Computer Engineering Commons^™

Parallelizing Scale Invariant Feature Transform On A Distributed Memory Cluster, Stanislav Bobovych

Inquiry: The University of Arkansas Undergraduate Research Journal

Scale Invariant Feature Transform (SIFT) is a computer vision algorithm that is widely-used to extract features from images. We explored accelerating an existing implementation of this algorithm with message passing in order to analyze large data sets. We successfully tested two approaches to data decomposition in order to parallelize SIFT on a distributed memory cluster.

Evidence Supporting Measure Of Similarity For Reducing The Complexity In Information Fusion, Florentin Smarandache, Jean Dezert, Xinde Li, Xinhan Huang

Branch Mathematics and Statistics Faculty and Staff Publications

This paper presents a new method for reducing the number of sources of evidence to combine in order to reduce the complexity of the fusion processing. Such a complexity reduction is often required in many applications where the real-time constraint and limited computing resources are of prime importance. The basic idea consists in selecting, among all sources available, only a subset of sources of evidence to combine. The selection is based on an evidence supporting measure of similarity (ESMS) criterion which is an efficient generic tool for outlier sources identification and rejection. The ESMS between two sources of evidence can …

Development Of Visualization Facility At The Gis And Remote Sensing Core Lab, University Of Nevada, Las Vegas, Haroon Stephen, William J. Smith, Zhongwei Liu

Public Policy and Leadership Faculty Presentations

Visualization using advanced computational and graphic equipment has become a standard way of present day research. Availability of low cost and fast processing units, high resolution displays with graphic processing units, and specialized software has brought complex visualization capabilities to an office desktop. Nevertheless, when dealing with large datasets such as, global climate, geospatial, and social data the office desktop falls short and calls for a centralized visualization facility with high end computing and graphics equipment.

Visualization Facility at GIS and Remote Sensing Core Lab would be a useful and important addition to the UNLV IT infrastructure. It would provide …

Investigations Into Library Web Scale Discovery Services, Jason Vaughan

Library Faculty Publications

Web scale discovery services for libraries provide deep discovery to a library’s local and licensed content, and represent an evolution, perhaps a revolution, for end user information discovery as pertains to library collections. This article frames the topic of Web scale discovery, and begins by illuminating Web scale discovery from an academic library’s perspective – that is, the internal perspective seeking widespread staff participation in the discovery conversation. This included the creation of a Discovery Task Force, a group which educated library staff, conducted internal staff surveys, and gathered observations from early adopters. The article next addresses the substantial research …

Semi-Automatic Management Of Knowledge Bases Using Formal Ontologies, Andreas Textor

Theses

This thesis presents an approach that deals with the ever-growing amount of data in knowledge bases, especially concerning knowledge interoperability and formal representation of domain knowledge. There arc multiple issues that must be addressed with current systems. A multitude of different formats, sources and tools exist in a domain, and it is desirable to develop their use further towards a standardised environment. Such an environment should support both the representation and processing of data from this domain, and the connection to other domains, where necessary. In order to manage large amounts of data, it should be possible to perform whatever …

Contextualized Mobile Support For Learning By Doing In The Real World, Ray Bareiss, Natalie Linnell, Martin Griss

Ray Bareiss

This research addresses the use of mobile devices with both embedded and external sensors to provide contextualized help, advice, and remediation to learners engaged in real-world learn-by-doing tasks. This work is situated within the context of learning a complex procedure, in particular emergency responders learning to conduct urban search and rescue operations. Research issues include the design and delivery of contextualized performance support and the inferring of learner actions and intentions from sensor data to ensure that the right support is delivered just in time, as it is relevant to what the learner is doing.