Density evolution and power profile optimization for iterative multiuser decoders based on individually optimum multiuser detectors

Iterative multiuser joint decoding based on exact Belief Propagation (BP) is analyzed in the large system limit by means of the replica method. It is shown that performance can be improved by appropriate power assignment to the users. The optimum power assignment can be found by linear programming in most technically relevant cases. The performance of BP iterative multiuser joint decoding is compared to suboptimum approximations based on Interference Cancellation (IC). While IC receivers show a significant loss for equal-power users, they yield performance close to BP under optimum power assignment.

EPiCS:engineering proprioception in computing systems

Modern compute systems continue to evolve towards increasingly complex, heterogeneous and distributed architectures. At the same time, functionality and performance are no longer the only aspects when developing applications for such systems, and additional concerns such as flexibility, power efficiency, resource usage, reliability and cost are becoming increasingly important. This does not only raise the question of how to efficiently develop applications for such systems, but also how to cope with dynamic changes in the application behaviour or the system environment. The EPiCS Project aims to address these aspects through exploring self-awareness and self-expression. Self-awareness allows systems and applications to gather and maintain information about their current state and environment, and reason about their behaviour. Self-expression enables systems to adapt their behaviour autonomously to changing conditions. Innovations in EPiCS are based on systematic integration of research in concepts and foundations, customisable hardware/software platforms and operating systems, and self-aware networking and middleware infrastructure. The developed technologies are validated in three application domains: computational finance, distributed smart cameras and interactive mobile media systems. © 2012 IEEE.

Architectural aspects of self-aware and self-expressive computing systems:from psychology to engineering

Work on human self-Awareness is the basis for a framework to develop computational systems that can adaptively manage complex dynamic tradeoffs at runtime. An architectural case study in cloud computing illustrates the framework's potential benefits.

Neural control of a batch distillation

The purpose of the work reported here was to investigate the application of neural control to a common industrial process. The chosen problem was the control of a batch distillation. In the first phase towards deployment, a complex software simulation of the process was controlled. Initially, the plant was modelled with a neural emulator. The neural emulator was used to train a neural controller using the backpropagation through time algorithm. A high accuracy was achieved with the emulator after a large number of training epochs. The controller converged more rapidly, but its performance varied more widely over its operating range. However, the controlled system was relatively robust to changes in ambient conditions.

Robust control of nonlinear stochastic systems by modelling conditional distributions of control signals

We introduce a novel inversion-based neuro-controller for solving control problems involving uncertain nonlinear systems that could also compensate for multi-valued systems. The approach uses recent developments in neural networks, especially in the context of modelling statistical distributions, which are applied to forward and inverse plant models. Provided that certain conditions are met, an estimate of the intrinsic uncertainty for the outputs of neural networks can be obtained using the statistical properties of networks. More generally, multicomponent distributions can be modelled by the mixture density network. In this work a novel robust inverse control approach is obtained based on importance sampling from these distributions. This importance sampling provides a structured and principled approach to constrain the complexity of the search space for the ideal control law. The performance of the new algorithm is illustrated through simulations with example systems.

Re-engineering construction communication in distance management framework

In an exploding and fluctuating construction market, managers are facing a challenge, which is how to manage business on a wider scale and to utilize modern developments in information technology to promote productivity. The extraordinary development of telecommunications and computer technology makes it possible for people to plan, lead, control, organize and manage projects from a distance without the need to be on site on a daily basis. A modern management known as distance management (DM) or remote management is emerging. Physical distance no longer determines the boundary of management since managers can now operate projects through virtual teams that organize manpower, material and production without face-to-face communication. What organization prototype could overcome psychological and physical barriers to reengineer a successful project through information technology? What criteria distinguishes the adapted way of communication of individual activities in a teamwork and assist the integration of an efficient and effective communication between face-to-face and a physical distance? The entire methodology has been explained through a case application on refuse incineration plant projects in Taiwan.

Neural network control of a gas turbine

In this paper we explore the practical use of neural networks for controlling complex non-linear systems. The system used to demonstrate this approach is a simulation of a gas turbine engine typical of those used to power commercial aircraft. The novelty of the work lies in the requirement for multiple controllers which are used to maintain system variables in safe operating regions as well as governing the engine thrust.

An investigation of thin amorphous carbon-based sputtered coatings for MEMS and micro-engineering applications

The work presented in this thesis describes an investigation into the production and properties of thin amorphous C films, with and without Cr doping, as a low wear / friction coating applicable to MEMS and other micro- and nano-engineering applications. Firstly, an assessment was made of the available testing techniques. Secondly, the optimised test methods were applied to a series of sputtered films of thickness 10 - 2000 nm in order to: (i) investigate the effect of thickness on the properties of coatingslcoating process (ii) investigate fundamental tribology at the nano-scale and (iii) provide a starting point for nanotribological coating optimisation at ultra low thickness. The use of XPS was investigated for the determination of Sp3/Sp2 carbon bonding. Under C 1s peak analysis, significant errors were identified and this was attributed to the absence of sufficient instrument resolution to guide the component peak structure (even with a high resolution instrument). A simple peak width analysis and correlation work with C KLL D value confirmed the errors. The use of XPS for Sp3/Sp2 was therefore limited to initial tentative estimations. Nanoindentation was shown to provide consistent hardness and reduced modulus results with depth (to < 7nm) when replicate data was suitably statistically processed. No significant pile-up or cracking of the films was identified under nanoindentation. Nanowear experimentation by multiple nanoscratching provided some useful information, however the conditions of test were very different to those expect for MEMS and micro- / nano-engineering systems. A novel 'sample oscillated nanoindentation' system was developed for testing nanowear under more relevant conditions. The films were produced in an industrial production coating line. In order to maximise the available information and to take account of uncontrolled process variation a statistical design of experiment procedure was used to investigate the effect of four key process control parameters. Cr doping was the most significant control parameter at all thicknesses tested and produced a softening effect and thus increased nanowear. Substrate bias voltage was also a significant parameter and produced hardening and a wear reducing effect at all thicknesses tested. The use of a Cr adhesion layer produced beneficial results at 150 nm thickness, but was ineffective at 50 nm. Argon flow to the coating chamber produced a complex effect. All effects reduced significantly with reducing film thickness. Classic fretting wear was produced at low amplitude under nanowear testing. Reciprocating sliding was produced at higher amplitude which generated three body abrasive wear and this was generally consistent with the Archard model. Specific wear rates were very low (typically 10-16 - 10-18 m3N-1m-1). Wear rates reduced exponentially with reduced film thickness and below (approx.) 20 nm, thickness was identified as the most important control of wear.

General-purpose autonomic computing

The success of mainstream computing is largely due to the widespread availability of general-purpose architectures and of generic approaches that can be used to solve real-world problems cost-effectively and across a broad range of application domains. In this chapter, we propose that a similar generic framework is used to make the development of autonomic solutions cost effective, and to establish autonomic computing as a major approach to managing the complexity of today’s large-scale systems and systems of systems. To demonstrate the feasibility of general-purpose autonomic computing, we introduce a generic autonomic computing framework comprising a policy-based autonomic architecture and a novel four-step method for the effective development of self-managing systems. A prototype implementation of the reconfigurable policy engine at the core of our architecture is then used to develop autonomic solutions for case studies from several application domains. Looking into the future, we describe a methodology for the engineering of self-managing systems that extends and generalises our autonomic computing framework further.

Software engineering techniques for the development of systems of systems

This paper investigates how existing software engineering techniques can be employed, adapted and integrated for the development of systems of systems. Starting from existing system-of-systems (SoS) studies, we identify computing paradigms and techniques that have the potential to help address the challenges associated with SoS development, and propose an SoS development framework that combines these techniques in a novel way. This framework addresses the development of a class of IT systems of systems characterised by high variability in the types of interactions between their component systems, and by relatively small numbers of such interactions. We describe how the framework supports the dynamic, automated generation of the system interfaces required to achieve these interactions, and present a case study illustrating the development of a data-centre SoS using the new framework.

PCIM:a project control and inhibiting‐factors management model

In construction projects, the aim of project control is to ensure projects finish on time, within budget, and achieve other project objectives. During the last few decades, numerous project control methods have been developed and adopted by project managers in practice. However, many existing methods focus on describing what the processes and tasks of project control are; not on how these tasks should be conducted. There is also a potential gap between principles that underly these methods and project control practice. As a result, time and cost overruns are still common in construction projects, partly attributable to deficiencies of existing project control methods and difficulties in implementing them. This paper describes a new project cost and time control model, the project control and inhibiting factors management (PCIM) model, developed through a study involving extensive interaction with construction practitioners in the UK, which better reflects the real needs of project managers. A set of good practice checklist is also developed to facilitate implementation of the model. © 2013 American Society of Civil Engineers.

The human factors aspects of alarms in human supervisory control tasks.

This research thesis is concerned with the human factors aspects of industrial alarm systems within human supervisory control tasks. Typically such systems are located in central control rooms, and the information may be presented via visual display units. The thesis develops a human, rather than engineering, centred approach to the assessment, measurement and analysis of the situation. A human factors methodology was employed to investigate the human requirements through: interviews, questionnaires, observation and controlled experiments. Based on the analysis of current industrial alarm systems in a variety of domains (power generation, manufacturing and coronary care), it is suggested that often designers do not pay due considerations to the human requirements. It is suggested that most alarm systems have severe shortcomings in human factors terms. The interviews, questionnaire and observations led to the proposal of 'alarm initiated activities' as a framework for the research to proceed. The framework comprises of six main stages: observe, accept, analyse, investigate, correct and monitor. This framework served as a basis for laboratory research into alarm media. Under consideration were speech-based alarm displays and visual alarm displays. Non-speech auditory displays were the subject of a literature review. The findings suggest that care needs to be taken when selecting the alarm media. Ideally it should be chosen to support the task requirements of the operator, rather than being arbitrarily assigned. It was also indicated that there may be some interference between the alarm initiated activities and the alarm media, i.e. information that supports one particular stage of alarm handling may interfere with another.

Neural network enhanced self tuning adaptive control application for non-linear control of dynamic systems

The main theme of research of this project concerns the study of neutral networks to control uncertain and non-linear control systems. This involves the control of continuous time, discrete time, hybrid and stochastic systems with input, state or output constraints by ensuring good performances. A great part of this project is devoted to the opening of frontiers between several mathematical and engineering approaches in order to tackle complex but very common non-linear control problems. The objectives are: 1. Design and develop procedures for neutral network enhanced self-tuning adaptive non-linear control systems; 2. To design, as a general procedure, neural network generalised minimum variance self-tuning controller for non-linear dynamic plants (Integration of neural network mapping with generalised minimum variance self-tuning controller strategies); 3. To develop a software package to evaluate control system performances using Matlab, Simulink and Neural Network toolbox. An adaptive control algorithm utilising a recurrent network as a model of a partial unknown non-linear plant with unmeasurable state is proposed. Appropriately, it appears that structured recurrent neural networks can provide conveniently parameterised dynamic models for many non-linear systems for use in adaptive control. Properties of static neural networks, which enabled successful design of stable adaptive control in the state feedback case, are also identified. A survey of the existing results is presented which puts them in a systematic framework showing their relation to classical self-tuning adaptive control application of neural control to a SISO/MIMO control. Simulation results demonstrate that the self-tuning design methods may be practically applicable to a reasonably large class of unknown linear and non-linear dynamic control systems.

Computer-assisted production scheduling, planning and control in foundries

The present study describes a pragmatic approach to the implementation of production planning and scheduling techniques in foundries of all types and looks at the use of `state-of-the-art' management control and information systems. Following a review of systems for the classification of manufacturing companies, a definitive statement is made which highlights the important differences between foundries (i.e. `component makers') and other manufacturing companies (i.e. `component buyers'). An investigation of the manual procedures which are used to plan and control the manufacture of components reveals the inherent problems facing foundry production management staff, which suggests the unsuitability of many manufacturing techniques which have been applied to general engineering companies. From the literature it was discovered that computer-assisted systems are required which are primarily `information-based' rather than `decision based', whilst the availability of low-cost computers and `packaged-software' has enabled foundries to `get their feet wet' without the financial penalties which characterized many of the early attempts at computer-assistance (i.e. pre-1980). Moreover, no evidence of a single methodology for foundry scheduling emerged from the review. A philosophy for the development of a CAPM system is presented, which details the essential information requirements and puts forward proposals for the subsequent interactions between types of information and the sub-system of CAPM which they support. The work developed was oriented specifically at the functions of production planning and scheduling and introduces the concept of `manual interaction' for effective scheduling. The techniques developed were designed to use the information which is readily available in foundries and were found to be practically successful following the implementation of the techniques into a wide variety of foundries. The limitations of the techniques developed are subsequently discussed within the wider issues which form a CAPM system, prior to a presentation of the conclusions which can be drawn from the study.

The application of knowledge based expert systems to mechanical engineering design

Investigation of the different approaches used by Expert Systems researchers to solve problems in the domain of Mechanical Design and Expert Systems was carried out. The techniques used for conventional formal logic programming were compared with those used when applying Expert Systems concepts. A literature survey of design processes was also conducted with a view to adopting a suitable model of the design process. A model, comprising a variation on two established ones, was developed and applied to a problem within what are described as class 3 design tasks. The research explored the application of these concepts to Mechanical Engineering Design problems and their implementation on a microcomputer using an Expert System building tool. It was necessary to explore the use of Expert Systems in this manner so as to bridge the gap between their use as a control structure and for detailed analytical design. The former application is well researched into and this thesis discusses the latter. Some Expert System building tools available to the author at the beginning of his work were evaluated specifically for their suitability for Mechanical Engineering design problems. Microsynics was found to be the most suitable on which to implement a design problem because of its simple but powerful Semantic Net Knowledge Representation structure and the ability to use other types of representation schemes. Two major implementations were carried out. The first involved a design program for a Helical compression spring and the second a gearpair system design. Two concepts were proposed in the thesis for the modelling and implementation of design systems involving many equations. The method proposed enables equation manipulation and analysis using a combination of frames, semantic nets and production rules. The use of semantic nets for purposes other than for psychology and natural language interpretation, is quite new and represents one of the major contributions to knowledge by the author. The development of a purpose built shell program for this type of design problems was recommended as an extension of the research. Microsynics may usefully be used as a platform for this development.