Case studies in X ray computed tomography surface texture measurement
(2019)
Conference Proceeding
All Outputs (303)
Parametric Virtual Design-based Multi-Objective Optimization for Sustainable Building Design (2019)
Conference Proceeding
With the development of Building Information Modelling aiming for automatic, the automating of sustainability analysis will be a certain requirement in the future. Unlike the current research stream, this paper investigates a novel approach of direct... Read More about Parametric Virtual Design-based Multi-Objective Optimization for Sustainable Building Design.
Adult Education 100: reflections & reconstructions: conference proceedings 2019 (2019)
Conference Proceeding
Papers presented at the 49th Annual Conference of the Standing Conference on University Teaching and Research in the Education of Adults, held at the University of Nottingham, 2-4 July 2019
Towards a streamlined stacking sequence optimisation methodology for blended composite aircraft structures (2019)
Conference Proceeding
In order to fully exploit the benefits provided by using composite materials in large scale aerospace structures, more efficient detailed design optimisation techniques need to be developed. In the present work, the optimisation procedure is split up... Read More about Towards a streamlined stacking sequence optimisation methodology for blended composite aircraft structures.
A Hybrid Evolutionary Strategy to Optimise Early-Stage Cancer Screening (2019)
Conference Proceeding
Current methods to identify cutoff values for tumour-associated molecules (antigens) discrimination are based on statistics and brute force. These methods applied to cancer screening problems are very inefficient, especially with large data sets with... Read More about A Hybrid Evolutionary Strategy to Optimise Early-Stage Cancer Screening.
On Comparing and Selecting Approaches to Model Interval-Valued Data as Fuzzy Sets (2019)
Conference Proceeding
The capture of interval-valued data is becoming an increasingly common approach in data collection (from survey based research to the collation of sensor data) as an efficient method of obtaining information about uncertainty associated with the data... Read More about On Comparing and Selecting Approaches to Model Interval-Valued Data as Fuzzy Sets.
Microarray Feature Selection and Dynamic Selection of Classifiers for Early Detection of Insect Bite Hypersensitivity in Horses (2019)
Conference Proceeding
Microarrays can be employed to better characterise allergies, as interactions between antibodies and allergens in mammals can be monitored. Once the joint dynamics of these elements in both healthy and diseased animals are understood, a model to pred... Read More about Microarray Feature Selection and Dynamic Selection of Classifiers for Early Detection of Insect Bite Hypersensitivity in Horses.
Wavelet-based ESS sizing strategy to enable power peak-shaving in PV systems (2019)
Conference Proceeding
This work presents an Energy Storage Systems (ESS) sizing strategy, that allows grid connected PV systems to provide peak-shaved maximum-power-Ramp-Rate (RR) compliant power while storing exceeding power. For this purpose power generation and power l... Read More about Wavelet-based ESS sizing strategy to enable power peak-shaving in PV systems.
Evolving Deep CNN-LSTMs for Inventory Time Series Prediction (2019)
Conference Proceeding
Inventory forecasting is a key component of effective inventory management. In this work, we utilise hybrid deep learning models for inventory forecasting. According to the highly nonlinear and non-stationary characteristics of inventory data, the mo... Read More about Evolving Deep CNN-LSTMs for Inventory Time Series Prediction.
DECSYS - Discrete and Ellipse-based response Capture SYStem (2019)
Conference Proceeding
Data-driven techniques that capture uncertainty through intervals or fuzzy sets can substantially improve systematic reasoning about uncertain information. Recent years have seen renewed interest in the capture of intervals from a variety of sources-... Read More about DECSYS - Discrete and Ellipse-based response Capture SYStem.
Path Spaces of Higher Inductive Types in Homotopy Type Theory (2019)
Conference Proceeding
The study of equality types is central to homotopy type theory. Characterizing these types is often tricky, and various strategies, such as the encode-decode method, have been developed. We prove a theorem about equality types of coequalizers and pus... Read More about Path Spaces of Higher Inductive Types in Homotopy Type Theory.
Fuzzy Integral Driven Ensemble Classification using A Priori Fuzzy Measures (2019)
Conference Proceeding
Aggregation operators are mathematical functions that enable the fusion of information from multiple sources. Fuzzy Integrals (FIs) are widely used aggregation operators, which combine information in respect to a Fuzzy Measure (FM) which captures the... Read More about Fuzzy Integral Driven Ensemble Classification using A Priori Fuzzy Measures.
New Reduced Asymmetric Basic Module Multilevel Converters for Cascaded Configurations (2019)
Conference Proceeding
Requiring a high number of power switches and their rating are the main limitations of multilevel converters in medium-voltage applications. The main objective of this paper is, introduce a reduced asymmetric basic module (RABM) for cascaded multilev... Read More about New Reduced Asymmetric Basic Module Multilevel Converters for Cascaded Configurations.
Fuzzy Hot Spot Identification for Big Data: An Initial Approach (2019)
Conference Proceeding
Hot spot identification problems are present across a wide range of areas, such as transportation, health care and energy. Hot spots are locations where a certain type of event occurs with high frequency. A recent big data approach is capable of iden... Read More about Fuzzy Hot Spot Identification for Big Data: An Initial Approach.
A Preliminary Approach for the Exploitation of Citizen Science Data for Fast and Robust Fuzzy k-Nearest Neighbour Classification (2019)
Conference Proceeding
Citizen science is becoming mainstream in a wide variety of real-world applications in astronomy or bioinformatics, in which, for example, classification tasks by experts are very time consuming. These projects engage amateur volunteers that are task... Read More about A Preliminary Approach for the Exploitation of Citizen Science Data for Fast and Robust Fuzzy k-Nearest Neighbour Classification.
A Novel Weighted Combination Method for Feature Selection using Fuzzy Sets (2019)
Conference Proceeding
In this paper, we propose a novel weighted combination feature selection method using bootstrap and fuzzy sets. The proposed method mainly consists of three processes, including fuzzy sets generation using bootstrap, weighted combination of fuzzy set... Read More about A Novel Weighted Combination Method for Feature Selection using Fuzzy Sets.
Leveraging IT2 Input Fuzzy Sets in Non-Singleton Fuzzy Logic Systems to Dynamically Adapt to Varying Uncertainty Levels (2019)
Conference Proceeding
Most real-world environments are subject to different sources of uncertainty which may vary in magnitude over time. We propose that while Type-1 (T1) Non-Singleton Fuzzy Logic System (NSFLSs) have the potential to tackle uncertainty within the input... Read More about Leveraging IT2 Input Fuzzy Sets in Non-Singleton Fuzzy Logic Systems to Dynamically Adapt to Varying Uncertainty Levels.
On the Concept of Meaningfulness in Constrained Type-2 Fuzzy Sets (2019)
Conference Proceeding
Constrained type-2 fuzzy sets have been proposed as a tool to model type-2 fuzzy sets starting from a type-1 generator set with uncertainty. This constrained representation only defines as acceptable the embedded sets that have the same shape as the... Read More about On the Concept of Meaningfulness in Constrained Type-2 Fuzzy Sets.
Uncertainty quantification in ultrasonic guided-waves based damage localization (2019)
Conference Proceeding
Bayesian methods for inverse problems offer higher robustness to noise and uncertainty than deterministic, yet accurate, inference methods. Both types of techniques typically focus on finding optimal model parameters that minimize an objective functi... Read More about Uncertainty quantification in ultrasonic guided-waves based damage localization.
Assessment of an Enhanced Thin Film Model to Capture Wetting and Drying Behavior in an Aero-Engine Bearing Chamber (2019)
Conference Proceeding
In the present work, a wetting and drying model is coupled with Eulerian Thin-Film model (ETFM) to analyze the wetting and drying behavior inside the bearing chamber. In the enhanced model, an additional source term is included to account for the con... Read More about Assessment of an Enhanced Thin Film Model to Capture Wetting and Drying Behavior in an Aero-Engine Bearing Chamber.