A compendium of modelling techniques

This Integration Insight provides a brief overview of the most popular modelling techniques used to analyse complex real-world problems, as well as some less popular but highly relevant techniques. The modelling methods are divided into three categories, with each encompassing a number of methods, as follows: 1) Qualitative Aggregate Models (Soft Systems Methodology, Concept Maps and Mind Mapping, Scenario Planning, Causal (Loop) Diagrams), 2) Quantitative Aggregate Models (Function fitting and Regression, Bayesian Nets, System of differential equations / Dynamical systems, System Dynamics, Evolutionary Algorithms) and 3) Individual Oriented Models (Cellular Automata, Microsimulation, Agent Based Models, Discrete Event Simulation, Social Network
Analysis). Each technique is broadly described with example uses, key attributes and reference material.

Directional Modulation Enhanced Retrodirective Array

Unlike the mathematical techniques adopted in classical cryptographic technology at higher protocol layers, it is shown that characteristics intrinsic to the physical layer can be exploited to secure useful information. It is shown that a retrodirective array can be made to operate more securely by incorporating directional modulation (DM) concepts. The presented new approach allows DM to operate in a multipath environment. Previously, DM systems could only operate in free space.

Methodology for Validating Artifact Removal Techniques for Physiological Signals

Artifact removal from physiological signals is an essential component of the biosignal processing pipeline. The need for powerful and robust methods for this process has become particularly acute as healthcare technology deployment undergoes transition from the current hospital-centric setting toward a wearable and ubiquitous monitoring environment. Currently, determining the relative efficacy and performance of the multiple artifact removal techniques available on real world data can be problematic, due to incomplete information on the uncorrupted desired signal. The majority of techniques are presently evaluated using simulated data, and therefore, the quality of the conclusions is contingent on the fidelity of the model used. Consequently, in the biomedical signal processing community, there is considerable focus on the generation and validation of appropriate signal models for use in artifact suppression. Most approaches rely on mathematical models which capture suitable approximations to the signal dynamics or underlying physiology and, therefore, introduce some uncertainty to subsequent predictions of algorithm performance. This paper describes a more empirical approach to the modeling of the desired signal that we demonstrate for functional brain monitoring tasks which allows for the procurement of a ground truth signal which is highly correlated to a true desired signal that has been contaminated with artifacts. The availability of this ground truth, together with the corrupted signal, can then aid in determining the efficacy of selected artifact removal techniques. A number of commonly implemented artifact removal techniques were evaluated using the described methodology to validate the proposed novel test platform. © 2012 IEEE.

Addressing the technical and market challenges to high wind power integration in Ireland

Over the last decade there has been a rapid global increase in wind power stimulated by energy and climate policies. However, as wind power is inherently variable and stochastic over a range of time scales, additional system balancing is required to ensure system reliability and stability. This paper reviews the technical, policy and market challenges to achieving ambitious wind power penetration targets in Ireland’s All-Island Grid and examines a number of measures proposed to address these challenges. Current government policy in Ireland is to address these challenges with additional grid reinforcement, interconnection and open-cycle gas plant. More recently smart grid combined with demand side management and electric vehicles have also been presented as options to mitigate the variability of wind power. In addition, the transmission system operators have developed wind farm specific grid codes requiring improved turbine controls and wind power forecasting techniques.

Early Implementation of Building Information Modeling into a Cold-Formed Steel Company: Providing Novel Project Management Techniques and Solutions to Industry

The ability of building information modeling (BIM) to positively impact projects in the AEC through greater collaboration and integration is widely acknowledged. This paper aims to examine the development of BIM and how it can contribute to the cold-formed steel (CFS) building industry. This is achieved through the adoption of a qualitative methodology encompassing a literature review, exploratory interviews with industry experts, culminating in the development of e-learning material for the sector. In doing so, the research team have collaborated with one of the United Kingdom’s largest cold-formed steel designer/fabricators. By demonstrating the capabilities of BIM software and providing technical and informative videos in its creation, this project has found two key outcomes. Firstly, to provide invaluable assistance in the transition from traditional processes to a fully collaborative 3D BIM as required by the UK Government under the “Government Construction Strategy” by 2016 in all public sector projects. Secondly, to demonstrate BIM’s potential not only within CFS companies, but also within the AEC sector as a whole. As the flexibility, adaptability and interoperability of BIM software is alluded to, the results indicate that the introduction and development of BIM and the underlying ethos suggests that it is a key tool in the development of the industry as a whole.

The feasibility of using near infrared and Raman spectroscopic techniques to detect fraudulent adulteration of chili powders with Sudan dye

Chili powder is a globally traded commodity which has been found to be adulterated with Sudan dyes from 2003 onwards. In this study, chili powders were adulterated with varying quantities of Sudan I dye (0.1-5%) and spectra were generated using near infrared reflectance spectroscopy (NIRS) and Raman
spectroscopy (on a spectrometer with a sample compartment modified as part of the study). Chemometrics were applied to the spectral data to produce quantitative and qualitative calibration models and prediction statistics. For the quantitative models coefficients of determination (R2) were found to be
0.891-0.994 depending on which spectral data (NIRS/Raman) was processed, the mathematical algorithm used and the data pre-processing applied. The corresponding values for the root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) were found to be 0.208-0.851%
and 0.141-0.831% respectively, once again depending on the spectral data and the chemometric treatment applied to the data. Indications are that the NIR spectroscopy based models are superior to the models produced from Raman spectral data based on a comparison of the values of the chemometric
parameters. The limit of detection (LOD) based on analysis of 20 blank chili powders against each calibration model gave 0.25% and 0.88% for the NIR and Raman data, respectively. In addition, adopting a qualitative approach with the spectral data and applying PCA or PLS-DA, it was possible to discriminate
between adulterated chili powders from non-adulterated chili powders.

Volumetric Carbon Content Calculations: A Geostatistical and Compositional Approach

This study applies spatial statistical techniques including cokriging to integrate airborne geophysical (radiometric) data with ground-based measurements of peat depth and soil organic carbon (SOC) to monitor change in peat cover for carbon stock calculations. The research is part of the EU funded Tellus Border project and is supported by the INTERREG IVA development programme of the European Regional Development Fund, which is managed by the Special EU Programmes Body (SEUPB). The premise is that saturated peat attenuates the radiometric signal from underlying soils and rocks. Contemporaneous ground-based measurements were collected to corroborate mapped estimates and develop a statistical model for volumetric carbon content (VCC) to 0.5 metres. Field measurements included ground penetrating radar, gamma ray spectrometry and a soil sampling methodology which measured bulk density and soil moisture to determine VCC. One aim of the study was to explore whether airborne radiometric survey data can be used to establish VCC across a region. To account for the footprint of airborne radiometric data, five cores were obtained at each soil sampling location: one at the centre of the ground radiometric equivalent sample location and one at each of the four corners 20 metres apart. This soil sampling strategy replicated the methodology deployed for the Tellus Border geochemistry survey. Two key issues will be discussed from this work. The first addresses the integration of different sampling supports for airborne and ground measured data and the second discusses the compositional nature of the VOC data.