An article published January 8th in The Gazette examines the impact of the Maryland Dream Act after its first year. The law allows undocumented immigrants who graduate from Maryland high schools and meet certain conditions to pay in-state and in-county tuition at Maryland public community colleges and public universities.

The article, titled “The First Year of ‘Dreamers,'” references UMBC’s Maryland Institute for Policy Analysis and Research study on the economic impact of the Dream Act. The report concluded the Dream Act would benefit state and local governments with $6.2 million in economic activity.

The article mentions opponents’ claims that the Dream Act would reduce the number of openings available at public institutions, but UMBC’s study refutes that claim, stating that “additional undocumented immigrant students admitted to Maryland public community colleges — which have open enrollment — will have no impact on the probability that other students will or will not be admitted. It also stated that the Dream Act will not hurt the number of citizens admitted as freshmen to a four-year public university.”

The study is also mentioned when analyzing costs of the program for additional schooling on a per-student basis, “but such costs will be more than offset by increased tax dollars, as well as a drop in spending on incarceration and other social programs that is expected to accompany a more educated population, according to the study.”

You can read the full article in The Gazette here.

Computer Science and Electrical Engineering
University of Maryland, Baltimore County

Ph.D. Dissertation Proposal

Functional Reference Ontology Development:
a Design Pattern Approach

Yunsu Lee

1:00pm Friday, January 10, 2014, ITE325b, UMBC

The next generation of smart manufacturing systems will be developed by composing advanced manufacturing components and IT services introducing new technologies. These new technologies can lead to dramatic improvements in the ability to monitor, control, and optimize all aspects of manufacturing. The ability to compose advanced manufacturing components and IT services enhances agility, resiliency, and productivity of a manufacturing system. In order to make the composition possible, functional knowledge of manufacturing components and IT services should be captured and shared explicitly. Recent researches have shown that a semantically precise and rich reference functional ontology enables effective composition. However, since domains of factories and production networks are large, evolving, and heterogeneous, developing a reference functional ontology is a challenging task. Specifically, conceptual functionality modeling that characterizes various features of manufacturing components and IT services at different levels of abstraction is a difficult task. Even if the reference functional ontology is developed successfully, there will certainly be interoperability issues between the reference functional ontology and local proprietary information models. Firstly, the conceptual conflict issues may arise primarily from the fact that the reference functional ontology does not reflect actual users’ or providers’ conceptualizations. Secondly, structural conflict issues may arise from diverse modeling choices in local, proprietary information models.

The objective of our research is to assess utility of design patterns in addressing the issues in the reference functional ontology development, specifically OWL ontology design patterns (ODPs). To achieve the objective, we will assess inductive approaches to identifying the ODPs, and explore development of a methodology for resolving structural differences between the reference functional ontology and local proprietary information models. The key potential contributions of this work include 1) new method to identify information patterns of functionalities in manufacturing components and IT services, 2) new inductive ODP development process which starts with the pattern definition of the specific functionality concepts, with subsequent grouping of these patterns into more general patterns, and 3) ODP-based ontology transformation to resolve structural conflicts between the reference functional ontology and local proprietary information models.

Committee: Drs. Yun Peng (chair), Tim Finin, Yelena Yesha, Milton Halem, Nenad Ivezic (NIST) and Boonserm Kulvatunyou (NIST)

Computer Science and Electrical Engineering
University of Maryland, Baltimore County

Ph.D. Dissertation Proposal

Functional Reference Ontology Development: a Design Pattern Approach

Yunsu Lee

1:00pm Friday, January 10, 2014, ITE325b, UMBC

The next generation of smart manufacturing systems will be developed by composing advanced manufacturing components and IT services introducing new technologies. These new technologies can lead to dramatic improvements in the ability to monitor, control, and optimize all aspects of manufacturing. The ability to compose advanced manufacturing components and IT services enhances agility, resiliency, and productivity of a manufacturing system. In order to make the composition possible, functional knowledge of manufacturing components and IT services should be captured and shared explicitly. Recent researches have shown that a semantically precise and rich reference functional ontology enables effective composition. However, since domains of factories and production networks are large, evolving, and heterogeneous, developing a reference functional ontology is a challenging task. Specifically, conceptual functionality modeling that characterizes various features of manufacturing components and IT services at different levels of abstraction is a difficult task. Even if the reference functional ontology is developed successfully, there will certainly be interoperability issues between the reference functional ontology and local proprietary information models. Firstly, the conceptual conflict issues may arise primarily from the fact that the reference functional ontology does not reflect actual users’ or providers’ conceptualizations. Secondly, structural conflict issues may arise from diverse modeling choices in local, proprietary information models.

The objective of our research is to assess utility of design patterns in addressing the issues in the reference functional ontology development, specifically OWL ontology design patterns (ODPs). To achieve the objective, we will assess inductive approaches to identifying the ODPs, and explore development of a methodology for resolving structural differences between the reference functional ontology and local proprietary information models. The key potential contributions of this work include 1) new method to identify information patterns of functionalities in manufacturing components and IT services, 2) new inductive ODP development process which starts with the pattern definition of the specific functionality concepts, with subsequent grouping of these patterns into more general patterns, and 3) ODP-based ontology transformation to resolve structural conflicts between the reference functional ontology and local proprietary information models.

Committee: Drs. Yun Peng (chair), Tim Finin, Yelena Yesha, Milton Halem, Nenad Ivezic (NIST) and Boonserm Kulvatunyou (NIST)

AFST Majors and Minors: PAID Spring Internships Available with MD Legislators

Maryland state legislators and state legislative candidates continue to
contact POLI and AFST staff about internship opportunities during the legislative session (January-April 2014) or on their campaigns (now until primary election in June or general election in November).

Through a new collaboration, AFST will offer up to three paid internships for AFST majors/minors interested in working for members of the Legislative Black Caucus of Maryland. Juniors and seniors with GPAs of 3.0 and higher may be eligible for academic credit for such internships through the POLI internship program (requires spring enrollment in POLI 448) or through the AFST internship program (requires spring enrollment in AFST 490 for six credits).

The stipends are modest but the experience is invaluable. If interested, please contact Dr. King-Meadows (tkingmea@umbc.edu) or Dr. Hussey (lhussey@umbc.edu) as soon as possible.