MS defense: eXtensible Dynamic Form (XDF) for Supplier Discovery

MS Thesis Defense

eXtensible Dynamic Form (XDF) for Supplier Discovery

Yan Kang

1:00PM Tuesday, 26 April 2011, ITE 346

Discovery of suppliers (supplier discovery) is essential for building a flexible network of suppliers in a supply chain. The first step for supplier discovery is to collect manufacturing capabilities of suppliers and requirements of customers. In traditional e-marketplaces, online form interfaces are typically used to collect the requirements and capabilities. However, those forms are mostly lack of flexibility to capture a variety of requirements and capabilities in a structured way. In this thesis, we propose new innovative form architecture called eXtensible Dynamic Form (XDF) to facilitate data collection process of supplier discovery.

This architecture provides several key innovations including: 1) architecture for users (suppliers or customers) to create new structure of form for their own contents; 2) an intelligent search engine facilitating users to reuse the existing form components 3) hierarchical representation of the requirements and capabilities as XML instances. Experimental results demonstrate that the proposed architecture is valuable for facilitating the supplier discovery process.

Thesis Committee:

  • Dr. Charles Nicholas
  • Dr. Yun Peng (Chair)
  • Dr. Yelena Yesha

MS defense: Recovering from Soft Node Failures in Wireless Sensor Networks using Neural Networks

MS Thesis Defense

Recovering from Soft Node Failures in
Wireless Sensor Networks using Neural Networks

Shivvasangari Subramani

9:00am Tuesday, 26 April 2011, ITE 346

In the past few years, wireless sensor networks (WSNs) have become important in different applications because of their robustness in hostile environments. WSNs need to perform in a timely manner in the face of interference, attacks, accidents, and failures. Being a battery operated system, there is a trade-off between performance and energy utilization. In this thesis we focus on WSN accuracy and consider ways to improve the performance of WSNs when sensors become damaged, resulting in poor input signal quality. When all other components of the sensor like the processor, memory, and battery are working, our proposed solution is to learn to undo the damage in a node by training on neighbors sensor values.

Thesis Committee:

  • Dr. Anupam Joshi
  • Dr. Tim Oates (chair)
  • Dr. Mohamed Younis

MS defense: Graph-Theoretic Approach to Collusion Detection in Multi-Agent Systems

MS Thesis Defense

A Graph-Theoretic Approach to
Collusion Detection in Multi-Agent Systems

Peter Hamilton

9:00am Thursday, 28 April 28 2011, ITE 325B

The study of trust and cooperation is a major component of multi-agent systems research. Such work often focuses on how best to estimate the reliability of a specific agent, or how to create strategies and protocols that engender the most cooperation from the most agents. However, when cooperation is not a desired aspect of a multi-agent system, these actions define collusive behavior, which can have a significant impact on the dynamics of the system.

This thesis defines a generic, graph-theoretic approach to collusion detection known as CODING. This approach detects group-based collusion, targeting two basic collusion mechanisms that rely on large numbers of colluding agents for success. CODING analyzes and classifies agent interactions from the system and constructs a series of interaction graphs from this data. These graphs are processed for structures that correspond to collusion mechanisms; the agents composing these structures are reported as colluders. CODING is applied to a game theory domain, in which it must detect agents adhering to group strategies in round-robin tournaments composed of single-player strategies.

Thesis Committee:

  • Dr. Marie desJardins (chair)
  • Dr. Tim Finin
  • Dr. Tim Oates

 

MS defense: Feature Extraction using a Hierarchical Growing Neural Gas

M.S. Thesis Defense Announcement

Feature Extraction using a Hierarchical Growing Neural Gas

Roger Guseman

12:00pm 25 April 2011, ITE 210

Unsupervised, data-driven, automatic feature extraction from image data is an interesting and difficult problem. High dimensional data, such as images, often contain less information than they do data. For an agent to better reason about this data, finding the "interesting" features in the data is helpful. A current technique, known as the Growing Neural Gas (GNG), is a neural network approach to feature extraction. There are, however, adaptations that can be made to the Growing Neural Gas in order to increase its performance.

Contributions of this work include development of a new neural network algorithm extending the Growing Neural Gas framework, known as the Hierarchical Growing Neural Gas (HGNG), identification of how the parameters of the HGNG affect feature extraction performance, and theoretical and empirical comparisons of performance between the normal GNG and the HGNG neural networks.

Thesis Committee:

  • Dr. Tim Oates (chair)
  • Dr. Tim Finin
  • Dr. Marie desJardins

 

MS defense: Problem selection of program tracing tasks in an intelligent tutoring system

Master's Thesis Defense Announcement

Problem Selection of Program Tracing Tasks in an Intelligent
Tutoring System and Visual Programming Environment

David Walser

2:00pm Thursday, 28 April 2011, ITE 325b

Intelligent tutoring systems (ITSs) have been shown to be an effective supplementary teaching tool or aid for many domains. Applying ITSs in open-ended domains such as computer programming is especially challenging, most notably when trying to assist with the process of programming itself. Existing ITSs for programming focus on a very limited set of problems and concepts and are only useful early in an introductory CS course and a few limited places afterward. Visual programming environments are another tool that have been used in introductory CS courses to help students learn basic concepts. The key idea behind my work is the recognition of the importance of students' ability to read, understand, and trace code in order to write programs successfully. A broader goal of my work is to show that an ITS based on a visual programming environment can be used to support students throughout an entire introductory CS course, without being severely constrained and limited to a small number of concepts and to low-level, simple tasks. In my system, called RUR-ITS, students are given a program and are asked to predict the robot's behavior when running this program in a given environment. RUR-ITS allows each problem to be assigned a difficulty level and multiple concepts that it involves within the conceptual model. RUR-ITS can then use a problem selection algorithm to choose a problem that is most able to help the student master the concepts that they have not yet mastered.

Thesis Committee:

  • Dr. Marie desJardins, Chair
  • Dr. Tim Finin
  • Dr. Tim Oates

     

Maryland Cyber Conference and Challenge (MDC3)

The Maryland Cyber Challenge and Conference site is up and student teams can now register for the competition, with the first qualifying round early in September. It is a chance to demonstrate your ability to work in a team and your cybersecurity and problem solving skills.

MDC3 is a joint effort between SAIC, UMBC, DBED, TCM and NCSA to bring people together to promote Maryland's commitment to cybersecurity and STEM education. The competition includes three levels: high school, collegiate and professionals from industry/government, providing opportunities to network with cybersecurity professionals, researchers, and scholars.

There will be orientation sessions at the UMBC Technology Center (1450 South Rolling Rd., 21224) on May 2, May 18 and June 21 at 4:30pm for professionals and 6:00pm for students.

Semantic Analysis of XML Schema Matching for B2B (Dissertation Defense)

PhD Dissertation Defense Announcement

A Semantic Analysis of XML Schema Matching
for B2B Systems Integration

Jaewook Kim

11:00am Thursday, 21 April 2011, ITE 346

One of the most critical steps to integrating heterogeneous e-Business applications using different XML schemas is schema matching, which is known to be costly and error-prone. Many automatic schema matching approaches have been proposed, but the challenge is still daunting because of the complexity of schemas and immaturity of technologies in semantic representation, measuring, and reasoning. The dissertation focuses on three challenging problems in the schema matching. First, the existing approaches have often failed to sufficiently investigate and utilize semantic information imbedded in the hierarchical structure of the XML schemas. Secondly, due to synonyms and polysemies found in natural languages, the meaning of a data node in the schema cannot be determined solely by the words in its label. Thirdly, it is difficult to correctly identify the best set of matching pairs for all data nodes between two schemas. To overcome these problems, we propose new innovative approaches for XML schema matching, particularly applicable to XML schema integration and data transformation between heterogeneous e-Business systems. Our research supports two different tasks: integration task between two different component schemas; and transformation task between two business documents which confirm to different document schemas.

Dissertation Committee:

  • Dr. Yun Peng, Chair
  • Dr. Charles Nicholas
  • Dr. Zary Segall
  • Dr. Milton Halem
  • Dr. Hyunbo Cho (POSTECH, Korea)
  • Dr. Nenad Ivezic (NIST)

CSEE IT Jobs Summer 2011 and Beyond

The CSEE Department at UMBC has IT job positions available.  The positions include a Web Administrator and System Administrator.  Full descriptions for each position below.  Details include how to apply and what information is expected to be provided.

Student Web Administrator position.

This position is a hybrid of providing support for the CSEE Web portals, software development, and leveraging the capabilities of UNIX systems as a host platform. Expected projects include Website design and content editing, develop/code dynamic content, and create/edit graphics.  There is a need to understand what good Web design means and the direction of where Web trends are going.
 
Are you the resource who people come to when they have a computer problem?  Do you find fixing computers easy?  Do you run your own server?  Do you like learning new skills, making people happy, and gaining a sense of accomplishment?  If you relate to these attributes, this is a great opportunity for you.

Duties:

  • Engineer solutions to Web-related problems in a UNIX environment.
  • Manage Web applications and be able to extend functionality by writing new code.
  • Support the users of Web sites/portals.
  • Assist in ongoing projects.
  • Other duties as assigned.

Requirements:

  • Experience with a Linux/UNIX system.
  • Program UNIX shell scripts, C/C++, PERL, Python, and/or PHP.
  • Understand HTML, CSS, and modern Web technologies.
  • Excellent oral and written communication skills.
  • Excellent troubleshooting skills.
  • Able to quickly learn new skills.
  • Able to work well in a group.
  • Available to work up to 20 hours/week.
  • Active UMBC student.

Desired (will train as needed):

  • Major in Computer Science, Computer Engineering, or a related field.
  • Exposed to content management system and revision control system.
  • Manage databases and write SQL queries.

Please submit resumes by email to cseeit-jobs AT cs DOT umbc DOT edu . Resumes accepted until the position is filled.  Also provide an example of something cool that you have done with a Web site.

UNIX Student System Administrator position.

This position will provide computer hardware, software, and network support for the operational needs of the CSEE department at UMBC.  The CSEE computer infrastructure is extremely diverse, dynamic, and challenging. This position will be part of a technical team of experts, who support over 700 user accounts and over 600 Linux, Solaris, Windows, and MacOS machines in office, data center, and research environments.  The computers range from individual desktops to production servers which run 24 hours per day (such as Web portals, email, and database servers).

Are you the resource who people come to when they have a computer problem? Do you find fixing computers easy?  Do you run your own server?  Do you like learning new skills, making people happy, and gaining a sense of accomplishment?  If you relate to these attributes, this is a great opportunity for you.

Duties:

  • Engineer solutions to problems in a UNIX environment.
  • Support desktop and server computers for end-users (operational staff, graduate students, and faculty) and networking needs through the installation and configuration of computer hardware and software.
  • Support the daily operations and maintenance of the CSEE computing and networking facilities (such as accounts, printers, applications, etc.).
  • Support real/virtual server environment and real/virtual disk storage systems
  • Assist in ongoing projects.
  • Other duties as assigned.

Requirements:

  • Experience with one or more types of Linux/UNIX system.
  • Program UNIX shell scripts, C/C++, PERL, Python, and/or PHP.
  • Excellent oral and written communication skills.
  • Excellent troubleshooting skills.
  • Able to quickly learn new skills.
  • Able to work well in a group.
  • Available to work up to 20 hours/week (up to 40 during summer or breaks).
  • Active UMBC student.

Desired (will train as needed):

  • Major in Computer Science, Computer Engineering, or a related field.
  • Familiar with the CSEE Department's computing environment.
  • A working knowledge of Sun/Oracle Solaris/OpenSolaris operating system and/or Windows.

Please submit resumes by email to cseeit-jobs AT cs DOT umbc DOT edu . Resumes accepted until the positions are filled.  Also provide an example of something cool that you have done with UNIX/Linux.

 

Dissertation Defense: Towards Relational Theory Formation from Undifferentiated Sensor Data

Dissertation Defense

Towards Relational Theory Formation
from Undifferentiated Sensor Data

Marc Pickett

10:00am Monday, 18 April 2011
ITE 325b, UMBC

Human adults have rich theories in their heads of how the world works. These theories include objects and relations for both concrete and abstract concepts. Everything we know either must be innate or learned through experience. Yet it's unclear how much of this model needs to be innate for a computer. The core question this dissertation addresses is how a computer can develop rich relational theories using only its raw sensor data. We address this by outlining a "bridge" between raw sensors and a rich relational theory. We have implemented parts of this bridge, with other parts as feasibility studies, while others remain conceptual.

At the core of this bridge is Ontol, a system that constructs a conceptual structure or "ontology" from feature-set data. Ontol is inspired by cortical models that have been shown to be able to express invariant concepts, such as images independent of any translation or rotation. As a demonstration of the utility of the ontologies created by Ontol, we present a novel semi-supervised learning algorithm that learns from only a handful of positive examples. Like humans, this algorithm doesn't require negative examples. Instead, this algorithm uses the ontologies created by Ontol from unlabeled data, and searches for a Bayes-optimal theory given this "background knowledge".

The rest of the dissertation shows in principle how Ontol can be used as the "workhorse" for a system that finds analogies, discovers useful mappings, and might ultimately create theories, such as a "gisty" theory of "number".

Committee:

  • Tim Oates, Associate Professor, UMBC
  • Tim Finin, Professor, UMBC
  • Rob Goldstone, Professor, Indiana University
  • Sergei Nirenburg, Professor, UMBC
  • Matt Schmill, Research Faculty, UMBC

Serial entrepreneur David Turock to talk at Baltimore Emerging Technology Center

The Baltimore ACM Chapter, the Greater Baltimore Technology Council, and the Emerging Technology Center are hosting a free, public lecture on entrepreneurship by David Turock at 7:00pm, Wednesday 27 April in the ETC Canton facility (2400 Boston St., Baltimore).

David Turock will present a side-by-side comparison of two telecommunications start-ups that he launched: one successful, and one not. He compares and contrasts their funding sources, agility and scalability of their business models, hiring practices, and more. His experience and lessons learned will be valuable for aspiring tech entrepreneurs. He finishes with how his interests have shifted to using technology to promote social and environmental causes.

David Turock is a veteran entrepreneur and currently a Director of Counsel RB Capital. He holds a patent on VoIP, and is an expert on telecommunications technologies and their applications. Mr. Turock began his career working with AT&T Bell Laboratories in 1982 and Bell Communications Research in 1988, and subsequently founded enhanced telephone service provider, Call Sciences. He later formed Interexchange, which designed and operated one of the world's largest debit card systems. Most recently, from 2001 to 2007, Mr. Turock was Chief Technology Officer of Therap Services, a provider of informatics services to disabled patients. Mr. Turock received his B.S. in Experimental Psychology from Syracuse University, his M.S. and Ph.D. degrees in Cognitive Psychology from Rutgers University, and his M.S.E. in Computer Science from the Moore School of the University of Pennsylvania.

The Baltimore ACM chapter invites attendees for pizza starting at 6:30pm. There is no charge, but please RSVP to Emil Volcheck at

The ETC Canton facility is located at the American Can Company complex, 2400 Boston Street in Baltimore. ETC is on the 3rd floor of the building that houses the Austin Grille restaurant and the entrance is next to the Lenscrafters store. There is a 3 hour visitor parking in front of the building on the Boston Street side.

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