On-demand aviation refers to an envisaged air taxi service, using small, autonomous, vertical-takeoff-and-landing, battery-powered electric aircraft. A conceptual design and optimization tool for on-demand aviation is presented in this thesis. The tool uses Geometric Programming, a class of optimization problems with extremely fast solve times and for which global optimality is guaranteed. The optimization model consists of a vehicle, a sizing mission, a revenue-generating mission, and a deadhead (non-passenger-carrying) mission. Cost per trip, including the additional cost due to the deadhead mission, is used as the objective function. Vehicle noise is computed during post-processing using a semi-empirical method. The tool is used to conduct a study of on-demand aviation from a vehicle design perspective.A trade study is conducted between several different on-demand aircraft configurations. Four configurations are viable: the lift + cruise configuration, the compound helicopter, the tilt wing, and the tilt rotor. Configurations with a higher lift-to-drag ratio, but a higher disk loading, generally weigh less and cost less to operate; configurations with a lower lift-to-drag ratio, but a lower disk loading, are quieter. Using New York City as an example market, it is shown that an on-demand air service will cost significantly less as compared to current helicopter air taxi operations. The two most important costs are pilot salary and battery amortization. If these two costs can be reduced (via vehicle automation and reduced battery manufacturing costs respectively), an on-demand air service becomes competitive with current car ridesharing on the basis of cost per seat mile. Therefore, on-demand aviation has the potential to become a system for everyday commutes.Technological assumptions and vehicle requirements, especially mission range, battery energy density, vehicle autonomy level, battery manufacturing cost, and reserve requirements, have significant impacts on vehicle weight and cost. Vehicle noise can be reduced through the careful selection of key design parameters. However, envisaged noise requirements cannot easily be met, even with the most generous long-termThe author wishes to thank all those who contributed their insights to this work. In particular,

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Purpose Given that Blockchain technology poses a growing challenge to the banking industry, this paper aims to analyse the innovation of Blockchain banking with regard to its systemic dimension, as well as dynamics of competition. The empirical research demonstrates how the systemic characteristics of Blockchain banking relate to the pursuit of strategies and to what extent these strategies influence the directional path and level of technology diffusion. Design/methodology/approach The research study uses a case study methodology to explore the strategic competition of Blockchain banking. The study proposes the systemic innovation model for analysing and tracking the path of innovations. The model can be applied to any industry to understand the process of innovation development and the strategies to win market share in the banking industry. This research makes a contribution towards the theory of technology diffusion to understand the directional path of innovations. Findings The analyses of findings reveal the situation whereby most banks still compete to create their own Blockchain banking systems. The analyses, based on the systemic innovation model, also shows the low systemic feature of Blockchain banking at present. From the technology diffusion perspective, the future of Blockchain banking may need cross-chain interoperability to support a full spectrum of payments and value exchanges on the internet of things. Originality/value The main contribution of this paper is the systemic analysis of the latest innovation of Blockchain banking. Given that the research also includes the major banking innovation cases of ATM/cash cards, credit cards and electronic fund transfer at the point of sale/debit cards, the comparative analyses offer strategic insights to predict the progress, as well as pattern of technology development and diffusion for the case of Blockchain banking.

Abstract--To fight terrorism successfully, the quality of data must be considered to avoid garbage-in-garbage-out. Research has shown that data quality (DQ) goes beyond accuracy to include dimensions such as believability, timeliness, and accessibility. In collecting, processing, and analyzing a much broader array of data than we do currently, therefore, a comprehensive approach must be developed to ensure that DQ is incorporated in determining the most probable current or future scenario for preemption, national security warning and decision making. Additional data such as who was the data source, when was the data made available, how, where, and why also need to be included to judge the quality of the information assembled from these data.We propose such an approach for Total Information Awareness with Quality (TIAQ), which includes concepts, models, and tools. Central to our approach is to manage information as a product with four principles. We have applied the information product approach to research sites where opportunities arise. For example, the Air Force Material Command uses requirements definition and forecasting processes to perform a number of functions. However, the Air Force experienced several complex problems due to DQ problems; as a result, fuel pumps were unavailable. Each engine needs a fuel pump; when a pump is not available, a military aircraft is grounded. We traced the fuel-pump throughout the process of remanufacture, and identified root causes such as delays by pump contractors and ordering problems. To a certain extent, detecting foreign terrorists and decipher their plots are analogous to tracing fuel pumps. Our research provides an interdisciplinary approach to facilitating Total Information Awareness.