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Alcohol misuse and related harm costs money, drains resource and takes lives. Alcohol brief interventional advice forms an important method to moderate alcohol consumption at both individual and population level. Alcohol exerts a significant negative influence on the oral cavity and is implicated in the development of oro-mucosal and dental disease. Alcohol and tobacco smoking are recognised a key aetiological agents in the development of oral cancer which is the 14th most common cancer, accounting for approximately 2% of new cases, killing over 2300 people in the UK every year. A crucial weapon to tackle the disease is prevention through management of those modifiable lifestyle factors. The role of the general dental practitioner (GDP) in providing alcohol advice has received sparse attention, however evidence suggests that GDPs do not routinely engage in this activity. The aim of this research was to identify factors preventing or facilitating GDP engagement and develop strategies to support them to deliver alcohol advice. GDPs salient beliefs were applied, using behaviour change theories (the Theory of Planned Behaviour and Social Cognitive Theory), to formulate a theory based questionnaire. A postal survey (n=300, RR 60%) identified that few (17%) GDPs routinely provide advice to patients exposing potential for improvement. Subsequent exploratory multiple regression analysis identified 5 key items which might act as targets. The resultant five-item model accounted for 41% of the variance in intention [Adjusted R2 for this model is .41; F = 15.34 (.001)].A theoretically informed intervention was administered as a multi-centre, parallel group, three-arm randomized controlled pilot study. The aims were to test the feasibility and acceptability of implementing an alcohol advice intervention in dental primary care. The intervention was not entirely acceptable to patients or dentists. Qualitative analysis revealed factors (not limited) to remuneration, perceived relevance, confidence, embarrassment and fear of consequences mar progress. Modifications to study processes and methods would seem a sensible prior to further study.

This thesis describes the research leading from the conception, through development, to the practical implementation of a comprehensive security architecture for use within, and as a value-added enhancement to, the ISO Open Systems Interconnection (OSI) model. The Comprehensive Security System (CSS) is arranged basically as an Application Layer service but can allow any of the ISO recommended security facilities to be provided at any layer of the model. It is suitable as an 'add-on' service to existing arrangements or can be fully integrated into new applications. For large scale, distributed processing operations, a network of security management centres (SMCs) is suggested, that can help to ensure that system misuse is minimised, and that flexible operation is provided in an efficient manner. The background to the OSI standards are covered in detail, followed by an introduction to security in open systems. A survey of existing techniques in formal analysis and verification is then presented. The architecture of the CSS is described in terms of a conceptual model using agents and protocols, followed by an extension of the CSS concept to a large scale network controlled by SMCs. A new approach to formal security analysis is described which is based on two main methodologies. Firstly, every function within the system is built from layers of provably secure sequences of finite state machines, using a recursive function to monitor and constrain the system to the desired state at all times. Secondly, the correctness of the protocols generated by the sequences to exchange security information and control data between agents in a distributed environment, is analysed in terms of a modified temporal Hoare logic. This is based on ideas concerning the validity of beliefs about the global state of a system as a result of actions performed by entities within the system, including the notion of timeliness. The two fundamental problems in number theory upon which the assumptions about the security of the finite state machine model rest are described, together with a comprehensive survey of the very latest progress in this area. Having assumed that the two problems will remain computationally intractable in the foreseeable future, the method is then applied to the formal analysis of some of the components of the Comprehensive Security System. A practical implementation of the CSS has been achieved as a demonstration system for a network of IBM Personal Computers connected via an Ethernet LAN, which fully meets the aims and objectives set out in Chapter 1. This implementation is described, and finally some comments are made on the possible future of research into security aspects of distributed systems.

The improvement of imaging acquisition technology directly influences the development of non-invasive methods in dental age estimation (DAE). The introduction of three-dimensional imaging - especially the Cone Beam Computed-Tomography (CBCT) - created a new perspective on DAE methods, especially for adults where regressive changes must be examined thoroughly. A preliminary systematic review and meta-analysis found that the CBCT DAE method can contribute to DAE methods in adults, especially if the volumetric analysis is used. Another finding is that a common approach used for the analysis is the quantification of the ratio between pulp and tooth volumetric information. However, the methods do not factor in different regressive changes that occur in the crown and root of a tooth, neither by combination nor separation. Therefore, this study explored the reproducibility and reliability of adult's DAE methods using CBCT imaging through a step-by-step volumetric segmentation approach. This study was performed on a CBCT scan dataset of the anterior maxillary teeth from patients of Indonesian origin. The methodology was developed using open-source software (ITK-SNAP), and the combination of human intervention and semi-automated segmentation gave the best quantified reproducibility value. Consequently, this approach was used to develop the 4-Part Tooth Segmentation (SG⁴t) method. The anterior maxillary lateral incisor presented the highest value of R². In this study phase, an additional regression model emerged as a tool for age estimation and can also be used in challenging cases such as when teeth are found fragmented. The expansion of the SG⁴t method was concentrated to the crown area, where attrition can be quantified using the enamel volume. This 3-Part Crown Segmentation (SG³cr) method gave the highest R² to the anterior maxillary canine. Furthermore, the 5-Part Tooth Segmentation (SG⁵t) method was developed by combining the previous significant variables. Additionally, subsequent supervised machine learning (SML) analyses were tested. It was found that the utilisation of SML did not significantly improve the method's reliability as it is comparable to the original multiple linear regression (MLR) model. In conclusion, the overall volumetric segmentation approach applied in the adult population using CBCT scans provides a better representation of CA without introducing collinearity within the predictive variables. The SG⁴t approach was better in analysing a whole tooth considering the labour time it takes and the minimal improvement in the model performance when compared to the SG⁵t method. In contrast, the SG³cr method is encouraged for age estimation using the anterior maxillary crown as enamel segmentation significantly improves the predictive model performance, albeit with a longer labour time.

Current economic appraisal guidelines focus on direct cost savings and over the last 10 to 15 years methods have also been developed to evaluate urbanisation effects within city regions but there has been much less focus on the effects of linking urban areas. These effects include the potential for fostering increased trade and specialisation leading to localisation benefits. The lack of focus on these impacts in economic appraisals is due to the complexity of the processes and the small evidence base which this thesis aims to contribute to. To investigate the economic impacts of inter-city connectivity a dynamic model was developed based on the system dynamics approach. The model includes an innovative structure with a target-based/goal-seeking approach for determining equilibrium in the labour and capital markets. Changes in effective density impact on wages and capital rents and labour and capital can move sector and zone to maximise their returns. The results show that sectoral and zonal mobility costs limit the potential for increased specialisation through investment in inter-city transport and increases in specialisation are more likely to arise when the scheme effects differ between sectors and between cities. The impact of including localisation benefits and changes in specialisation in the economic appraisal of inter-city connectivity schemes was investigated using an abstract static model. With the central case assumptions it was estimated that their inclusion would increase the total present value of benefits by 7.9% for a 150km distance between two cities. Using a similar method a case study was undertaken of the proposed Northern Powerhouse Rail scheme in the north of England. This showed that with detailed GJT and land-use changes the estimated additional benefits are comparable to those from the abstract model but they can be unevenly distributed and that there can be losers as well as winners.

Radiographic methods using PV and PTVR are important for dental age estimation. According to previous studies, these two markers possess different relationships with age in different sexes but none of the studies have used a homogenous (approximately equal numbers of individuals in each age range) age distribution to assess this relationship and the effect of sex as predictor on age estimation. This study was performed on 719 subjects of Pakistani origin (368 females and 349 males) aged from 15-65 years. Cone beam computed tomography images of 521 left maxillary and 681 left mandibular canines were collected. Planmeca Romexis® software was used to trace the outline of the pulp cavity and tooth and to calculate respective volumes. Subsequently, Microsoft® Office Excel 2016 was used to calculate the ratios. Regression analysis was performed to assess the correlation between PV and PTVR factoring sex in as a predictor for age estimation. The obtained results showed that mandibular canine PV (R2 =0.33) and maxillary PTVR (R2 =0.46) with sex have the highest predictive power. The relationship between mandibular canine PV and maxillary PTVR with sex against chronological age demonstrates an odd S-shaped non-linear relationship. The conclusion is that using predictors such as the PV and PTVR with sex produced the best estimates of chronological age.

The connected and automated vehicle (CAV) is a promising technology that will reshape the transport. It has potentials in reducing fuel consumption as well as improving capacity and safety. The traffic control of CAVs on urban roads is investigated in the thesis, which consists of two aspects: intersection control and trajectory planning. For the intersection control with CAVs, a bilevel programming model integrating intersection control with trajectory planning is proposed to improve the efficiency of the intersection when all vehicles are CAVs. The feedback structure adapts a wide range of conditions and improves capacity. The cooperation between the two levels and their linear properties ensure reasonable solving time. A platoon-based method is also proposed to improve the calculation speed. For the trajectory planning with CAVs, a platoon-based eco-driving model is proposed using model predictive control. The model is used in mixed autonomy traffic and considers traffic efficiency, fuel consumption, and driving comfort. The cooperation between automated vehicles and human-driven vehicles reduces the negative impact of eco-driving on the following vehicles and reduces fuel consumption even further. The performance under different platoon sizes and penetrations of automated vehicles are also tested in the simulation. At an intersection controlled by the adaptive traffic control system, the vehicle may not be able to get accurate information on the future signal timing. A multi-phase model predictive control model is proposed to reduce fuel consumption by considering the stochastic signal information. Two driving regimes are considered based on the state of the traffic signal at each time step: accelerating to pass the intersection when the light is green or keeping waiting for the possible green light in the next time step. This model is further extended to the case that the vehicle can receive the information on the future signal timing some seconds in advance. An additional eco-driving strategy is considered in this case.

On-line responsive traffic signal optimization strategies most commonly use data received from loop detectors to feed information into an underlying traffic model. The limited data available from conventional detection systems has dictated the way that current 'state-of-the-art' traffic signal control systems have been developed. Such systems tend to consider traffic as having homogenous properties to avoid the requirement for more detailed knowledge of individual vehicle properties. However, a consequence of this simplification is to limit an optimizer in achieving its objectives. The first element of this study investigates whether additional data regarding vehicle type can be reliably extracted from conventional detection to improve optimizer performance using existing infrastructure. A single detector classification algorithm is developed and it is shown that, using a modification of an existing state-of-the-art optimization method, a modest improvement in performance can be achieved. The emergence of connected vehicle technology and, in particular, Vehicle-to-Infrastructure (V2I) communications promises more comprehensive data. V2I-based optimization methods proposed in literature require a minimum penetration rate of V2I equipped vehicles before performance matches existing systems. To address this problem, the second part of the study focuses on the development of a hybrid detection model that is capable of simultaneously using information from conventional and V2I detection. It is demonstrated that the hybrid detection model can begin to realise benefits as soon as V2I data becomes available. V2I-based vehicle classification is then applied to the developed hybrid model and significant benefits are demonstrated for HGVs. The final section of the thesis introduces the use of a more sophisticated internal traffic model and a new optimization method is developed to implement it. The car-following model based optimization method addresses the lack of modelled interaction between vehicles and is shown to be capable of reducing vehicle stops over and above the developed (vertical queue based) hybrid model.

High-risk cities worldwide face problems regarding increases in vulnerability to natural disaster combined with urban-transport problems. Up till now, there has been no study that was specifically concerned with these two issues simultaneously regarding how these cities should define their sustainability concept and formulate their land use and transport strategies in the framework of sustainable development. This study presents an approach for integrating concepts for disaster mitigation strategies into the land-use transport interaction (LUTI) plan by combining the disaster mitigation strategies with the conventional land use and transport strategies in the framework of urban risk reduction and urban transport sustainability. There were 18 combined alternative policy measures selected, which were classified into three different land use strategies and five alternative different transport policy measures. The land use strategies consist of (A) accommodation (BAU), (B) planned-retreat with strict zoning, and (C) planned-retreat with pricing policy. The alternative transport policy measures consist of (1) Bus rapid transit (BRT), (2) parking charge, (3) cut fuel subsidy, (4) combination of BRT and parking, and (5) combination of BRT, parking and cut subsidy This innovative approach is the first original contribution of this research. MARS LUTI model was modified by adding disaster risk factor in its sub land use of model, which become as the second original contribution of this research. In the level of strategies evaluation, all of the strategies tested were measured using four indicators, which consist of (1) vulnerability, (2) environment, (3) economic and (4) efficiency indicators. The additional of vulnerability indicator the framework of urban transport sustainability is the third original contribution of this research. The main finding for the case study are as follows : (1) the application of the two land use policy measures (strict zoning and pricing) gave significant contribution in reducing city vulnerability to potential tsunami disaster in the future, which could be applied to promote the concept of urban risk reduction. (2) The combination of “push and pull transport strategies” application through the combined BRT, parking and cut subsidy produced the best performance compared to the others alternative policy measures selected. The push and pull transport strategy succeed to direct the evolution of urban transport condition in the framework of urban transport sustainability in order to reach the sustainability objectives.

Despite the increasingly stringent type approval limit values for vehicle emissions no quantitative difference has been seen in roadside concentrations of NOX concentrations (Carslaw et al., 2011b). This thesis aims to improve the ability of measuring and modelling the NOX emissions of passenger cars in urban environments by taking an in depth look at the emissions of vehicles observed in real driving environments over a number of years in Aberdeen, Cambridge, Leeds and Sheffield using a Remote Sensing Device. The remote sensing device is tested under controlled conditions to ascertain its measurement accuracy for both pollutants and vehicle specific power. A mathematical distribution function for describing the emissions of a fleet is presented and shown to be a good description of over 90% of the vehicles and a superposition of two of these distribution functions was able to describe the distribution of the rest of the fleet’s NO emissions with a high degree of accuracy. The distribution functions derived for one city were used to create a predictive model to determine how the average emission of a passenger car fleet vehicle performance would evolve over time showing that by 2025 a ≈ 30% reduction in NOX could be expected if the fleet was allowed to evolve naturally. In addition to these results a number of real world problems were assessed using the new framework developed in this thesis. The emissions of taxis compared to privately owned vehicles was assessed with taxis being shown to emit ≈ 50% more NOX than their equivalent vehicles in the fleet. The Volkswagen Group scandal, #dieselgate, is discussed and the data that the remote sensing device has been used to assess the real driving emissions of VWG passenger cars fitted with the EA189 engine. The observations show that whilst VWG vehicles are exceeding the limit values in real driving environments, they are observed to have equivalent or lower emissions factors than other marques.

Within a highway transportation network, the social welfare implications of two different groups of agents setting tolls in competition for revenues are studied. The first group comprises private sector toll road operators aiming to maximise revenues. The second group comprises local governments or jurisdictions who may engage in tax exporting. Extending insights from the public economics literature, jurisdictions tax export because when setting tolls to maximise welfare for their electorate, they simultaneously benefit from revenues from extra-jurisdictional users. Hence the tolls levied by both groups will be higher than those intended solely to internalise congestion, which then results in welfare losses. Therefore the overarching question investigated is the extent of welfare losses stemming from such competition for toll revenues. While these groups of agents are separately studied, the interactions between agents in each group in competition can be modelled within the common framework of Equilibrium Problems with Equilibrium Constraints. Several solution algorithms, adapting methodologies from microeconomics as well as evolutionary computation, are proposed to identify Nash Equilibrium toll levels. These are demonstrated on realistic transportation networks. As an alternative paradigm to competition, the possibilities for co-operation between agents in each group are also explored. In the case of toll road operators, the welfare consequences of competition could be positive or adverse depending on the interrelationships between the toll roads in competition. The results therefore generalise those previously obtained to a more realistic setting investigated here. In the case of competition between jurisdictions, it is shown that the fiscal externality of tax exporting resulting from their toll setting decisions can substantially reduce the welfare gains from internalising congestion. The ability of regulation, co-operation and bilateral bargaining to reduce the welfare losses are assessed. The research thus contributes to informing debates regarding the appropriate level of institutional governance for toll pricing policies.

This research recognises a conflict between climate change mitigation and a lock-in of carbon-intense lifestyles. The concern is that, in the short term, policies to aid the transition to Low Carbon Vehicles (LCVs) may bring about unacceptable impacts on those amongst the worst-off. The approach that is taken is interdisciplinary, and suggests a novel approach to policy appraisal through combining ethics with a system dynamic model. An ethical framework is established that claims coercive LCV policies are permitted due to the harms of climate change, but certain groups require protection from impacts on car ownership. This protection could be similar to policy in other sectors, such as tax exemptions for the worst-off. The framework also improves on current practise by offering a new perspective on the limitations of models in policy-making. Two model case studies examine LCV policies, focused on subsidies and market regulation of electric vehicles. The first is relatively simple and develops basic skills and understanding, but still gives policy insight and explores the sensitivity of results. A more complex second model is used to understand the policy impacts in more detail, and in relation to ethical concerns. Combining the findings of both models suggests that subsidies are only successful in reducing emissions under a failing market and although regulation is more successful it raises the cost of all vehicles, disproportionately impacting the poorest in society. Combining these policies will allow a more even distribution of burdens. From this, recommendations are made that suggest the policy-maker needs to ensure affordability, protect the vulnerable and distribute burdens. Finally, a framework for an improved approach to modelling and policy appraisal, which incorporates ethics, is proposed. Although the focus of this work is on LCVs, the fundamental approach is transferable to other areas of transport and energy use.

The importance of the data authentication has resulted in the science of the data protection. Interest in this knowledge has been growing due to the increase in privacy of the user's identity, especially after the widespread use of online transactions. Many security techniques are available to maintain the privacy of the user's identity. These include password, smart card or token and face recognition or finger print. But unfortunately, the possibility to duplicate the identity of a user is still possible. Recently, specialists used the user's physical location as a new factor in order to increase the strength of the verification of the user's identity. This thesis focused on the authentication-based user's location. It is based on the idea of using the Global Position System in order to verify the user identity. Improving Kerberos protocol using GPS signal is proposed in order to eliminate the effect of replay attack. This proposal does not expect a high performance from the user during the implementation of the security system. Moreover, to give users more confidence to use security protocol, it has to be evaluated before accepting it. Thus, a measurement tool used to validate protocols called BAN logic was described. In this thesis, a new form of BAN logic which aims to raise the efficiency checking process of the protocol protection strength using the GPS signal is proposed. The proposed form of Kerberos protocol has been analysed using the new form of BAN logic. The new scheme has been tested and compared with the existing techniques to demonstrate its merits and capabilities.

In the last decade, a considerable growth has been added to the volume of the credit risk derivatives market. This growth has been followed by the current financial market turbulence. These two periods have outlined how significant and important are the credit derivatives market and its products. Modelling-wise, this growth has parallelised by more complicated and assembled credit derivatives products such as mth to default Credit Default Swaps (CDS), m out of n (CDS) and collateralised debt obligation (CDO). In this thesis, the Lévy process has been proposed to generalise and overcome the Credit Risk derivatives standard pricing model's limitations, i.e. Gaussian Factor Copula Model. One of the most important drawbacks is that it has a lack of tail dependence or, in other words, it needs more skewed correlation. However, by the Lévy Factor Copula Model, the microscopic approach of exploring this factor copula models has been developed and standardised to incorporate an endless number of distribution alternatives those admits the Lévy process. Since the Lévy process could include a variety of processes structural assumptions from pure jumps to continuous stochastic, then those distributions who admit this process could represent asymmetry and fat tails as they could characterise symmetry and normal tails. As a consequence they could capture both high and low events' probabilities. Subsequently, other techniques those could enhance the skewness of its correlation and be incorporated within the Lévy Factor Copula Model has been proposed, i.e. the 'Stochastic Correlated Lévy Factor Copula Model' and 'Lévy Random Factor Loading Copula Model'. Then the Lévy process has been applied through a number of proposed Pricing Basket CDS&CDO by Lévy Factor Copula and its skewed versions and evaluated by V-FFT limiting and mixture cases of the Lévy Skew Alpha-Stable distribution and Generalized Hyperbolic distribution. Numerically, the characteristic functions of the mth to default CDS's and (n/m) th to default CDS's number of defaults, the CDO's cumulative loss, and loss given default are evaluated by semi-explicit techniques, i.e. via the DFT's Fast form (FFT) and the proposed Very Fast form (VFFT). This technique through its fast and very fast forms reduce the computational complexity from O(N2) to, respectively, O(N log2 N ) and O(N ).