Gongzhu Hu

Study of definable subsets in covering approximation spaces of rough sets

Intelligent decision systems often need to deal with vague and uncertain data. Several approaches are commonly used to address this problem, such as statistical methods, machine learning, and fuzzy set. Overlapping with but different from the fuzzy set theory, rough set theory is a relatively new mathematical approach to vague data analysis. A rough set is basically an approximation representation of the given data. The representation is expressed in two subsets defined on the data set: the upper and lower approximations. The main difference between the rough set theory and other approaches is that it does not rely on preliminary information about the data such as membership probabilities of the data items required for fuzzy set. One of the open questions in rough set is to decide if a subset of a covering approximation space is definable. In this paper, we answer this question by investigating the approximation operator and conclude the relation of the inner definable, outer definable, and definable subsets of a covering approximation space under certain conditions.

Innovations in News Media: Crisis Classification System

Research in crisis management is a relatively new area of study, originating in the 1980s. Researchers have created several different models that separate organizational crises into discrete stages, such as pre-crisis, crisis and post-crisis. In this article we discuss a natural language based crisis detection system which classifies news articles relating to crises into the appropriate crisis stage. We use news articles from the New York Times as a source of training data, and use this data along with state of the art data mining and machine learning algorithms as the core of the system. In the future, our system may be expanded to identify and evaluate crisis management strategies, suggest crisis management strategies for the current state of a crisis, or provide stakeholders with summaries of crises in news media.

Panel discussion: Re-use of information and data in energy management

With the current world economic crisis and the responsibility of all citizens to “go green” comes the need to provide efficient means for improving energy consumption. For example, the demand for electricity is at its peak during the summer months in general and during hot summer days in particular. The increased use of electrical appliances, HVAC systems and electric vehicles for residential customers, for example, plays a considerable role in this demand. However, usage of these appliances can be done in a more cost efficient manner through scheduling, avoiding peak demand periods, and reducing consumption when the home is vacated. So how can the research and technologies associated with information re-use and integration (IRI) be applied to alleviate the energy crisis? This panel focuses on the energy management issue and looks at ways of applying information re-use principles to address energy management. Particular issues that our panelists may address include: • What technologies are available that could be enhance by IRI to address the energy crisis? • What new technologies need to be developed? • How does the government, industry and academia participate in solving the crisis? • What are some of the political, social and/or security barriers that impede the use of IRI in resolving our energy problems? • Where should the funding be placed in developing better energy management programs (industry, academia…)? • What is the role of knowledge-based systems in improving the efficiency of energy systems and in reducing associated costs? • What is our role as researchers and academicians to enhance the use of information integration for energy management? • How does education play a role in resolving this crisis? The focus of this IRI 2013 panel is to investigate how IRI research and its technologies can resolve some of the energy issues and how to use this to encourage funding for IRI. Panelists will look at not only the technical issues but also the sociological and cultural issue that need to be addressed in order to make a difference in our world.

Geographic clustering of research universities in specialized fields using Microsoft Academic Search

Search is no doubt the most common activities on the Web. One of the most frequent search activities people in the educational and academic communities do is to search for research topics and papers and their author/affiliation information. For example, undergraduate students searching for graduate schools and master-level students searching for institutions for doctoral studies may go online to find universities that are conducting research in a highly specific field of their interest. A common way of doing this is to search journals and conferences for pertinent articles, and then accumulating the affiliations of the authors. In this paper, we present an interactive web-based academic search interface for discovering geographic clusters of academic institutions given a specific field by the user. The underlying system interacts with Microsoft Academic Search API and Google Places API, as well as Weka for clustering analysis. The system can be easily extended to accommodate other types of queries.

Panel: Converting innovation to commercialization: Information re-use from the research sector to the public sector

There exist many centers within the academic and government environments which have as its mission providing a catalyst for moving ideas to commercialization, in order to create jobs and enhance the economy. For example, The von Liebig Center at the University of California at San Diego, The Deshpande Center at MIT and the Inventor Resource Center at North Carolina State University provide researchers the opportunity to investigate the potential of commercialization. As another example, The Center for Commercialization of Advanced Technology (CCAT) at San Diego State University is a technology commercialization and transition collaborative partnership of academia, industry, and government. The Center is funded by the Office of Naval Research, the Office of Secretary of Defense, and the Department of Homeland Security and focuses on identifying innovative technologies that address “critical homeland security and national defense challenges” and in moving these technologies through the prototype stage to full deployment systems in the commercial marketplace.

Panel title: Critical need for funding of basic and applied research in large-scale computing

Information re-use and integration can be applied to a multitude of areas in the civil, military, and commercial arenas. In IT, the approach has been applied to coding, frameworks, and architectures, amongst others. In the commercial sector, information re-use and integration has been successfully applied to web services, e-commerce, and VLSI design.