Climate change is a significant issue in today's society as countries work towards decarbonising the economic sectors that contribute to significant greenhouse gas emissions. The electric vehicle (EV) is proposed as a solution to reduce the level of emissions in the transport sector. However, if an EV is powered by an electrical fossil fuelled source, their penetration into the UK market will have minimal mitigating effects, as emissions will simply shift from the transport sector to the energy production sector. Limited research has evaluated the loss of propulsion energy as a result of operating on-board climate control systems, and has focused more on traction energy. Unlike conventional fossil fuelled vehicles, EVs do not produce waste heat to warm the interior space of the vehicle. The present research found that up to 30% of a vehicle's total energy consumed per trip is allocated to heating requirements, thus the present research developed a temperature predicting numerical algorithm to compute indoor cabin temperatures. The vehicle was exposed to ambient climate conditions with an auxiliary heating or cooling system to evaluate this thermal model. The numerical algorithm could predict the temperature of a cabin space under solar space heating conditions with 62% more accuracy than previously developed models when comparing the Root Mean Square Error performance indicator. The presently developed temperature prediction algorithm may be applied to a route planning application, thus indicating the electrical energy required by the vehicle's battery for users to increase or decrease the desired temperature level. Additionally, this study investigated the ability of a renewable energy resource to decarbonise the vehicle's built-in climate control system. Integrating solar panels on the roof and bonnet of an EV to power an auxiliary climate control system reduced the electrical loading required to reach the occupant's thermal comfort. By installing an auxiliary heating system to increase cabin temperature by 2 or 5°C, the present research found that energy consumption of the built-in climate control system was reduced by 22% or 57%, respectively. This illuminates the potential an auxiliary climate control system has in improving the thermal performance of EVs.

This doctoral thesis will examine how relations between the United States and Britain, and internal dynamics within each country, affected the nature and development of the two countries’ information strategies in a shared theatre of war. It examines the two governments’ distinct organisational cultures and bureaucratic structures in explaining the shape this took. Going beyond the policy level it considers how cultures and power relationships contributed to propaganda war planning. The research emphasises important changes in policy development and circumstance which, it is argued, despite the obvious power imbalance, situated Britain in a key position in the Anglo-American propaganda effort. The analysis draws on empirical research conducted in both countries. This fieldwork involved elite interviews focussing on the period of the ‘War on Terror’, including policymakers, key bureaucrats, intelligence personnel, contractors and military planners in both Britain and America.

This study investigates the broadcast/multicast authentication problems in wireless sensor networks (WSNs), particularly sensor nodes broadcast authentication and outside user authentication, and proposes efficient and secure solutions for them. The low cost and immunity from cabling have become motivations for many applications of WSNs, for instance, the forest fire alarm, the intelligent traffic system etc. However, the sensitive nature of communication in these applications makes authentication a compulsory security requirement for them. The conventional security solutions are unfeasible for WSNs due to the unique features of sensor networks. Designing a new security mechanism for WSNs, on the other hand, is a challenging task due to the nature of WSNs. This research proposes a solution to the above mentioned authentication problems in the form of an authentication framework for wireless sensor networks. The proposed framework is comprised of two authentication protocols: one for sensor nodes broadcast authentication and the other for outside user authentication. The latter also facilitates a third type of authentication, i.e., base station to sensor nodes broadcast authentication. These protocols can be applied in WSNs independently tackling individual security problems to achieve different level of security. However, deployed as a unified framework, they ensure a high degree of security with efficiency, providing a single solution to all three authentication problems in WSNs. The performance evaluation results showed that the proposed framework is the most efficient solution when compared to the existing authentication schemes for WSNs, giving a reasonable trade-off between security and efficiency.

Over the last decade, Ubiquitous Real-time Passenger Information (URTPI) has become popular among public transport passengers. The effectiveness of URTPI and hence the value of the investments into the necessary systems can be increased with a clear understanding of how URTPI influences passenger behaviour. However, such an understanding is still limited and fragmented. In particular, very little is known about the impact of URTPI on route choice. This study fills this gap evaluating the impact of URTPI on bus passengers' route choice. A revealed preference survey methodology was adopted for data collection and two questionnaire surveys targeting bus users were carried out. Categorical Regression and discrete choice models, such as Binary Logit Model and Multinomial Logit Model, have been applied to analyse the survey data. The study reveals that trip length, passenger age and profession are the main factors influencing the use of URTPI.Having access toURTPI, the frequency of its use is strongly influenced by the attributes of information and social norms. Bus arrival time and bus stop location are the two most important contents of information. Changing time ofdeparture from the start and the boarding time are the two most popular actions taken by bus passengers after consulting URTPI. Passengers' decisions are influenced by information on bus arrival time, bus route, and walking distance. As a result of the impact of URTPI on passengers' choices, the demand distribution for bus runs could potentially be changed by 33% and for bus lines by 22%. The overall network demand distribution could be affected in 42% of cases as a result of consulting URTPI.This study implicates that while investing in tailoring the sources of URTPI, passengers' preferred attributes and contents of information should be considered. Transport planners and operators should take the potential impact of URTPI into account to make better predictions of the PT demand distribution.