An empirical study of inter-concept similarities in multimedia ontologies

Generic concept detection has been a widely studied topic in recent research on multimedia analysis and retrieval, but the issue of how to exploit the structure of a multimedia ontology as well as different inter-concept relations, has not received similar attention. In this paper, we present results from our empirical analysis of different types of similarity among semantic concepts in two multimedia ontologies, LSCOM-Lite and CDVP-206. The results show promise that the proposed methods may be helpful in providing insight into the existing inter-concept relations within an ontology and selecting the most facilitating set of concepts and hierarchical relations. Such an analysis as this can be utilized in various tasks such as building more reliable concept detectors and designing large-scale ontologies

Technology Forecasting Using Data Mining and Semantics: First Annual Report

The planning and management of research and development is a challenging process which is compounded by the large amounts of information which is available. The goal of this project is to mine science and technology databases for patterns and trends which facilitate the formation of research strategies. Examples of the types of information sources which we exploit are diverse and include academic journals, patents, blogs and news stories. The intended outputs of the project include growth forecasts for various technological sectors (with an emphasis on sustainable energy), an improved understanding of the underlying research landscape, as well as the identification of influential researchers or research groups. This paper focuses on the development of techniques to both organize and visualize the data in a way which reflects the semantic relationships between keywords. We studied the use of the joint term frequencies of pairs of keywords, as a means of characterizing this semantic relationship – this is based on the intuition that terms which frequently appear together are more likely to be closely related. Some of the results reported herein describe: (1) Using appropriate tools and methods, exploitable patterns and information can certainly be extracted from publicly available databases, (2) Adaptation of the Normalized Google Distance (NGD) formalism can provide measures of keyword distances that facilitate keyword clustering and hierarchical visualization, (3) Further adaptation of the NGD formalism can be used to provide an asymmetric measure of keyword distances to allow the automatic creation of a keyword taxonomy, and (4) Adaptation of the Latent Semantic Approach (LSA) can be used to identify concepts underlying collections of keywords

A Unified Approach for Taxonomy-based Technology Forecasting

For decision makers and researchers working in a technical domain, understanding the state of their area of interest is of the highest importance. For this reason, we consider in this chapter, a novel framework for Web-based technology forecasting using bibliometrics (i.e. the analysis of information from trends and patterns of scientific publications). The proposed framework consists of a few conceptual stages based on a data acquisition process from bibliographic online repositories: extraction of domainrelevant keywords, the generation of taxonomy of the research field of interests and the development of early growth indicators which helps to find interesting technologies in their first phase of development. To provide a concrete application domain for developing and testing our tools, we conducted a case study in the field of renewable energy and in particular one of its subfields: Waste-to-Energy (W2E). The results on this particular research domain confirm the benefit of our approach

A Framework for Technology Forecasting and Visualization

This paper presents a novel framework for supporting the development of well-informed research policies and plans. The proposed methodology is based on the use of bibliometrics; i.e., analysis is conducted using information regarding trends and patterns of publication. Information thus obtained is analyzed to predict probable future developments in the technological fields being studied. While using bibliometric techniques to study science and technology is not a new idea, the proposed approach extends previous studies in a number of important ways. Firstly, instead of being purely exploratory, the focus of our research has been on developing techniques for detecting technologies that are in the early growth phase, characterized by a rapid increase in the number of relevant publications. Secondly, to increase the reliability of the forecasting effort, we propose the use of automatically generated keyword taxonomies, allowing the growth potentials of subordinate technologies to aggregated into the overall potential of larger technology categories. As a demonstration, a proof-of-concept implementation of each component of the framework is presented, and is used to study the domain of renewable energy technologies. Results from this analysis are presented and discussed

Exploring Terms and Taxonomies Relating to the Cyber International Relations Research Field: or are "Cyberspace" and "Cyber Space" the same?

This project has at least two facets to it: (1) advancing the algorithms in the sub-field of bibliometrics often referred to as "text mining" whereby hundreds of thousands of documents (such as journal articles) are scanned and relationships amongst words and phrases are established and (2) applying these tools in support of the Explorations in Cyber International Relations (ECIR) research effort. In international relations, it is important that all the parties understand each other. Although dictionaries, glossaries, and other sources tell you what words/phrases are supposed to mean (somewhat complicated by the fact that they often contradict each other), they do not tell you how people are actually using them. As an example, when we started, we assumed that "cyberspace" and "cyber space" were essentially the same word with just a minor variation in punctuation (i.e., the space, or lack thereof, between "cyber" and "space") and that the choice of the punctuation was a rather random occurrence. With that assumption in mind, we would expect that the taxonomies that would be constructed by our algorithms using "cyberspace" and "cyber space" as seed terms would be basically the same. As it turned out, they were quite different, both in overall shape and groupings within the taxonomy. Since the overall field of cyber international relations is so new, understanding the field and how people think about (as evidenced by their actual usage of terminology, and how usage changes over time) is an important goal as part of the overall ECIR project

Towards Identifying and closing Gaps in Assurance of autonomous Road vehicleS - a collection of Technical Notes Part 2

This report provides an introduction and overview of the Technical Topic Notes (TTNs) produced in the Towards Identifying and closing Gaps in Assurance of autonomous Road vehicleS (Tigars) project. These notes aim to support the development and evaluation of autonomous vehicles. Part 1 addresses: Assurance-overview and issues, Resilience and Safety Requirements, Open Systems Perspective and Formal Verification and Static Analysis of ML Systems. This report is Part 2 and discusses: Simulation and Dynamic Testing, Defence in Depth and Diversity, Security-Informed Safety Analysis, Standards and Guidelines

Analysis of detector performance in a gigahertz clock rate quantum key distribution system

We present a detailed analysis of a gigahertz clock rate environmentally robust phase-encoded quantum key distribution (QKD) system utilizing several different single-photon detectors, including the first implementation of an experimental resonant cavity thin-junction silicon single-photon avalanche diode. The system operates at a wavelength of 850 nm using standard telecommunications optical fibre. A general-purpose theoretical model for the performance of QKD systems is presented with reference to these experimental results before predictions are made about realistic detector developments in this system. We discuss, with reference to the theoretical model, how detector operating parameters can be further optimized to maximize key exchange rates