Paul Mc Kevitt

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Phone: +44 28 71675433
Address: Professor Paul Mc Kevitt
Chair in Digital MultiMedia
School of Creative Arts & Technologies
Faculty of Arts
University of Ulster, Magee
BT48 7JL, Derry/Londonderry
NORTHERN IRELAND

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ULTIMEDIA is growing rapidly and internationally, with various meanings from different points of ... more ULTIMEDIA is growing rapidly and internationally, with various meanings from different points of view. It can be separated into at least two areas: (traditional) MultiMedia and Intelligent MultiMedia (IntelliMedia). Traditional MultiMedia encompasses the display of text, voice, sound and video/graphics with possibly touch and virtual reality linked in. However, the computer has little or no understanding of the meaning of what it is presenting. IntelliMedia, which involves the computer processing and understanding perceptual input from at least speech, text and visual images, and then reacting to it, is much more complex and involves signal and symbol processing techniques from not just engineering and computer science but also artificial intelligence and cognitive science. Mark Maybury is right in his Introduction when he points to global information highways (or SuperinformationhighwayS-see Mc Kevitt 1997a) as one of the key factors driving the need towards Intelligent MultiMedia. SuperinformationhighwayS alone are reason enough for us to seek more effective means of retrieving and interacting with spoken language and images. In Maybury's review of the blue book he notes that some reordering of the papers (for example, Srihari) might be useful, although we were constrained not only by time (we got all four books out in two years which is unusual in academic circles) but also by the fact that we were spinning off from the AI Review Journal. I should point out that the rainbow collection builds upon Mark's original collection on Intelligent MultiMedia (Maybury 1993) which is reviewed in the 'black book', and furthermore his new collection on Intelligent User Interfaces (Maybury 1998) builds in turn upon the rainbow.

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Acquisition of Entity-Relationship Models from Natural Language Specifications using Heuristics

Editorial

A Skin Tone Detection Algorithm for An Adaptive Approach to Steganography

by Paul Mc Kevitt and Abbas Cheddad

Signal Processing, Jan 1, 2009

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Why machines should analyse intention in natural language dialogue

International Journal of Human-Computer Studies, 1999

Integration of Natural Language and Vision Processing: Grounding representations

Artificial Intelligence Review, 1996

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Mobile MultiModal dynamic output morphing tourist systems

TeleMorph dynamically generates multimedia presentations using output modalities that are determi... more TeleMorph dynamically generates multimedia presentations using output modalities that are determined by the bandwidth available on a mobile device's wireless connection. To demonstrate the effectiveness of this research TeleTuras, a tourist information guide for the city of Derry will implement the solution provided by TeleMorph, thus demonstrating its effectiveness. This paper concentrates on the motivation for & issues surrounding intelligent tourist systems.

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The relevance of beliefs to natural language communication

Language, Vision, and Music: Report on the Eighth International Workshop on the Cognitive Science of Natural Language Processing (CSNLP-8)

AI Magazine, 2000

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Query Construction and Result Presentation based on Graph Codes

Indexing and Retrieval of Multimedia is generally implemented by employing feature graphs. These ... more Indexing and Retrieval of Multimedia is generally implemented by employing feature graphs. These graphs typically contain a significant number of nodes and edges to reflect the level of detail in feature detection. A higher level of detail increases the effectiveness of the results, but also leads to more complex graph structures. However, graph-traversal-based algorithms for similarity are quite inefficient and computation intensive, especially for large data structures. Graph Codes provide a flexible and highly efficient solution to deliver fast and effective retrieval. This significant increase in efficiency and effectiveness, especially for Multimedia indexing and retrieval, is applicable to images, videos, text, and Social Media information features. However, existing query construction methodologies and retrieval algorithms have to be extended to utilize the higher level-of-detail and the fusion of these various Multimedia technologies. Thus, in this paper we present detailed ...

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Towards Automated Semantic Explainability of Multimedia Feature Graphs

Information

Multimedia feature graphs are employed to represent features of images, video, audio, or text. Va... more Multimedia feature graphs are employed to represent features of images, video, audio, or text. Various techniques exist to extract such features from multimedia objects. In this paper, we describe the extension of such a feature graph to represent the meaning of such multimedia features and introduce a formal context-free PS-grammar (Phrase Structure grammar) to automatically generate human-understandable natural language expressions based on such features. To achieve this, we define a semantic extension to syntactic multimedia feature graphs and introduce a set of production rules for phrases of natural language English expressions. This explainability, which is founded on a semantic model provides the opportunity to represent any multimedia feature in a human-readable and human-understandable form, which largely closes the gap between the technical representation of such features and their semantics. We show how this explainability can be formally defined and demonstrate the corre...

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Fast and Effective Retrieval for Large Multimedia Collections

Big Data and Cognitive Computing

The indexing and retrieval of multimedia content is generally implemented by employing feature gr... more The indexing and retrieval of multimedia content is generally implemented by employing feature graphs. These graphs typically contain a significant number of nodes and edges to reflect the level of detail in feature detection. A higher level of detail increases the effectiveness of the results, but also leads to more complex graph structures. However, graph traversal-based algorithms for similarity are quite inefficient and computationally expensive, especially for large data structures. To deliver fast and effective retrieval especially for large multimedia collections and multimedia big data, an efficient similarity algorithm for large graphs in particular is desirable. Hence, in this paper, we define a graph projection into a 2D space (Graph Code) and the corresponding algorithms for indexing and retrieval. We show that calculations in this space can be performed more efficiently than graph traversals due to the simpler processing model and the high level of parallelization. As a...

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A metagenomic content and knowledge management ecosystem platform

2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2019

The reduced cost of DNA sequencing allows metagenomics to be applied on a larger scale. With meta... more The reduced cost of DNA sequencing allows metagenomics to be applied on a larger scale. With metagenomic analysis, we have better insight into supplement usage, methane production, and feed conversion efficiency in livestock systems. Nevertheless, sequencing machines generate an enormous amount of complex data. Conventional methods used in the analysis of genomic data involve pre-processing and synchronous reconstruction by multiple systems, which is time consuming and prone to failure. Furthermore, the sequencing datasets and analysis results need to be organized and stored properly in order for scientists to search and access them. To tackle these challenges, a new workflow for metagenomic analysis with improved infrastructure is needed. The MetaPlat project supports experts in both academic and non-academic sectors dealing with challenges in the field of metagenomics by focusing on improved hardware and software platforms. High-performance, fault-tolerant, flexible, and scalable ...

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Analyzing Large Microbiome Datasets Using Machine Learning and Big Data

BioMedInformatics

Metagenomics promises to provide new valuable insights into the role of microbiomes in eukaryotic... more Metagenomics promises to provide new valuable insights into the role of microbiomes in eukaryotic hosts such as humans. Due to the decreasing costs for sequencing, public and private repositories for human metagenomic datasets are growing fast. Metagenomic datasets can contain terabytes of raw data, which is a challenge for data processing but also an opportunity for advanced machine learning methods like deep learning that require large datasets. However, in contrast to classical machine learning algorithms, the use of deep learning in metagenomics is still an exception. Regardless of the algorithms used, they are usually not applied to raw data but require several preprocessing steps. Performing this preprocessing and the actual analysis in an automated, reproducible, and scalable way is another challenge. This and other challenges can be addressed by adjusting known big data methods and architectures to the needs of microbiome analysis and DNA sequence processing. A conceptual ar...

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Combining Speech and Vision Processing in a Platform for Intelligent MultiMedia

In this paper we present the &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;Intellimed... more In this paper we present the &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;Intellimedia WorkBench&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; which has been developed at AalborgUniversity. The workbench makes a set of tools available which can be used in differentapplications within the area of intelligent multi media. The goals of the workbench are tofacilitate research on integration of visual and spoken information, and as a platform whereIntelligent-multimedia students can develop projects.1 BackgroundDriven

Artificial Intelligence Review Volume 13 Issue 3

Artificial Intelligence Review Volume 10 Issue 1-2

Michael Manthey, Paul Mc Kevitt, Thomas B. Moeslund

Conference review

Intelligence/sigart Bulletin, 2000

CHAMELEON meets spatial cognition

Advances in Consciousness Research, 2000

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