All Outputs (221)

Selecting genetic operators to maximise preference satisfaction in a workforce scheduling and routing problem (2017)
Conference Proceeding

The Workforce Scheduling and Routing Problem (WSRP) is a combinatorial optimisation problem that involves scheduling and routing of workforce. Tackling this type of problem often requires handling a considerable number of requirements, including cust... Read More about Selecting genetic operators to maximise preference satisfaction in a workforce scheduling and routing problem.

Towards collaborative optimisation in a shared-logistics environment for pickup and delivery operations (2017)
Conference Proceeding

This paper gives an overview of research work in progress within the COSLE (Collaborative Optimisation in a Shared Logistics Environment) project between the University of Nottingham and Microlise Ltd. This is an R&D project that seeks to develop opt... Read More about Towards collaborative optimisation in a shared-logistics environment for pickup and delivery operations.

Combining residual networks with LSTMs for lipreading (2017)
Conference Proceeding

We propose an end-to-end deep learning architecture for word-level visual speech recognition. The system is a combination of spatiotemporal convolutional, residual and bidirectional Long Short-Term Memory networks. We train and evaluate it on the Lip... Read More about Combining residual networks with LSTMs for lipreading.

Industrial R&D expenditure: its determinants and propensity of technology transfer of top ten companies in Malaysia, Singapore and Taiwan (2017)
Journal Article

Global research and development (R&D) spending has increased in recent years as the need for new technologies has grown and structural changes in the market have become evident. R&D and its transfer into the commercial sector have an important relati... Read More about Industrial R&D expenditure: its determinants and propensity of technology transfer of top ten companies in Malaysia, Singapore and Taiwan.

A fast community detection method in bipartite networks by distance dynamics (2017)
Journal Article

Many real bipartite networks are found to be divided into two-mode communities. In this paper, we formulate a new two-mode community detection algorithm BiAttractor. It is based on distance dynamics model Attractor proposed by Shao et al. with extens... Read More about A fast community detection method in bipartite networks by distance dynamics.

Univalent higher categories via complete semi-segal types (2017)
Journal Article

Category theory in homotopy type theory is intricate as categorical laws can only be stated “up to homotopy”, and thus require coherences. The established notion of a univalent category (as introduced by Ahrens et al.)solves this by considering only... Read More about Univalent higher categories via complete semi-segal types.

Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression (2017)
Conference Proceeding

3D face reconstruction is a fundamental Computer Vision problem of extraordinary difficulty. Current systems often assume the availability of multiple facial images (sometimes from the same subject) as input, and must address a number of methodologic... Read More about Large Pose 3D Face Reconstruction from a Single Image via Direct Volumetric CNN Regression.

Binarized Convolutional Landmark Localizers for Human Pose Estimation and Face Alignment with Limited Resources (2017)
Conference Proceeding

Our goal is to design architectures that retain the groundbreaking performance of CNNs for landmark localization and at the same time are lightweight, compact and suitable for applications with limited computational resources. To this end, we make th... Read More about Binarized Convolutional Landmark Localizers for Human Pose Estimation and Face Alignment with Limited Resources.

A Learning Automata-Based Multiobjective Hyper-Heuristic (2017)
Journal Article

© 1997-2012 IEEE. Metaheuristics, being tailored to each particular domain by experts, have been successfully applied to many computationally hard optimization problems. However, once implemented, their application to a new problem domain or a slight... Read More about A Learning Automata-Based Multiobjective Hyper-Heuristic.

Social music machine: crowdsourcing for composition & creativity (2017)
Conference Proceeding

This poster describes a compositional technique that used crowd-sourced midi clips in order to develop a piece of music, which was later performed. This work in progress highlighted some of the issues facing the designers of systems that enable the ‘... Read More about Social music machine: crowdsourcing for composition & creativity.

The art and ‘science’ of opera: composing, staging & designing new forms of interactive theatrical performance (2017)
Conference Proceeding

New technologies, such as Virtual Reality (VR), Robotics and Artificial Intelligence (AI) are steadily having an impact upon the world of opera. The evolving use of performance-based software such as Ableton Live and Max/MSP has created new and excit... Read More about The art and ‘science’ of opera: composing, staging & designing new forms of interactive theatrical performance.

An agent on my shoulder: AI, privacy and the application of human-like computing technologies to music creation (2017)
Conference Proceeding

Human-Like Computing technologies are intelligent systems that interact with people in human-like way. By bringing together the disciplines of Artificial Intelligence, Ethnography and Interaction Design, and applying them in a real world context we... Read More about An agent on my shoulder: AI, privacy and the application of human-like computing technologies to music creation.

Hearing the humanities: sonifying Steele’s Shakespeare (2017)
Conference Proceeding

We present initial work that explores the use of sonification to represent Joshua Steele’s symbolic notation. This provides a manner of overhearing a previous performance and testing the method’s reproducibility and uncertainties within it.

Using simulation to incorporate dynamic criteria into multiple criteria decision making (2017)
Journal Article

In this paper we present a case study demonstrating how dynamic and uncertain criteria can be incorporated into a multi-criteria analysis with the help of discrete event simulation. The simulation guided multi-criteria analysis can include both monet... Read More about Using simulation to incorporate dynamic criteria into multiple criteria decision making.

Analysing the opinions of UK veterinarians on practice-based research using corpus linguistic and mathematical methods (2017)
Journal Article

The use of corpus linguistic techniques and other related mathematical analyses have rarely, if ever, been applied to qualitative data collected from the veterinary field. The aim of this study was to explore the use of a combination of corpus lingui... Read More about Analysing the opinions of UK veterinarians on practice-based research using corpus linguistic and mathematical methods.

Effective parallelisation for machine learning (2017)
Conference Proceeding

We present a novel parallelisation scheme that simplifies the adaptation of learning algorithms to growing amounts of data as well as growing needs for accurate and confident predictions in critical applications. In contrast to other parallelisation... Read More about Effective parallelisation for machine learning.

What is home? An art-based workshop to explore the physical, relational and wellbeing properties of Home (2017)
Journal Article

This feasibility study was framed under the notion of creative practices as mutual recovery – the idea that shared creativity, collective experience and mutual benefit can promote resilience in mental health and well-being. The study evaluated the im... Read More about What is home? An art-based workshop to explore the physical, relational and wellbeing properties of Home.

Abstract modelling: towards a typed declarative language for the conceptual modelling phase (2017)
Conference Proceeding

Modelling languages have become an indispensable aid to practising engineers. They offer modelling at a high level of abstraction backed by features such as automatic simulation and even derivation of production code. However, partly because of the o... Read More about Abstract modelling: towards a typed declarative language for the conceptual modelling phase.

Bread stories: understanding the drivers of bread consumption for digital food customisation (2017)
Conference Proceeding

Consumer demand for food that satisfies specific needs rather than generic mass produced food is growing. In response, the food industry is actively investigating techniques for efficient and comprehensive food customisation. Digital approaches to fo... Read More about Bread stories: understanding the drivers of bread consumption for digital food customisation.

Extended Kalman filter-based learning of interval type-2 intuitionistic fuzzy logic system (2017)
Conference Proceeding

Fuzzy logic systems have been extensively applied for solving many real world application problems because they are found to be universal approximators and many methods, particularly, gradient descent (GD) methods have been widely adopted for the opt... Read More about Extended Kalman filter-based learning of interval type-2 intuitionistic fuzzy logic system.