A total quality management (TQM) strategic measurement perspective with specific reference to the software industry

The dissertation aims to obtain an integrated and comprehensive perspective on measurement issues that play a strategic role in organisations that aim at continuous quality improvement through TQM. The multidimensional definition of quality is proposed to view quality holistically. The definition is dynamic, thus dimensions are subject to evolution. Measurement of the quality dimensions is investigated. The relationship between quality and cost, productivity and profitability respectively is examined. The product quality dimensions are redefined for processes. Measurement is a strategic component ofTQM. Integration of financial measures with supplier-; customer-; performance- and internal process measurement is essential for synergism. Measurement of quality management is an additional strategic quality dimension. Applicable research was integrated. Quantitative structures used successfully in industry to achieve quality improvement is important, thus the quality management maturity grid, cleanroom software engineering, software factories, quality function deployment, benchmarking and the ISO 9000 standards are briefly described. Software Metrics Programs are considered to be an application of a holistic measurement approach to quality. Two practical approaches are identified. A framework for initiating implementation is proposed. Two strategic software measurement issues are reliability and cost estimation. Software reliability measurement and modelling are introduced. A strategic approach to software cost estimation is suggested. The critical role of data collection is emphasized. Different approaches to implement software cost estimation in organisations are proposed. A total installed cost template as the ultimate goal is envisaged. An overview of selected software cost estimation models is provided. Potential research areas are identified. The linearity/nonlinearity nature of the software production function is analysed. The synergy between software cost estimation models and project management techniques is investigated. The quantification aspects of uncertainty in activity durations, pertaining to project scheduling, are discussed. Statistical distributions for activity durations are reviewed and compared. A structural view of criteria determining activity duration distribution selection is provided. Estimation issues are reviewed. The integration of knowledge from dispersed fields leads to new dimensions of interaction. Research and practical experience regarding software metrics and software metrics programs can be successfully applied to address the measurement of strategic indicators in other industries.Business ManagementD. Phil. (Operations Research

GPS/Galileo simulation for reduced dynamic LEO satellite orbit determination

Global Navigation Satellite Systems (GNSS) have an endless number of applications in industry, science, military, transportation and recreation & sports. Two systems are currently in operation namely GPS (the USA Global Positioning System) and GLONASS (the Russian GLObal NAvigation Satellite System), and a third is planned, the European satellite navigation system GALILEO. The potential performance improvements achievable through combining these systems could be significant and expectations are high. Computer software can be used to simulate the overall process of GNSS (signal transmission and reception) and produce realistic simulated GNSS measurements. Using such simulated measurements, current and future GNSS systems and possible new applications of GNSS can be investigated. Thus data simulation is the perfect research tool in GNSS fields. Oceanography, is one application of GNSS, which requires position determination with a high accuracy. LEO satellites are used to measure the precise height of the sea surface for studying the dynamics of the world's oceans. Achieving maximum benefit from the altimetric data collected by LEO satellites requires a radial orbit accuracy of 10 cm, or better. It is in determining this orbit where GNSS may be utilised. GPS already delivers high quality position information for LEO satellite orbits such as Topex/Poseidon (1992- present). However LEO satellite orbits determination can still benefit from using GPS combined with GALILEO as there will be more visible satellites and a higher quality of measurements. Investigation of LEO satellite orbit determination using GPS or GALILEO or both systems requires GPS and GALILEO measurements. Due to the lack of real GALILEO measurements, as the system is still in development, the simulation of GPS and GALILEO measurements is required. In order to generate realistic simulated GPS and GALILEO data, the errors, which predominate in GNSS measurements, must be accurately modelled. During this research, it has been shown that it is possible to generate realistic simulated GPS data through the more realistic simulation of the ionospheric, tropospheric and multipath delays. Models with a high spatial resolution have been implemented to simulate the real behaviour of the ionosphere and troposphere. The behaviour of the resulting simulated GPS data is shown to follow the behaviour of real GPS data with a strong agreement. It has also been possible to generate GALILEO simulated data through modifying the simulation software using the GALELEO Design technical specifications. The potential impact of using GPS and GALILEO on LEO satellite orbit determination could be investigated on Topex/Poseidon mission which real GPS data was available from the beginning of this study. The performance of GPS, GALILEO, combined GPS/GALILEO and combined GPS-modernised/GALELEO constellations have been investigated in relation to the reduced dynamic orbit determination of the LEO satellite Topex/Poseidon. It can be concluded that the GALILEO constellation will provide high quality real time LEO satellite orbits compared with GPS. GALELEO constellation will provide slightly better quality real time LEO satellite orbits over the combined GPS-present/GALELEO constellation. However the best quality real time LEO satellite orbits will result from the combined GPS-modernised/GALILEO constellation

Automated photoelastic determination of fracture parameters for bimaterial interface cracks

This thesis details an experimental study on the determination of the fracture parameters for a crack located at the interface between two dissimilar materials using the method of photoelasticity. The interface is potential1y an inherent weak spot of any composite material, structure"or adhesively bonded joint. Accurate description of the state of stress at the crack tip is required for strength prediction. The concept of the complex stress intensity factor is used to characterise the elastic crack tip stress field for an interface crack. Complex stress intensity factors and their moduli have been measured experimental1y for standard bimaterial crack geometries using the wel1 established technique of photo elasticity. Bimaterial specimens comprising aluminium al10y and epoxy resin components were used. This creates a large material mismatch at the interface and al10ws data to be col1ected from the epoxy component of the specimen using transmission photoelasticity. An automated ful1 field photoelastic technique was developed to significantly reduce the data col1ection time. The technique comprises elements from the approaches of three wavelength and phase stepping photoelasticity and is a significant improvement on techniques previously available. Stress intensity factors were determined by fitting a theoretical stress field solution for the bimaterial crack to the experimental data. A computational routine automatical1y selects the region of best fit between the experimental data and the theoretical solution. This data is then used to determine the complex stress intensity factor and its modulus value. In order to provide a robust fit between the experimental data and the theoretical field solution a weighting function was incorporated into the routine. The measured bimaterial stress intensity factors are compared with those determined experimental1y for equivalent homogeneous specimens made from epoxy resin. The differences between the two are then discussed. The experimental results agree with the wel1 known concept that tension and shear effects are inherently coupled at the crack tip. However, the effects of changing the load angle with respect to the interface also demonstrate that some contrasts exist with known numerical solutions

GPS/Galileo simulation for reduced dynamic LEO satellite orbit determination

Global Navigation Satellite Systems (GNSS) have an endless number of applications in industry, science, military, transportation and recreation & sports. Two systems are currently in operation namely GPS (the USA Global Positioning System) and GLONASS (the Russian GLObal NAvigation Satellite System), and a third is planned, the European satellite navigation system GALILEO. The potential performance improvements achievable through combining these systems could be significant and expectations are high. Computer software can be used to simulate the overall process of GNSS (signal transmission and reception) and produce realistic simulated GNSS measurements. Using such simulated measurements, current and future GNSS systems and possible new applications of GNSS can be investigated. Thus data simulation is the perfect research tool in GNSS fields. Oceanography, is one application of GNSS, which requires position determination with a high accuracy. LEO satellites are used to measure the precise height of the sea surface for studying the dynamics of the world's oceans. Achieving maximum benefit from the altimetric data collected by LEO satellites requires a radial orbit accuracy of 10 cm, or better. It is in determining this orbit where GNSS may be utilised. GPS already delivers high quality position information for LEO satellite orbits such as Topex/Poseidon (1992- present). However LEO satellite orbits determination can still benefit from using GPS combined with GALILEO as there will be more visible satellites and a higher quality of measurements. Investigation of LEO satellite orbit determination using GPS or GALILEO or both systems requires GPS and GALILEO measurements. Due to the lack of real GALILEO measurements, as the system is still in development, the simulation of GPS and GALILEO measurements is required. In order to generate realistic simulated GPS and GALILEO data, the errors, which predominate in GNSS measurements, must be accurately modelled. During this research, it has been shown that it is possible to generate realistic simulated GPS data through the more realistic simulation of the ionospheric, tropospheric and multipath delays. Models with a high spatial resolution have been implemented to simulate the real behaviour of the ionosphere and troposphere. The behaviour of the resulting simulated GPS data is shown to follow the behaviour of real GPS data with a strong agreement. It has also been possible to generate GALILEO simulated data through modifying the simulation software using the GALELEO Design technical specifications. The potential impact of using GPS and GALILEO on LEO satellite orbit determination could be investigated on Topex/Poseidon mission which real GPS data was available from the beginning of this study. The performance of GPS, GALILEO, combined GPS/GALILEO and combined GPS-modernised/GALELEO constellations have been investigated in relation to the reduced dynamic orbit determination of the LEO satellite Topex/Poseidon. It can be concluded that the GALILEO constellation will provide high quality real time LEO satellite orbits compared with GPS. GALELEO constellation will provide slightly better quality real time LEO satellite orbits over the combined GPS-present/GALELEO constellation. However the best quality real time LEO satellite orbits will result from the combined GPS-modernised/GALILEO constellation

Protection of data privacy based on artificial intelligence in Cyber-Physical Systems

With the rapid evolution of cyber attack techniques, the security and privacy of Cyber-Physical Systems (CPSs) have become key challenges. CPS environments have several properties that make them unique in efforts to appropriately secure them when compared with the processes, techniques and processes that have evolved for traditional IT networks and platforms. CPS ecosystems are comprised of heterogeneous systems, each with long lifespans. They use multitudes of operating systems and communication protocols and are often designed without security as a consideration. From a privacy perspective, there are also additional challenges. It is hard to capture and filter the heterogeneous data sources of CPSs, especially power systems, as their data should include network traffic and the sensing data of sensors. Protecting such data during the stages of collection, analysis and publication still open the possibility of new cyber threats disrupting the operational loops of power systems. Moreover, while protecting the original data of CPSs, identifying cyberattacks requires intrusion detection that produces high false alarm rates. This thesis significantly contributes to the protection of heterogeneous data sources, along with the high performance of discovering cyber-attacks in CPSs, especially smart power networks (i.e., power systems and their networks). For achieving high data privacy, innovative privacy-preserving techniques based on Artificial Intelligence (AI) are proposed to protect the original and sensitive data generated by CPSs and their networks. For cyber-attack discovery, meanwhile applying privacy-preserving techniques, new anomaly detection algorithms are developed to ensure high performances in terms of data utility and accuracy detection. The first main contribution of this dissertation is the development of a privacy preservation intrusion detection methodology that uses the correlation coefficient, independent component analysis, and Expectation Maximisation (EM) clustering algorithms to select significant data portions and discover cyber attacks against power networks. Before and after applying this technique, machine learning algorithms are used to assess their capabilities to classify normal and suspicious vectors. The second core contribution of this work is the design of a new privacy-preserving anomaly detection technique protecting the confidential information of CPSs and discovering malicious observations. Firstly, a data pre-processing technique filters and transforms data into a new format that accomplishes the aim of preserving privacy. Secondly, an anomaly detection technique using a Gaussian mixture model which fits selected features, and a Kalman filter technique that accurately computes the posterior probabilities of legitimate and anomalous events are employed. The third significant contribution of this thesis is developing a novel privacy-preserving framework for achieving the privacy and security criteria of smart power networks. In the first module, a two-level privacy module is developed, including an enhanced proof of work technique-based blockchain for accomplishing data integrity and a variational autoencoder approach for changing the data to an encoded data format to prevent inference attacks. In the second module, a long short-term memory deep learning algorithm is employed in anomaly detection to train and validate the outputs from the two-level privacy modules