situation awareness; a more holistic variant of context awareness where situations are regarded as logically aggregated contexts. We demonstrate an application of situation aware computing in healthcare. We primarily focus on laparoscopic cholecystectomy, a complex yet commonly performed surgical procedure. The outcome of the surgery is influenced greatly by the training, skill, and judgment of the surgeon. Many surgical simulators have been developed to meet the training and practice needs of the surgeons. However few systems provide feedback during the actual surgery. We present a method to detect a situation, that shows possibility of injury to an artery by analyzing the laparoscopic cholecystectomy surgical video. The system can be used to provide feedback to the operating surgeon in case of a possible risk. We have also built a prototype to demonstrate the use of our system in telemedicine, in the form of a web service.

Thesis Committee:

• Dr. Yelena Yesha (chair)
• Dr. Anupam Joshi
• Dr. Milton Halem
• Dr. Michael Grasso

EE Graduate Seminar

Complex-valued Adaptive Signal Processing:
Applications in Medical Imaging

Prof. Tulay Adali
Machine Learning for Signal Processing Laboratory
CSEE Dept/UMBC

1-2pm Friday, 29 April 2011, ITE 237

Complex-valued signals arise frequently in applications as diverse as communications, radar, geophysics, optics, and biomedicine, as most practical modulation formats are of complex type and applications such as radar and magnetic resonance imaging lead to data that are inherently complex valued. The complex domain, however, presents unique challenges for signal processing, in particular for adaptive nonlinear processing, and as a result, until recently, most algorithms derived for the complex domain have taken engineering shortcuts limiting their usefulness. The most common one among those has been assuming the circularity of the signal, thus ignoring the information conveyed by the phase. Similarly when taking gradients in the complex domain, a "split" approach that performs optimization separately with respect to the real and imaginary variables has been the dominant practice.

There have been important advances in the area within the last decade that clearly demonstrate that noncircularity is an intrinsic characteristic of many signals of practical interest, and when taken into account, the methods developed for their processing may provide significant performance gains. Similarly, it has been shown that using Wirtinger calculus, all calculations can be carried out in a manner similar to real-valued calculus while keeping all the computations in the complex domain.

In this talk, after a brief introduction to optimization using Wirtinger calculus and statistics in the complex domain, and then I will give examples from some of the recent work conducted at the MLSP-Lab.

MS Defense

Exploiting Architectural Techniques for Boosting
Base Station Anonymity in Wireless Sensor Networks

Zhong Ren

2:00pm Thursday, 28 April 2011, ITE 346

Wireless Sensor Networks (WSNs) can be deployed to serve mission-critical applications in hostile environments such as battlefield and territorial borders. In these setups, the WSN may be subject to attacks in order to disrupt the network operation. The most effective way for an adversary to do so is by targeting the Base-Station (BS), where the sensor data are collected in the field. By identifying and locating the BS, the adversary can launch attacks to damage or disrupt the operation of the BS. Therefore, maintaining the BS anonymity is of utmost importance in WSNs.

In this thesis we propose three novel approaches to boost the anonymity of the BS nodes to protect them from potential threats. We first explore the deployment of more BS nodes. We compare the BS anonymity of one versus multiple stationary BS under different network topologies. Our results show that having more base-stations can boost both the average and max anonymity of BS nodes. We further provide guidelines on a cost versus anonymity trade-off to determine the most suitable BS count for a network. Second we exploit the mobility of base-stations and explore the effect of relocating some of the existing BS nodes to the lowest anonymity regions. Our results show that having one mobile BS can dramatically boost the anonymity of the network and moving multiple BS does not provide much value. Finally, we propose to pursue dynamic sensor to cluster re-association to confuse the adversary. This can be employed when base-stations cannot safely move.

Committee members:

• Mohamed Younis (Chair)
• Yun Peng
• Charles Nicholas

Congratulations to the record number of CSEE graduate students who will make oral or poster presentations at the 2011 UMBC Graduate Research Conference on Friday April 29th. The presentations will take place in two sessions, one 9:00 to 10:50 and another 11:00 to 12:50. Poster sessions will be on the seventh floor of the library and oral presentations in UC 312. See the GRC site for a program booklet with abstracts and the session schedules.

Oral presentations:

• Yousef Ebrahimi, Increasing Transmission Power for Higher Base-station Anonymity in Wireless Sensor Network
• Zamon Granger, Stabilizing Air Pressure in a Hermetic Environment with Embedded Technology
• Congchong Liu, Optimizing MapReduce Programming Model through Adaptive Load Balance
• Kavita Krishnaswamy, Path planning a robotic arm efficiently
• Varish Mulwad, Generating knowledge from tables
• Darshana Dalvi, Genome-based Clinical Decision Support System
• Ashwini Lahane, Detection of unsafe actions in laparoscopic cholecystectomy surgical videos
• Karuna Pande Joshi, Lifecycle of virtualized services on the cloud
• Jon Ward, ICF: A Physical Layer Metric for Measuring Anonymity in Wireless Sensor Networks
• Theoplis E. Stewart Sr., Smart Grid: What are some underlying implications to overlaying digital technology onto the electric power grids?

Poster presentations:

• Sai Ma, Tom Eichele and Nicolle M. Correa, Hierarchical and graphical analysis of fMRI network connectivity in healthy and schizophrenic groups.
• Shiming Yang , Near Real"time Data Assimilation for the HYSPLIT Aerosol Dispersion Model.
• Yu Wang , A Framework for GPU 3D Model Reconstruction using Structure-from-Motion
• Akshaya Iyengar, Estimating Temporal Boundaries of Events using Social Media Data
• Brice Cannon, Paveen Apiratikul and John Hryniewicz, Characterization of semiconductor optical waveguides
• Brian White Jr., The Mobile Memory
• Xing Chen, Standoff photoacoustic chemical detection using quantum cascade lasers
• Yi Xin, On Gas Detection and Concentration Estimation via Mid-IR-based Gas Detection System Analysis Model
• Robert J. Weiblen, Calculation of the expected bandwidth for a mid-infrared supercontinuum source based on As2S3 chalcogenide photonic crystal fibers
• Pramod Jagtap, Privacy Preservation in Context Aware Geo-social Networking Applications

MS Defense

Privacy Preservation in Context-Aware Systems

Pramod Jagtap

1:00pm Wednesday, 27 April 2011, ITE 210

Recent years have seen a confluence of two major trends – the increase of mobile devices such as smart phones as the primary access point to networked information and the rise of social media platforms that connect people. Their convergence supports the emergence of a new class of context-aware geosocial networking applications. While existing systems focus mostly on location, our work centers on models for representing and reasoning about a more inclusive and higher-level notion of context, including the user’s location and surroundings, the presence of other people and devices, feeds from social networking systems they use, and the inferred activities in which they are engaged. A key element of our work is the use of collaborative information sharing where devices share and integrate knowledge about their context. This introduces the need for privacy and security mechanisms. We present a framework to provide users with appropriate levels of privacy to protect the personal information their mobile devices are collecting including the inferences that can be drawn from the information. We use Semantic Web technologies to specify high-level, declarative policies that describe user’s information sharing preferences. We have built a prototype system that aggregates information from a variety of sensors on the phone, online sources, and sources internal to the campus intranet, and infers the dynamic user context. We show how our policy framework can be effectively used to devise better privacy control mechanisms to control information flow between users in such dynamic mobile systems.

Presentation

Thesis Committee:

• Dr. Anupam Joshi (chair)
• Dr. Tim Finin
• Dr. Yelena Yesha
• Dr. Laura Zavala