Jim Smith's Outputs (43)

A multi-language toolkit for the semi-automated checking of research outputs (2025)
Journal Article

This article presents a free and open source toolkit that supports the semi-automated checking of research outputs (SACRO) for privacy disclosure within secure data environments. SACRO is a framework that applies best-practice principles-based statis... Read More about A multi-language toolkit for the semi-automated checking of research outputs.

Hybrid graph convolutional LSTM model for spatio-temporal air quality transfer learning (2025)
Journal Article

The short-term air quality forecasting models serve as an early warning system for local agencies, aiding in preparing mitigation strategies against severe pollution episodes. This paper explores the application of Transfer Learning to enhance short-... Read More about Hybrid graph convolutional LSTM model for spatio-temporal air quality transfer learning.

The inadvertently revealing statistic: A systemic gap in statistical training? (2024)
Journal Article

While concerns around data privacy are well-known, there's a lack of awareness and training when it comes to the confidentiality risk of published statistics, argue Ben Derrick, Elizabeth Green, Felix Ritchie, Jim Smith, Paul White

Machine learning models in trusted research environments - Understanding operational risks (2023)
Journal Article

IntroductionTrusted research environments (TREs) provide secure access to very sensitive data for research. All TREs operate manual checks on outputs to ensure there is no residual disclosure risk. Machine learning (ML) models require very large amou... Read More about Machine learning models in trusted research environments - Understanding operational risks.

Disclosure control of machine learning models from trusted research environments (TRE): New challenges and opportunities (2023)
Journal Article

Introduction: Artificial intelligence (AI) applications in healthcare and medicine have increased in recent years. To enable access to personal data, Trusted Research Environments (TREs) (otherwise known as Safe Havens) provide safe and secure enviro... Read More about Disclosure control of machine learning models from trusted research environments (TRE): New challenges and opportunities.

A novel mirror neuron inspired decision-making architecture for human–robot interaction (2023)
Journal Article

Inspired by the role of mirror neurons and the importance of predictions in joint action, a novel decision-making structure is proposed, designed and tested for both individual and dyadic action. The structure comprises models representing individual... Read More about A novel mirror neuron inspired decision-making architecture for human–robot interaction.

Inter-annotator agreement using the Conversation Analysis Modelling Schema, for dialogue (2022)
Journal Article

We present the Conversation Analysis Modeling Schema (CAMS), a novel dialogue labeling schema that combines the Conversation Analysis concept of Adjacency Pairs, with Dialogue Acts. The aim is to capture both the semantic and syntactic structure of d... Read More about Inter-annotator agreement using the Conversation Analysis Modelling Schema, for dialogue.

Sentence encoding for dialogue act classification (2021)
Journal Article

In this study, we investigate the process of generating single-sentence representations for the purpose of Dialogue Act (DA) classification, including several aspects of text pre-processing and input representation which are often overlooked or under... Read More about Sentence encoding for dialogue act classification.

Automatic Checking of Research Outputs (ACRO): A tool for dynamic disclosure checks (2021)
Journal Article

This paper discusses the issues surrounding the creation of an automatic tool to reduce the burden of output checking in research environments. It describes ACRO (Automatic Checking of Research Outputs), a Stata tool written as a proof-of-concept, an... Read More about Automatic Checking of Research Outputs (ACRO): A tool for dynamic disclosure checks.

Protein structured reservoir computing for spike-based pattern recognition (2021)
Journal Article

Nowadays we witness a miniaturisation trend in the semiconductor industry backed up by groundbreaking discoveries and designs in nanoscale characterisation and fabrication. To facilitate the trend and produce ever smaller, faster and cheaper computin... Read More about Protein structured reservoir computing for spike-based pattern recognition.

Visual analytics for collaborative human-machine confidence in human-centric active learning tasks (2019)
Journal Article

Active machine learning is a human-centric paradigm that leverages a small labelled dataset to build an initial weak classifier, that can then be improved over time through human-machine collaboration. As new unlabelled samples are observed, the mach... Read More about Visual analytics for collaborative human-machine confidence in human-centric active learning tasks.

Evolutionary n-level hypergraph partitioning with adaptive coarsening (2019)
Journal Article

Hypergraph partitioning is an NP-hard problem that occurs in many computer science applications where it is necessary to reduce large problems into a number of smaller, computationally tractable sub-problems. Current techniques use a multilevel appro... Read More about Evolutionary n-level hypergraph partitioning with adaptive coarsening.

Predicting user confidence during visual decision making (2018)
Journal Article

© 2018 ACM People are not infallible consistent “oracles”: their confidence in decision-making may vary significantly between tasks and over time. We have previously reported the benefits of using an interface and algorithms that explicitly captured... Read More about Predicting user confidence during visual decision making.

From evolutionary computation to the evolution of things (2015)
Journal Article

© 2015 Macmillan Publishers Limited. All rights reserved . Evolution has provided a source of inspiration for algorithm designers since the birth of computers. The resulting field, evolutionary computation, has been successful in solving engineering... Read More about From evolutionary computation to the evolution of things.

Interactive ant colony optimization (iACO) for early lifecycle software design (2014)
Journal Article

Finding good designs in the early stages of the software development lifecycle is a demanding multi-objective problem that is crucial to success. Previously, both interactive and non-interactive techniques based on evolutionary algorithms (EAs) have... Read More about Interactive ant colony optimization (iACO) for early lifecycle software design.

A genetic algorithm for the one-dimensional cutting stock problem with setups (2014)
Journal Article

This paper investigates the one-dimensional cutting stock problem considering two conflicting objective functions: minimization of both the number of objects and the number of different cutting patterns used. A new heuristic method based on the conce... Read More about A genetic algorithm for the one-dimensional cutting stock problem with setups.

A comparison of meta-heuristic search for interactive software design (2013)
Journal Article

Advances in processing capacity, coupled with the desire to tackle problems where a human subjective judgment plays an important role in determining the value of a proposed solution, has led to a dramatic rise in the number of applications of Interac... Read More about A comparison of meta-heuristic search for interactive software design.

A preprocessing optimization applied to the cell suppression problem in statistical disclosure control (2013)
Journal Article

As organizations start to publish the data that they collect, either internally or externally, in the form of statistical tables they need to consider the protection of the confidential information held in those tables. The algorithms used to protect... Read More about A preprocessing optimization applied to the cell suppression problem in statistical disclosure control.

Estimating meme fitness in adaptive memetic algorithms for combinatorial problems (2012)
Journal Article

Among the most promising and active research areas in heuristic optimisation is the field of adaptive memetic algorithms (AMAs). These gain much of their reported robustness by adapting the probability with which each of a set of local improvement op... Read More about Estimating meme fitness in adaptive memetic algorithms for combinatorial problems.

A genetic approach to statistical disclosure control (2012)
Journal Article

Statistical disclosure control is the collective name for a range of tools used by data providers such as government departments to protect the confidentiality of individuals or organizations. When the published tables contain magnitude data such as... Read More about A genetic approach to statistical disclosure control.