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.

Evaluation of a substructured soft Real-time Hybrid Test for performing Seismic analysis of complex structural systems

The hybrid test method is a relatively recently developed dynamic testing technique that uses numerical modelling combined with simultaneous physical testing. The concept of substructuring allows the critical or highly nonlinear part of the structure that is difficult to numerically model with accuracy to be physically tested whilst the remainder of the structure, that has a more predictable response, is numerically modelled. In this paper, a substructured soft-real time hybrid test is evaluated as an accurate means of performing seismic tests of complex structures. The structure analysed is a three-storey, two-by-one bay concentrically braced frame (CBF) steel structure subjected to seismic excitation. A ground storey braced frame substructure whose response is critical to the overall response of the structure is tested, whilst the remainder of the structure is numerically modelled. OpenSees is used for numerical modelling and OpenFresco is used for the communication between the test equipment and numerical model. A novel approach using OpenFresco to define the complex numerical substructure of an X-braced frame within a hybrid test is also presented. The results of the hybrid tests are compared to purely numerical models using OpenSees and a simulated test using a combination of OpenSees and OpenFresco. The comparative results indicate that the test method provides an accurate and cost effective procedure for performing
full scale seismic tests of complex structural systems.

Learning soft computing control strategies in a modular neural network architecture

Modelling and control of nonlinear dynamical systems is a challenging problem since the dynamics of such systems change over their parameter space. Conventional methodologies for designing nonlinear control laws, such as gain scheduling, are effective because the designer partitions the overall complex control into a number of simpler sub-tasks. This paper describes a new genetic algorithm based method for the design of a modular neural network (MNN) control architecture that learns such partitions of an overall complex control task. Here a chromosome represents both the structure and parameters of an individual neural network in the MNN controller and a hierarchical fuzzy approach is used to select the chromosomes required to accomplish a given control task. This new strategy is applied to the end-point tracking of a single-link flexible manipulator modelled from experimental data. Results show that the MNN controller is simple to design and produces superior performance compared to a single neural network (SNN) controller which is theoretically capable of achieving the desired trajectory. (C) 2003 Elsevier Ltd. All rights reserved.

Three-dimensional pattern formation, multiple homogeneous soft modes, and nonlinear dielectric electroconvection

Patterns forming spontaneously in extended, three-dimensional, dissipative systems are likely to excite several homogeneous soft modes (approximate to hydrodynamic modes) of the underlying physical system, much more than quasi-one- (1D) and two-dimensional (2D) patterns are. The reason is the lack of damping boundaries. This paper compares two analytic techniques to derive the pattern dynamics from hydrodynamics, which are usually equivalent but lead to different results when applied to multiple homogeneous soft modes. Dielectric electroconvection in nematic liquid crystals is introduced as a model for 3D pattern formation. The 3D pattern dynamics including soft modes are derived. For slabs of large but finite thickness the description is reduced further to a 2D one. It is argued that the range of validity of 2D descriptions is limited to a very small region above threshold. The transition from 2D to 3D pattern dynamics is discussed. Experimentally testable predictions for the stable range of ideal patterns and the electric Nusselt numbers are made. For most results analytic approximations in terms of material parameters are given. [S1063-651X(00)09512-X].

COLLISION PUMPED SOFT-X-RAY LASERS - PROGRESS AT RAL

Recent developments and progress on collision pumped soft X-ray lasers using the VULCAN glass laser at Rutherford-Appleton Laboratory are presented. This includes saturated output operation of a double target germanium system within a low Fresnel number half-cavity, measurement of the spatial coherence of the output beam in the above and other geometries, use of the beam to demonstrate almost-equal-to 0.15 mum spatial resolution in a full-field microscope and initial studies of other Ne-like and Ni-like systems. Future directions, in the light of new developments of VULCAN facilities, are outlined.

FPGA based Soft-core SIMD Processing: A MIMO-OFDM Fixed-Complexity Sphere Decoder Case Study

To enable reliable data transfer in next generation Multiple-Input Multiple-Output (MIMO) communication systems, terminals must be able to react to fluctuating channel conditions by having flexible modulation schemes and antenna configurations. This creates a challenging real-time implementation problem: to provide the high performance required of cutting edge MIMO standards, such as 802.11n, with the flexibility for this behavioural variability. FPGA softcore processors offer a solution to this problem, and in this paper we show how heterogeneous SISD/SIMD/MIMD architectures can enable programmable multicore architectures on FPGA with similar performance and cost as traditional dedicated circuit-based architectures. When applied to a 4×4 16-QAM Fixed-Complexity Sphere Decoder (FSD) detector we present the first soft-processor based solution for real-time 802.11n MIMO.

A Kernel Interleaved Scheduling Method for Streaming Applications on Soft-core Vector Processors

Massively parallel networks of highly efficient, high performance Single Instruction Multiple Data (SIMD) processors have been shown to enable FPGA-based implementation of real-time signal processing applications with performance and
cost comparable to dedicated hardware architectures. This is achieved by exploiting simple datapath units with deep processing pipelines. However, these architectures are highly susceptible to pipeline bubbles resulting from data and control hazards; the only way to mitigate against these is manual interleaving of
application tasks on each datapath, since no suitable automated interleaving approach exists. In this paper we describe a new automated integrated mapping/scheduling approach to map algorithm tasks to processors and a new low-complexity list scheduling technique to generate the interleaved schedules. When applied to a spatial Fixed-Complexity Sphere Decoding (FSD) detector
for next-generation Multiple-Input Multiple-Output (MIMO) systems, the resulting schedules achieve real-time performance for IEEE 802.11n systems on a network of 16-way SIMD processors on FPGA, enable better performance/complexity balance than current approaches and produce results comparable to handcrafted implementations.

Dataflow toolset for soft-core processors on FPGA for image processing applications

With security and surveillance, there is an increasing need to be able to process image data efficiently and effectively either at source or in a large data networks. Whilst Field Programmable Gate Arrays have been seen as a key technology for enabling this, they typically use high level and/or hardware description language synthesis approaches; this provides a major disadvantage in terms of the time needed to design or program them and to verify correct operation; it considerably reduces the programmability capability of any technique based on this technology. The work here proposes a different approach of using optimised soft-core processors which can be programmed in software. In particular, the paper proposes a design tool chain for programming such processors that uses the CAL Actor Language as a starting point for describing an image processing algorithm and targets its implementation to these custom designed, soft-core processors on FPGA. The main purpose is to exploit the task and data parallelism in order to achieve the same parallelism as a previous HDL implementation but avoiding the design time, verification and debugging steps associated with such approaches.

Lanthanide luminescent logic gate mimics in soft matter: [H(+)] and [F(-)] dual-input device in a polymer gel with potential for selective component release

The non-covalent incorporation of responsive luminescent lanthanide, Ln(iii), complexes with orthogonal outputs from Eu(iii) and Tb(iii) in a gel matrix allows for in situ logic operation with colorimetric outputs. Herein, we report an exemplar system with two inputs ([H(+)] and [F(-)]) within a p(HEMA-co-MMA) polymer organogel acting as a dual-responsive device and identify future potential for such systems.

Soft-core Stream Processor for Sliding Window Applications

Software-programmable `soft' processors have shown tremendous potential for efficient realisation of high performance signal processing operations on Field Programmable Gate Array (FPGA), whilst lowering the design burden by avoiding the need to design fine-grained custom circuit archi-tectures. However, the complex data access patterns, high memory bandwidth and computational requirements of sliding window applications, such as Motion Estimation (ME) and Matrix Multiplication (MM), lead to low performance, inefficient soft processor realisations. This paper resolves this issue, showing how by adding support for block data addressing and accelerators for high performance loop execution, performance and resource efficiency over four times better than current best-in-class metrics can be achieved. In addition, it demonstrates the first recorded real-time soft ME estimation realisation for H.263 systems.

The EU referendum and the UK environment:The Future Under a 'Hard' and a 'Soft' Brexit

'Brexit means Brexit’: but what does Brexit mean for the environment? In the new EUrefEnv study, Dr Charlotte Burns (University of York), Prof Andrew Jordan and Dr Viviane Gravey (University of East Anglia) explore what Brexit may mean for UK environmental policies and governance processes by comparing two scenarios: a ‘soft’ and a ‘hard’ Brexit. A ‘soft’ Brexit would see the UK remain as close as possible to the EU, establishing a new relationship akin to Norway’s relationship with the EU. Conversely a ‘hard’ Brexit would see the UK trade with the EU under World Trade Organisation rules. Both will generate radically different impacts on policies, systems of governance and levels of environmental quality in the UK – key issues that should inform forthcoming negotiations to effect Brexit. The study concludes with suggestions for future research and policy.