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Articles 1 - 11 of 11
Full-Text Articles in Engineering
A Multi-Task Approach To Incremental Dialogue State Tracking, Anh Duong Trinh, Robert J. Ross, John D. Kelleher
A Multi-Task Approach To Incremental Dialogue State Tracking, Anh Duong Trinh, Robert J. Ross, John D. Kelleher
Conference papers
Incrementality is a fundamental feature of language in real world use. To this point, however, the vast majority of work in automated dialogue processing has focused on language as turn based. In this paper we explore the challenge of incremental dialogue state tracking through the development and analysis of a multi-task approach to incremental dialogue state tracking. We present the design of our incremental dialogue state tracker in detail and provide evaluation against the well known Dialogue State Tracking Challenge 2 (DSTC2) dataset. In addition to a standard evaluation of the tracker, we also provide an analysis of the Incrementality …
Interoperable Ocean Observing Using Archetypes: A Use-Case Based Evaluation, Paul Stacey, Damon Berry
Interoperable Ocean Observing Using Archetypes: A Use-Case Based Evaluation, Paul Stacey, Damon Berry
Conference papers
This paper presents a use-case based evaluation of the impact of two-level modeling on the automatic federation of ocean observational data. The goal of the work is to increase the interoperability and data quality of aggregated ocean observations to support convenient discovery and consumption by applications. An assessment of the interoperability of served data flows from publicly available ocean observing spatial data infrastructures was performed. Barriers to consumption of existing standards-compliant ocean-observing data streams were examined, including the impact of adherence to agreed data standards. Historical data flows were mapped to a set of archetypes and a backward integration experiment …
Using Regular Languages To Explore The Representational Capacity Of Recurrent Neural Architectures, Abhijit Mahalunkar, John D. Kelleher
Using Regular Languages To Explore The Representational Capacity Of Recurrent Neural Architectures, Abhijit Mahalunkar, John D. Kelleher
Conference papers
The presence of Long Distance Dependencies (LDDs) in sequential data poses significant challenges for computational models. Various recurrent neural architectures have been designed to mitigate this issue. In order to test these state-of-the-art architectures, there is growing need for rich benchmarking datasets. However, one of the drawbacks of existing datasets is the lack of experimental control with regards to the presence and/or degree of LDDs. This lack of control limits the analysis of model performance in relation to the specific challenge posed by LDDs. One way to address this is to use synthetic data having the properties of subregular languages. …
Streaming Vr For Immersion: Quality Aspects Of Compressed Spatial Audio, Miroslaw Narbutt, Sean O’Leary, Andrew Allen, Jan Skoglund, Andrew Hines
Streaming Vr For Immersion: Quality Aspects Of Compressed Spatial Audio, Miroslaw Narbutt, Sean O’Leary, Andrew Allen, Jan Skoglund, Andrew Hines
Conference papers
Delivering a 360-degree soundscape that matches full sphere visuals is an essential aspect of immersive VR. Ambisonics is a full sphere surround sound technique that takes into account the azimuth and elevation of sound sources, portraying source location above and below as well as around the horizontal plane of the listener. In contrast to channel-based methods, ambisonics representation offers the advantage of being independent of a specific loudspeaker set-up. Streaming ambisonics over networks requires efficient encoding techniques that compress the raw audio content without compromising quality of experience (QoE). This work investigates the effect of audio channel compression via the …
Investigating The Impact Of Unsupervised Feature-Extraction From Multi-Wavelength Image Data For Photometric Classification Of Stars, Galaxies And Qsos, Annika Lindh
Conference papers
Accurate classification of astronomical objects currently relies on spectroscopic data. Acquiring this data is time-consuming and expensive compared to photometric data. Hence, improving the accuracy of photometric classification could lead to far better coverage and faster classification pipelines. This paper investigates the benefit of using unsupervised feature-extraction from multi-wavelength image data for photometric classification of stars, galaxies and QSOs. An unsupervised Deep Belief Network is used, giving the model a higher level of interpretability thanks to its generative nature and layer-wise training. A Random Forest classifier is used to measure the contribution of the novel features compared to a set …
On The Applications Of Deterministic Chaos For Encrypting Data On The Cloud, Jonathan Blackledge, Nikolai Ptitsyn
On The Applications Of Deterministic Chaos For Encrypting Data On The Cloud, Jonathan Blackledge, Nikolai Ptitsyn
Conference papers
Cloud computing is expected to grow considerably in the future because it has so many advantages with regard to sale and cost, change management, next generation architectures, choice and agility. However, one of the principal concerns for users of the Cloud is lack of control and above all, data security. This paper considers an approach to encrypting information before it is ‘placed’ on the Cloud where each user has access to their own encryption algorithm, an algorithm that is based on a set of iterated function systems that outputs a chaotic number stream, designed to produce a cryptographically secure cipher. …
Information Hiding Using Stochastic Diffusion For The Covert Transmission Of Encrypted Images, Jonathan Blackledge
Information Hiding Using Stochastic Diffusion For The Covert Transmission Of Encrypted Images, Jonathan Blackledge
Conference papers
A principal weakness of all encryption systems is that the output data can be `seen' to be encrypted. In other words, encrypted data provides a 'flag' on the potential value of the information that has been encrypted. In this paper, we provide a novel approach to `hiding' encrypted data in a digital image. We consider an approach in which a plaintext image is encrypted with a cipher using the processes of `stochastic diffusion' and the output quantized into a 1-bit array generating a binary image cipher-text. This output is then `embedded' in a host image which is undertaken either in …
Authentication Of Biometric Features Using Texture Coding For Id Cards, Jonathan Blackledge, Eugene Coyle
Authentication Of Biometric Features Using Texture Coding For Id Cards, Jonathan Blackledge, Eugene Coyle
Conference papers
The use of image based information exchange has grown rapidly over the years in terms of both e-to-e image storage and transmission and in terms of maintaining paper documents in electronic form. Further, with the dramatic improvements in the quality of COTS (Commercial-Off-The-Shelf) printing and scanning devices, the ability to counterfeit electronic and printed documents has become a widespread problem. Consequently, there has been an increasing demand to develop digital watermarking techniques which can be applied to both electronic and printed images (and documents) that can be authenticated, prevent unauthorized copying of their content and, in the case of printed …
On The Applications Of Deterministic Chaos For Encrypting Data On The Cloud, Jonathan Blackledge, Nikolai Ptitsyn
On The Applications Of Deterministic Chaos For Encrypting Data On The Cloud, Jonathan Blackledge, Nikolai Ptitsyn
Conference papers
Cloud computing is expected to grow considerably in the future because it has so many advantages with regard to sale and cost, change management, next generation architectures, choice and agility. However, one of the principal concerns for users of the Cloud is lack of control and above all, data security. This paper considers an approach to encrypting information before it is ‘place’ on the Cloud where each user has access to their own encryption algorithm, an algorithm that is based on a set of Iterative Function Systems that outputs a chaotic number stream, designed to produce a cryptographically secure cipher. …
Self-Authentication Of Audio Signals By Chirp Coding, Jonathan Blackledge, Eugene Coyle
Self-Authentication Of Audio Signals By Chirp Coding, Jonathan Blackledge, Eugene Coyle
Conference papers
This paper discusses a new approach to ‘watermarking’ digital signals using linear frequency modulated or ‘chirp’ coding. The principles underlying this approach are based on the use of a matched filter to provide a reconstruction of a chirped code that is uniquely robust in the case of signals with very low signal-to-noise ratios. Chirp coding for authenticating data is generic in the sense that it can be used for a range of data types and applications (the authentication of speech and audio signals, for example). The theoretical and computational aspects of the matched filter and the properties of a chirp …
Crafting A Research Paper, Ronan Fitzpatrick, Kevin O'Donnell
Crafting A Research Paper, Ronan Fitzpatrick, Kevin O'Donnell
Conference papers
Writing research papers presents numerous different challenges, which vary from how to layout the various pages and format the text to what to include in the different sections that make up the paper. In order to clarify these issues this paper sets out guidelines and best practice approaches and demonstrates their use in the style of this paper.